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select count ( * ) where game > 6 col : game | date | opponent | location | score | ot | attendance | record row 1 : 1 | 2006-01-06 00:00:00 | philadelphia wings | xcel energy center | l 11-15 | none | 8024 | 0-1 row 2 : 2 | 2006-01-14 00:00:00 | @ philadelphia wings | wachovia center | w 13-10 | none | 11874 | 1-1 row 3 : 3 | 2006-01-20 00:00:00 | @ calgary roughnecks | pengrowth saddledome | w 12-8 | none | 10637 | 2-1 row 4 : 4 | 2006-01-21 00:00:00 | rochester knighthawks | xcel energy center | l 6-12 | none | 7124 | 2-2 row 5 : 5 | 2006-01-29 00:00:00 | rochester knighthawks | xcel energy center | l 9-10 | none | 7544 | 3-2 row 6 : 6 | 2006-02-03 00:00:00 | @ edmonton rush | rexall place | w 7-6 | none | 8745 | 3-3 row 7 : 7 | 2006-02-10 00:00:00 | philadelphia wings | xcel energy center | w 11-10 | none | 7524 | 4-3 row 8 : 8 | 2006-02-18 00:00:00 | @ buffalo bandits | hsbc arena | l 9-14 | none | 12458 | 4-4 row 9 : 9 | 2006-03-03 00:00:00 | @ toronto rock | air canada centre | l 8-13 | none | 15830 | 4-5 row 10 : 10 | 2006-03-04 00:00:00 | @ buffalo bandits | hsbc arena | w 11-8 | none | 10961 | 5-5 row 11 : 11 | 2006-03-17 00:00:00 | @ portland lumberjax | rose garden | w 14-12 | none | 5487 | 6-5 row 12 : 12 | 2006-03-24 00:00:00 | buffalo bandits | xcel energy center | l 11-13 | none | 9533 | 6-6 row 13 : 13 | 2006-04-01 00:00:00 | toronto rock | xcel energy center | w 10-9 | none | 10084 | 7-6 row 14 : 14 | 2006-04-08 00:00:00 | @ rochester knighthawks | blue cross arena | l 9-10 | none | 10352 | 7-7 row 15 : 15 | 2006-04-09 00:00:00 | san jose stealth | xcel energy center | w 9-8 | ot | 7044 | 8-7 row 16 : 16 | 2006-04-15 00:00:00 | portland lumberjax | xcel energy center | l 8-13 | none | 10104 | 8-8 | col : count ( "*" ) row 1 : 3 | select count ( * ) where game > 6 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& game & date & opponent & location & score & ot & attendance & record \\
\midrule
0 & 1 & 2006-01-06 00:00:00 & philadelphia wings & xcel energy center & l 11-15 & none & 8024 & 0-1 \\
1 & 2 & 2006-01-14 00:00:00 & @ philadelphia wings & wachovia center & w 13-10 & none & 11874 & 1-1 \\
2 & 3 & 2006-01-20 00:00:00 & @ calgary roughnecks & pengrowth saddledome & w 12-8 & none & 10637 & 2-1 \\
3 & 4 & 2006-01-21 00:00:00 & rochester knighthawks & xcel energy center & l 6-12 & none & 7124 & 2-2 \\
4 & 5 & 2006-01-29 00:00:00 & rochester knighthawks & xcel energy center & l 9-10 & none & 7544 & 3-2 \\
5 & 6 & 2006-02-03 00:00:00 & @ edmonton rush & rexall place & w 7-6 & none & 8745 & 3-3 \\
6 & 7 & 2006-02-10 00:00:00 & philadelphia wings & xcel energy center & w 11-10 & none & 7524 & 4-3 \\
7 & 8 & 2006-02-18 00:00:00 & @ buffalo bandits & hsbc arena & l 9-14 & none & 12458 & 4-4 \\
8 & 9 & 2006-03-03 00:00:00 & @ toronto rock & air canada centre & l 8-13 & none & 15830 & 4-5 \\
9 & 10 & 2006-03-04 00:00:00 & @ buffalo bandits & hsbc arena & w 11-8 & none & 10961 & 5-5 \\
10 & 11 & 2006-03-17 00:00:00 & @ portland lumberjax & rose garden & w 14-12 & none & 5487 & 6-5 \\
11 & 12 & 2006-03-24 00:00:00 & buffalo bandits & xcel energy center & l 11-13 & none & 9533 & 6-6 \\
12 & 13 & 2006-04-01 00:00:00 & toronto rock & xcel energy center & w 10-9 & none & 10084 & 7-6 \\
13 & 14 & 2006-04-08 00:00:00 & @ rochester knighthawks & blue cross arena & l 9-10 & none & 10352 & 7-7 \\
14 & 15 & 2006-04-09 00:00:00 & san jose stealth & xcel energy center & w 9-8 & ot & 7044 & 8-7 \\
15 & 16 & 2006-04-15 00:00:00 & portland lumberjax & xcel energy center & l 8-13 & none & 10104 & 8-8 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( * ) where game > 6 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>date</th>
<th>opponent</th>
<th>location</th>
<th>score</th>
<th>ot</th>
<th>attendance</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2006-01-06 00:00:00</td>
<td>philadelphia wings</td>
<td>xcel energy center</td>
<td>l 11-15</td>
<td>none</td>
<td>8024</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2006-01-14 00:00:00</td>
<td>@ philadelphia wings</td>
<td>wachovia center</td>
<td>w 13-10</td>
<td>none</td>
<td>11874</td>
<td>1-1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2006-01-20 00:00:00</td>
<td>@ calgary roughnecks</td>
<td>pengrowth saddledome</td>
<td>w 12-8</td>
<td>none</td>
<td>10637</td>
<td>2-1</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2006-01-21 00:00:00</td>
<td>rochester knighthawks</td>
<td>xcel energy center</td>
<td>l 6-12</td>
<td>none</td>
<td>7124</td>
<td>2-2</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2006-01-29 00:00:00</td>
<td>rochester knighthawks</td>
<td>xcel energy center</td>
<td>l 9-10</td>
<td>none</td>
<td>7544</td>
<td>3-2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2006-02-03 00:00:00</td>
<td>@ edmonton rush</td>
<td>rexall place</td>
<td>w 7-6</td>
<td>none</td>
<td>8745</td>
<td>3-3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2006-02-10 00:00:00</td>
<td>philadelphia wings</td>
<td>xcel energy center</td>
<td>w 11-10</td>
<td>none</td>
<td>7524</td>
<td>4-3</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2006-02-18 00:00:00</td>
<td>@ buffalo bandits</td>
<td>hsbc arena</td>
<td>l 9-14</td>
<td>none</td>
<td>12458</td>
<td>4-4</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2006-03-03 00:00:00</td>
<td>@ toronto rock</td>
<td>air canada centre</td>
<td>l 8-13</td>
<td>none</td>
<td>15830</td>
<td>4-5</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2006-03-04 00:00:00</td>
<td>@ buffalo bandits</td>
<td>hsbc arena</td>
<td>w 11-8</td>
<td>none</td>
<td>10961</td>
<td>5-5</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2006-03-17 00:00:00</td>
<td>@ portland lumberjax</td>
<td>rose garden</td>
<td>w 14-12</td>
<td>none</td>
<td>5487</td>
<td>6-5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>2006-03-24 00:00:00</td>
<td>buffalo bandits</td>
<td>xcel energy center</td>
<td>l 11-13</td>
<td>none</td>
<td>9533</td>
<td>6-6</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>2006-04-01 00:00:00</td>
<td>toronto rock</td>
<td>xcel energy center</td>
<td>w 10-9</td>
<td>none</td>
<td>10084</td>
<td>7-6</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>2006-04-08 00:00:00</td>
<td>@ rochester knighthawks</td>
<td>blue cross arena</td>
<td>l 9-10</td>
<td>none</td>
<td>10352</td>
<td>7-7</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>2006-04-09 00:00:00</td>
<td>san jose stealth</td>
<td>xcel energy center</td>
<td>w 9-8</td>
<td>ot</td>
<td>7044</td>
<td>8-7</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>2006-04-15 00:00:00</td>
<td>portland lumberjax</td>
<td>xcel energy center</td>
<td>l 8-13</td>
<td>none</td>
<td>10104</td>
<td>8-8</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( * ) where game > 6 <table_name> : table | | game | date | opponent | location | score | ot | attendance | record |
|---:|-------:|:--------------------|:------------------------|:---------------------|:--------|:-----|-------------:|:---------|
| 0 | 1 | 2006-01-06 00:00:00 | philadelphia wings | xcel energy center | l 11-15 | none | 8024 | 0-1 |
| 1 | 2 | 2006-01-14 00:00:00 | @ philadelphia wings | wachovia center | w 13-10 | none | 11874 | 1-1 |
| 2 | 3 | 2006-01-20 00:00:00 | @ calgary roughnecks | pengrowth saddledome | w 12-8 | none | 10637 | 2-1 |
| 3 | 4 | 2006-01-21 00:00:00 | rochester knighthawks | xcel energy center | l 6-12 | none | 7124 | 2-2 |
| 4 | 5 | 2006-01-29 00:00:00 | rochester knighthawks | xcel energy center | l 9-10 | none | 7544 | 3-2 |
| 5 | 6 | 2006-02-03 00:00:00 | @ edmonton rush | rexall place | w 7-6 | none | 8745 | 3-3 |
| 6 | 7 | 2006-02-10 00:00:00 | philadelphia wings | xcel energy center | w 11-10 | none | 7524 | 4-3 |
| 7 | 8 | 2006-02-18 00:00:00 | @ buffalo bandits | hsbc arena | l 9-14 | none | 12458 | 4-4 |
| 8 | 9 | 2006-03-03 00:00:00 | @ toronto rock | air canada centre | l 8-13 | none | 15830 | 4-5 |
| 9 | 10 | 2006-03-04 00:00:00 | @ buffalo bandits | hsbc arena | w 11-8 | none | 10961 | 5-5 |
| 10 | 11 | 2006-03-17 00:00:00 | @ portland lumberjax | rose garden | w 14-12 | none | 5487 | 6-5 |
| 11 | 12 | 2006-03-24 00:00:00 | buffalo bandits | xcel energy center | l 11-13 | none | 9533 | 6-6 |
| 12 | 13 | 2006-04-01 00:00:00 | toronto rock | xcel energy center | w 10-9 | none | 10084 | 7-6 |
| 13 | 14 | 2006-04-08 00:00:00 | @ rochester knighthawks | blue cross arena | l 9-10 | none | 10352 | 7-7 |
| 14 | 15 | 2006-04-09 00:00:00 | san jose stealth | xcel energy center | w 9-8 | ot | 7044 | 8-7 |
| 15 | 16 | 2006-04-15 00:00:00 | portland lumberjax | xcel energy center | l 8-13 | none | 10104 | 8-8 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 3 | | [
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] |
select count ( * ) where make/model = 'new flyer' col : make/model | series | model | year | notes row 1 : new flyer | 101-135 | d40lfr | 2010 | none row 2 : new flyer | 140-169 | d40lfr | 2011 | 140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps row 3 : new flyer | 201-230 | d40lf | 2004 | 204 retired due to fire row 4 : new flyer | 231-260 | d40lf | 2005 | none row 5 : new flyer | 270-281 | d40lf | 2007 | none row 6 : mci | 301-334 | classic | 1988 | all retired row 7 : new flyer | 340-366 | d40 | 1992 | 365 remains, used only during rush hour row 8 : new flyer | 370-399 | d40 | 1994 | 370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour row 9 : new flyer | 401-443 | d40lf | 1998 | all have been rebuilt row 10 : new flyer | 444-504 | d40lf | 1999 | all have been rebuilt row 11 : new flyer | 510-561 | d40lf | 2002 | being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545 row 12 : new flyer | 570-599 | d40lf | 2003 | none row 13 : new flyer | 601-640 | d40lfr | 2011 | 601 603 605 wrap for rt row 14 : new flyer | 671-699 | d40 | 1994 | 684 retired, used only during rush hour row 15 : new flyer | 701-733 | d40lfr | 2008 | none row 16 : new flyer | 735-799 | d40lfr | 2009 | none row 17 : new flyer | 800-829 | d40lfr | 2013 | 800-830 now inservice 822 had a fire row 18 : new flyer | 901-910 | invero/d40i | 2004 | ex701-710 only used for rush hour row 19 : new flyer | 911-925 | d30lf | 1996 | all rebuild row 20 : new flyer | 930-949 | d30lf | 2001 | 931 rebuild row 21 : new flyer | 971-990 | d60lf | 2003 | ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service row 22 : new flyer | 991-993 | d40lf | 1994 | all rebuilt, used only during rush hour | col : count ( "*" ) row 1 : 21 | select count ( * ) where make/model = 'new flyer' <table_name> : table \begin{tabular}{llllll}
\toprule
& make/model & series & model & year & notes \\
\midrule
0 & new flyer & 101-135 & d40lfr & 2010 & none \\
1 & new flyer & 140-169 & d40lfr & 2011 & 140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps \\
2 & new flyer & 201-230 & d40lf & 2004 & 204 retired due to fire \\
3 & new flyer & 231-260 & d40lf & 2005 & none \\
4 & new flyer & 270-281 & d40lf & 2007 & none \\
5 & mci & 301-334 & classic & 1988 & all retired \\
6 & new flyer & 340-366 & d40 & 1992 & 365 remains, used only during rush hour \\
7 & new flyer & 370-399 & d40 & 1994 & 370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour \\
8 & new flyer & 401-443 & d40lf & 1998 & all have been rebuilt \\
9 & new flyer & 444-504 & d40lf & 1999 & all have been rebuilt \\
10 & new flyer & 510-561 & d40lf & 2002 & being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545 \\
11 & new flyer & 570-599 & d40lf & 2003 & none \\
12 & new flyer & 601-640 & d40lfr & 2011 & 601 603 605 wrap for rt \\
13 & new flyer & 671-699 & d40 & 1994 & 684 retired, used only during rush hour \\
14 & new flyer & 701-733 & d40lfr & 2008 & none \\
15 & new flyer & 735-799 & d40lfr & 2009 & none \\
16 & new flyer & 800-829 & d40lfr & 2013 & 800-830 now inservice 822 had a fire \\
17 & new flyer & 901-910 & invero/d40i & 2004 & ex701-710 only used for rush hour \\
18 & new flyer & 911-925 & d30lf & 1996 & all rebuild \\
19 & new flyer & 930-949 & d30lf & 2001 & 931 rebuild \\
20 & new flyer & 971-990 & d60lf & 2003 & ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service \\
21 & new flyer & 991-993 & d40lf & 1994 & all rebuilt, used only during rush hour \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 21 \\
\bottomrule
\end{tabular}
| select count ( * ) where make/model = 'new flyer' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>make/model</th>
<th>series</th>
<th>model</th>
<th>year</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>new flyer</td>
<td>101-135</td>
<td>d40lfr</td>
<td>2010</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>new flyer</td>
<td>140-169</td>
<td>d40lfr</td>
<td>2011</td>
<td>140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps</td>
</tr>
<tr>
<th>2</th>
<td>new flyer</td>
<td>201-230</td>
<td>d40lf</td>
<td>2004</td>
<td>204 retired due to fire</td>
</tr>
<tr>
<th>3</th>
<td>new flyer</td>
<td>231-260</td>
<td>d40lf</td>
<td>2005</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>new flyer</td>
<td>270-281</td>
<td>d40lf</td>
<td>2007</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>mci</td>
<td>301-334</td>
<td>classic</td>
<td>1988</td>
<td>all retired</td>
</tr>
<tr>
<th>6</th>
<td>new flyer</td>
<td>340-366</td>
<td>d40</td>
<td>1992</td>
<td>365 remains, used only during rush hour</td>
</tr>
<tr>
<th>7</th>
<td>new flyer</td>
<td>370-399</td>
<td>d40</td>
<td>1994</td>
<td>370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour</td>
</tr>
<tr>
<th>8</th>
<td>new flyer</td>
<td>401-443</td>
<td>d40lf</td>
<td>1998</td>
<td>all have been rebuilt</td>
</tr>
<tr>
<th>9</th>
<td>new flyer</td>
<td>444-504</td>
<td>d40lf</td>
<td>1999</td>
<td>all have been rebuilt</td>
</tr>
<tr>
<th>10</th>
<td>new flyer</td>
<td>510-561</td>
<td>d40lf</td>
<td>2002</td>
<td>being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545</td>
</tr>
<tr>
<th>11</th>
<td>new flyer</td>
<td>570-599</td>
<td>d40lf</td>
<td>2003</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>new flyer</td>
<td>601-640</td>
<td>d40lfr</td>
<td>2011</td>
<td>601 603 605 wrap for rt</td>
</tr>
<tr>
<th>13</th>
<td>new flyer</td>
<td>671-699</td>
<td>d40</td>
<td>1994</td>
<td>684 retired, used only during rush hour</td>
</tr>
<tr>
<th>14</th>
<td>new flyer</td>
<td>701-733</td>
<td>d40lfr</td>
<td>2008</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>new flyer</td>
<td>735-799</td>
<td>d40lfr</td>
<td>2009</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>new flyer</td>
<td>800-829</td>
<td>d40lfr</td>
<td>2013</td>
<td>800-830 now inservice 822 had a fire</td>
</tr>
<tr>
<th>17</th>
<td>new flyer</td>
<td>901-910</td>
<td>invero/d40i</td>
<td>2004</td>
<td>ex701-710 only used for rush hour</td>
</tr>
<tr>
<th>18</th>
<td>new flyer</td>
<td>911-925</td>
<td>d30lf</td>
<td>1996</td>
<td>all rebuild</td>
</tr>
<tr>
<th>19</th>
<td>new flyer</td>
<td>930-949</td>
<td>d30lf</td>
<td>2001</td>
<td>931 rebuild</td>
</tr>
<tr>
<th>20</th>
<td>new flyer</td>
<td>971-990</td>
<td>d60lf</td>
<td>2003</td>
<td>ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service</td>
</tr>
<tr>
<th>21</th>
<td>new flyer</td>
<td>991-993</td>
<td>d40lf</td>
<td>1994</td>
<td>all rebuilt, used only during rush hour</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>21</td>
</tr>
</tbody>
</table> | select count ( * ) where make/model = 'new flyer' <table_name> : table | | make/model | series | model | year | notes |
|---:|:-------------|:---------|:------------|-------:|:----------------------------------------------------------------------------------------|
| 0 | new flyer | 101-135 | d40lfr | 2010 | none |
| 1 | new flyer | 140-169 | d40lfr | 2011 | 140-143 145-153 155-169 wrap for rt 144 and 154 lost there rt wraps |
| 2 | new flyer | 201-230 | d40lf | 2004 | 204 retired due to fire |
| 3 | new flyer | 231-260 | d40lf | 2005 | none |
| 4 | new flyer | 270-281 | d40lf | 2007 | none |
| 5 | mci | 301-334 | classic | 1988 | all retired |
| 6 | new flyer | 340-366 | d40 | 1992 | 365 remains, used only during rush hour |
| 7 | new flyer | 370-399 | d40 | 1994 | 370 371 372 373 374 379 380 390 395? 397 398 399 retired, used only during rush hour |
| 8 | new flyer | 401-443 | d40lf | 1998 | all have been rebuilt |
| 9 | new flyer | 444-504 | d40lf | 1999 | all have been rebuilt |
| 10 | new flyer | 510-561 | d40lf | 2002 | being rebuilt 510 513 515 516 517 519 520 521 522 529 532 534 536 537 539 540 545 |
| 11 | new flyer | 570-599 | d40lf | 2003 | none |
| 12 | new flyer | 601-640 | d40lfr | 2011 | 601 603 605 wrap for rt |
| 13 | new flyer | 671-699 | d40 | 1994 | 684 retired, used only during rush hour |
| 14 | new flyer | 701-733 | d40lfr | 2008 | none |
| 15 | new flyer | 735-799 | d40lfr | 2009 | none |
| 16 | new flyer | 800-829 | d40lfr | 2013 | 800-830 now inservice 822 had a fire |
| 17 | new flyer | 901-910 | invero/d40i | 2004 | ex701-710 only used for rush hour |
| 18 | new flyer | 911-925 | d30lf | 1996 | all rebuild |
| 19 | new flyer | 930-949 | d30lf | 2001 | 931 rebuild |
| 20 | new flyer | 971-990 | d60lf | 2003 | ex octranspo most units are between ex 6302-6338 971 973 976 977 979 are now in service |
| 21 | new flyer | 991-993 | d40lf | 1994 | all rebuilt, used only during rush hour | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 21 | | [
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select produced where model = '735i' col : model | volume | engine | fuel | power/torque | years produced | produced row 1 : 728i | 2.8l | m52b28 i6 | petrol | 142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft) | 1996-2001 | 38947 row 2 : 728il | 2.8l | m52b28 i6 | petrol | 142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft) | 1996-2001 | 6816 row 3 : 730i | 3.0l | m60b30 v8 | petrol | 160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft) | 1994-1996 | 20876 row 4 : 730il | 3.0l | m60b30 v8 | petrol | 160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft) | 1994-1996 | 2137 row 5 : 735i | 3.5l | m62b35 v8 | petrol | 173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft) | 1994-1997 | 21481 row 6 : 735i | 3.5l | m62tub35 v8 | petrol | 174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft) | 1998-2001 | none row 7 : 735il | 3.5l | m62b35 v8 | petrol | 173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft) | 1994-1997 | 6963 row 8 : 735il | 3.5l | m62tub35 v8 | petrol | 174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft) | 1998-2001 | none row 9 : 740i | 4.0l | m60b40 v8 | petrol | 210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft) | 1994-1996 | none row 10 : 740il | 4.0l | m60b40 v8 | petrol | 210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft) | 1994-1996 | none row 11 : 740i | 4.4l | m62b44 v8 | petrol | 210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft) | 1996-1998 | 88853 row 12 : 740i | 4.4l | m62tub44 v8 | petrol | 210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft) | 1998-2001 | none row 13 : 740il | 4.4l | m62b44 v8 | petrol | 210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft) | 1996-1998 | 91431 row 14 : 740il | 4.4l | m62tub44 v8 | petrol | 210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft) | 1998-2001 | none row 15 : 750i-il | 5.4l | m73b54 v12 | petrol | 240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft) | 1995-1997 | 15759 row 16 : 750i-il | 5.4l | m73tub54 v12 | petrol | 240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft) | 1998-2001 | 1032 row 17 : 725tds | 2.5l | m51d25 turbocharged i6 | diesel | 105 kw (143 ps; 141 hp) / 280 n·m (207 lb·ft) | 1995-2001 | 9053 row 18 : 730d | 2.9l | m57d30 turbocharged i6 | diesel | 142 kw (193 ps; 190 hp) / 410 n·m (302 lb·ft) | 1998-2001 | 12336 row 19 : 740d | 3.9l | m67d40 turbocharged v8 | diesel | 180 kw (245 ps; 241 hp) / 560 n·m (413 lb·ft) | 1998-2001 | 3450 | col : produced row 1 : 21481 row 2 : none | select produced where model = '735i' <table_name> : table \begin{tabular}{llllllll}
\toprule
& model & volume & engine & fuel & power/torque & years produced & produced \\
\midrule
0 & 728i & 2.8l & m52b28 i6 & petrol & 142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft) & 1996-2001 & 38947 \\
1 & 728il & 2.8l & m52b28 i6 & petrol & 142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft) & 1996-2001 & 6816 \\
2 & 730i & 3.0l & m60b30 v8 & petrol & 160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft) & 1994-1996 & 20876 \\
3 & 730il & 3.0l & m60b30 v8 & petrol & 160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft) & 1994-1996 & 2137 \\
4 & 735i & 3.5l & m62b35 v8 & petrol & 173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft) & 1994-1997 & 21481 \\
5 & 735i & 3.5l & m62tub35 v8 & petrol & 174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft) & 1998-2001 & none \\
6 & 735il & 3.5l & m62b35 v8 & petrol & 173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft) & 1994-1997 & 6963 \\
7 & 735il & 3.5l & m62tub35 v8 & petrol & 174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft) & 1998-2001 & none \\
8 & 740i & 4.0l & m60b40 v8 & petrol & 210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft) & 1994-1996 & none \\
9 & 740il & 4.0l & m60b40 v8 & petrol & 210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft) & 1994-1996 & none \\
10 & 740i & 4.4l & m62b44 v8 & petrol & 210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft) & 1996-1998 & 88853 \\
11 & 740i & 4.4l & m62tub44 v8 & petrol & 210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft) & 1998-2001 & none \\
12 & 740il & 4.4l & m62b44 v8 & petrol & 210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft) & 1996-1998 & 91431 \\
13 & 740il & 4.4l & m62tub44 v8 & petrol & 210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft) & 1998-2001 & none \\
14 & 750i-il & 5.4l & m73b54 v12 & petrol & 240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft) & 1995-1997 & 15759 \\
15 & 750i-il & 5.4l & m73tub54 v12 & petrol & 240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft) & 1998-2001 & 1032 \\
16 & 725tds & 2.5l & m51d25 turbocharged i6 & diesel & 105 kw (143 ps; 141 hp) / 280 n·m (207 lb·ft) & 1995-2001 & 9053 \\
17 & 730d & 2.9l & m57d30 turbocharged i6 & diesel & 142 kw (193 ps; 190 hp) / 410 n·m (302 lb·ft) & 1998-2001 & 12336 \\
18 & 740d & 3.9l & m67d40 turbocharged v8 & diesel & 180 kw (245 ps; 241 hp) / 560 n·m (413 lb·ft) & 1998-2001 & 3450 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& produced \\
\midrule
0 & 21481 \\
1 & none \\
\bottomrule
\end{tabular}
| select produced where model = '735i' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>model</th>
<th>volume</th>
<th>engine</th>
<th>fuel</th>
<th>power/torque</th>
<th>years produced</th>
<th>produced</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>728i</td>
<td>2.8l</td>
<td>m52b28 i6</td>
<td>petrol</td>
<td>142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft)</td>
<td>1996-2001</td>
<td>38947</td>
</tr>
<tr>
<th>1</th>
<td>728il</td>
<td>2.8l</td>
<td>m52b28 i6</td>
<td>petrol</td>
<td>142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft)</td>
<td>1996-2001</td>
<td>6816</td>
</tr>
<tr>
<th>2</th>
<td>730i</td>
<td>3.0l</td>
<td>m60b30 v8</td>
<td>petrol</td>
<td>160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft)</td>
<td>1994-1996</td>
<td>20876</td>
</tr>
<tr>
<th>3</th>
<td>730il</td>
<td>3.0l</td>
<td>m60b30 v8</td>
<td>petrol</td>
<td>160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft)</td>
<td>1994-1996</td>
<td>2137</td>
</tr>
<tr>
<th>4</th>
<td>735i</td>
<td>3.5l</td>
<td>m62b35 v8</td>
<td>petrol</td>
<td>173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft)</td>
<td>1994-1997</td>
<td>21481</td>
</tr>
<tr>
<th>5</th>
<td>735i</td>
<td>3.5l</td>
<td>m62tub35 v8</td>
<td>petrol</td>
<td>174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft)</td>
<td>1998-2001</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>735il</td>
<td>3.5l</td>
<td>m62b35 v8</td>
<td>petrol</td>
<td>173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft)</td>
<td>1994-1997</td>
<td>6963</td>
</tr>
<tr>
<th>7</th>
<td>735il</td>
<td>3.5l</td>
<td>m62tub35 v8</td>
<td>petrol</td>
<td>174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft)</td>
<td>1998-2001</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>740i</td>
<td>4.0l</td>
<td>m60b40 v8</td>
<td>petrol</td>
<td>210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft)</td>
<td>1994-1996</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>740il</td>
<td>4.0l</td>
<td>m60b40 v8</td>
<td>petrol</td>
<td>210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft)</td>
<td>1994-1996</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>740i</td>
<td>4.4l</td>
<td>m62b44 v8</td>
<td>petrol</td>
<td>210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft)</td>
<td>1996-1998</td>
<td>88853</td>
</tr>
<tr>
<th>11</th>
<td>740i</td>
<td>4.4l</td>
<td>m62tub44 v8</td>
<td>petrol</td>
<td>210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft)</td>
<td>1998-2001</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>740il</td>
<td>4.4l</td>
<td>m62b44 v8</td>
<td>petrol</td>
<td>210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft)</td>
<td>1996-1998</td>
<td>91431</td>
</tr>
<tr>
<th>13</th>
<td>740il</td>
<td>4.4l</td>
<td>m62tub44 v8</td>
<td>petrol</td>
<td>210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft)</td>
<td>1998-2001</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>750i-il</td>
<td>5.4l</td>
<td>m73b54 v12</td>
<td>petrol</td>
<td>240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft)</td>
<td>1995-1997</td>
<td>15759</td>
</tr>
<tr>
<th>15</th>
<td>750i-il</td>
<td>5.4l</td>
<td>m73tub54 v12</td>
<td>petrol</td>
<td>240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft)</td>
<td>1998-2001</td>
<td>1032</td>
</tr>
<tr>
<th>16</th>
<td>725tds</td>
<td>2.5l</td>
<td>m51d25 turbocharged i6</td>
<td>diesel</td>
<td>105 kw (143 ps; 141 hp) / 280 n·m (207 lb·ft)</td>
<td>1995-2001</td>
<td>9053</td>
</tr>
<tr>
<th>17</th>
<td>730d</td>
<td>2.9l</td>
<td>m57d30 turbocharged i6</td>
<td>diesel</td>
<td>142 kw (193 ps; 190 hp) / 410 n·m (302 lb·ft)</td>
<td>1998-2001</td>
<td>12336</td>
</tr>
<tr>
<th>18</th>
<td>740d</td>
<td>3.9l</td>
<td>m67d40 turbocharged v8</td>
<td>diesel</td>
<td>180 kw (245 ps; 241 hp) / 560 n·m (413 lb·ft)</td>
<td>1998-2001</td>
<td>3450</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>produced</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>21481</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
</tr>
</tbody>
</table> | select produced where model = '735i' <table_name> : table | | model | volume | engine | fuel | power/torque | years produced | produced |
|---:|:--------|:---------|:-----------------------|:-------|:----------------------------------------------|:-----------------|:-----------|
| 0 | 728i | 2.8l | m52b28 i6 | petrol | 142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft) | 1996-2001 | 38947 |
| 1 | 728il | 2.8l | m52b28 i6 | petrol | 142 kw (193 ps; 190 hp) / 280 n·m (207 lb·ft) | 1996-2001 | 6816 |
| 2 | 730i | 3.0l | m60b30 v8 | petrol | 160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft) | 1994-1996 | 20876 |
| 3 | 730il | 3.0l | m60b30 v8 | petrol | 160 kw (218 ps; 215 hp) / 290 n·m (214 lb·ft) | 1994-1996 | 2137 |
| 4 | 735i | 3.5l | m62b35 v8 | petrol | 173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft) | 1994-1997 | 21481 |
| 5 | 735i | 3.5l | m62tub35 v8 | petrol | 174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft) | 1998-2001 | none |
| 6 | 735il | 3.5l | m62b35 v8 | petrol | 173 kw (235 ps; 232 hp) / 320 n·m (236 lb·ft) | 1994-1997 | 6963 |
| 7 | 735il | 3.5l | m62tub35 v8 | petrol | 174 kw (237 ps; 233 hp) / 345 n·m (254 lb·ft) | 1998-2001 | none |
| 8 | 740i | 4.0l | m60b40 v8 | petrol | 210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft) | 1994-1996 | none |
| 9 | 740il | 4.0l | m60b40 v8 | petrol | 210 kw (286 ps; 282 hp) / 400 n·m (295 lb·ft) | 1994-1996 | none |
| 10 | 740i | 4.4l | m62b44 v8 | petrol | 210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft) | 1996-1998 | 88853 |
| 11 | 740i | 4.4l | m62tub44 v8 | petrol | 210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft) | 1998-2001 | none |
| 12 | 740il | 4.4l | m62b44 v8 | petrol | 210 kw (286 ps; 282 hp) / 420 n·m (310 lb·ft) | 1996-1998 | 91431 |
| 13 | 740il | 4.4l | m62tub44 v8 | petrol | 210 kw (286 ps; 282 hp) / 440 n·m (325 lb·ft) | 1998-2001 | none |
| 14 | 750i-il | 5.4l | m73b54 v12 | petrol | 240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft) | 1995-1997 | 15759 |
| 15 | 750i-il | 5.4l | m73tub54 v12 | petrol | 240 kw (326 ps; 322 hp) / 490 n·m (361 lb·ft) | 1998-2001 | 1032 |
| 16 | 725tds | 2.5l | m51d25 turbocharged i6 | diesel | 105 kw (143 ps; 141 hp) / 280 n·m (207 lb·ft) | 1995-2001 | 9053 |
| 17 | 730d | 2.9l | m57d30 turbocharged i6 | diesel | 142 kw (193 ps; 190 hp) / 410 n·m (302 lb·ft) | 1998-2001 | 12336 |
| 18 | 740d | 3.9l | m67d40 turbocharged v8 | diesel | 180 kw (245 ps; 241 hp) / 560 n·m (413 lb·ft) | 1998-2001 | 3450 | | | | produced |
|---:|:-----------|
| 0 | 21481 |
| 1 | none | | [
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select count ( * ) where venue = 'paris, france' col : year | competition | venue | position | event row 1 : 1997 | world indoor championships | paris, france | 5th | 60 m hurdles row 2 : 1997 | usa outdoor championships | indianapolis, united states | 1st | 100 m hurdles row 3 : 1998 | grand prix final | moscow, russia | 2nd | 100 m hurdles row 4 : 1998 | usa indoor championships | none | 1st | 60 m hurdles row 5 : 1999 | world indoor championships | maebashi, japan | 6th | 60 m hurdles row 6 : 2000 | olympic games | sydney, australia | 3rd | 100 m hurdles row 7 : 2000 | grand prix final | doha, qatar | 4th | 100 m hurdles row 8 : 2002 | grand prix final | paris, france | 7th | 100 m hurdles row 9 : 2002 | usa indoor championships | none | 1st | 60 m hurdles row 10 : 2003 | world indoor championships | birmingham, england | 3rd | 60 m hurdles row 11 : 2003 | world athletics final | monaco | 6th | 100 m hurdles row 12 : 2004 | olympic games | athens, greece | 3rd | 100 m hurdles | col : count ( "*" ) row 1 : 2 | select count ( * ) where venue = 'paris, france' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & competition & venue & position & event \\
\midrule
0 & 1997 & world indoor championships & paris, france & 5th & 60 m hurdles \\
1 & 1997 & usa outdoor championships & indianapolis, united states & 1st & 100 m hurdles \\
2 & 1998 & grand prix final & moscow, russia & 2nd & 100 m hurdles \\
3 & 1998 & usa indoor championships & none & 1st & 60 m hurdles \\
4 & 1999 & world indoor championships & maebashi, japan & 6th & 60 m hurdles \\
5 & 2000 & olympic games & sydney, australia & 3rd & 100 m hurdles \\
6 & 2000 & grand prix final & doha, qatar & 4th & 100 m hurdles \\
7 & 2002 & grand prix final & paris, france & 7th & 100 m hurdles \\
8 & 2002 & usa indoor championships & none & 1st & 60 m hurdles \\
9 & 2003 & world indoor championships & birmingham, england & 3rd & 60 m hurdles \\
10 & 2003 & world athletics final & monaco & 6th & 100 m hurdles \\
11 & 2004 & olympic games & athens, greece & 3rd & 100 m hurdles \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( * ) where venue = 'paris, france' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>competition</th>
<th>venue</th>
<th>position</th>
<th>event</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1997</td>
<td>world indoor championships</td>
<td>paris, france</td>
<td>5th</td>
<td>60 m hurdles</td>
</tr>
<tr>
<th>1</th>
<td>1997</td>
<td>usa outdoor championships</td>
<td>indianapolis, united states</td>
<td>1st</td>
<td>100 m hurdles</td>
</tr>
<tr>
<th>2</th>
<td>1998</td>
<td>grand prix final</td>
<td>moscow, russia</td>
<td>2nd</td>
<td>100 m hurdles</td>
</tr>
<tr>
<th>3</th>
<td>1998</td>
<td>usa indoor championships</td>
<td>none</td>
<td>1st</td>
<td>60 m hurdles</td>
</tr>
<tr>
<th>4</th>
<td>1999</td>
<td>world indoor championships</td>
<td>maebashi, japan</td>
<td>6th</td>
<td>60 m hurdles</td>
</tr>
<tr>
<th>5</th>
<td>2000</td>
<td>olympic games</td>
<td>sydney, australia</td>
<td>3rd</td>
<td>100 m hurdles</td>
</tr>
<tr>
<th>6</th>
<td>2000</td>
<td>grand prix final</td>
<td>doha, qatar</td>
<td>4th</td>
<td>100 m hurdles</td>
</tr>
<tr>
<th>7</th>
<td>2002</td>
<td>grand prix final</td>
<td>paris, france</td>
<td>7th</td>
<td>100 m hurdles</td>
</tr>
<tr>
<th>8</th>
<td>2002</td>
<td>usa indoor championships</td>
<td>none</td>
<td>1st</td>
<td>60 m hurdles</td>
</tr>
<tr>
<th>9</th>
<td>2003</td>
<td>world indoor championships</td>
<td>birmingham, england</td>
<td>3rd</td>
<td>60 m hurdles</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>world athletics final</td>
<td>monaco</td>
<td>6th</td>
<td>100 m hurdles</td>
</tr>
<tr>
<th>11</th>
<td>2004</td>
<td>olympic games</td>
<td>athens, greece</td>
<td>3rd</td>
<td>100 m hurdles</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( * ) where venue = 'paris, france' <table_name> : table | | year | competition | venue | position | event |
|---:|-------:|:---------------------------|:----------------------------|:-----------|:--------------|
| 0 | 1997 | world indoor championships | paris, france | 5th | 60 m hurdles |
| 1 | 1997 | usa outdoor championships | indianapolis, united states | 1st | 100 m hurdles |
| 2 | 1998 | grand prix final | moscow, russia | 2nd | 100 m hurdles |
| 3 | 1998 | usa indoor championships | none | 1st | 60 m hurdles |
| 4 | 1999 | world indoor championships | maebashi, japan | 6th | 60 m hurdles |
| 5 | 2000 | olympic games | sydney, australia | 3rd | 100 m hurdles |
| 6 | 2000 | grand prix final | doha, qatar | 4th | 100 m hurdles |
| 7 | 2002 | grand prix final | paris, france | 7th | 100 m hurdles |
| 8 | 2002 | usa indoor championships | none | 1st | 60 m hurdles |
| 9 | 2003 | world indoor championships | birmingham, england | 3rd | 60 m hurdles |
| 10 | 2003 | world athletics final | monaco | 6th | 100 m hurdles |
| 11 | 2004 | olympic games | athens, greece | 3rd | 100 m hurdles | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 2 | | [
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select height of pylons where country = 'usa' col : tramway | country | city | height of pylons | span width, leaning straight line | span width, horizontal measurement | height of cable over ground | year of inauguration | notes row 1 : peak 2 peak gondola | canada | whistler | 65m | 3024 m | 3019 m | 436 m | 2008 | 3s aerial tramway constructed by doppelmayr row 2 : hut of regensburg material transport aerial railway | austria | falbeson | none | none | none | 430 m | none | none row 3 : vanoise express | france | vanoise | none | 1850 m | 1800 m | 380 m | 2003 | none row 4 : aiguille du midi | france | chamonix | none | 2867 m | 2500 m | none | 1955 | 2nd section row 5 : vallee blanche aerial tramway | france | mont blanc | none | 2831 m, 1684 m | span is almost horizontal | appr. 300 m | 1958 | rock anchored support structure row 6 : 3s aerial tramway | austria | kitzbuhel | 0 m, 80m | 2507 m | none | 400 m | 2004 | none row 7 : sandia peak tramway | usa | albuquerque | 70.7 m, 21.33 m | 2353 m | none | 274 m | 1966 | none row 8 : feldmoos-chli-titlis aerial tramway | switzerland | titlis | 37.6 m | 3476,2 m | none | none | 1979 | temp. site tramway, demolished in 1986 | col : height of pylons row 1 : 70.7 m, 21.33 m | select height of pylons where country = 'usa' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& tramway & country & city & height of pylons & span width, leaning straight line & span width, horizontal measurement & height of cable over ground & year of inauguration & notes \\
\midrule
0 & peak 2 peak gondola & canada & whistler & 65m & 3024 m & 3019 m & 436 m & 2008 & 3s aerial tramway constructed by doppelmayr \\
1 & hut of regensburg material transport aerial railway & austria & falbeson & none & none & none & 430 m & none & none \\
2 & vanoise express & france & vanoise & none & 1850 m & 1800 m & 380 m & 2003 & none \\
3 & aiguille du midi & france & chamonix & none & 2867 m & 2500 m & none & 1955 & 2nd section \\
4 & vallee blanche aerial tramway & france & mont blanc & none & 2831 m, 1684 m & span is almost horizontal & appr. 300 m & 1958 & rock anchored support structure \\
5 & 3s aerial tramway & austria & kitzbuhel & 0 m, 80m & 2507 m & none & 400 m & 2004 & none \\
6 & sandia peak tramway & usa & albuquerque & 70.7 m, 21.33 m & 2353 m & none & 274 m & 1966 & none \\
7 & feldmoos-chli-titlis aerial tramway & switzerland & titlis & 37.6 m & 3476,2 m & none & none & 1979 & temp. site tramway, demolished in 1986 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& height of pylons \\
\midrule
0 & 70.7 m, 21.33 m \\
\bottomrule
\end{tabular}
| select height of pylons where country = 'usa' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>tramway</th>
<th>country</th>
<th>city</th>
<th>height of pylons</th>
<th>span width, leaning straight line</th>
<th>span width, horizontal measurement</th>
<th>height of cable over ground</th>
<th>year of inauguration</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>peak 2 peak gondola</td>
<td>canada</td>
<td>whistler</td>
<td>65m</td>
<td>3024 m</td>
<td>3019 m</td>
<td>436 m</td>
<td>2008</td>
<td>3s aerial tramway constructed by doppelmayr</td>
</tr>
<tr>
<th>1</th>
<td>hut of regensburg material transport aerial railway</td>
<td>austria</td>
<td>falbeson</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>430 m</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>vanoise express</td>
<td>france</td>
<td>vanoise</td>
<td>none</td>
<td>1850 m</td>
<td>1800 m</td>
<td>380 m</td>
<td>2003</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>aiguille du midi</td>
<td>france</td>
<td>chamonix</td>
<td>none</td>
<td>2867 m</td>
<td>2500 m</td>
<td>none</td>
<td>1955</td>
<td>2nd section</td>
</tr>
<tr>
<th>4</th>
<td>vallee blanche aerial tramway</td>
<td>france</td>
<td>mont blanc</td>
<td>none</td>
<td>2831 m, 1684 m</td>
<td>span is almost horizontal</td>
<td>appr. 300 m</td>
<td>1958</td>
<td>rock anchored support structure</td>
</tr>
<tr>
<th>5</th>
<td>3s aerial tramway</td>
<td>austria</td>
<td>kitzbuhel</td>
<td>0 m, 80m</td>
<td>2507 m</td>
<td>none</td>
<td>400 m</td>
<td>2004</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>sandia peak tramway</td>
<td>usa</td>
<td>albuquerque</td>
<td>70.7 m, 21.33 m</td>
<td>2353 m</td>
<td>none</td>
<td>274 m</td>
<td>1966</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>feldmoos-chli-titlis aerial tramway</td>
<td>switzerland</td>
<td>titlis</td>
<td>37.6 m</td>
<td>3476,2 m</td>
<td>none</td>
<td>none</td>
<td>1979</td>
<td>temp. site tramway, demolished in 1986</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>height of pylons</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>70.7 m, 21.33 m</td>
</tr>
</tbody>
</table> | select height of pylons where country = 'usa' <table_name> : table | | tramway | country | city | height of pylons | span width, leaning straight line | span width, horizontal measurement | height of cable over ground | year of inauguration | notes |
|---:|:----------------------------------------------------|:------------|:------------|:-------------------|:------------------------------------|:-------------------------------------|:------------------------------|:-----------------------|:--------------------------------------------|
| 0 | peak 2 peak gondola | canada | whistler | 65m | 3024 m | 3019 m | 436 m | 2008 | 3s aerial tramway constructed by doppelmayr |
| 1 | hut of regensburg material transport aerial railway | austria | falbeson | none | none | none | 430 m | none | none |
| 2 | vanoise express | france | vanoise | none | 1850 m | 1800 m | 380 m | 2003 | none |
| 3 | aiguille du midi | france | chamonix | none | 2867 m | 2500 m | none | 1955 | 2nd section |
| 4 | vallee blanche aerial tramway | france | mont blanc | none | 2831 m, 1684 m | span is almost horizontal | appr. 300 m | 1958 | rock anchored support structure |
| 5 | 3s aerial tramway | austria | kitzbuhel | 0 m, 80m | 2507 m | none | 400 m | 2004 | none |
| 6 | sandia peak tramway | usa | albuquerque | 70.7 m, 21.33 m | 2353 m | none | 274 m | 1966 | none |
| 7 | feldmoos-chli-titlis aerial tramway | switzerland | titlis | 37.6 m | 3476,2 m | none | none | 1979 | temp. site tramway, demolished in 1986 | | | | height of pylons |
|---:|:-------------------|
| 0 | 70.7 m, 21.33 m | | [
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] |
select count ( * ) where choke = 'full' col : choke | constriction (inch) | percentage of lead shot in 30-inch circle at 40 yards | identification (notches) | identification (stars) (spanish shotguns) row 1 : cylinder | 0 | 40 at 40 yd 70 at 25 yd | 5 | 5 row 2 : skeet 1 | 0.005 | 45 at 40 yd 75 at 25 yd | none | none row 3 : 2 | 0.01 | 50 | 4 | 4 row 4 : skeet 2 (light mod.) | 0.015 | 55 | none | none row 5 : modified | 0.02 | 60 | 3 | 3 row 6 : 3 | 0.025 | 65 | 2 | 2 row 7 : full | 0.03 | 70 | 1 | 1 row 8 : extra full | 0.04 | 73 | 1 | none row 9 : turkey | 0.045 plus | 75 plus | 1 | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where choke = 'full' <table_name> : table \begin{tabular}{llllll}
\toprule
& choke & constriction (inch) & percentage of lead shot in 30-inch circle at 40 yards & identification (notches) & identification (stars) (spanish shotguns) \\
\midrule
0 & cylinder & 0 & 40 at 40 yd 70 at 25 yd & 5 & 5 \\
1 & skeet 1 & 0.005 & 45 at 40 yd 75 at 25 yd & none & none \\
2 & 2 & 0.01 & 50 & 4 & 4 \\
3 & skeet 2 (light mod.) & 0.015 & 55 & none & none \\
4 & modified & 0.02 & 60 & 3 & 3 \\
5 & 3 & 0.025 & 65 & 2 & 2 \\
6 & full & 0.03 & 70 & 1 & 1 \\
7 & extra full & 0.04 & 73 & 1 & none \\
8 & turkey & 0.045 plus & 75 plus & 1 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where choke = 'full' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>choke</th>
<th>constriction (inch)</th>
<th>percentage of lead shot in 30-inch circle at 40 yards</th>
<th>identification (notches)</th>
<th>identification (stars) (spanish shotguns)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cylinder</td>
<td>0</td>
<td>40 at 40 yd 70 at 25 yd</td>
<td>5</td>
<td>5</td>
</tr>
<tr>
<th>1</th>
<td>skeet 1</td>
<td>0.005</td>
<td>45 at 40 yd 75 at 25 yd</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2</td>
<td>0.01</td>
<td>50</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>skeet 2 (light mod.)</td>
<td>0.015</td>
<td>55</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>modified</td>
<td>0.02</td>
<td>60</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>5</th>
<td>3</td>
<td>0.025</td>
<td>65</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>full</td>
<td>0.03</td>
<td>70</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>extra full</td>
<td>0.04</td>
<td>73</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>turkey</td>
<td>0.045 plus</td>
<td>75 plus</td>
<td>1</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where choke = 'full' <table_name> : table | | choke | constriction (inch) | percentage of lead shot in 30-inch circle at 40 yards | identification (notches) | identification (stars) (spanish shotguns) |
|---:|:---------------------|:----------------------|:--------------------------------------------------------|:---------------------------|:--------------------------------------------|
| 0 | cylinder | 0 | 40 at 40 yd 70 at 25 yd | 5 | 5 |
| 1 | skeet 1 | 0.005 | 45 at 40 yd 75 at 25 yd | none | none |
| 2 | 2 | 0.01 | 50 | 4 | 4 |
| 3 | skeet 2 (light mod.) | 0.015 | 55 | none | none |
| 4 | modified | 0.02 | 60 | 3 | 3 |
| 5 | 3 | 0.025 | 65 | 2 | 2 |
| 6 | full | 0.03 | 70 | 1 | 1 |
| 7 | extra full | 0.04 | 73 | 1 | none |
| 8 | turkey | 0.045 plus | 75 plus | 1 | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select album where year = 1979 col : year | album | label | peak chart positions us | peak chart positions us r&b row 1 : 1969 | gimme shelter | ode | none | none row 2 : 1971 | celebration | ode | none | none row 3 : 1971 | merry clayton | ode | 180 | 36 row 4 : 1975 | keep your eye on the spar | | | row 5 : | ode | 146 | 50 | row 6 : 1979 | emotion | fontana | none | none row 7 : 1994 | miracles | a&m | none | none | col : album row 1 : emotion | select album where year = 1979 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & album & label & peak chart positions us & peak chart positions us r&b \\
\midrule
0 & 1969 & gimme shelter & ode & none & none \\
1 & 1971 & celebration & ode & none & none \\
2 & 1971 & merry clayton & ode & 180 & 36 \\
3 & 1975 & keep your eye on the spar & & & \\
4 & & ode & 146 & 50 & \\
5 & 1979 & emotion & fontana & none & none \\
6 & 1994 & miracles & a&m & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& album \\
\midrule
0 & emotion \\
\bottomrule
\end{tabular}
| select album where year = 1979 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>album</th>
<th>label</th>
<th>peak chart positions us</th>
<th>peak chart positions us r&b</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1969</td>
<td>gimme shelter</td>
<td>ode</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1971</td>
<td>celebration</td>
<td>ode</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1971</td>
<td>merry clayton</td>
<td>ode</td>
<td>180</td>
<td>36</td>
</tr>
<tr>
<th>3</th>
<td>1975</td>
<td>keep your eye on the spar</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>4</th>
<td></td>
<td>ode</td>
<td>146</td>
<td>50</td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>1979</td>
<td>emotion</td>
<td>fontana</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1994</td>
<td>miracles</td>
<td>a&m</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>album</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>emotion</td>
</tr>
</tbody>
</table> | select album where year = 1979 <table_name> : table | | year | album | label | peak chart positions us | peak chart positions us r&b |
|---:|:-------|:--------------------------|:--------|:--------------------------|:------------------------------|
| 0 | 1969 | gimme shelter | ode | none | none |
| 1 | 1971 | celebration | ode | none | none |
| 2 | 1971 | merry clayton | ode | 180 | 36 |
| 3 | 1975 | keep your eye on the spar | | | |
| 4 | | ode | 146 | 50 | |
| 5 | 1979 | emotion | fontana | none | none |
| 6 | 1994 | miracles | a&m | none | none | | | | album |
|---:|:--------|
| 0 | emotion | | [
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select season finale where season = 4 col : season | episodes | season premiere | season finale row 1 : 1 | 20 | march 4, 2006 | may 13, 2006 row 2 : 2 | 52 | october 7, 2006 | july 16, 2007 row 3 : 3 | 44 | october 15, 2007 | june 2, 2008 row 4 : 4 | 48 | october 13, 2008 | may 11, 2009 row 5 : 5 | 40 | october 12, 2009 | june 14, 2010 row 6 : 6 | 20 | september 6, 2010 | december 6, 2010 row 7 : 7 | 8 | october 29, 2013 | december 17, 2013 | col : season finale row 1 : may 11, 2009 | select season finale where season = 4 <table_name> : table \begin{tabular}{lllll}
\toprule
& season & episodes & season premiere & season finale \\
\midrule
0 & 1 & 20 & march 4, 2006 & may 13, 2006 \\
1 & 2 & 52 & october 7, 2006 & july 16, 2007 \\
2 & 3 & 44 & october 15, 2007 & june 2, 2008 \\
3 & 4 & 48 & october 13, 2008 & may 11, 2009 \\
4 & 5 & 40 & october 12, 2009 & june 14, 2010 \\
5 & 6 & 20 & september 6, 2010 & december 6, 2010 \\
6 & 7 & 8 & october 29, 2013 & december 17, 2013 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& season finale \\
\midrule
0 & may 11, 2009 \\
\bottomrule
\end{tabular}
| select season finale where season = 4 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>episodes</th>
<th>season premiere</th>
<th>season finale</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>20</td>
<td>march 4, 2006</td>
<td>may 13, 2006</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>52</td>
<td>october 7, 2006</td>
<td>july 16, 2007</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>44</td>
<td>october 15, 2007</td>
<td>june 2, 2008</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>48</td>
<td>october 13, 2008</td>
<td>may 11, 2009</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>40</td>
<td>october 12, 2009</td>
<td>june 14, 2010</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>20</td>
<td>september 6, 2010</td>
<td>december 6, 2010</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>8</td>
<td>october 29, 2013</td>
<td>december 17, 2013</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season finale</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>may 11, 2009</td>
</tr>
</tbody>
</table> | select season finale where season = 4 <table_name> : table | | season | episodes | season premiere | season finale |
|---:|---------:|-----------:|:------------------|:------------------|
| 0 | 1 | 20 | march 4, 2006 | may 13, 2006 |
| 1 | 2 | 52 | october 7, 2006 | july 16, 2007 |
| 2 | 3 | 44 | october 15, 2007 | june 2, 2008 |
| 3 | 4 | 48 | october 13, 2008 | may 11, 2009 |
| 4 | 5 | 40 | october 12, 2009 | june 14, 2010 |
| 5 | 6 | 20 | september 6, 2010 | december 6, 2010 |
| 6 | 7 | 8 | october 29, 2013 | december 17, 2013 | | | | season finale |
|---:|:----------------|
| 0 | may 11, 2009 | | [
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select pos where driver = 'tiago monteiro' col : pos | no | driver | team | laps | time/retired | grid | points row 1 : 1 | 32 | patrick carpentier | team player's | 87 | 1:48:11.023 | 1 | 22 row 2 : 2 | 1 | bruno junqueira | newman/haas racing | 87 | +0.8 secs | 2 | 17 row 3 : 3 | 3 | paul tracy | team player's | 87 | +28.6 secs | 3 | 14 row 4 : 4 | 9 | michel jourdain, jr | team rahal | 87 | +40.8 secs | 13 | 12 row 5 : 5 | 34 | mario haberfeld | mi-jack conquest racing | 87 | +42.1 secs | 6 | 10 row 6 : 6 | 20 | oriol servia | patrick racing | 87 | +1:00.2 | 10 | 8 row 7 : 7 | 51 | adrian fernandez | fernandez racing | 87 | +1:01.4 | 5 | 6 row 8 : 8 | 12 | jimmy vasser | american spirit team johansson | 87 | +1:01.8 | 8 | 5 row 9 : 9 | 7 | tiago monteiro | fittipaldi-dingman racing | 86 | + 1 lap | 15 | 4 row 10 : 10 | 55 | mario dominguez | herdez competition | 86 | + 1 lap | 11 | 3 row 11 : 11 | 27 | bryan herta | pk racing | 86 | + 1 lap | 12 | 2 row 12 : 12 | 31 | ryan hunter-reay | american spirit team johansson | 86 | + 1 lap | 17 | 1 row 13 : 13 | 19 | joel camathias | dale coyne racing | 85 | + 2 laps | 18 | 0 row 14 : 14 | 33 | alex tagliani | rocketsports racing | 85 | + 2 laps | 14 | 0 row 15 : 15 | 4 | roberto moreno | herdez competition | 85 | + 2 laps | 9 | 0 row 16 : 16 | 11 | geoff boss | dale coyne racing | 83 | mechanical | 19 | 0 row 17 : 17 | 2 | sebastien bourdais | newman/haas racing | 77 | mechanical | 4 | 0 row 18 : 18 | 15 | darren manning | walker racing | 12 | mechanical | 7 | 0 row 19 : 19 | 5 | rodolfo lavin | walker racing | 10 | mechanical | 16 | 0 | col : pos row 1 : 9 | select pos where driver = 'tiago monteiro' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& pos & no & driver & team & laps & time/retired & grid & points \\
\midrule
0 & 1 & 32 & patrick carpentier & team player's & 87 & 1:48:11.023 & 1 & 22 \\
1 & 2 & 1 & bruno junqueira & newman/haas racing & 87 & +0.8 secs & 2 & 17 \\
2 & 3 & 3 & paul tracy & team player's & 87 & +28.6 secs & 3 & 14 \\
3 & 4 & 9 & michel jourdain, jr & team rahal & 87 & +40.8 secs & 13 & 12 \\
4 & 5 & 34 & mario haberfeld & mi-jack conquest racing & 87 & +42.1 secs & 6 & 10 \\
5 & 6 & 20 & oriol servia & patrick racing & 87 & +1:00.2 & 10 & 8 \\
6 & 7 & 51 & adrian fernandez & fernandez racing & 87 & +1:01.4 & 5 & 6 \\
7 & 8 & 12 & jimmy vasser & american spirit team johansson & 87 & +1:01.8 & 8 & 5 \\
8 & 9 & 7 & tiago monteiro & fittipaldi-dingman racing & 86 & + 1 lap & 15 & 4 \\
9 & 10 & 55 & mario dominguez & herdez competition & 86 & + 1 lap & 11 & 3 \\
10 & 11 & 27 & bryan herta & pk racing & 86 & + 1 lap & 12 & 2 \\
11 & 12 & 31 & ryan hunter-reay & american spirit team johansson & 86 & + 1 lap & 17 & 1 \\
12 & 13 & 19 & joel camathias & dale coyne racing & 85 & + 2 laps & 18 & 0 \\
13 & 14 & 33 & alex tagliani & rocketsports racing & 85 & + 2 laps & 14 & 0 \\
14 & 15 & 4 & roberto moreno & herdez competition & 85 & + 2 laps & 9 & 0 \\
15 & 16 & 11 & geoff boss & dale coyne racing & 83 & mechanical & 19 & 0 \\
16 & 17 & 2 & sebastien bourdais & newman/haas racing & 77 & mechanical & 4 & 0 \\
17 & 18 & 15 & darren manning & walker racing & 12 & mechanical & 7 & 0 \\
18 & 19 & 5 & rodolfo lavin & walker racing & 10 & mechanical & 16 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& pos \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select pos where driver = 'tiago monteiro' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>no</th>
<th>driver</th>
<th>team</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>32</td>
<td>patrick carpentier</td>
<td>team player's</td>
<td>87</td>
<td>1:48:11.023</td>
<td>1</td>
<td>22</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1</td>
<td>bruno junqueira</td>
<td>newman/haas racing</td>
<td>87</td>
<td>+0.8 secs</td>
<td>2</td>
<td>17</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>3</td>
<td>paul tracy</td>
<td>team player's</td>
<td>87</td>
<td>+28.6 secs</td>
<td>3</td>
<td>14</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>9</td>
<td>michel jourdain, jr</td>
<td>team rahal</td>
<td>87</td>
<td>+40.8 secs</td>
<td>13</td>
<td>12</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>34</td>
<td>mario haberfeld</td>
<td>mi-jack conquest racing</td>
<td>87</td>
<td>+42.1 secs</td>
<td>6</td>
<td>10</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>20</td>
<td>oriol servia</td>
<td>patrick racing</td>
<td>87</td>
<td>+1:00.2</td>
<td>10</td>
<td>8</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>51</td>
<td>adrian fernandez</td>
<td>fernandez racing</td>
<td>87</td>
<td>+1:01.4</td>
<td>5</td>
<td>6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>12</td>
<td>jimmy vasser</td>
<td>american spirit team johansson</td>
<td>87</td>
<td>+1:01.8</td>
<td>8</td>
<td>5</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>7</td>
<td>tiago monteiro</td>
<td>fittipaldi-dingman racing</td>
<td>86</td>
<td>+ 1 lap</td>
<td>15</td>
<td>4</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>55</td>
<td>mario dominguez</td>
<td>herdez competition</td>
<td>86</td>
<td>+ 1 lap</td>
<td>11</td>
<td>3</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>27</td>
<td>bryan herta</td>
<td>pk racing</td>
<td>86</td>
<td>+ 1 lap</td>
<td>12</td>
<td>2</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>31</td>
<td>ryan hunter-reay</td>
<td>american spirit team johansson</td>
<td>86</td>
<td>+ 1 lap</td>
<td>17</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>19</td>
<td>joel camathias</td>
<td>dale coyne racing</td>
<td>85</td>
<td>+ 2 laps</td>
<td>18</td>
<td>0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>33</td>
<td>alex tagliani</td>
<td>rocketsports racing</td>
<td>85</td>
<td>+ 2 laps</td>
<td>14</td>
<td>0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>4</td>
<td>roberto moreno</td>
<td>herdez competition</td>
<td>85</td>
<td>+ 2 laps</td>
<td>9</td>
<td>0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>11</td>
<td>geoff boss</td>
<td>dale coyne racing</td>
<td>83</td>
<td>mechanical</td>
<td>19</td>
<td>0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>2</td>
<td>sebastien bourdais</td>
<td>newman/haas racing</td>
<td>77</td>
<td>mechanical</td>
<td>4</td>
<td>0</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>15</td>
<td>darren manning</td>
<td>walker racing</td>
<td>12</td>
<td>mechanical</td>
<td>7</td>
<td>0</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>5</td>
<td>rodolfo lavin</td>
<td>walker racing</td>
<td>10</td>
<td>mechanical</td>
<td>16</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select pos where driver = 'tiago monteiro' <table_name> : table | | pos | no | driver | team | laps | time/retired | grid | points |
|---:|------:|-----:|:--------------------|:-------------------------------|-------:|:---------------|-------:|---------:|
| 0 | 1 | 32 | patrick carpentier | team player's | 87 | 1:48:11.023 | 1 | 22 |
| 1 | 2 | 1 | bruno junqueira | newman/haas racing | 87 | +0.8 secs | 2 | 17 |
| 2 | 3 | 3 | paul tracy | team player's | 87 | +28.6 secs | 3 | 14 |
| 3 | 4 | 9 | michel jourdain, jr | team rahal | 87 | +40.8 secs | 13 | 12 |
| 4 | 5 | 34 | mario haberfeld | mi-jack conquest racing | 87 | +42.1 secs | 6 | 10 |
| 5 | 6 | 20 | oriol servia | patrick racing | 87 | +1:00.2 | 10 | 8 |
| 6 | 7 | 51 | adrian fernandez | fernandez racing | 87 | +1:01.4 | 5 | 6 |
| 7 | 8 | 12 | jimmy vasser | american spirit team johansson | 87 | +1:01.8 | 8 | 5 |
| 8 | 9 | 7 | tiago monteiro | fittipaldi-dingman racing | 86 | + 1 lap | 15 | 4 |
| 9 | 10 | 55 | mario dominguez | herdez competition | 86 | + 1 lap | 11 | 3 |
| 10 | 11 | 27 | bryan herta | pk racing | 86 | + 1 lap | 12 | 2 |
| 11 | 12 | 31 | ryan hunter-reay | american spirit team johansson | 86 | + 1 lap | 17 | 1 |
| 12 | 13 | 19 | joel camathias | dale coyne racing | 85 | + 2 laps | 18 | 0 |
| 13 | 14 | 33 | alex tagliani | rocketsports racing | 85 | + 2 laps | 14 | 0 |
| 14 | 15 | 4 | roberto moreno | herdez competition | 85 | + 2 laps | 9 | 0 |
| 15 | 16 | 11 | geoff boss | dale coyne racing | 83 | mechanical | 19 | 0 |
| 16 | 17 | 2 | sebastien bourdais | newman/haas racing | 77 | mechanical | 4 | 0 |
| 17 | 18 | 15 | darren manning | walker racing | 12 | mechanical | 7 | 0 |
| 18 | 19 | 5 | rodolfo lavin | walker racing | 10 | mechanical | 16 | 0 | | | | pos |
|---:|------:|
| 0 | 9 | | [
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select draft order choice where position = 'te' col : draft order round | draft order choice | player | position | height | weight | college row 1 : 1 | 1 | matthew stafford | qb | 6 ft 2 in (1.88 m) | 223 lb (101 kg) | georgia row 2 : 1 | 20 | brandon pettigrew | te | 6 ft 5 in (1.96 m) | 263 lb (119 kg) | oklahoma state row 3 : 2 | 33 | louis delmas | s | 5 ft 11 in (1.80 m) | 202 lb (92 kg) | western michigan row 4 : 3 | 76 | deandre levy | olb | 6 ft 2 in (1.88 m) | 236 lb (107 kg) | wisconsin row 5 : 3 | 82 | derrick williams | wr | 5 ft 11 in (1.80 m) | 197 lb (89 kg) | penn state row 6 : 4 | 115 | sammie lee hill | dt | 6 ft 4 in (1.93 m) | 329 lb (149 kg) | stillman row 7 : 6 | 192 | aaron brown | rb | 6 ft 1 in (1.85 m) | 196 lb (89 kg) | texas christian row 8 : 7 | 228 | lydon murtha | ot | 6 ft 7 in (2.01 m) | 315 lb (143 kg) | nebraska row 9 : 7 | 235 | zack follett | olb | 6 ft 1 in (1.85 m) | 238 lb (108 kg) | california row 10 : 7 | 255 | dan gronkowski | te | 6 ft 6 in (1.98 m) | 255 lb (116 kg) | maryland | col : draft order choice row 1 : 20 row 2 : 255 | select draft order choice where position = 'te' <table_name> : table \begin{tabular}{llllllll}
\toprule
& draft order round & draft order choice & player & position & height & weight & college \\
\midrule
0 & 1 & 1 & matthew stafford & qb & 6 ft 2 in (1.88 m) & 223 lb (101 kg) & georgia \\
1 & 1 & 20 & brandon pettigrew & te & 6 ft 5 in (1.96 m) & 263 lb (119 kg) & oklahoma state \\
2 & 2 & 33 & louis delmas & s & 5 ft 11 in (1.80 m) & 202 lb (92 kg) & western michigan \\
3 & 3 & 76 & deandre levy & olb & 6 ft 2 in (1.88 m) & 236 lb (107 kg) & wisconsin \\
4 & 3 & 82 & derrick williams & wr & 5 ft 11 in (1.80 m) & 197 lb (89 kg) & penn state \\
5 & 4 & 115 & sammie lee hill & dt & 6 ft 4 in (1.93 m) & 329 lb (149 kg) & stillman \\
6 & 6 & 192 & aaron brown & rb & 6 ft 1 in (1.85 m) & 196 lb (89 kg) & texas christian \\
7 & 7 & 228 & lydon murtha & ot & 6 ft 7 in (2.01 m) & 315 lb (143 kg) & nebraska \\
8 & 7 & 235 & zack follett & olb & 6 ft 1 in (1.85 m) & 238 lb (108 kg) & california \\
9 & 7 & 255 & dan gronkowski & te & 6 ft 6 in (1.98 m) & 255 lb (116 kg) & maryland \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& draft order choice \\
\midrule
0 & 20 \\
1 & 255 \\
\bottomrule
\end{tabular}
| select draft order choice where position = 'te' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>draft order round</th>
<th>draft order choice</th>
<th>player</th>
<th>position</th>
<th>height</th>
<th>weight</th>
<th>college</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>matthew stafford</td>
<td>qb</td>
<td>6 ft 2 in (1.88 m)</td>
<td>223 lb (101 kg)</td>
<td>georgia</td>
</tr>
<tr>
<th>1</th>
<td>1</td>
<td>20</td>
<td>brandon pettigrew</td>
<td>te</td>
<td>6 ft 5 in (1.96 m)</td>
<td>263 lb (119 kg)</td>
<td>oklahoma state</td>
</tr>
<tr>
<th>2</th>
<td>2</td>
<td>33</td>
<td>louis delmas</td>
<td>s</td>
<td>5 ft 11 in (1.80 m)</td>
<td>202 lb (92 kg)</td>
<td>western michigan</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>76</td>
<td>deandre levy</td>
<td>olb</td>
<td>6 ft 2 in (1.88 m)</td>
<td>236 lb (107 kg)</td>
<td>wisconsin</td>
</tr>
<tr>
<th>4</th>
<td>3</td>
<td>82</td>
<td>derrick williams</td>
<td>wr</td>
<td>5 ft 11 in (1.80 m)</td>
<td>197 lb (89 kg)</td>
<td>penn state</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>115</td>
<td>sammie lee hill</td>
<td>dt</td>
<td>6 ft 4 in (1.93 m)</td>
<td>329 lb (149 kg)</td>
<td>stillman</td>
</tr>
<tr>
<th>6</th>
<td>6</td>
<td>192</td>
<td>aaron brown</td>
<td>rb</td>
<td>6 ft 1 in (1.85 m)</td>
<td>196 lb (89 kg)</td>
<td>texas christian</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>228</td>
<td>lydon murtha</td>
<td>ot</td>
<td>6 ft 7 in (2.01 m)</td>
<td>315 lb (143 kg)</td>
<td>nebraska</td>
</tr>
<tr>
<th>8</th>
<td>7</td>
<td>235</td>
<td>zack follett</td>
<td>olb</td>
<td>6 ft 1 in (1.85 m)</td>
<td>238 lb (108 kg)</td>
<td>california</td>
</tr>
<tr>
<th>9</th>
<td>7</td>
<td>255</td>
<td>dan gronkowski</td>
<td>te</td>
<td>6 ft 6 in (1.98 m)</td>
<td>255 lb (116 kg)</td>
<td>maryland</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>draft order choice</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>20</td>
</tr>
<tr>
<th>1</th>
<td>255</td>
</tr>
</tbody>
</table> | select draft order choice where position = 'te' <table_name> : table | | draft order round | draft order choice | player | position | height | weight | college |
|---:|--------------------:|---------------------:|:------------------|:-----------|:--------------------|:----------------|:-----------------|
| 0 | 1 | 1 | matthew stafford | qb | 6 ft 2 in (1.88 m) | 223 lb (101 kg) | georgia |
| 1 | 1 | 20 | brandon pettigrew | te | 6 ft 5 in (1.96 m) | 263 lb (119 kg) | oklahoma state |
| 2 | 2 | 33 | louis delmas | s | 5 ft 11 in (1.80 m) | 202 lb (92 kg) | western michigan |
| 3 | 3 | 76 | deandre levy | olb | 6 ft 2 in (1.88 m) | 236 lb (107 kg) | wisconsin |
| 4 | 3 | 82 | derrick williams | wr | 5 ft 11 in (1.80 m) | 197 lb (89 kg) | penn state |
| 5 | 4 | 115 | sammie lee hill | dt | 6 ft 4 in (1.93 m) | 329 lb (149 kg) | stillman |
| 6 | 6 | 192 | aaron brown | rb | 6 ft 1 in (1.85 m) | 196 lb (89 kg) | texas christian |
| 7 | 7 | 228 | lydon murtha | ot | 6 ft 7 in (2.01 m) | 315 lb (143 kg) | nebraska |
| 8 | 7 | 235 | zack follett | olb | 6 ft 1 in (1.85 m) | 238 lb (108 kg) | california |
| 9 | 7 | 255 | dan gronkowski | te | 6 ft 6 in (1.98 m) | 255 lb (116 kg) | maryland | | | | draft order choice |
|---:|---------------------:|
| 0 | 20 |
| 1 | 255 | | [
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select count ( 18-49 (rating/share) ) where viewers (m) = '9.71' col : # | air date | timeslot (est) | season | rating | share | 18-49 (rating/share) | viewers (m) | weekly rank (#) row 1 : 1 | march 2, 2008 | sunday 9:00 p.m | 2007-2008 | 9.4 | 14 | 5.3/12 | 15.55 | 4 row 2 : 2 | march 9, 2008 | sunday 9:00 p.m | 2007-2008 | 7.4 | 11 | 4.1/10 | 11.83 | 10 row 3 : 3 | march 16, 2008 | sunday 9:00 p.m | 2007-2008 | 6.0 | 9 | 3.6/9 | 9.71 | 18 row 4 : 4 | march 23, 2008 | sunday 9:00 p.m | 2007-2008 | 6.1 | 10 | 3.5/9 | 9.92 | 19 row 5 : 5 | march 30, 2008 | sunday 9:00 p.m | 2007-2008 | 7.1 | 11 | 3.9/9 | 11.35 | 13 row 6 : 6 | april 6, 2008 | sunday 9:00 p.m | 2007-2008 | 5.9 | 9 | 3.2/8 | 9.42 | 27 row 7 : 7 | april 13, 2008 | sunday 8:00 p.m | 2007-2008 | 5.6 | 9 | 2.9/9 | 8.88 | 19 row 8 : 8 | april 20, 2008 | sunday 8:00 p.m | 2007-2008 | 6.4 | 10 | 3.2/9 | 10.03 | none | col : count ( "18-49 (rating/share" ) row 1 : 1 | select count ( 18-49 (rating/share) ) where viewers (m) = '9.71' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& # & air date & timeslot (est) & season & rating & share & 18-49 (rating/share) & viewers (m) & weekly rank (#) \\
\midrule
0 & 1 & march 2, 2008 & sunday 9:00 p.m & 2007-2008 & 9.4 & 14 & 5.3/12 & 15.55 & 4 \\
1 & 2 & march 9, 2008 & sunday 9:00 p.m & 2007-2008 & 7.4 & 11 & 4.1/10 & 11.83 & 10 \\
2 & 3 & march 16, 2008 & sunday 9:00 p.m & 2007-2008 & 6.0 & 9 & 3.6/9 & 9.71 & 18 \\
3 & 4 & march 23, 2008 & sunday 9:00 p.m & 2007-2008 & 6.1 & 10 & 3.5/9 & 9.92 & 19 \\
4 & 5 & march 30, 2008 & sunday 9:00 p.m & 2007-2008 & 7.1 & 11 & 3.9/9 & 11.35 & 13 \\
5 & 6 & april 6, 2008 & sunday 9:00 p.m & 2007-2008 & 5.9 & 9 & 3.2/8 & 9.42 & 27 \\
6 & 7 & april 13, 2008 & sunday 8:00 p.m & 2007-2008 & 5.6 & 9 & 2.9/9 & 8.88 & 19 \\
7 & 8 & april 20, 2008 & sunday 8:00 p.m & 2007-2008 & 6.4 & 10 & 3.2/9 & 10.03 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "18-49 (rating/share" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( 18-49 (rating/share) ) where viewers (m) = '9.71' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>air date</th>
<th>timeslot (est)</th>
<th>season</th>
<th>rating</th>
<th>share</th>
<th>18-49 (rating/share)</th>
<th>viewers (m)</th>
<th>weekly rank (#)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>march 2, 2008</td>
<td>sunday 9:00 p.m</td>
<td>2007-2008</td>
<td>9.4</td>
<td>14</td>
<td>5.3/12</td>
<td>15.55</td>
<td>4</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>march 9, 2008</td>
<td>sunday 9:00 p.m</td>
<td>2007-2008</td>
<td>7.4</td>
<td>11</td>
<td>4.1/10</td>
<td>11.83</td>
<td>10</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>march 16, 2008</td>
<td>sunday 9:00 p.m</td>
<td>2007-2008</td>
<td>6.0</td>
<td>9</td>
<td>3.6/9</td>
<td>9.71</td>
<td>18</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>march 23, 2008</td>
<td>sunday 9:00 p.m</td>
<td>2007-2008</td>
<td>6.1</td>
<td>10</td>
<td>3.5/9</td>
<td>9.92</td>
<td>19</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>march 30, 2008</td>
<td>sunday 9:00 p.m</td>
<td>2007-2008</td>
<td>7.1</td>
<td>11</td>
<td>3.9/9</td>
<td>11.35</td>
<td>13</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>april 6, 2008</td>
<td>sunday 9:00 p.m</td>
<td>2007-2008</td>
<td>5.9</td>
<td>9</td>
<td>3.2/8</td>
<td>9.42</td>
<td>27</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>april 13, 2008</td>
<td>sunday 8:00 p.m</td>
<td>2007-2008</td>
<td>5.6</td>
<td>9</td>
<td>2.9/9</td>
<td>8.88</td>
<td>19</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>april 20, 2008</td>
<td>sunday 8:00 p.m</td>
<td>2007-2008</td>
<td>6.4</td>
<td>10</td>
<td>3.2/9</td>
<td>10.03</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "18-49 (rating/share" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( 18-49 (rating/share) ) where viewers (m) = '9.71' <table_name> : table | | # | air date | timeslot (est) | season | rating | share | 18-49 (rating/share) | viewers (m) | weekly rank (#) |
|---:|----:|:---------------|:-----------------|:----------|---------:|--------:|:-----------------------|--------------:|:------------------|
| 0 | 1 | march 2, 2008 | sunday 9:00 p.m | 2007-2008 | 9.4 | 14 | 5.3/12 | 15.55 | 4 |
| 1 | 2 | march 9, 2008 | sunday 9:00 p.m | 2007-2008 | 7.4 | 11 | 4.1/10 | 11.83 | 10 |
| 2 | 3 | march 16, 2008 | sunday 9:00 p.m | 2007-2008 | 6 | 9 | 3.6/9 | 9.71 | 18 |
| 3 | 4 | march 23, 2008 | sunday 9:00 p.m | 2007-2008 | 6.1 | 10 | 3.5/9 | 9.92 | 19 |
| 4 | 5 | march 30, 2008 | sunday 9:00 p.m | 2007-2008 | 7.1 | 11 | 3.9/9 | 11.35 | 13 |
| 5 | 6 | april 6, 2008 | sunday 9:00 p.m | 2007-2008 | 5.9 | 9 | 3.2/8 | 9.42 | 27 |
| 6 | 7 | april 13, 2008 | sunday 8:00 p.m | 2007-2008 | 5.6 | 9 | 2.9/9 | 8.88 | 19 |
| 7 | 8 | april 20, 2008 | sunday 8:00 p.m | 2007-2008 | 6.4 | 10 | 3.2/9 | 10.03 | none | | | | count ( "18-49 (rating/share" ) |
|---:|----------------------------------:|
| 0 | 1 | | [
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select count ( league ) where reg. season = '7th, western' col : year | division | league | reg. season | playoffs row 1 : 2003 | 2 | usl w-league | 5th, western | none row 2 : 2004 | 1 | usl w-league | 8th, western | none row 3 : 2005 | 1 | usl w-league | 6th, western | none row 4 : 2006 | 1 | usl w-league | 5th, western | none row 5 : 2007 | 1 | usl w-league | 5th, western | none row 6 : 2008 | 1 | usl w-league | 6th, western | did not qualify row 7 : 2009 | 1 | usl w-league | 7th, western | did not qualify row 8 : 2010 | 1 | usl w-league | 6th, western | did not qualify row 9 : 2011 | 1 | usl w-league | 7th, western | did not qualify row 10 : 2012 | 1 | usl w-league | 4th, western | did not qualify row 11 : 2013 | 1 | usl w-league | 4th, western | did not qualify | col : count ( "league" ) row 1 : 2 | select count ( league ) where reg. season = '7th, western' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & division & league & reg. season & playoffs \\
\midrule
0 & 2003 & 2 & usl w-league & 5th, western & none \\
1 & 2004 & 1 & usl w-league & 8th, western & none \\
2 & 2005 & 1 & usl w-league & 6th, western & none \\
3 & 2006 & 1 & usl w-league & 5th, western & none \\
4 & 2007 & 1 & usl w-league & 5th, western & none \\
5 & 2008 & 1 & usl w-league & 6th, western & did not qualify \\
6 & 2009 & 1 & usl w-league & 7th, western & did not qualify \\
7 & 2010 & 1 & usl w-league & 6th, western & did not qualify \\
8 & 2011 & 1 & usl w-league & 7th, western & did not qualify \\
9 & 2012 & 1 & usl w-league & 4th, western & did not qualify \\
10 & 2013 & 1 & usl w-league & 4th, western & did not qualify \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "league" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( league ) where reg. season = '7th, western' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>division</th>
<th>league</th>
<th>reg. season</th>
<th>playoffs</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003</td>
<td>2</td>
<td>usl w-league</td>
<td>5th, western</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>1</td>
<td>usl w-league</td>
<td>8th, western</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>1</td>
<td>usl w-league</td>
<td>6th, western</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>1</td>
<td>usl w-league</td>
<td>5th, western</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>1</td>
<td>usl w-league</td>
<td>5th, western</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>1</td>
<td>usl w-league</td>
<td>6th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>6</th>
<td>2009</td>
<td>1</td>
<td>usl w-league</td>
<td>7th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>7</th>
<td>2010</td>
<td>1</td>
<td>usl w-league</td>
<td>6th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>1</td>
<td>usl w-league</td>
<td>7th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>9</th>
<td>2012</td>
<td>1</td>
<td>usl w-league</td>
<td>4th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>10</th>
<td>2013</td>
<td>1</td>
<td>usl w-league</td>
<td>4th, western</td>
<td>did not qualify</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "league" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( league ) where reg. season = '7th, western' <table_name> : table | | year | division | league | reg. season | playoffs |
|---:|-------:|-----------:|:-------------|:--------------|:----------------|
| 0 | 2003 | 2 | usl w-league | 5th, western | none |
| 1 | 2004 | 1 | usl w-league | 8th, western | none |
| 2 | 2005 | 1 | usl w-league | 6th, western | none |
| 3 | 2006 | 1 | usl w-league | 5th, western | none |
| 4 | 2007 | 1 | usl w-league | 5th, western | none |
| 5 | 2008 | 1 | usl w-league | 6th, western | did not qualify |
| 6 | 2009 | 1 | usl w-league | 7th, western | did not qualify |
| 7 | 2010 | 1 | usl w-league | 6th, western | did not qualify |
| 8 | 2011 | 1 | usl w-league | 7th, western | did not qualify |
| 9 | 2012 | 1 | usl w-league | 4th, western | did not qualify |
| 10 | 2013 | 1 | usl w-league | 4th, western | did not qualify | | | | count ( "league" ) |
|---:|---------------------:|
| 0 | 2 | | [
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select count ( imdb ) where imdb = '5.1/10' col : year | film | rotten tomatoes | metacritic | imdb row 1 : 1982 | images of liberation | none | none | 5.1/10 row 2 : 1984 | the element of crime | 77% | none | 6.9/10 row 3 : 1987 | epidemic | 33% | 66% | 6.1/10 row 4 : 1991 | europa | 85% | 66% | 7.7/10 row 5 : 1996 | breaking the waves | 86% | 76% | 7.9/10 row 6 : 1998 | the idiots | 70% | 47% | 6.9/10 row 7 : 2000 | dancer in the dark | 68% | 61% | 8.0/10 row 8 : 2003 | the five obstructions | 88% | 79% | 7.5/10 row 9 : 2003 | dogville | 70% | 59% | 8.0/10 row 10 : 2005 | manderlay | 51% | 46% | 7.4/10 row 11 : 2006 | the boss of it all | 74% | 71% | 6.7/10 row 12 : 2009 | antichrist | 48% | 49% | 6.6/10 row 13 : 2011 | melancholia | 77% | 80% | 7.1/10 row 14 : 2013 | nymphomaniac: volume i | 77% | 63% | 7.5/10 row 15 : 2013 | nymphomaniac: volume ii | 79% | 76% | 7.2/10 | col : count ( "imdb" ) row 1 : 1 | select count ( imdb ) where imdb = '5.1/10' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & film & rotten tomatoes & metacritic & imdb \\
\midrule
0 & 1982 & images of liberation & none & none & 5.1/10 \\
1 & 1984 & the element of crime & 77% & none & 6.9/10 \\
2 & 1987 & epidemic & 33% & 66% & 6.1/10 \\
3 & 1991 & europa & 85% & 66% & 7.7/10 \\
4 & 1996 & breaking the waves & 86% & 76% & 7.9/10 \\
5 & 1998 & the idiots & 70% & 47% & 6.9/10 \\
6 & 2000 & dancer in the dark & 68% & 61% & 8.0/10 \\
7 & 2003 & the five obstructions & 88% & 79% & 7.5/10 \\
8 & 2003 & dogville & 70% & 59% & 8.0/10 \\
9 & 2005 & manderlay & 51% & 46% & 7.4/10 \\
10 & 2006 & the boss of it all & 74% & 71% & 6.7/10 \\
11 & 2009 & antichrist & 48% & 49% & 6.6/10 \\
12 & 2011 & melancholia & 77% & 80% & 7.1/10 \\
13 & 2013 & nymphomaniac: volume i & 77% & 63% & 7.5/10 \\
14 & 2013 & nymphomaniac: volume ii & 79% & 76% & 7.2/10 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "imdb" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( imdb ) where imdb = '5.1/10' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>film</th>
<th>rotten tomatoes</th>
<th>metacritic</th>
<th>imdb</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1982</td>
<td>images of liberation</td>
<td>none</td>
<td>none</td>
<td>5.1/10</td>
</tr>
<tr>
<th>1</th>
<td>1984</td>
<td>the element of crime</td>
<td>77%</td>
<td>none</td>
<td>6.9/10</td>
</tr>
<tr>
<th>2</th>
<td>1987</td>
<td>epidemic</td>
<td>33%</td>
<td>66%</td>
<td>6.1/10</td>
</tr>
<tr>
<th>3</th>
<td>1991</td>
<td>europa</td>
<td>85%</td>
<td>66%</td>
<td>7.7/10</td>
</tr>
<tr>
<th>4</th>
<td>1996</td>
<td>breaking the waves</td>
<td>86%</td>
<td>76%</td>
<td>7.9/10</td>
</tr>
<tr>
<th>5</th>
<td>1998</td>
<td>the idiots</td>
<td>70%</td>
<td>47%</td>
<td>6.9/10</td>
</tr>
<tr>
<th>6</th>
<td>2000</td>
<td>dancer in the dark</td>
<td>68%</td>
<td>61%</td>
<td>8.0/10</td>
</tr>
<tr>
<th>7</th>
<td>2003</td>
<td>the five obstructions</td>
<td>88%</td>
<td>79%</td>
<td>7.5/10</td>
</tr>
<tr>
<th>8</th>
<td>2003</td>
<td>dogville</td>
<td>70%</td>
<td>59%</td>
<td>8.0/10</td>
</tr>
<tr>
<th>9</th>
<td>2005</td>
<td>manderlay</td>
<td>51%</td>
<td>46%</td>
<td>7.4/10</td>
</tr>
<tr>
<th>10</th>
<td>2006</td>
<td>the boss of it all</td>
<td>74%</td>
<td>71%</td>
<td>6.7/10</td>
</tr>
<tr>
<th>11</th>
<td>2009</td>
<td>antichrist</td>
<td>48%</td>
<td>49%</td>
<td>6.6/10</td>
</tr>
<tr>
<th>12</th>
<td>2011</td>
<td>melancholia</td>
<td>77%</td>
<td>80%</td>
<td>7.1/10</td>
</tr>
<tr>
<th>13</th>
<td>2013</td>
<td>nymphomaniac: volume i</td>
<td>77%</td>
<td>63%</td>
<td>7.5/10</td>
</tr>
<tr>
<th>14</th>
<td>2013</td>
<td>nymphomaniac: volume ii</td>
<td>79%</td>
<td>76%</td>
<td>7.2/10</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "imdb" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( imdb ) where imdb = '5.1/10' <table_name> : table | | year | film | rotten tomatoes | metacritic | imdb |
|---:|-------:|:------------------------|:------------------|:-------------|:-------|
| 0 | 1982 | images of liberation | none | none | 5.1/10 |
| 1 | 1984 | the element of crime | 77% | none | 6.9/10 |
| 2 | 1987 | epidemic | 33% | 66% | 6.1/10 |
| 3 | 1991 | europa | 85% | 66% | 7.7/10 |
| 4 | 1996 | breaking the waves | 86% | 76% | 7.9/10 |
| 5 | 1998 | the idiots | 70% | 47% | 6.9/10 |
| 6 | 2000 | dancer in the dark | 68% | 61% | 8.0/10 |
| 7 | 2003 | the five obstructions | 88% | 79% | 7.5/10 |
| 8 | 2003 | dogville | 70% | 59% | 8.0/10 |
| 9 | 2005 | manderlay | 51% | 46% | 7.4/10 |
| 10 | 2006 | the boss of it all | 74% | 71% | 6.7/10 |
| 11 | 2009 | antichrist | 48% | 49% | 6.6/10 |
| 12 | 2011 | melancholia | 77% | 80% | 7.1/10 |
| 13 | 2013 | nymphomaniac: volume i | 77% | 63% | 7.5/10 |
| 14 | 2013 | nymphomaniac: volume ii | 79% | 76% | 7.2/10 | | | | count ( "imdb" ) |
|---:|-------------------:|
| 0 | 1 | | [
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select max ( division ) where season < 1974 col : season | level | division | section | position | movements row 1 : 1960 | tier 4 | division 4 | halsingland | 3rd | none row 2 : 1961 | tier 4 | division 4 | halsingland | 2nd | none row 3 : 1962 | tier 4 | division 4 | halsingland | 1st | promoted row 4 : 1963 | tier 3 | division 3 | sodra norrland | 6th | none row 5 : 1964 | tier 3 | division 3 | sodra norrland nedre | 4th | none row 6 : 1965 | tier 3 | division 3 | sodra norrland nedre | 10th | relegated row 7 : 1966 | tier 4 | division 4 | halsingland | 9th | none row 8 : 1967 | tier 4 | division 4 | halsingland | 2nd | none row 9 : 1968 | tier 4 | division 4 | halsingland | 6th | none row 10 : 1969 | tier 4 | division 4 | halsingland | 3rd | none row 11 : 1970 | tier 4 | division 4 | halsingland | 2nd | none row 12 : 1971 | tier 4 | division 4 | halsingland | 1st | promotion playoffs - promoted row 13 : 1972 | tier 3 | division 3 | norra svealand | 6th | none row 14 : 1973 | tier 3 | division 3 | norra svealand | 11th | relegated row 15 : 1974 | tier 4 | division 4 | halsingland | 1st | promoted row 16 : 1975 | tier 3 | division 3 | sodra norrland | 9th | none row 17 : 1976 | tier 3 | division 3 | sodra norrland | 9th | none row 18 : 1977 | tier 3 | division 3 | sodra norrland | 9th | none row 19 : 1978 | tier 3 | division 3 | sodra norrland | 6th | none row 20 : 1979 | tier 3 | division 3 | sodra norrland | 9th | none row 21 : 1980 | tier 3 | division 3 | sodra norrland | 7th | none row 22 : 1981 | tier 3 | division 3 | sodra norrland | 9th | none row 23 : 1982 | tier 3 | division 3 | sodra norrland | 12th | relegated row 24 : 1982 | tier 4 | division 4 | halsingland | 3rd | none | col : max ( "division" ) row 1 : division 4 | select max ( division ) where season < 1974 <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & level & division & section & position & movements \\
\midrule
0 & 1960 & tier 4 & division 4 & halsingland & 3rd & none \\
1 & 1961 & tier 4 & division 4 & halsingland & 2nd & none \\
2 & 1962 & tier 4 & division 4 & halsingland & 1st & promoted \\
3 & 1963 & tier 3 & division 3 & sodra norrland & 6th & none \\
4 & 1964 & tier 3 & division 3 & sodra norrland nedre & 4th & none \\
5 & 1965 & tier 3 & division 3 & sodra norrland nedre & 10th & relegated \\
6 & 1966 & tier 4 & division 4 & halsingland & 9th & none \\
7 & 1967 & tier 4 & division 4 & halsingland & 2nd & none \\
8 & 1968 & tier 4 & division 4 & halsingland & 6th & none \\
9 & 1969 & tier 4 & division 4 & halsingland & 3rd & none \\
10 & 1970 & tier 4 & division 4 & halsingland & 2nd & none \\
11 & 1971 & tier 4 & division 4 & halsingland & 1st & promotion playoffs - promoted \\
12 & 1972 & tier 3 & division 3 & norra svealand & 6th & none \\
13 & 1973 & tier 3 & division 3 & norra svealand & 11th & relegated \\
14 & 1974 & tier 4 & division 4 & halsingland & 1st & promoted \\
15 & 1975 & tier 3 & division 3 & sodra norrland & 9th & none \\
16 & 1976 & tier 3 & division 3 & sodra norrland & 9th & none \\
17 & 1977 & tier 3 & division 3 & sodra norrland & 9th & none \\
18 & 1978 & tier 3 & division 3 & sodra norrland & 6th & none \\
19 & 1979 & tier 3 & division 3 & sodra norrland & 9th & none \\
20 & 1980 & tier 3 & division 3 & sodra norrland & 7th & none \\
21 & 1981 & tier 3 & division 3 & sodra norrland & 9th & none \\
22 & 1982 & tier 3 & division 3 & sodra norrland & 12th & relegated \\
23 & 1982 & tier 4 & division 4 & halsingland & 3rd & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& max ( "division" ) \\
\midrule
0 & division 4 \\
\bottomrule
\end{tabular}
| select max ( division ) where season < 1974 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>level</th>
<th>division</th>
<th>section</th>
<th>position</th>
<th>movements</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1960</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1961</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1962</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>3</th>
<td>1963</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1964</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland nedre</td>
<td>4th</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1965</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland nedre</td>
<td>10th</td>
<td>relegated</td>
</tr>
<tr>
<th>6</th>
<td>1966</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1967</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1968</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1969</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>1970</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1971</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>1st</td>
<td>promotion playoffs - promoted</td>
</tr>
<tr>
<th>12</th>
<td>1972</td>
<td>tier 3</td>
<td>division 3</td>
<td>norra svealand</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1973</td>
<td>tier 3</td>
<td>division 3</td>
<td>norra svealand</td>
<td>11th</td>
<td>relegated</td>
</tr>
<tr>
<th>14</th>
<td>1974</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>15</th>
<td>1975</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>1976</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>1977</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>1978</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>1979</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>1980</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>1981</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>1982</td>
<td>tier 3</td>
<td>division 3</td>
<td>sodra norrland</td>
<td>12th</td>
<td>relegated</td>
</tr>
<tr>
<th>23</th>
<td>1982</td>
<td>tier 4</td>
<td>division 4</td>
<td>halsingland</td>
<td>3rd</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>max ( "division" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>division 4</td>
</tr>
</tbody>
</table> | select max ( division ) where season < 1974 <table_name> : table | | season | level | division | section | position | movements |
|---:|---------:|:--------|:-----------|:---------------------|:-----------|:------------------------------|
| 0 | 1960 | tier 4 | division 4 | halsingland | 3rd | none |
| 1 | 1961 | tier 4 | division 4 | halsingland | 2nd | none |
| 2 | 1962 | tier 4 | division 4 | halsingland | 1st | promoted |
| 3 | 1963 | tier 3 | division 3 | sodra norrland | 6th | none |
| 4 | 1964 | tier 3 | division 3 | sodra norrland nedre | 4th | none |
| 5 | 1965 | tier 3 | division 3 | sodra norrland nedre | 10th | relegated |
| 6 | 1966 | tier 4 | division 4 | halsingland | 9th | none |
| 7 | 1967 | tier 4 | division 4 | halsingland | 2nd | none |
| 8 | 1968 | tier 4 | division 4 | halsingland | 6th | none |
| 9 | 1969 | tier 4 | division 4 | halsingland | 3rd | none |
| 10 | 1970 | tier 4 | division 4 | halsingland | 2nd | none |
| 11 | 1971 | tier 4 | division 4 | halsingland | 1st | promotion playoffs - promoted |
| 12 | 1972 | tier 3 | division 3 | norra svealand | 6th | none |
| 13 | 1973 | tier 3 | division 3 | norra svealand | 11th | relegated |
| 14 | 1974 | tier 4 | division 4 | halsingland | 1st | promoted |
| 15 | 1975 | tier 3 | division 3 | sodra norrland | 9th | none |
| 16 | 1976 | tier 3 | division 3 | sodra norrland | 9th | none |
| 17 | 1977 | tier 3 | division 3 | sodra norrland | 9th | none |
| 18 | 1978 | tier 3 | division 3 | sodra norrland | 6th | none |
| 19 | 1979 | tier 3 | division 3 | sodra norrland | 9th | none |
| 20 | 1980 | tier 3 | division 3 | sodra norrland | 7th | none |
| 21 | 1981 | tier 3 | division 3 | sodra norrland | 9th | none |
| 22 | 1982 | tier 3 | division 3 | sodra norrland | 12th | relegated |
| 23 | 1982 | tier 4 | division 4 | halsingland | 3rd | none | | | | max ( "division" ) |
|---:|:---------------------|
| 0 | division 4 | | [
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select silver where nation = 'kuwait (kuw)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | vietnam (vie) | 3 | 0 | 3 | 6 row 2 : 2 | south korea (kor) | 2 | 1 | 2 | 5 row 3 : 3 | kyrgyzstan (kgz) | 1 | 1 | 2 | 4 row 4 : 4 | kazakhstan (kaz) | 1 | 1 | 1 | 3 row 5 : 5 | iraq (irq) | 1 | 0 | 1 | 2 row 6 : 5 | turkmenistan (tkm) | 1 | 0 | 1 | 2 row 7 : 7 | jordan (jor) | 0 | 2 | 3 | 5 row 8 : 8 | uzbekistan (uzb) | 0 | 2 | 1 | 3 row 9 : 9 | tajikistan (tjk) | 0 | 1 | 1 | 2 row 10 : 10 | kuwait (kuw) | 0 | 1 | 0 | 1 row 11 : 11 | independent athletes (aoi) | 0 | 0 | 1 | 1 row 12 : 11 | mongolia (mgl) | 0 | 0 | 1 | 1 row 13 : 11 | palestine (ple) | 0 | 0 | 1 | 1 row 14 : total | total | 9 | 9 | 18 | 36 | col : silver row 1 : 1 | select silver where nation = 'kuwait (kuw)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & vietnam (vie) & 3 & 0 & 3 & 6 \\
1 & 2 & south korea (kor) & 2 & 1 & 2 & 5 \\
2 & 3 & kyrgyzstan (kgz) & 1 & 1 & 2 & 4 \\
3 & 4 & kazakhstan (kaz) & 1 & 1 & 1 & 3 \\
4 & 5 & iraq (irq) & 1 & 0 & 1 & 2 \\
5 & 5 & turkmenistan (tkm) & 1 & 0 & 1 & 2 \\
6 & 7 & jordan (jor) & 0 & 2 & 3 & 5 \\
7 & 8 & uzbekistan (uzb) & 0 & 2 & 1 & 3 \\
8 & 9 & tajikistan (tjk) & 0 & 1 & 1 & 2 \\
9 & 10 & kuwait (kuw) & 0 & 1 & 0 & 1 \\
10 & 11 & independent athletes (aoi) & 0 & 0 & 1 & 1 \\
11 & 11 & mongolia (mgl) & 0 & 0 & 1 & 1 \\
12 & 11 & palestine (ple) & 0 & 0 & 1 & 1 \\
13 & total & total & 9 & 9 & 18 & 36 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& silver \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select silver where nation = 'kuwait (kuw)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>vietnam (vie)</td>
<td>3</td>
<td>0</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>south korea (kor)</td>
<td>2</td>
<td>1</td>
<td>2</td>
<td>5</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>kyrgyzstan (kgz)</td>
<td>1</td>
<td>1</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>kazakhstan (kaz)</td>
<td>1</td>
<td>1</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>iraq (irq)</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>turkmenistan (tkm)</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jordan (jor)</td>
<td>0</td>
<td>2</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>uzbekistan (uzb)</td>
<td>0</td>
<td>2</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>tajikistan (tjk)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>kuwait (kuw)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>independent athletes (aoi)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>mongolia (mgl)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>palestine (ple)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>total</td>
<td>total</td>
<td>9</td>
<td>9</td>
<td>18</td>
<td>36</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>silver</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select silver where nation = 'kuwait (kuw)' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | vietnam (vie) | 3 | 0 | 3 | 6 |
| 1 | 2 | south korea (kor) | 2 | 1 | 2 | 5 |
| 2 | 3 | kyrgyzstan (kgz) | 1 | 1 | 2 | 4 |
| 3 | 4 | kazakhstan (kaz) | 1 | 1 | 1 | 3 |
| 4 | 5 | iraq (irq) | 1 | 0 | 1 | 2 |
| 5 | 5 | turkmenistan (tkm) | 1 | 0 | 1 | 2 |
| 6 | 7 | jordan (jor) | 0 | 2 | 3 | 5 |
| 7 | 8 | uzbekistan (uzb) | 0 | 2 | 1 | 3 |
| 8 | 9 | tajikistan (tjk) | 0 | 1 | 1 | 2 |
| 9 | 10 | kuwait (kuw) | 0 | 1 | 0 | 1 |
| 10 | 11 | independent athletes (aoi) | 0 | 0 | 1 | 1 |
| 11 | 11 | mongolia (mgl) | 0 | 0 | 1 | 1 |
| 12 | 11 | palestine (ple) | 0 | 0 | 1 | 1 |
| 13 | total | total | 9 | 9 | 18 | 36 | | | | silver |
|---:|---------:|
| 0 | 1 | | [
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select count ( date ) where game = 5 col : game | date | team | score | high points | high rebounds | high assists | location attendance | record row 1 : 1 | october 5 | @ portland | l 86-115 | chris kaman (14) | chris kaman, blake griffin (7) | randy foye (5) | rose garden 18,209 | 0-1 row 2 : 2 | october 7 | @ sacramento | w 120-88 | chris kaman (20) | blake griffin (13) | randy foye (8) | arco arena 10,284 | 1-1 row 3 : 3 | october 8 | @ golden state | l 87-127 | blake griffin (23) | blake griffin (9) | randy foye (6) | oracle arena 10,004 | 1-2 row 4 : 4 | october 12 | san antonio | l 99-100 | eric gordon (23) | blake griffin (17) | baron davis (7) | palacio de los deportes 18,674 | 1-3 row 5 : 5 | october 14 | denver | l 95-100 | blake griffin (24) | blake griffin (14) | baron davis (6) | staples center 10,572 | 1-4 row 6 : 6 | october 16 | utah | l 91-103 | eric gordon (23) | blake griffin (14) | baron davis (8) | staples center 18,997 | 1-5 row 7 : 7 | october 17 | denver | l 104-108 | brian cook (28) | al-farouq aminu (8) | baron davis, eric bledsoe (7) | staples center | 1-6 row 8 : 8 | october 19 | sacramento | l 94-96 | chris kaman (21) | chris kaman (10) | baron davis (8) | staples center 10,838 | 1-7 | col : count ( "date" ) row 1 : 1 | select count ( date ) where game = 5 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& game & date & team & score & high points & high rebounds & high assists & location attendance & record \\
\midrule
0 & 1 & october 5 & @ portland & l 86-115 & chris kaman (14) & chris kaman, blake griffin (7) & randy foye (5) & rose garden 18,209 & 0-1 \\
1 & 2 & october 7 & @ sacramento & w 120-88 & chris kaman (20) & blake griffin (13) & randy foye (8) & arco arena 10,284 & 1-1 \\
2 & 3 & october 8 & @ golden state & l 87-127 & blake griffin (23) & blake griffin (9) & randy foye (6) & oracle arena 10,004 & 1-2 \\
3 & 4 & october 12 & san antonio & l 99-100 & eric gordon (23) & blake griffin (17) & baron davis (7) & palacio de los deportes 18,674 & 1-3 \\
4 & 5 & october 14 & denver & l 95-100 & blake griffin (24) & blake griffin (14) & baron davis (6) & staples center 10,572 & 1-4 \\
5 & 6 & october 16 & utah & l 91-103 & eric gordon (23) & blake griffin (14) & baron davis (8) & staples center 18,997 & 1-5 \\
6 & 7 & october 17 & denver & l 104-108 & brian cook (28) & al-farouq aminu (8) & baron davis, eric bledsoe (7) & staples center & 1-6 \\
7 & 8 & october 19 & sacramento & l 94-96 & chris kaman (21) & chris kaman (10) & baron davis (8) & staples center 10,838 & 1-7 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "date" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( date ) where game = 5 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>date</th>
<th>team</th>
<th>score</th>
<th>high points</th>
<th>high rebounds</th>
<th>high assists</th>
<th>location attendance</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>october 5</td>
<td>@ portland</td>
<td>l 86-115</td>
<td>chris kaman (14)</td>
<td>chris kaman, blake griffin (7)</td>
<td>randy foye (5)</td>
<td>rose garden 18,209</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>october 7</td>
<td>@ sacramento</td>
<td>w 120-88</td>
<td>chris kaman (20)</td>
<td>blake griffin (13)</td>
<td>randy foye (8)</td>
<td>arco arena 10,284</td>
<td>1-1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>october 8</td>
<td>@ golden state</td>
<td>l 87-127</td>
<td>blake griffin (23)</td>
<td>blake griffin (9)</td>
<td>randy foye (6)</td>
<td>oracle arena 10,004</td>
<td>1-2</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>october 12</td>
<td>san antonio</td>
<td>l 99-100</td>
<td>eric gordon (23)</td>
<td>blake griffin (17)</td>
<td>baron davis (7)</td>
<td>palacio de los deportes 18,674</td>
<td>1-3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>october 14</td>
<td>denver</td>
<td>l 95-100</td>
<td>blake griffin (24)</td>
<td>blake griffin (14)</td>
<td>baron davis (6)</td>
<td>staples center 10,572</td>
<td>1-4</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>october 16</td>
<td>utah</td>
<td>l 91-103</td>
<td>eric gordon (23)</td>
<td>blake griffin (14)</td>
<td>baron davis (8)</td>
<td>staples center 18,997</td>
<td>1-5</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>october 17</td>
<td>denver</td>
<td>l 104-108</td>
<td>brian cook (28)</td>
<td>al-farouq aminu (8)</td>
<td>baron davis, eric bledsoe (7)</td>
<td>staples center</td>
<td>1-6</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>october 19</td>
<td>sacramento</td>
<td>l 94-96</td>
<td>chris kaman (21)</td>
<td>chris kaman (10)</td>
<td>baron davis (8)</td>
<td>staples center 10,838</td>
<td>1-7</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "date" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( date ) where game = 5 <table_name> : table | | game | date | team | score | high points | high rebounds | high assists | location attendance | record |
|---:|-------:|:-----------|:---------------|:----------|:-------------------|:-------------------------------|:------------------------------|:-------------------------------|:---------|
| 0 | 1 | october 5 | @ portland | l 86-115 | chris kaman (14) | chris kaman, blake griffin (7) | randy foye (5) | rose garden 18,209 | 0-1 |
| 1 | 2 | october 7 | @ sacramento | w 120-88 | chris kaman (20) | blake griffin (13) | randy foye (8) | arco arena 10,284 | 1-1 |
| 2 | 3 | october 8 | @ golden state | l 87-127 | blake griffin (23) | blake griffin (9) | randy foye (6) | oracle arena 10,004 | 1-2 |
| 3 | 4 | october 12 | san antonio | l 99-100 | eric gordon (23) | blake griffin (17) | baron davis (7) | palacio de los deportes 18,674 | 1-3 |
| 4 | 5 | october 14 | denver | l 95-100 | blake griffin (24) | blake griffin (14) | baron davis (6) | staples center 10,572 | 1-4 |
| 5 | 6 | october 16 | utah | l 91-103 | eric gordon (23) | blake griffin (14) | baron davis (8) | staples center 18,997 | 1-5 |
| 6 | 7 | october 17 | denver | l 104-108 | brian cook (28) | al-farouq aminu (8) | baron davis, eric bledsoe (7) | staples center | 1-6 |
| 7 | 8 | october 19 | sacramento | l 94-96 | chris kaman (21) | chris kaman (10) | baron davis (8) | staples center 10,838 | 1-7 | | | | count ( "date" ) |
|---:|-------------------:|
| 0 | 1 | | [
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select count ( birth ) where birth = '2 february 1208 montpellier son of peter ii of aragon and marie of montpellier' col : name | birth | marriages | death row 1 : james i 1231-1276 | 2 february 1208 montpellier son of peter ii of aragon and marie of montpellier | eleanor 1221 1 child violant of hungary 1235 10 children teresa gil de vidaure 2 children | 27 july 1276 valencia aged 68 row 2 : james ii 1276-1286 (first rule) | 1243 montpellier son of james i of aragon and violant of hungary | esclaramunda of foix 1275 6 children | 1311 palma de mallorca aged 68 row 3 : alfonso i 1286-1291 | 1265 valencia son of peter iii of aragon and constance of sicily | unmarried | 18 june 1291 barcelona aged 27 row 4 : james iii 1291-1295 | 10 august 1267 valencia son of peter iii and constance of sicily | isabella of castile 1 december 1291 no children blanche of anjou 29 october 1295 10 children marie de lusignan 15 june 1315 no children elisenda de montcada 25 december 1322 no children | 5 november 1327 barcelona aged 60 row 5 : james ii 1295-1311 (second rule) | 1243 montpellier son of james i of aragon and violant of hungary | esclaramunda of foix 1275 6 children | 1311 palma de mallorca aged 68 row 6 : sancho 1311-1324 | 1276 son of james ii of majorca and esclaramunda of foix | maria of naples 20 september 1304 no children | 4 september 1324 formiguera aged 48 row 7 : james iii of majorca 1324-1344 | 5 april 1315 catania son of ferdinand of majorca and isabelle of sabran | constance of aragon 2 children violant of vilaragut 10 november 1347 1 child | 25 october 1349 llucmajor aged 34 | col : count ( "birth" ) row 1 : 1 | select count ( birth ) where birth = '2 february 1208 montpellier son of peter ii of aragon and marie of montpellier' <table_name> : table \begin{tabular}{lllll}
\toprule
& name & birth & marriages & death \\
\midrule
0 & james i 1231-1276 & 2 february 1208 montpellier son of peter ii of aragon and marie of montpellier & eleanor 1221 1 child violant of hungary 1235 10 children teresa gil de vidaure 2 children & 27 july 1276 valencia aged 68 \\
1 & james ii 1276-1286 (first rule) & 1243 montpellier son of james i of aragon and violant of hungary & esclaramunda of foix 1275 6 children & 1311 palma de mallorca aged 68 \\
2 & alfonso i 1286-1291 & 1265 valencia son of peter iii of aragon and constance of sicily & unmarried & 18 june 1291 barcelona aged 27 \\
3 & james iii 1291-1295 & 10 august 1267 valencia son of peter iii and constance of sicily & isabella of castile 1 december 1291 no children blanche of anjou 29 october 1295 10 children marie de lusignan 15 june 1315 no children elisenda de montcada 25 december 1322 no children & 5 november 1327 barcelona aged 60 \\
4 & james ii 1295-1311 (second rule) & 1243 montpellier son of james i of aragon and violant of hungary & esclaramunda of foix 1275 6 children & 1311 palma de mallorca aged 68 \\
5 & sancho 1311-1324 & 1276 son of james ii of majorca and esclaramunda of foix & maria of naples 20 september 1304 no children & 4 september 1324 formiguera aged 48 \\
6 & james iii of majorca 1324-1344 & 5 april 1315 catania son of ferdinand of majorca and isabelle of sabran & constance of aragon 2 children violant of vilaragut 10 november 1347 1 child & 25 october 1349 llucmajor aged 34 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "birth" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( birth ) where birth = '2 february 1208 montpellier son of peter ii of aragon and marie of montpellier' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>birth</th>
<th>marriages</th>
<th>death</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>james i 1231-1276</td>
<td>2 february 1208 montpellier son of peter ii of aragon and marie of montpellier</td>
<td>eleanor 1221 1 child violant of hungary 1235 10 children teresa gil de vidaure 2 children</td>
<td>27 july 1276 valencia aged 68</td>
</tr>
<tr>
<th>1</th>
<td>james ii 1276-1286 (first rule)</td>
<td>1243 montpellier son of james i of aragon and violant of hungary</td>
<td>esclaramunda of foix 1275 6 children</td>
<td>1311 palma de mallorca aged 68</td>
</tr>
<tr>
<th>2</th>
<td>alfonso i 1286-1291</td>
<td>1265 valencia son of peter iii of aragon and constance of sicily</td>
<td>unmarried</td>
<td>18 june 1291 barcelona aged 27</td>
</tr>
<tr>
<th>3</th>
<td>james iii 1291-1295</td>
<td>10 august 1267 valencia son of peter iii and constance of sicily</td>
<td>isabella of castile 1 december 1291 no children blanche of anjou 29 october 1295 10 children marie de lusignan 15 june 1315 no children elisenda de montcada 25 december 1322 no children</td>
<td>5 november 1327 barcelona aged 60</td>
</tr>
<tr>
<th>4</th>
<td>james ii 1295-1311 (second rule)</td>
<td>1243 montpellier son of james i of aragon and violant of hungary</td>
<td>esclaramunda of foix 1275 6 children</td>
<td>1311 palma de mallorca aged 68</td>
</tr>
<tr>
<th>5</th>
<td>sancho 1311-1324</td>
<td>1276 son of james ii of majorca and esclaramunda of foix</td>
<td>maria of naples 20 september 1304 no children</td>
<td>4 september 1324 formiguera aged 48</td>
</tr>
<tr>
<th>6</th>
<td>james iii of majorca 1324-1344</td>
<td>5 april 1315 catania son of ferdinand of majorca and isabelle of sabran</td>
<td>constance of aragon 2 children violant of vilaragut 10 november 1347 1 child</td>
<td>25 october 1349 llucmajor aged 34</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "birth" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( birth ) where birth = '2 february 1208 montpellier son of peter ii of aragon and marie of montpellier' <table_name> : table | | name | birth | marriages | death |
|---:|:---------------------------------|:-------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------|
| 0 | james i 1231-1276 | 2 february 1208 montpellier son of peter ii of aragon and marie of montpellier | eleanor 1221 1 child violant of hungary 1235 10 children teresa gil de vidaure 2 children | 27 july 1276 valencia aged 68 |
| 1 | james ii 1276-1286 (first rule) | 1243 montpellier son of james i of aragon and violant of hungary | esclaramunda of foix 1275 6 children | 1311 palma de mallorca aged 68 |
| 2 | alfonso i 1286-1291 | 1265 valencia son of peter iii of aragon and constance of sicily | unmarried | 18 june 1291 barcelona aged 27 |
| 3 | james iii 1291-1295 | 10 august 1267 valencia son of peter iii and constance of sicily | isabella of castile 1 december 1291 no children blanche of anjou 29 october 1295 10 children marie de lusignan 15 june 1315 no children elisenda de montcada 25 december 1322 no children | 5 november 1327 barcelona aged 60 |
| 4 | james ii 1295-1311 (second rule) | 1243 montpellier son of james i of aragon and violant of hungary | esclaramunda of foix 1275 6 children | 1311 palma de mallorca aged 68 |
| 5 | sancho 1311-1324 | 1276 son of james ii of majorca and esclaramunda of foix | maria of naples 20 september 1304 no children | 4 september 1324 formiguera aged 48 |
| 6 | james iii of majorca 1324-1344 | 5 april 1315 catania son of ferdinand of majorca and isabelle of sabran | constance of aragon 2 children violant of vilaragut 10 november 1347 1 child | 25 october 1349 llucmajor aged 34 | | | | count ( "birth" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select ( select count ( * ) where year = 1976 ) - ( select count ( * ) where year = 1975 ) col : year | single | chart | position row 1 : 1975 | "sun goddess" | black singles | 20 row 2 : 1975 | "sun goddess" | disco singles | 5 row 3 : 1975 | "sun goddess" | pop singles | 44 row 4 : 1976 | "can't hide love" | black singles | 11 row 5 : 1976 | "can't hide love" | pop singles | 39 row 6 : 1976 | "sing a song/gratitude" | club play singles | 1 row 7 : 1976 | "sing a song" | black singles | 1 row 8 : 1976 | "sing a song" | pop singles | 5 | col : count ( "select count ( *" ) row 1 : 0 | select ( select count ( * ) where year = 1976 ) - ( select count ( * ) where year = 1975 ) <table_name> : table \begin{tabular}{lllll}
\toprule
& year & single & chart & position \\
\midrule
0 & 1975 & "sun goddess" & black singles & 20 \\
1 & 1975 & "sun goddess" & disco singles & 5 \\
2 & 1975 & "sun goddess" & pop singles & 44 \\
3 & 1976 & "can't hide love" & black singles & 11 \\
4 & 1976 & "can't hide love" & pop singles & 39 \\
5 & 1976 & "sing a song/gratitude" & club play singles & 1 \\
6 & 1976 & "sing a song" & black singles & 1 \\
7 & 1976 & "sing a song" & pop singles & 5 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "select count ( *" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select ( select count ( * ) where year = 1976 ) - ( select count ( * ) where year = 1975 ) <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>chart</th>
<th>position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1975</td>
<td>"sun goddess"</td>
<td>black singles</td>
<td>20</td>
</tr>
<tr>
<th>1</th>
<td>1975</td>
<td>"sun goddess"</td>
<td>disco singles</td>
<td>5</td>
</tr>
<tr>
<th>2</th>
<td>1975</td>
<td>"sun goddess"</td>
<td>pop singles</td>
<td>44</td>
</tr>
<tr>
<th>3</th>
<td>1976</td>
<td>"can't hide love"</td>
<td>black singles</td>
<td>11</td>
</tr>
<tr>
<th>4</th>
<td>1976</td>
<td>"can't hide love"</td>
<td>pop singles</td>
<td>39</td>
</tr>
<tr>
<th>5</th>
<td>1976</td>
<td>"sing a song/gratitude"</td>
<td>club play singles</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>1976</td>
<td>"sing a song"</td>
<td>black singles</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>1976</td>
<td>"sing a song"</td>
<td>pop singles</td>
<td>5</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "select count ( *" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select ( select count ( * ) where year = 1976 ) - ( select count ( * ) where year = 1975 ) <table_name> : table | | year | single | chart | position |
|---:|-------:|:------------------------|:------------------|-----------:|
| 0 | 1975 | "sun goddess" | black singles | 20 |
| 1 | 1975 | "sun goddess" | disco singles | 5 |
| 2 | 1975 | "sun goddess" | pop singles | 44 |
| 3 | 1976 | "can't hide love" | black singles | 11 |
| 4 | 1976 | "can't hide love" | pop singles | 39 |
| 5 | 1976 | "sing a song/gratitude" | club play singles | 1 |
| 6 | 1976 | "sing a song" | black singles | 1 |
| 7 | 1976 | "sing a song" | pop singles | 5 | | | | count ( "select count ( *" ) |
|---:|-------------------------------:|
| 0 | 0 | | [
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select winner where stages = 17 col : year | name | date | stages | distance | winner | time row 1 : 1982 | marlboro tour | 22 april-9 may | 15 | 2,192 km | jacinto sicam (phi) | 61:29:17 row 2 : 1983 | marlboro tour | 16 april-1 may | 14 | 2,313.11 km | romeo bonzo (phi) | 63:54:31 row 3 : 1984 | marlboro tour | 26 may-10 june | 14 | 2,464 km | ruben carino (phi) | 68:08:49 row 4 : 1985 | marlboro tour | 18 april-12 may | 21 | 3,668.97 km | pepito calip (phi) | 97:04:42 row 5 : 1986 | marlboro tour | 26 april-11 may | 10 | 2,900.77 km | rolando pagnanawon (phi) | 77:39:53 row 6 : 1987 | marlboro tour | 21 may-7 june | 17 | 3,282 km | reynaldo dequito (phi) | 88:06:50 row 7 : 1988 | marlboro tour | 28 april-15 may | 17 | 3,544.53 km | armando catalan (phi) | 94:44:03 row 8 : 1989 | marlboro tour | 26 april-14 may | 18 | 3,539.47 km | gerardo igos (phi) | 95:40:23 row 9 : 1990 | marlboro tour | 18 april-6 may | 18 | 3,317.42 km | manuel buenaventura (phi) | 95:58:38 row 10 : 1991 | marlboro tour | 25 april-12 may | 17 | 2,373.61 km | bernardo llentada (phi) | 63:33:17 row 11 : 1992 | marlboro tour | 21 may-7 june | 17 | 2,731.38 km | renato dolosa (phi) | 71:21:49 row 12 : 1993 | marlboro tour | 17 april-9 may | 21 | 3,480 km | carlo guieb (phi) | 91:41:54 row 13 : 1994 | marlboro tour | 17 april-9 may | 20 | 3,563 km | carlo guieb (phi) | 91:24:13 row 14 : 1995 | marlboro tour | 18 march-8 april | 19 | 3,280.33 km | renato dolosa (phi) | 83:43:39 row 15 : 1996 | marlboro tour | 14 april-5 may | 19 | 3,257.29 km | victor espiritu (phi) | 80:50:46 row 16 : 1997 | marlboro tour | 16 april-4 may | 16 | 2,472 km | wong kam-po (hkg) | 62:06:28 row 17 : 1998 | marlboro centennial tour | 15 april-3 may | 16 | 2,494 km | warren davadilla (phi) | 64:58:57 row 18 : 1999-2001 | cancelled | cancelled | cancelled | cancelled | cancelled | cancelled | col : winner row 1 : reynaldo dequito (phi) row 2 : armando catalan (phi) row 3 : bernardo llentada (phi) row 4 : renato dolosa (phi) | select winner where stages = 17 <table_name> : table \begin{tabular}{llllllll}
\toprule
& year & name & date & stages & distance & winner & time \\
\midrule
0 & 1982 & marlboro tour & 22 april-9 may & 15 & 2,192 km & jacinto sicam (phi) & 61:29:17 \\
1 & 1983 & marlboro tour & 16 april-1 may & 14 & 2,313.11 km & romeo bonzo (phi) & 63:54:31 \\
2 & 1984 & marlboro tour & 26 may-10 june & 14 & 2,464 km & ruben carino (phi) & 68:08:49 \\
3 & 1985 & marlboro tour & 18 april-12 may & 21 & 3,668.97 km & pepito calip (phi) & 97:04:42 \\
4 & 1986 & marlboro tour & 26 april-11 may & 10 & 2,900.77 km & rolando pagnanawon (phi) & 77:39:53 \\
5 & 1987 & marlboro tour & 21 may-7 june & 17 & 3,282 km & reynaldo dequito (phi) & 88:06:50 \\
6 & 1988 & marlboro tour & 28 april-15 may & 17 & 3,544.53 km & armando catalan (phi) & 94:44:03 \\
7 & 1989 & marlboro tour & 26 april-14 may & 18 & 3,539.47 km & gerardo igos (phi) & 95:40:23 \\
8 & 1990 & marlboro tour & 18 april-6 may & 18 & 3,317.42 km & manuel buenaventura (phi) & 95:58:38 \\
9 & 1991 & marlboro tour & 25 april-12 may & 17 & 2,373.61 km & bernardo llentada (phi) & 63:33:17 \\
10 & 1992 & marlboro tour & 21 may-7 june & 17 & 2,731.38 km & renato dolosa (phi) & 71:21:49 \\
11 & 1993 & marlboro tour & 17 april-9 may & 21 & 3,480 km & carlo guieb (phi) & 91:41:54 \\
12 & 1994 & marlboro tour & 17 april-9 may & 20 & 3,563 km & carlo guieb (phi) & 91:24:13 \\
13 & 1995 & marlboro tour & 18 march-8 april & 19 & 3,280.33 km & renato dolosa (phi) & 83:43:39 \\
14 & 1996 & marlboro tour & 14 april-5 may & 19 & 3,257.29 km & victor espiritu (phi) & 80:50:46 \\
15 & 1997 & marlboro tour & 16 april-4 may & 16 & 2,472 km & wong kam-po (hkg) & 62:06:28 \\
16 & 1998 & marlboro centennial tour & 15 april-3 may & 16 & 2,494 km & warren davadilla (phi) & 64:58:57 \\
17 & 1999-2001 & cancelled & cancelled & cancelled & cancelled & cancelled & cancelled \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& winner \\
\midrule
0 & reynaldo dequito (phi) \\
1 & armando catalan (phi) \\
2 & bernardo llentada (phi) \\
3 & renato dolosa (phi) \\
\bottomrule
\end{tabular}
| select winner where stages = 17 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>name</th>
<th>date</th>
<th>stages</th>
<th>distance</th>
<th>winner</th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1982</td>
<td>marlboro tour</td>
<td>22 april-9 may</td>
<td>15</td>
<td>2,192 km</td>
<td>jacinto sicam (phi)</td>
<td>61:29:17</td>
</tr>
<tr>
<th>1</th>
<td>1983</td>
<td>marlboro tour</td>
<td>16 april-1 may</td>
<td>14</td>
<td>2,313.11 km</td>
<td>romeo bonzo (phi)</td>
<td>63:54:31</td>
</tr>
<tr>
<th>2</th>
<td>1984</td>
<td>marlboro tour</td>
<td>26 may-10 june</td>
<td>14</td>
<td>2,464 km</td>
<td>ruben carino (phi)</td>
<td>68:08:49</td>
</tr>
<tr>
<th>3</th>
<td>1985</td>
<td>marlboro tour</td>
<td>18 april-12 may</td>
<td>21</td>
<td>3,668.97 km</td>
<td>pepito calip (phi)</td>
<td>97:04:42</td>
</tr>
<tr>
<th>4</th>
<td>1986</td>
<td>marlboro tour</td>
<td>26 april-11 may</td>
<td>10</td>
<td>2,900.77 km</td>
<td>rolando pagnanawon (phi)</td>
<td>77:39:53</td>
</tr>
<tr>
<th>5</th>
<td>1987</td>
<td>marlboro tour</td>
<td>21 may-7 june</td>
<td>17</td>
<td>3,282 km</td>
<td>reynaldo dequito (phi)</td>
<td>88:06:50</td>
</tr>
<tr>
<th>6</th>
<td>1988</td>
<td>marlboro tour</td>
<td>28 april-15 may</td>
<td>17</td>
<td>3,544.53 km</td>
<td>armando catalan (phi)</td>
<td>94:44:03</td>
</tr>
<tr>
<th>7</th>
<td>1989</td>
<td>marlboro tour</td>
<td>26 april-14 may</td>
<td>18</td>
<td>3,539.47 km</td>
<td>gerardo igos (phi)</td>
<td>95:40:23</td>
</tr>
<tr>
<th>8</th>
<td>1990</td>
<td>marlboro tour</td>
<td>18 april-6 may</td>
<td>18</td>
<td>3,317.42 km</td>
<td>manuel buenaventura (phi)</td>
<td>95:58:38</td>
</tr>
<tr>
<th>9</th>
<td>1991</td>
<td>marlboro tour</td>
<td>25 april-12 may</td>
<td>17</td>
<td>2,373.61 km</td>
<td>bernardo llentada (phi)</td>
<td>63:33:17</td>
</tr>
<tr>
<th>10</th>
<td>1992</td>
<td>marlboro tour</td>
<td>21 may-7 june</td>
<td>17</td>
<td>2,731.38 km</td>
<td>renato dolosa (phi)</td>
<td>71:21:49</td>
</tr>
<tr>
<th>11</th>
<td>1993</td>
<td>marlboro tour</td>
<td>17 april-9 may</td>
<td>21</td>
<td>3,480 km</td>
<td>carlo guieb (phi)</td>
<td>91:41:54</td>
</tr>
<tr>
<th>12</th>
<td>1994</td>
<td>marlboro tour</td>
<td>17 april-9 may</td>
<td>20</td>
<td>3,563 km</td>
<td>carlo guieb (phi)</td>
<td>91:24:13</td>
</tr>
<tr>
<th>13</th>
<td>1995</td>
<td>marlboro tour</td>
<td>18 march-8 april</td>
<td>19</td>
<td>3,280.33 km</td>
<td>renato dolosa (phi)</td>
<td>83:43:39</td>
</tr>
<tr>
<th>14</th>
<td>1996</td>
<td>marlboro tour</td>
<td>14 april-5 may</td>
<td>19</td>
<td>3,257.29 km</td>
<td>victor espiritu (phi)</td>
<td>80:50:46</td>
</tr>
<tr>
<th>15</th>
<td>1997</td>
<td>marlboro tour</td>
<td>16 april-4 may</td>
<td>16</td>
<td>2,472 km</td>
<td>wong kam-po (hkg)</td>
<td>62:06:28</td>
</tr>
<tr>
<th>16</th>
<td>1998</td>
<td>marlboro centennial tour</td>
<td>15 april-3 may</td>
<td>16</td>
<td>2,494 km</td>
<td>warren davadilla (phi)</td>
<td>64:58:57</td>
</tr>
<tr>
<th>17</th>
<td>1999-2001</td>
<td>cancelled</td>
<td>cancelled</td>
<td>cancelled</td>
<td>cancelled</td>
<td>cancelled</td>
<td>cancelled</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>winner</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>reynaldo dequito (phi)</td>
</tr>
<tr>
<th>1</th>
<td>armando catalan (phi)</td>
</tr>
<tr>
<th>2</th>
<td>bernardo llentada (phi)</td>
</tr>
<tr>
<th>3</th>
<td>renato dolosa (phi)</td>
</tr>
</tbody>
</table> | select winner where stages = 17 <table_name> : table | | year | name | date | stages | distance | winner | time |
|---:|:----------|:-------------------------|:-----------------|:----------|:------------|:--------------------------|:----------|
| 0 | 1982 | marlboro tour | 22 april-9 may | 15 | 2,192 km | jacinto sicam (phi) | 61:29:17 |
| 1 | 1983 | marlboro tour | 16 april-1 may | 14 | 2,313.11 km | romeo bonzo (phi) | 63:54:31 |
| 2 | 1984 | marlboro tour | 26 may-10 june | 14 | 2,464 km | ruben carino (phi) | 68:08:49 |
| 3 | 1985 | marlboro tour | 18 april-12 may | 21 | 3,668.97 km | pepito calip (phi) | 97:04:42 |
| 4 | 1986 | marlboro tour | 26 april-11 may | 10 | 2,900.77 km | rolando pagnanawon (phi) | 77:39:53 |
| 5 | 1987 | marlboro tour | 21 may-7 june | 17 | 3,282 km | reynaldo dequito (phi) | 88:06:50 |
| 6 | 1988 | marlboro tour | 28 april-15 may | 17 | 3,544.53 km | armando catalan (phi) | 94:44:03 |
| 7 | 1989 | marlboro tour | 26 april-14 may | 18 | 3,539.47 km | gerardo igos (phi) | 95:40:23 |
| 8 | 1990 | marlboro tour | 18 april-6 may | 18 | 3,317.42 km | manuel buenaventura (phi) | 95:58:38 |
| 9 | 1991 | marlboro tour | 25 april-12 may | 17 | 2,373.61 km | bernardo llentada (phi) | 63:33:17 |
| 10 | 1992 | marlboro tour | 21 may-7 june | 17 | 2,731.38 km | renato dolosa (phi) | 71:21:49 |
| 11 | 1993 | marlboro tour | 17 april-9 may | 21 | 3,480 km | carlo guieb (phi) | 91:41:54 |
| 12 | 1994 | marlboro tour | 17 april-9 may | 20 | 3,563 km | carlo guieb (phi) | 91:24:13 |
| 13 | 1995 | marlboro tour | 18 march-8 april | 19 | 3,280.33 km | renato dolosa (phi) | 83:43:39 |
| 14 | 1996 | marlboro tour | 14 april-5 may | 19 | 3,257.29 km | victor espiritu (phi) | 80:50:46 |
| 15 | 1997 | marlboro tour | 16 april-4 may | 16 | 2,472 km | wong kam-po (hkg) | 62:06:28 |
| 16 | 1998 | marlboro centennial tour | 15 april-3 may | 16 | 2,494 km | warren davadilla (phi) | 64:58:57 |
| 17 | 1999-2001 | cancelled | cancelled | cancelled | cancelled | cancelled | cancelled | | | | winner |
|---:|:------------------------|
| 0 | reynaldo dequito (phi) |
| 1 | armando catalan (phi) |
| 2 | bernardo llentada (phi) |
| 3 | renato dolosa (phi) | | [
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select count ( * ) where reg. season = '2007' col : year | division | league | reg. season | playoffs row 1 : 2003 | 2 | usl w-league | 5th, western | none row 2 : 2004 | 1 | usl w-league | 8th, western | none row 3 : 2005 | 1 | usl w-league | 6th, western | none row 4 : 2006 | 1 | usl w-league | 5th, western | none row 5 : 2007 | 1 | usl w-league | 5th, western | none row 6 : 2008 | 1 | usl w-league | 6th, western | did not qualify row 7 : 2009 | 1 | usl w-league | 7th, western | did not qualify row 8 : 2010 | 1 | usl w-league | 6th, western | did not qualify row 9 : 2011 | 1 | usl w-league | 7th, western | did not qualify row 10 : 2012 | 1 | usl w-league | 4th, western | did not qualify row 11 : 2013 | 1 | usl w-league | 4th, western | did not qualify | col : count ( "*" ) row 1 : 0 | select count ( * ) where reg. season = '2007' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & division & league & reg. season & playoffs \\
\midrule
0 & 2003 & 2 & usl w-league & 5th, western & none \\
1 & 2004 & 1 & usl w-league & 8th, western & none \\
2 & 2005 & 1 & usl w-league & 6th, western & none \\
3 & 2006 & 1 & usl w-league & 5th, western & none \\
4 & 2007 & 1 & usl w-league & 5th, western & none \\
5 & 2008 & 1 & usl w-league & 6th, western & did not qualify \\
6 & 2009 & 1 & usl w-league & 7th, western & did not qualify \\
7 & 2010 & 1 & usl w-league & 6th, western & did not qualify \\
8 & 2011 & 1 & usl w-league & 7th, western & did not qualify \\
9 & 2012 & 1 & usl w-league & 4th, western & did not qualify \\
10 & 2013 & 1 & usl w-league & 4th, western & did not qualify \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where reg. season = '2007' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>division</th>
<th>league</th>
<th>reg. season</th>
<th>playoffs</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2003</td>
<td>2</td>
<td>usl w-league</td>
<td>5th, western</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2004</td>
<td>1</td>
<td>usl w-league</td>
<td>8th, western</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>2005</td>
<td>1</td>
<td>usl w-league</td>
<td>6th, western</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2006</td>
<td>1</td>
<td>usl w-league</td>
<td>5th, western</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>2007</td>
<td>1</td>
<td>usl w-league</td>
<td>5th, western</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2008</td>
<td>1</td>
<td>usl w-league</td>
<td>6th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>6</th>
<td>2009</td>
<td>1</td>
<td>usl w-league</td>
<td>7th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>7</th>
<td>2010</td>
<td>1</td>
<td>usl w-league</td>
<td>6th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>8</th>
<td>2011</td>
<td>1</td>
<td>usl w-league</td>
<td>7th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>9</th>
<td>2012</td>
<td>1</td>
<td>usl w-league</td>
<td>4th, western</td>
<td>did not qualify</td>
</tr>
<tr>
<th>10</th>
<td>2013</td>
<td>1</td>
<td>usl w-league</td>
<td>4th, western</td>
<td>did not qualify</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where reg. season = '2007' <table_name> : table | | year | division | league | reg. season | playoffs |
|---:|-------:|-----------:|:-------------|:--------------|:----------------|
| 0 | 2003 | 2 | usl w-league | 5th, western | none |
| 1 | 2004 | 1 | usl w-league | 8th, western | none |
| 2 | 2005 | 1 | usl w-league | 6th, western | none |
| 3 | 2006 | 1 | usl w-league | 5th, western | none |
| 4 | 2007 | 1 | usl w-league | 5th, western | none |
| 5 | 2008 | 1 | usl w-league | 6th, western | did not qualify |
| 6 | 2009 | 1 | usl w-league | 7th, western | did not qualify |
| 7 | 2010 | 1 | usl w-league | 6th, western | did not qualify |
| 8 | 2011 | 1 | usl w-league | 7th, western | did not qualify |
| 9 | 2012 | 1 | usl w-league | 4th, western | did not qualify |
| 10 | 2013 | 1 | usl w-league | 4th, western | did not qualify | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( * ) where robot's name = 'noshi origami' col : subject | robot's name | who? | when? | where? | occupation row 1 : solar system | cosmo-bot | copernicus | 1531 | poland | cosmonaut row 2 : olympics | rhonda robot | greeks | 776 b.c | greece | beauty queen row 3 : basketball | danny defrost-bot | james naismith | 1891 | united states | snowman row 4 : nursing | dr. bug-bot | florence nightengale | 1860 | england | doctor row 5 : scuba gear | flip the high-diving robot | jacques cousteau | 1946 | france | diver row 6 : helicopter | amelia air-bot | leonardo da vinci | 1483 | italy | pilot row 7 : corn flakes | chef boy-robot | william kellogg | 1894 | battle creek, michigan | cook row 8 : radium | miss battery-bot | marie curie | 1898 | france | battery lady row 9 : chewing gum | bubble-bot | mayans | 400 | mexico | bubble man row 10 : painting | pierro-bot | stone-age humans | 35,000 b.c | europe | clown/artist row 11 : phonograph | slide the heavy-metal robot | thomas edison | 1877 | new jersey | rock star row 12 : paper | noshi origami | ts'ai lun | 105 | china | origami maker row 13 : round earth | vasco da robot | ferdinand magellan | 1522 | spain | early sailor row 14 : dynamite | robby robot | alfred nobel | 1866 | sweden | prankster row 15 : microscope | slobot | antonie van leeuwenhoek | 1674 | the netherlands | dirty person row 16 : writing | eraser-bot | sumerians | 3,500 b.c | middle east | pencil man row 17 : sausage | sock-bot | babylonians | 3,000 b.c | middle east | sock man row 18 : bicycle | booster-bot | karl von drais | 1816 | germany | rocket man row 19 : wheel | rollin' road-bot | sumerians | 3,000 b.c | middle east | race starter row 20 : germs | roast-bot | louis pasteur | 1865 | france | firefighter row 21 : boomerang | oswald the mailman robot | aborigines | 40,000 years ago | australia | mailman row 22 : coins | verna the vend-bot | lydians | 600 b.c | turkey | vending machine row 23 : tools | hank the handyman robot | stone-age humans | 21⁄2 million years ago | africa | mechanic row 24 : saxophone | bongo-bot the six-armed robot | antoine-joseph sax | 1846 | france | six-armed drum player row 25 : toilet | brunwella the bombshell | minoans | 2000 b.c | crete | demolisher | col : count ( "*" ) row 1 : 1 | select count ( * ) where robot's name = 'noshi origami' <table_name> : table \begin{tabular}{lllllll}
\toprule
& subject & robot's name & who? & when? & where? & occupation \\
\midrule
0 & solar system & cosmo-bot & copernicus & 1531 & poland & cosmonaut \\
1 & olympics & rhonda robot & greeks & 776 b.c & greece & beauty queen \\
2 & basketball & danny defrost-bot & james naismith & 1891 & united states & snowman \\
3 & nursing & dr. bug-bot & florence nightengale & 1860 & england & doctor \\
4 & scuba gear & flip the high-diving robot & jacques cousteau & 1946 & france & diver \\
5 & helicopter & amelia air-bot & leonardo da vinci & 1483 & italy & pilot \\
6 & corn flakes & chef boy-robot & william kellogg & 1894 & battle creek, michigan & cook \\
7 & radium & miss battery-bot & marie curie & 1898 & france & battery lady \\
8 & chewing gum & bubble-bot & mayans & 400 & mexico & bubble man \\
9 & painting & pierro-bot & stone-age humans & 35,000 b.c & europe & clown/artist \\
10 & phonograph & slide the heavy-metal robot & thomas edison & 1877 & new jersey & rock star \\
11 & paper & noshi origami & ts'ai lun & 105 & china & origami maker \\
12 & round earth & vasco da robot & ferdinand magellan & 1522 & spain & early sailor \\
13 & dynamite & robby robot & alfred nobel & 1866 & sweden & prankster \\
14 & microscope & slobot & antonie van leeuwenhoek & 1674 & the netherlands & dirty person \\
15 & writing & eraser-bot & sumerians & 3,500 b.c & middle east & pencil man \\
16 & sausage & sock-bot & babylonians & 3,000 b.c & middle east & sock man \\
17 & bicycle & booster-bot & karl von drais & 1816 & germany & rocket man \\
18 & wheel & rollin' road-bot & sumerians & 3,000 b.c & middle east & race starter \\
19 & germs & roast-bot & louis pasteur & 1865 & france & firefighter \\
20 & boomerang & oswald the mailman robot & aborigines & 40,000 years ago & australia & mailman \\
21 & coins & verna the vend-bot & lydians & 600 b.c & turkey & vending machine \\
22 & tools & hank the handyman robot & stone-age humans & 21⁄2 million years ago & africa & mechanic \\
23 & saxophone & bongo-bot the six-armed robot & antoine-joseph sax & 1846 & france & six-armed drum player \\
24 & toilet & brunwella the bombshell & minoans & 2000 b.c & crete & demolisher \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where robot's name = 'noshi origami' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>subject</th>
<th>robot's name</th>
<th>who?</th>
<th>when?</th>
<th>where?</th>
<th>occupation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>solar system</td>
<td>cosmo-bot</td>
<td>copernicus</td>
<td>1531</td>
<td>poland</td>
<td>cosmonaut</td>
</tr>
<tr>
<th>1</th>
<td>olympics</td>
<td>rhonda robot</td>
<td>greeks</td>
<td>776 b.c</td>
<td>greece</td>
<td>beauty queen</td>
</tr>
<tr>
<th>2</th>
<td>basketball</td>
<td>danny defrost-bot</td>
<td>james naismith</td>
<td>1891</td>
<td>united states</td>
<td>snowman</td>
</tr>
<tr>
<th>3</th>
<td>nursing</td>
<td>dr. bug-bot</td>
<td>florence nightengale</td>
<td>1860</td>
<td>england</td>
<td>doctor</td>
</tr>
<tr>
<th>4</th>
<td>scuba gear</td>
<td>flip the high-diving robot</td>
<td>jacques cousteau</td>
<td>1946</td>
<td>france</td>
<td>diver</td>
</tr>
<tr>
<th>5</th>
<td>helicopter</td>
<td>amelia air-bot</td>
<td>leonardo da vinci</td>
<td>1483</td>
<td>italy</td>
<td>pilot</td>
</tr>
<tr>
<th>6</th>
<td>corn flakes</td>
<td>chef boy-robot</td>
<td>william kellogg</td>
<td>1894</td>
<td>battle creek, michigan</td>
<td>cook</td>
</tr>
<tr>
<th>7</th>
<td>radium</td>
<td>miss battery-bot</td>
<td>marie curie</td>
<td>1898</td>
<td>france</td>
<td>battery lady</td>
</tr>
<tr>
<th>8</th>
<td>chewing gum</td>
<td>bubble-bot</td>
<td>mayans</td>
<td>400</td>
<td>mexico</td>
<td>bubble man</td>
</tr>
<tr>
<th>9</th>
<td>painting</td>
<td>pierro-bot</td>
<td>stone-age humans</td>
<td>35,000 b.c</td>
<td>europe</td>
<td>clown/artist</td>
</tr>
<tr>
<th>10</th>
<td>phonograph</td>
<td>slide the heavy-metal robot</td>
<td>thomas edison</td>
<td>1877</td>
<td>new jersey</td>
<td>rock star</td>
</tr>
<tr>
<th>11</th>
<td>paper</td>
<td>noshi origami</td>
<td>ts'ai lun</td>
<td>105</td>
<td>china</td>
<td>origami maker</td>
</tr>
<tr>
<th>12</th>
<td>round earth</td>
<td>vasco da robot</td>
<td>ferdinand magellan</td>
<td>1522</td>
<td>spain</td>
<td>early sailor</td>
</tr>
<tr>
<th>13</th>
<td>dynamite</td>
<td>robby robot</td>
<td>alfred nobel</td>
<td>1866</td>
<td>sweden</td>
<td>prankster</td>
</tr>
<tr>
<th>14</th>
<td>microscope</td>
<td>slobot</td>
<td>antonie van leeuwenhoek</td>
<td>1674</td>
<td>the netherlands</td>
<td>dirty person</td>
</tr>
<tr>
<th>15</th>
<td>writing</td>
<td>eraser-bot</td>
<td>sumerians</td>
<td>3,500 b.c</td>
<td>middle east</td>
<td>pencil man</td>
</tr>
<tr>
<th>16</th>
<td>sausage</td>
<td>sock-bot</td>
<td>babylonians</td>
<td>3,000 b.c</td>
<td>middle east</td>
<td>sock man</td>
</tr>
<tr>
<th>17</th>
<td>bicycle</td>
<td>booster-bot</td>
<td>karl von drais</td>
<td>1816</td>
<td>germany</td>
<td>rocket man</td>
</tr>
<tr>
<th>18</th>
<td>wheel</td>
<td>rollin' road-bot</td>
<td>sumerians</td>
<td>3,000 b.c</td>
<td>middle east</td>
<td>race starter</td>
</tr>
<tr>
<th>19</th>
<td>germs</td>
<td>roast-bot</td>
<td>louis pasteur</td>
<td>1865</td>
<td>france</td>
<td>firefighter</td>
</tr>
<tr>
<th>20</th>
<td>boomerang</td>
<td>oswald the mailman robot</td>
<td>aborigines</td>
<td>40,000 years ago</td>
<td>australia</td>
<td>mailman</td>
</tr>
<tr>
<th>21</th>
<td>coins</td>
<td>verna the vend-bot</td>
<td>lydians</td>
<td>600 b.c</td>
<td>turkey</td>
<td>vending machine</td>
</tr>
<tr>
<th>22</th>
<td>tools</td>
<td>hank the handyman robot</td>
<td>stone-age humans</td>
<td>21⁄2 million years ago</td>
<td>africa</td>
<td>mechanic</td>
</tr>
<tr>
<th>23</th>
<td>saxophone</td>
<td>bongo-bot the six-armed robot</td>
<td>antoine-joseph sax</td>
<td>1846</td>
<td>france</td>
<td>six-armed drum player</td>
</tr>
<tr>
<th>24</th>
<td>toilet</td>
<td>brunwella the bombshell</td>
<td>minoans</td>
<td>2000 b.c</td>
<td>crete</td>
<td>demolisher</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where robot's name = 'noshi origami' <table_name> : table | | subject | robot's name | who? | when? | where? | occupation |
|---:|:-------------|:------------------------------|:------------------------|:-----------------------|:-----------------------|:----------------------|
| 0 | solar system | cosmo-bot | copernicus | 1531 | poland | cosmonaut |
| 1 | olympics | rhonda robot | greeks | 776 b.c | greece | beauty queen |
| 2 | basketball | danny defrost-bot | james naismith | 1891 | united states | snowman |
| 3 | nursing | dr. bug-bot | florence nightengale | 1860 | england | doctor |
| 4 | scuba gear | flip the high-diving robot | jacques cousteau | 1946 | france | diver |
| 5 | helicopter | amelia air-bot | leonardo da vinci | 1483 | italy | pilot |
| 6 | corn flakes | chef boy-robot | william kellogg | 1894 | battle creek, michigan | cook |
| 7 | radium | miss battery-bot | marie curie | 1898 | france | battery lady |
| 8 | chewing gum | bubble-bot | mayans | 400 | mexico | bubble man |
| 9 | painting | pierro-bot | stone-age humans | 35,000 b.c | europe | clown/artist |
| 10 | phonograph | slide the heavy-metal robot | thomas edison | 1877 | new jersey | rock star |
| 11 | paper | noshi origami | ts'ai lun | 105 | china | origami maker |
| 12 | round earth | vasco da robot | ferdinand magellan | 1522 | spain | early sailor |
| 13 | dynamite | robby robot | alfred nobel | 1866 | sweden | prankster |
| 14 | microscope | slobot | antonie van leeuwenhoek | 1674 | the netherlands | dirty person |
| 15 | writing | eraser-bot | sumerians | 3,500 b.c | middle east | pencil man |
| 16 | sausage | sock-bot | babylonians | 3,000 b.c | middle east | sock man |
| 17 | bicycle | booster-bot | karl von drais | 1816 | germany | rocket man |
| 18 | wheel | rollin' road-bot | sumerians | 3,000 b.c | middle east | race starter |
| 19 | germs | roast-bot | louis pasteur | 1865 | france | firefighter |
| 20 | boomerang | oswald the mailman robot | aborigines | 40,000 years ago | australia | mailman |
| 21 | coins | verna the vend-bot | lydians | 600 b.c | turkey | vending machine |
| 22 | tools | hank the handyman robot | stone-age humans | 21⁄2 million years ago | africa | mechanic |
| 23 | saxophone | bongo-bot the six-armed robot | antoine-joseph sax | 1846 | france | six-armed drum player |
| 24 | toilet | brunwella the bombshell | minoans | 2000 b.c | crete | demolisher | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select name where stage = 'ss3' col : leg | stage | time -1 | name | length | winner | time -2 | avg. spd. | rally leader row 1 : 1 (16 feb) | ss1 | 07:43 | loten 1 | 30.30 km | m. hirvonen | 16:14.1 | 111.98 km/h | m. hirvonen row 2 : 1 (16 feb) | ss2 | 08:34 | haslemoen | 11.92 km | s. loeb | 8:08.4 | 87.86 km/h | m. hirvonen row 3 : 1 (16 feb) | ss3 | 11:24 | loten 2 | 30.30 km | m. hirvonen | 16:09.9 | 112.47 km/h | m. hirvonen row 4 : 1 (16 feb) | ss4 | 12:30 | grue | 14.36 km | s. loeb | 7:31.8 | 114.42 km/h | m. hirvonen row 5 : 1 (16 feb) | ss5 | 13:52 | opaker | 14.64 km | j. latvala | 7:59.8 | 109.85 km/h | m. hirvonen row 6 : 1 (16 feb) | ss6 | 14:36 | kongsvinger | 14.60 km | s. loeb | 9:44.5 | 89.92 km/h | m. hirvonen row 7 : 1 (16 feb) | ss7 | 15:30 | finnskogen | 21.29 km | s. loeb | 12:42.3 | 100.54 km/h | m. hirvonen row 8 : 1 (16 feb) | ss8 | 16:33 | kirkanaer | 6.75 km | s. loeb | 5:48.9 | 69.65 km/h | m. hirvonen row 9 : 2 (17 feb) | ss9 | 08:09 | eleverum 1 | 44.27 km | m. hirvonen | 24:40.3 | 107.66 km/h | m. hirvonen row 10 : 2 (17 feb) | ss10 | 09:23 | terningmoen | 12.71 km | d. sordo | 7:59.1 | 95.5 km/h | m. hirvonen row 11 : 2 (17 feb) | ss11 | 12:05 | mountain 1 | 24.36 km | m. hirvonen | 14:01.8 | 104.18 km/h | m. hirvonen row 12 : 2 (17 feb) | ss12 | 13:06 | lillehammar | 5.98 km | m. gronholm | 4:33.9 | 78.6 km/h | m. hirvonen row 13 : 2 (17 feb) | ss13 | 14:00 | ringsaker 1 | 27.30 km | m. gronholm | 16:29.7 | 99.3 km/h | m. hirvonen row 14 : 2 (17 feb) | ss14 | 15:10 | hamar 1 | 1.14 km | m. gronholm | 1:13.8 | 55.61 km/h | m. hirvonen row 15 : 3 (18 feb) | ss15 | 08:08 | mountain 2 | 24.36 km | s. loeb | 13:18.2 | 109.87 km/h | m. hirvonen row 16 : 3 (18 feb) | ss16 | 08:55 | ringsaker 2 | 27.30 km | h. solberg | 15:28.6 | 105.84 km/h | m. hirvonen row 17 : 3 (18 feb) | ss17 | 10:05 | hamar 2 | 1.14 km | x. pons s. loeb p. solberg | 1:11.8 | 57.16 km/h | m. hirvonen row 18 : 3 (18 feb) | ss18 | 12:14 | eleverum 2 | 44.27 km | m. gronholm | 24:10.3 | 109.89 km/h | m. hirvonen | col : name row 1 : loten 2 | select name where stage = 'ss3' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& leg & stage & time -1 & name & length & winner & time -2 & avg. spd. & rally leader \\
\midrule
0 & 1 (16 feb) & ss1 & 07:43 & loten 1 & 30.30 km & m. hirvonen & 16:14.1 & 111.98 km/h & m. hirvonen \\
1 & 1 (16 feb) & ss2 & 08:34 & haslemoen & 11.92 km & s. loeb & 8:08.4 & 87.86 km/h & m. hirvonen \\
2 & 1 (16 feb) & ss3 & 11:24 & loten 2 & 30.30 km & m. hirvonen & 16:09.9 & 112.47 km/h & m. hirvonen \\
3 & 1 (16 feb) & ss4 & 12:30 & grue & 14.36 km & s. loeb & 7:31.8 & 114.42 km/h & m. hirvonen \\
4 & 1 (16 feb) & ss5 & 13:52 & opaker & 14.64 km & j. latvala & 7:59.8 & 109.85 km/h & m. hirvonen \\
5 & 1 (16 feb) & ss6 & 14:36 & kongsvinger & 14.60 km & s. loeb & 9:44.5 & 89.92 km/h & m. hirvonen \\
6 & 1 (16 feb) & ss7 & 15:30 & finnskogen & 21.29 km & s. loeb & 12:42.3 & 100.54 km/h & m. hirvonen \\
7 & 1 (16 feb) & ss8 & 16:33 & kirkanaer & 6.75 km & s. loeb & 5:48.9 & 69.65 km/h & m. hirvonen \\
8 & 2 (17 feb) & ss9 & 08:09 & eleverum 1 & 44.27 km & m. hirvonen & 24:40.3 & 107.66 km/h & m. hirvonen \\
9 & 2 (17 feb) & ss10 & 09:23 & terningmoen & 12.71 km & d. sordo & 7:59.1 & 95.5 km/h & m. hirvonen \\
10 & 2 (17 feb) & ss11 & 12:05 & mountain 1 & 24.36 km & m. hirvonen & 14:01.8 & 104.18 km/h & m. hirvonen \\
11 & 2 (17 feb) & ss12 & 13:06 & lillehammar & 5.98 km & m. gronholm & 4:33.9 & 78.6 km/h & m. hirvonen \\
12 & 2 (17 feb) & ss13 & 14:00 & ringsaker 1 & 27.30 km & m. gronholm & 16:29.7 & 99.3 km/h & m. hirvonen \\
13 & 2 (17 feb) & ss14 & 15:10 & hamar 1 & 1.14 km & m. gronholm & 1:13.8 & 55.61 km/h & m. hirvonen \\
14 & 3 (18 feb) & ss15 & 08:08 & mountain 2 & 24.36 km & s. loeb & 13:18.2 & 109.87 km/h & m. hirvonen \\
15 & 3 (18 feb) & ss16 & 08:55 & ringsaker 2 & 27.30 km & h. solberg & 15:28.6 & 105.84 km/h & m. hirvonen \\
16 & 3 (18 feb) & ss17 & 10:05 & hamar 2 & 1.14 km & x. pons s. loeb p. solberg & 1:11.8 & 57.16 km/h & m. hirvonen \\
17 & 3 (18 feb) & ss18 & 12:14 & eleverum 2 & 44.27 km & m. gronholm & 24:10.3 & 109.89 km/h & m. hirvonen \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & loten 2 \\
\bottomrule
\end{tabular}
| select name where stage = 'ss3' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>leg</th>
<th>stage</th>
<th>time -1</th>
<th>name</th>
<th>length</th>
<th>winner</th>
<th>time -2</th>
<th>avg. spd.</th>
<th>rally leader</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1 (16 feb)</td>
<td>ss1</td>
<td>07:43</td>
<td>loten 1</td>
<td>30.30 km</td>
<td>m. hirvonen</td>
<td>16:14.1</td>
<td>111.98 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>1</th>
<td>1 (16 feb)</td>
<td>ss2</td>
<td>08:34</td>
<td>haslemoen</td>
<td>11.92 km</td>
<td>s. loeb</td>
<td>8:08.4</td>
<td>87.86 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>2</th>
<td>1 (16 feb)</td>
<td>ss3</td>
<td>11:24</td>
<td>loten 2</td>
<td>30.30 km</td>
<td>m. hirvonen</td>
<td>16:09.9</td>
<td>112.47 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>3</th>
<td>1 (16 feb)</td>
<td>ss4</td>
<td>12:30</td>
<td>grue</td>
<td>14.36 km</td>
<td>s. loeb</td>
<td>7:31.8</td>
<td>114.42 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>4</th>
<td>1 (16 feb)</td>
<td>ss5</td>
<td>13:52</td>
<td>opaker</td>
<td>14.64 km</td>
<td>j. latvala</td>
<td>7:59.8</td>
<td>109.85 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>5</th>
<td>1 (16 feb)</td>
<td>ss6</td>
<td>14:36</td>
<td>kongsvinger</td>
<td>14.60 km</td>
<td>s. loeb</td>
<td>9:44.5</td>
<td>89.92 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>6</th>
<td>1 (16 feb)</td>
<td>ss7</td>
<td>15:30</td>
<td>finnskogen</td>
<td>21.29 km</td>
<td>s. loeb</td>
<td>12:42.3</td>
<td>100.54 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>7</th>
<td>1 (16 feb)</td>
<td>ss8</td>
<td>16:33</td>
<td>kirkanaer</td>
<td>6.75 km</td>
<td>s. loeb</td>
<td>5:48.9</td>
<td>69.65 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>8</th>
<td>2 (17 feb)</td>
<td>ss9</td>
<td>08:09</td>
<td>eleverum 1</td>
<td>44.27 km</td>
<td>m. hirvonen</td>
<td>24:40.3</td>
<td>107.66 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>9</th>
<td>2 (17 feb)</td>
<td>ss10</td>
<td>09:23</td>
<td>terningmoen</td>
<td>12.71 km</td>
<td>d. sordo</td>
<td>7:59.1</td>
<td>95.5 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>10</th>
<td>2 (17 feb)</td>
<td>ss11</td>
<td>12:05</td>
<td>mountain 1</td>
<td>24.36 km</td>
<td>m. hirvonen</td>
<td>14:01.8</td>
<td>104.18 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>11</th>
<td>2 (17 feb)</td>
<td>ss12</td>
<td>13:06</td>
<td>lillehammar</td>
<td>5.98 km</td>
<td>m. gronholm</td>
<td>4:33.9</td>
<td>78.6 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>12</th>
<td>2 (17 feb)</td>
<td>ss13</td>
<td>14:00</td>
<td>ringsaker 1</td>
<td>27.30 km</td>
<td>m. gronholm</td>
<td>16:29.7</td>
<td>99.3 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>13</th>
<td>2 (17 feb)</td>
<td>ss14</td>
<td>15:10</td>
<td>hamar 1</td>
<td>1.14 km</td>
<td>m. gronholm</td>
<td>1:13.8</td>
<td>55.61 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>14</th>
<td>3 (18 feb)</td>
<td>ss15</td>
<td>08:08</td>
<td>mountain 2</td>
<td>24.36 km</td>
<td>s. loeb</td>
<td>13:18.2</td>
<td>109.87 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>15</th>
<td>3 (18 feb)</td>
<td>ss16</td>
<td>08:55</td>
<td>ringsaker 2</td>
<td>27.30 km</td>
<td>h. solberg</td>
<td>15:28.6</td>
<td>105.84 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>16</th>
<td>3 (18 feb)</td>
<td>ss17</td>
<td>10:05</td>
<td>hamar 2</td>
<td>1.14 km</td>
<td>x. pons s. loeb p. solberg</td>
<td>1:11.8</td>
<td>57.16 km/h</td>
<td>m. hirvonen</td>
</tr>
<tr>
<th>17</th>
<td>3 (18 feb)</td>
<td>ss18</td>
<td>12:14</td>
<td>eleverum 2</td>
<td>44.27 km</td>
<td>m. gronholm</td>
<td>24:10.3</td>
<td>109.89 km/h</td>
<td>m. hirvonen</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>loten 2</td>
</tr>
</tbody>
</table> | select name where stage = 'ss3' <table_name> : table | | leg | stage | time -1 | name | length | winner | time -2 | avg. spd. | rally leader |
|---:|:-----------|:--------|:----------|:------------|:---------|:---------------------------|:----------|:------------|:---------------|
| 0 | 1 (16 feb) | ss1 | 07:43 | loten 1 | 30.30 km | m. hirvonen | 16:14.1 | 111.98 km/h | m. hirvonen |
| 1 | 1 (16 feb) | ss2 | 08:34 | haslemoen | 11.92 km | s. loeb | 8:08.4 | 87.86 km/h | m. hirvonen |
| 2 | 1 (16 feb) | ss3 | 11:24 | loten 2 | 30.30 km | m. hirvonen | 16:09.9 | 112.47 km/h | m. hirvonen |
| 3 | 1 (16 feb) | ss4 | 12:30 | grue | 14.36 km | s. loeb | 7:31.8 | 114.42 km/h | m. hirvonen |
| 4 | 1 (16 feb) | ss5 | 13:52 | opaker | 14.64 km | j. latvala | 7:59.8 | 109.85 km/h | m. hirvonen |
| 5 | 1 (16 feb) | ss6 | 14:36 | kongsvinger | 14.60 km | s. loeb | 9:44.5 | 89.92 km/h | m. hirvonen |
| 6 | 1 (16 feb) | ss7 | 15:30 | finnskogen | 21.29 km | s. loeb | 12:42.3 | 100.54 km/h | m. hirvonen |
| 7 | 1 (16 feb) | ss8 | 16:33 | kirkanaer | 6.75 km | s. loeb | 5:48.9 | 69.65 km/h | m. hirvonen |
| 8 | 2 (17 feb) | ss9 | 08:09 | eleverum 1 | 44.27 km | m. hirvonen | 24:40.3 | 107.66 km/h | m. hirvonen |
| 9 | 2 (17 feb) | ss10 | 09:23 | terningmoen | 12.71 km | d. sordo | 7:59.1 | 95.5 km/h | m. hirvonen |
| 10 | 2 (17 feb) | ss11 | 12:05 | mountain 1 | 24.36 km | m. hirvonen | 14:01.8 | 104.18 km/h | m. hirvonen |
| 11 | 2 (17 feb) | ss12 | 13:06 | lillehammar | 5.98 km | m. gronholm | 4:33.9 | 78.6 km/h | m. hirvonen |
| 12 | 2 (17 feb) | ss13 | 14:00 | ringsaker 1 | 27.30 km | m. gronholm | 16:29.7 | 99.3 km/h | m. hirvonen |
| 13 | 2 (17 feb) | ss14 | 15:10 | hamar 1 | 1.14 km | m. gronholm | 1:13.8 | 55.61 km/h | m. hirvonen |
| 14 | 3 (18 feb) | ss15 | 08:08 | mountain 2 | 24.36 km | s. loeb | 13:18.2 | 109.87 km/h | m. hirvonen |
| 15 | 3 (18 feb) | ss16 | 08:55 | ringsaker 2 | 27.30 km | h. solberg | 15:28.6 | 105.84 km/h | m. hirvonen |
| 16 | 3 (18 feb) | ss17 | 10:05 | hamar 2 | 1.14 km | x. pons s. loeb p. solberg | 1:11.8 | 57.16 km/h | m. hirvonen |
| 17 | 3 (18 feb) | ss18 | 12:14 | eleverum 2 | 44.27 km | m. gronholm | 24:10.3 | 109.89 km/h | m. hirvonen | | | | name |
|---:|:--------|
| 0 | loten 2 | | [
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select count ( writer ) where writer = 'jacques stoquart and andre-paul duchateau' col : series | years | volumes | writer | editor | remarks row 1 : bruno brazil | 1973-1977 | 5 | greg | magic-strip | william vance drew the comics, follet provided the page lay-out row 2 : ivan zourine | 1979 | 2 | jacques stoquart | magic-strip | none row 3 : steve severin | 1981-2003 | 9 | jacques stoquart and yvan delporte | glenat | 3 in french - 6 additional in dutch row 4 : l'iliade | 1982 | 1 | jacques stoquart | glenat | adapted from the ilias by homer row 5 : jacques le gall | 1984-1985 | 2 | jean-michel charlier | dupuis | a collaboration with mitacq row 6 : valhardi | 1984-1986 | 2 | jacques stoquart and andre-paul duchateau | dupuis | continuation of the series after jije and eddy paape row 7 : alain brisant | 1985 | 1 | maurice tillieux | dupuis | none row 8 : edmund bell | 1987-1990 | 4 | jacques stoquart and martin lodewijk | cl. lefrancq | based on the stories by john flanders (jean ray) row 9 : daddy | 1991-92 | 2 | loup durand | cl. lefrancq | none row 10 : bob morane | 1991-2000 | 3 | henri vernes | nautilus and claude lefrancq | follet drew one story in 2000, and made the cover art for two others (drawn by gerald forton) row 11 : harricana | 1992 | 1 | jean-claude de la royere | claude lefrancq | drawn by denis merezette, follet did the page lay-out row 12 : marshall blueberry | 1994 | 1 | jean giraud | alpen | drawn by william vance, follet did the page lay-out row 13 : ikar | 1995-1997 | 2 | pierre makyo | glenat | none row 14 : les autos de l'aventure | 1996-1998 | 2 | de la royere | citroen | promotional comics row 15 : terreur | 2002-2004 | 2 | andre-paul duchateau | le lombard | fictional biography of madame tussaud row 16 : les zingari | 2004-2005 | 2 | yvan delporte | hibou | none row 17 : shelena | 2005 | 1 | jeromine pasteur | casterman | none row 18 : l'etoile du soldat | 2007 | 1 | christophe de ponfilly | casterman | announced (28 august 2007) row 19 : l'affaire dominici | 2010 | 1 | pascal bresson | glenat | none | col : count ( "writer" ) row 1 : 1 | select count ( writer ) where writer = 'jacques stoquart and andre-paul duchateau' <table_name> : table \begin{tabular}{lllllll}
\toprule
& series & years & volumes & writer & editor & remarks \\
\midrule
0 & bruno brazil & 1973-1977 & 5 & greg & magic-strip & william vance drew the comics, follet provided the page lay-out \\
1 & ivan zourine & 1979 & 2 & jacques stoquart & magic-strip & none \\
2 & steve severin & 1981-2003 & 9 & jacques stoquart and yvan delporte & glenat & 3 in french - 6 additional in dutch \\
3 & l'iliade & 1982 & 1 & jacques stoquart & glenat & adapted from the ilias by homer \\
4 & jacques le gall & 1984-1985 & 2 & jean-michel charlier & dupuis & a collaboration with mitacq \\
5 & valhardi & 1984-1986 & 2 & jacques stoquart and andre-paul duchateau & dupuis & continuation of the series after jije and eddy paape \\
6 & alain brisant & 1985 & 1 & maurice tillieux & dupuis & none \\
7 & edmund bell & 1987-1990 & 4 & jacques stoquart and martin lodewijk & cl. lefrancq & based on the stories by john flanders (jean ray) \\
8 & daddy & 1991-92 & 2 & loup durand & cl. lefrancq & none \\
9 & bob morane & 1991-2000 & 3 & henri vernes & nautilus and claude lefrancq & follet drew one story in 2000, and made the cover art for two others (drawn by gerald forton) \\
10 & harricana & 1992 & 1 & jean-claude de la royere & claude lefrancq & drawn by denis merezette, follet did the page lay-out \\
11 & marshall blueberry & 1994 & 1 & jean giraud & alpen & drawn by william vance, follet did the page lay-out \\
12 & ikar & 1995-1997 & 2 & pierre makyo & glenat & none \\
13 & les autos de l'aventure & 1996-1998 & 2 & de la royere & citroen & promotional comics \\
14 & terreur & 2002-2004 & 2 & andre-paul duchateau & le lombard & fictional biography of madame tussaud \\
15 & les zingari & 2004-2005 & 2 & yvan delporte & hibou & none \\
16 & shelena & 2005 & 1 & jeromine pasteur & casterman & none \\
17 & l'etoile du soldat & 2007 & 1 & christophe de ponfilly & casterman & announced (28 august 2007) \\
18 & l'affaire dominici & 2010 & 1 & pascal bresson & glenat & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "writer" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( writer ) where writer = 'jacques stoquart and andre-paul duchateau' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>series</th>
<th>years</th>
<th>volumes</th>
<th>writer</th>
<th>editor</th>
<th>remarks</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>bruno brazil</td>
<td>1973-1977</td>
<td>5</td>
<td>greg</td>
<td>magic-strip</td>
<td>william vance drew the comics, follet provided the page lay-out</td>
</tr>
<tr>
<th>1</th>
<td>ivan zourine</td>
<td>1979</td>
<td>2</td>
<td>jacques stoquart</td>
<td>magic-strip</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>steve severin</td>
<td>1981-2003</td>
<td>9</td>
<td>jacques stoquart and yvan delporte</td>
<td>glenat</td>
<td>3 in french - 6 additional in dutch</td>
</tr>
<tr>
<th>3</th>
<td>l'iliade</td>
<td>1982</td>
<td>1</td>
<td>jacques stoquart</td>
<td>glenat</td>
<td>adapted from the ilias by homer</td>
</tr>
<tr>
<th>4</th>
<td>jacques le gall</td>
<td>1984-1985</td>
<td>2</td>
<td>jean-michel charlier</td>
<td>dupuis</td>
<td>a collaboration with mitacq</td>
</tr>
<tr>
<th>5</th>
<td>valhardi</td>
<td>1984-1986</td>
<td>2</td>
<td>jacques stoquart and andre-paul duchateau</td>
<td>dupuis</td>
<td>continuation of the series after jije and eddy paape</td>
</tr>
<tr>
<th>6</th>
<td>alain brisant</td>
<td>1985</td>
<td>1</td>
<td>maurice tillieux</td>
<td>dupuis</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>edmund bell</td>
<td>1987-1990</td>
<td>4</td>
<td>jacques stoquart and martin lodewijk</td>
<td>cl. lefrancq</td>
<td>based on the stories by john flanders (jean ray)</td>
</tr>
<tr>
<th>8</th>
<td>daddy</td>
<td>1991-92</td>
<td>2</td>
<td>loup durand</td>
<td>cl. lefrancq</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>bob morane</td>
<td>1991-2000</td>
<td>3</td>
<td>henri vernes</td>
<td>nautilus and claude lefrancq</td>
<td>follet drew one story in 2000, and made the cover art for two others (drawn by gerald forton)</td>
</tr>
<tr>
<th>10</th>
<td>harricana</td>
<td>1992</td>
<td>1</td>
<td>jean-claude de la royere</td>
<td>claude lefrancq</td>
<td>drawn by denis merezette, follet did the page lay-out</td>
</tr>
<tr>
<th>11</th>
<td>marshall blueberry</td>
<td>1994</td>
<td>1</td>
<td>jean giraud</td>
<td>alpen</td>
<td>drawn by william vance, follet did the page lay-out</td>
</tr>
<tr>
<th>12</th>
<td>ikar</td>
<td>1995-1997</td>
<td>2</td>
<td>pierre makyo</td>
<td>glenat</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>les autos de l'aventure</td>
<td>1996-1998</td>
<td>2</td>
<td>de la royere</td>
<td>citroen</td>
<td>promotional comics</td>
</tr>
<tr>
<th>14</th>
<td>terreur</td>
<td>2002-2004</td>
<td>2</td>
<td>andre-paul duchateau</td>
<td>le lombard</td>
<td>fictional biography of madame tussaud</td>
</tr>
<tr>
<th>15</th>
<td>les zingari</td>
<td>2004-2005</td>
<td>2</td>
<td>yvan delporte</td>
<td>hibou</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>shelena</td>
<td>2005</td>
<td>1</td>
<td>jeromine pasteur</td>
<td>casterman</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>l'etoile du soldat</td>
<td>2007</td>
<td>1</td>
<td>christophe de ponfilly</td>
<td>casterman</td>
<td>announced (28 august 2007)</td>
</tr>
<tr>
<th>18</th>
<td>l'affaire dominici</td>
<td>2010</td>
<td>1</td>
<td>pascal bresson</td>
<td>glenat</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "writer" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( writer ) where writer = 'jacques stoquart and andre-paul duchateau' <table_name> : table | | series | years | volumes | writer | editor | remarks |
|---:|:------------------------|:----------|----------:|:------------------------------------------|:-----------------------------|:----------------------------------------------------------------------------------------------|
| 0 | bruno brazil | 1973-1977 | 5 | greg | magic-strip | william vance drew the comics, follet provided the page lay-out |
| 1 | ivan zourine | 1979 | 2 | jacques stoquart | magic-strip | none |
| 2 | steve severin | 1981-2003 | 9 | jacques stoquart and yvan delporte | glenat | 3 in french - 6 additional in dutch |
| 3 | l'iliade | 1982 | 1 | jacques stoquart | glenat | adapted from the ilias by homer |
| 4 | jacques le gall | 1984-1985 | 2 | jean-michel charlier | dupuis | a collaboration with mitacq |
| 5 | valhardi | 1984-1986 | 2 | jacques stoquart and andre-paul duchateau | dupuis | continuation of the series after jije and eddy paape |
| 6 | alain brisant | 1985 | 1 | maurice tillieux | dupuis | none |
| 7 | edmund bell | 1987-1990 | 4 | jacques stoquart and martin lodewijk | cl. lefrancq | based on the stories by john flanders (jean ray) |
| 8 | daddy | 1991-92 | 2 | loup durand | cl. lefrancq | none |
| 9 | bob morane | 1991-2000 | 3 | henri vernes | nautilus and claude lefrancq | follet drew one story in 2000, and made the cover art for two others (drawn by gerald forton) |
| 10 | harricana | 1992 | 1 | jean-claude de la royere | claude lefrancq | drawn by denis merezette, follet did the page lay-out |
| 11 | marshall blueberry | 1994 | 1 | jean giraud | alpen | drawn by william vance, follet did the page lay-out |
| 12 | ikar | 1995-1997 | 2 | pierre makyo | glenat | none |
| 13 | les autos de l'aventure | 1996-1998 | 2 | de la royere | citroen | promotional comics |
| 14 | terreur | 2002-2004 | 2 | andre-paul duchateau | le lombard | fictional biography of madame tussaud |
| 15 | les zingari | 2004-2005 | 2 | yvan delporte | hibou | none |
| 16 | shelena | 2005 | 1 | jeromine pasteur | casterman | none |
| 17 | l'etoile du soldat | 2007 | 1 | christophe de ponfilly | casterman | announced (28 august 2007) |
| 18 | l'affaire dominici | 2010 | 1 | pascal bresson | glenat | none | | | | count ( "writer" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select speed (mph) where date = '3 oct 1967' col : category | speed (km/h) | speed (mph) | vehicle | pilot | date row 1 : rocket-powered aircraft | 7258.0 | 4510.0 | north american x-15 | william j. knight | 1967-10-03 00:00:00 row 2 : manned air-breathing craft | 3530.0 | 2194.0 | lockheed sr-71 blackbird | eldon w. joersz | 1976-07-28 00:00:00 row 3 : propeller-driven aircraft | 870.0 | 541.0 | tupolev tu-114 | ivan soukhomline | 1960-01-01 00:00:00 row 4 : piston-engined propeller-driven aircraft | 850.1 | 528.33 | grumman f8f bearcat rare bear (n777l) | lyle shelton | 1989-08-21 00:00:00 row 5 : helicopter | 401.0 | 249.1 | westland lynx 800 g-lynx | john egginton | 1986-08-11 00:00:00 row 6 : glider (sailplane) | 306.8 | 190.6 | schempp-hirth nimbus-4dm | klaus ohlmann and matias garcia mazzaro | 2006-12-22 00:00:00 row 7 : human-powered aircraft | 32.0 | 19.8 | mit monarch b | frank scarabino | 1984-05-01 00:00:00 | col : speed (mph) row 1 : 4510 | select speed (mph) where date = '3 oct 1967' <table_name> : table \begin{tabular}{lllllll}
\toprule
& category & speed (km/h) & speed (mph) & vehicle & pilot & date \\
\midrule
0 & rocket-powered aircraft & 7258.0 & 4510.0 & north american x-15 & william j. knight & 1967-10-03 00:00:00 \\
1 & manned air-breathing craft & 3530.0 & 2194.0 & lockheed sr-71 blackbird & eldon w. joersz & 1976-07-28 00:00:00 \\
2 & propeller-driven aircraft & 870.0 & 541.0 & tupolev tu-114 & ivan soukhomline & 1960-01-01 00:00:00 \\
3 & piston-engined propeller-driven aircraft & 850.1 & 528.33 & grumman f8f bearcat rare bear (n777l) & lyle shelton & 1989-08-21 00:00:00 \\
4 & helicopter & 401.0 & 249.1 & westland lynx 800 g-lynx & john egginton & 1986-08-11 00:00:00 \\
5 & glider (sailplane) & 306.8 & 190.6 & schempp-hirth nimbus-4dm & klaus ohlmann and matias garcia mazzaro & 2006-12-22 00:00:00 \\
6 & human-powered aircraft & 32.0 & 19.8 & mit monarch b & frank scarabino & 1984-05-01 00:00:00 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& speed (mph) \\
\midrule
0 & 4510 \\
\bottomrule
\end{tabular}
| select speed (mph) where date = '3 oct 1967' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
<th>speed (km/h)</th>
<th>speed (mph)</th>
<th>vehicle</th>
<th>pilot</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rocket-powered aircraft</td>
<td>7258.0</td>
<td>4510.0</td>
<td>north american x-15</td>
<td>william j. knight</td>
<td>1967-10-03 00:00:00</td>
</tr>
<tr>
<th>1</th>
<td>manned air-breathing craft</td>
<td>3530.0</td>
<td>2194.0</td>
<td>lockheed sr-71 blackbird</td>
<td>eldon w. joersz</td>
<td>1976-07-28 00:00:00</td>
</tr>
<tr>
<th>2</th>
<td>propeller-driven aircraft</td>
<td>870.0</td>
<td>541.0</td>
<td>tupolev tu-114</td>
<td>ivan soukhomline</td>
<td>1960-01-01 00:00:00</td>
</tr>
<tr>
<th>3</th>
<td>piston-engined propeller-driven aircraft</td>
<td>850.1</td>
<td>528.33</td>
<td>grumman f8f bearcat rare bear (n777l)</td>
<td>lyle shelton</td>
<td>1989-08-21 00:00:00</td>
</tr>
<tr>
<th>4</th>
<td>helicopter</td>
<td>401.0</td>
<td>249.1</td>
<td>westland lynx 800 g-lynx</td>
<td>john egginton</td>
<td>1986-08-11 00:00:00</td>
</tr>
<tr>
<th>5</th>
<td>glider (sailplane)</td>
<td>306.8</td>
<td>190.6</td>
<td>schempp-hirth nimbus-4dm</td>
<td>klaus ohlmann and matias garcia mazzaro</td>
<td>2006-12-22 00:00:00</td>
</tr>
<tr>
<th>6</th>
<td>human-powered aircraft</td>
<td>32.0</td>
<td>19.8</td>
<td>mit monarch b</td>
<td>frank scarabino</td>
<td>1984-05-01 00:00:00</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>speed (mph)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4510</td>
</tr>
</tbody>
</table> | select speed (mph) where date = '3 oct 1967' <table_name> : table | | category | speed (km/h) | speed (mph) | vehicle | pilot | date |
|---:|:-----------------------------------------|---------------:|--------------:|:--------------------------------------|:----------------------------------------|:--------------------|
| 0 | rocket-powered aircraft | 7258 | 4510 | north american x-15 | william j. knight | 1967-10-03 00:00:00 |
| 1 | manned air-breathing craft | 3530 | 2194 | lockheed sr-71 blackbird | eldon w. joersz | 1976-07-28 00:00:00 |
| 2 | propeller-driven aircraft | 870 | 541 | tupolev tu-114 | ivan soukhomline | 1960-01-01 00:00:00 |
| 3 | piston-engined propeller-driven aircraft | 850.1 | 528.33 | grumman f8f bearcat rare bear (n777l) | lyle shelton | 1989-08-21 00:00:00 |
| 4 | helicopter | 401 | 249.1 | westland lynx 800 g-lynx | john egginton | 1986-08-11 00:00:00 |
| 5 | glider (sailplane) | 306.8 | 190.6 | schempp-hirth nimbus-4dm | klaus ohlmann and matias garcia mazzaro | 2006-12-22 00:00:00 |
| 6 | human-powered aircraft | 32 | 19.8 | mit monarch b | frank scarabino | 1984-05-01 00:00:00 | | | | speed (mph) |
|---:|--------------:|
| 0 | 4510 | | [
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select count ( * ) where country = 1149 col : season | team | country | division | apps | goals | assists row 1 : 01/02 | esteghlal | iran | 1 | none | 3 | none row 2 : 02/03 | esteghlal | iran | 1 | none | 2 | none row 3 : 03/04 | esteghlal | iran | 1 | none | 6 | none row 4 : 04/05 | eseghlal | iran | 1 | 27 | 3 | none row 5 : 05/06 | esteghlal | iran | 1 | 21 | 0 | 2 row 6 : 06/07 | esteghlal | iran | 1 | 14 | 1 | 1 row 7 : 07/08 | steel azin | iran | 1 | none | 2 | none row 8 : 10/11 | gostaresh foolad | iran | 2 | 0 | 0 | 0 | col : count ( "*" ) row 1 : 0 | select count ( * ) where country = 1149 <table_name> : table \begin{tabular}{llllllll}
\toprule
& season & team & country & division & apps & goals & assists \\
\midrule
0 & 01/02 & esteghlal & iran & 1 & none & 3 & none \\
1 & 02/03 & esteghlal & iran & 1 & none & 2 & none \\
2 & 03/04 & esteghlal & iran & 1 & none & 6 & none \\
3 & 04/05 & eseghlal & iran & 1 & 27 & 3 & none \\
4 & 05/06 & esteghlal & iran & 1 & 21 & 0 & 2 \\
5 & 06/07 & esteghlal & iran & 1 & 14 & 1 & 1 \\
6 & 07/08 & steel azin & iran & 1 & none & 2 & none \\
7 & 10/11 & gostaresh foolad & iran & 2 & 0 & 0 & 0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where country = 1149 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>team</th>
<th>country</th>
<th>division</th>
<th>apps</th>
<th>goals</th>
<th>assists</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>01/02</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>02/03</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>03/04</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>04/05</td>
<td>eseghlal</td>
<td>iran</td>
<td>1</td>
<td>27</td>
<td>3</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>05/06</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>21</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>06/07</td>
<td>esteghlal</td>
<td>iran</td>
<td>1</td>
<td>14</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>07/08</td>
<td>steel azin</td>
<td>iran</td>
<td>1</td>
<td>none</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>10/11</td>
<td>gostaresh foolad</td>
<td>iran</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where country = 1149 <table_name> : table | | season | team | country | division | apps | goals | assists |
|---:|:---------|:-----------------|:----------|-----------:|:-------|--------:|:----------|
| 0 | 01/02 | esteghlal | iran | 1 | none | 3 | none |
| 1 | 02/03 | esteghlal | iran | 1 | none | 2 | none |
| 2 | 03/04 | esteghlal | iran | 1 | none | 6 | none |
| 3 | 04/05 | eseghlal | iran | 1 | 27 | 3 | none |
| 4 | 05/06 | esteghlal | iran | 1 | 21 | 0 | 2 |
| 5 | 06/07 | esteghlal | iran | 1 | 14 | 1 | 1 |
| 6 | 07/08 | steel azin | iran | 1 | none | 2 | none |
| 7 | 10/11 | gostaresh foolad | iran | 2 | 0 | 0 | 0 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select v2 where n = 154 col : category | age (ethnicity) | n | v1 | v2 | v3 | v4 | v5 | v6 row 1 : none | 1 week - 1 y | 210 | 92% | 74% | 27% | 20% | 0.50% | 0% row 2 : none | 1 y - 2 y | 154 | 96% | 85% | 39% | 10% | 0.70% | 0% row 3 : none | 2 y - 5 y | 202 | 98% | 50% | 22% | 7% | 1% | 0% row 4 : none | 5 y - 8 y | 94 | 91% | 25% | 14% | 5% | 1% | 1% row 5 : none | 8 y - 16 y | 90 | 62% | 7% | 2% | 0% | 0% | 0% row 6 : males | 12 y - 13 y | 209 | 47% | 7% | 0% | 0% | 0% | 0% row 7 : males | 13 y - 14 y | 260 | 35% | 4.60% | 0.80% | 0% | 0% | 0% row 8 : males | 16 y - 19 y (whites) | 50 | 32% | 0% | 0% | 0% | 0% | 0% row 9 : males | 16 y - 19 y (blacks) | 310 | 46% | 7% | 2.90% | 1.30% | 0% | 0% row 10 : males | 20 - 30 y (whites) | 285 | 41% | 0% | 0% | 0% | 0% | 0% row 11 : males | 20 - 30 y (blacks) | 295 | 37% | 0% | 0% | 0% | 0% | 0% row 12 : females | 12 y - 13 y | 174 | 69% | 11% | 1.20% | 0% | 0% | 0% row 13 : females | 13 y - 14 y | 154 | 52% | 8.40% | 1.40% | 0% | 0% | 0% row 14 : females | 16 y - 19 y (whites) | 50 | 66% | 0% | 0% | 0% | 0% | 0% row 15 : females | 16 - 19 y (blacks) | 310 | 73% | 9% | 1.30% | 0.60% | 0% | 0% row 16 : females | 20 - 30 y (whites) | 280 | 55% | 0% | 0% | 0% | 0% | 0% row 17 : females | 20 - 30 y (blacks) | 330 | 55% | 2.40% | 1% | 0% | 0% | 0% | col : v2 row 1 : 85% row 2 : 8.40% | select v2 where n = 154 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& category & age (ethnicity) & n & v1 & v2 & v3 & v4 & v5 & v6 \\
\midrule
0 & none & 1 week - 1 y & 210 & 92% & 74% & 27% & 20% & 0.50% & 0% \\
1 & none & 1 y - 2 y & 154 & 96% & 85% & 39% & 10% & 0.70% & 0% \\
2 & none & 2 y - 5 y & 202 & 98% & 50% & 22% & 7% & 1% & 0% \\
3 & none & 5 y - 8 y & 94 & 91% & 25% & 14% & 5% & 1% & 1% \\
4 & none & 8 y - 16 y & 90 & 62% & 7% & 2% & 0% & 0% & 0% \\
5 & males & 12 y - 13 y & 209 & 47% & 7% & 0% & 0% & 0% & 0% \\
6 & males & 13 y - 14 y & 260 & 35% & 4.60% & 0.80% & 0% & 0% & 0% \\
7 & males & 16 y - 19 y (whites) & 50 & 32% & 0% & 0% & 0% & 0% & 0% \\
8 & males & 16 y - 19 y (blacks) & 310 & 46% & 7% & 2.90% & 1.30% & 0% & 0% \\
9 & males & 20 - 30 y (whites) & 285 & 41% & 0% & 0% & 0% & 0% & 0% \\
10 & males & 20 - 30 y (blacks) & 295 & 37% & 0% & 0% & 0% & 0% & 0% \\
11 & females & 12 y - 13 y & 174 & 69% & 11% & 1.20% & 0% & 0% & 0% \\
12 & females & 13 y - 14 y & 154 & 52% & 8.40% & 1.40% & 0% & 0% & 0% \\
13 & females & 16 y - 19 y (whites) & 50 & 66% & 0% & 0% & 0% & 0% & 0% \\
14 & females & 16 - 19 y (blacks) & 310 & 73% & 9% & 1.30% & 0.60% & 0% & 0% \\
15 & females & 20 - 30 y (whites) & 280 & 55% & 0% & 0% & 0% & 0% & 0% \\
16 & females & 20 - 30 y (blacks) & 330 & 55% & 2.40% & 1% & 0% & 0% & 0% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& v2 \\
\midrule
0 & 85% \\
1 & 8.40% \\
\bottomrule
\end{tabular}
| select v2 where n = 154 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>category</th>
<th>age (ethnicity)</th>
<th>n</th>
<th>v1</th>
<th>v2</th>
<th>v3</th>
<th>v4</th>
<th>v5</th>
<th>v6</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>1 week - 1 y</td>
<td>210</td>
<td>92%</td>
<td>74%</td>
<td>27%</td>
<td>20%</td>
<td>0.50%</td>
<td>0%</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>1 y - 2 y</td>
<td>154</td>
<td>96%</td>
<td>85%</td>
<td>39%</td>
<td>10%</td>
<td>0.70%</td>
<td>0%</td>
</tr>
<tr>
<th>2</th>
<td>none</td>
<td>2 y - 5 y</td>
<td>202</td>
<td>98%</td>
<td>50%</td>
<td>22%</td>
<td>7%</td>
<td>1%</td>
<td>0%</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
<td>5 y - 8 y</td>
<td>94</td>
<td>91%</td>
<td>25%</td>
<td>14%</td>
<td>5%</td>
<td>1%</td>
<td>1%</td>
</tr>
<tr>
<th>4</th>
<td>none</td>
<td>8 y - 16 y</td>
<td>90</td>
<td>62%</td>
<td>7%</td>
<td>2%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>5</th>
<td>males</td>
<td>12 y - 13 y</td>
<td>209</td>
<td>47%</td>
<td>7%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>6</th>
<td>males</td>
<td>13 y - 14 y</td>
<td>260</td>
<td>35%</td>
<td>4.60%</td>
<td>0.80%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>7</th>
<td>males</td>
<td>16 y - 19 y (whites)</td>
<td>50</td>
<td>32%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>8</th>
<td>males</td>
<td>16 y - 19 y (blacks)</td>
<td>310</td>
<td>46%</td>
<td>7%</td>
<td>2.90%</td>
<td>1.30%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>9</th>
<td>males</td>
<td>20 - 30 y (whites)</td>
<td>285</td>
<td>41%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>10</th>
<td>males</td>
<td>20 - 30 y (blacks)</td>
<td>295</td>
<td>37%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>11</th>
<td>females</td>
<td>12 y - 13 y</td>
<td>174</td>
<td>69%</td>
<td>11%</td>
<td>1.20%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>12</th>
<td>females</td>
<td>13 y - 14 y</td>
<td>154</td>
<td>52%</td>
<td>8.40%</td>
<td>1.40%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>13</th>
<td>females</td>
<td>16 y - 19 y (whites)</td>
<td>50</td>
<td>66%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>14</th>
<td>females</td>
<td>16 - 19 y (blacks)</td>
<td>310</td>
<td>73%</td>
<td>9%</td>
<td>1.30%</td>
<td>0.60%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>15</th>
<td>females</td>
<td>20 - 30 y (whites)</td>
<td>280</td>
<td>55%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
<tr>
<th>16</th>
<td>females</td>
<td>20 - 30 y (blacks)</td>
<td>330</td>
<td>55%</td>
<td>2.40%</td>
<td>1%</td>
<td>0%</td>
<td>0%</td>
<td>0%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>v2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>85%</td>
</tr>
<tr>
<th>1</th>
<td>8.40%</td>
</tr>
</tbody>
</table> | select v2 where n = 154 <table_name> : table | | category | age (ethnicity) | n | v1 | v2 | v3 | v4 | v5 | v6 |
|---:|:-----------|:---------------------|----:|:-----|:------|:------|:------|:------|:-----|
| 0 | none | 1 week - 1 y | 210 | 92% | 74% | 27% | 20% | 0.50% | 0% |
| 1 | none | 1 y - 2 y | 154 | 96% | 85% | 39% | 10% | 0.70% | 0% |
| 2 | none | 2 y - 5 y | 202 | 98% | 50% | 22% | 7% | 1% | 0% |
| 3 | none | 5 y - 8 y | 94 | 91% | 25% | 14% | 5% | 1% | 1% |
| 4 | none | 8 y - 16 y | 90 | 62% | 7% | 2% | 0% | 0% | 0% |
| 5 | males | 12 y - 13 y | 209 | 47% | 7% | 0% | 0% | 0% | 0% |
| 6 | males | 13 y - 14 y | 260 | 35% | 4.60% | 0.80% | 0% | 0% | 0% |
| 7 | males | 16 y - 19 y (whites) | 50 | 32% | 0% | 0% | 0% | 0% | 0% |
| 8 | males | 16 y - 19 y (blacks) | 310 | 46% | 7% | 2.90% | 1.30% | 0% | 0% |
| 9 | males | 20 - 30 y (whites) | 285 | 41% | 0% | 0% | 0% | 0% | 0% |
| 10 | males | 20 - 30 y (blacks) | 295 | 37% | 0% | 0% | 0% | 0% | 0% |
| 11 | females | 12 y - 13 y | 174 | 69% | 11% | 1.20% | 0% | 0% | 0% |
| 12 | females | 13 y - 14 y | 154 | 52% | 8.40% | 1.40% | 0% | 0% | 0% |
| 13 | females | 16 y - 19 y (whites) | 50 | 66% | 0% | 0% | 0% | 0% | 0% |
| 14 | females | 16 - 19 y (blacks) | 310 | 73% | 9% | 1.30% | 0.60% | 0% | 0% |
| 15 | females | 20 - 30 y (whites) | 280 | 55% | 0% | 0% | 0% | 0% | 0% |
| 16 | females | 20 - 30 y (blacks) | 330 | 55% | 2.40% | 1% | 0% | 0% | 0% | | | | v2 |
|---:|:------|
| 0 | 85% |
| 1 | 8.40% | | [
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select count ( * ) where notes = 'a japanese/mcgee take on little red riding hood' col : title | year | platforms | developer | publisher | notes row 1 : american mcgee's grimm | 2008 | pc | spicy horse | gametap | episodic mcgee takes on various grimm tales row 2 : dexiq | 2009 | ipad, iphone, ipod | spicy pony | none | puzzle game row 3 : american mcgee presents akaneiro | 2010 | ipad | spicy pony | none | little red riding hood in japan row 4 : american mcgee's crooked house | 2010 | ipad, iphone, ipod | spicy pony | none | puzzle game row 5 : alice: madness returns | 2011 | playstation 3, xbox 360, pc | spicy horse | electronic arts | sequel to american mcgee's alice row 6 : bighead bash | 2012 | none | spicy horse | none | side scrolling/battle multiplayer. (unreleased) row 7 : crazy fairies | 2012 | mobile, facebook | spicy horse | none | currently in the closed beta stage. (unreleased) row 8 : akaneiro: demon hunters | 2013 | browsers, tegra-powered tablets | spicy horse | spicy horse | a japanese/mcgee take on little red riding hood | col : count ( "*" ) row 1 : 1 | select count ( * ) where notes = 'a japanese/mcgee take on little red riding hood' <table_name> : table \begin{tabular}{lllllll}
\toprule
& title & year & platforms & developer & publisher & notes \\
\midrule
0 & american mcgee's grimm & 2008 & pc & spicy horse & gametap & episodic mcgee takes on various grimm tales \\
1 & dexiq & 2009 & ipad, iphone, ipod & spicy pony & none & puzzle game \\
2 & american mcgee presents akaneiro & 2010 & ipad & spicy pony & none & little red riding hood in japan \\
3 & american mcgee's crooked house & 2010 & ipad, iphone, ipod & spicy pony & none & puzzle game \\
4 & alice: madness returns & 2011 & playstation 3, xbox 360, pc & spicy horse & electronic arts & sequel to american mcgee's alice \\
5 & bighead bash & 2012 & none & spicy horse & none & side scrolling/battle multiplayer. (unreleased) \\
6 & crazy fairies & 2012 & mobile, facebook & spicy horse & none & currently in the closed beta stage. (unreleased) \\
7 & akaneiro: demon hunters & 2013 & browsers, tegra-powered tablets & spicy horse & spicy horse & a japanese/mcgee take on little red riding hood \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where notes = 'a japanese/mcgee take on little red riding hood' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
<th>year</th>
<th>platforms</th>
<th>developer</th>
<th>publisher</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>american mcgee's grimm</td>
<td>2008</td>
<td>pc</td>
<td>spicy horse</td>
<td>gametap</td>
<td>episodic mcgee takes on various grimm tales</td>
</tr>
<tr>
<th>1</th>
<td>dexiq</td>
<td>2009</td>
<td>ipad, iphone, ipod</td>
<td>spicy pony</td>
<td>none</td>
<td>puzzle game</td>
</tr>
<tr>
<th>2</th>
<td>american mcgee presents akaneiro</td>
<td>2010</td>
<td>ipad</td>
<td>spicy pony</td>
<td>none</td>
<td>little red riding hood in japan</td>
</tr>
<tr>
<th>3</th>
<td>american mcgee's crooked house</td>
<td>2010</td>
<td>ipad, iphone, ipod</td>
<td>spicy pony</td>
<td>none</td>
<td>puzzle game</td>
</tr>
<tr>
<th>4</th>
<td>alice: madness returns</td>
<td>2011</td>
<td>playstation 3, xbox 360, pc</td>
<td>spicy horse</td>
<td>electronic arts</td>
<td>sequel to american mcgee's alice</td>
</tr>
<tr>
<th>5</th>
<td>bighead bash</td>
<td>2012</td>
<td>none</td>
<td>spicy horse</td>
<td>none</td>
<td>side scrolling/battle multiplayer. (unreleased)</td>
</tr>
<tr>
<th>6</th>
<td>crazy fairies</td>
<td>2012</td>
<td>mobile, facebook</td>
<td>spicy horse</td>
<td>none</td>
<td>currently in the closed beta stage. (unreleased)</td>
</tr>
<tr>
<th>7</th>
<td>akaneiro: demon hunters</td>
<td>2013</td>
<td>browsers, tegra-powered tablets</td>
<td>spicy horse</td>
<td>spicy horse</td>
<td>a japanese/mcgee take on little red riding hood</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where notes = 'a japanese/mcgee take on little red riding hood' <table_name> : table | | title | year | platforms | developer | publisher | notes |
|---:|:---------------------------------|-------:|:--------------------------------|:------------|:----------------|:-------------------------------------------------|
| 0 | american mcgee's grimm | 2008 | pc | spicy horse | gametap | episodic mcgee takes on various grimm tales |
| 1 | dexiq | 2009 | ipad, iphone, ipod | spicy pony | none | puzzle game |
| 2 | american mcgee presents akaneiro | 2010 | ipad | spicy pony | none | little red riding hood in japan |
| 3 | american mcgee's crooked house | 2010 | ipad, iphone, ipod | spicy pony | none | puzzle game |
| 4 | alice: madness returns | 2011 | playstation 3, xbox 360, pc | spicy horse | electronic arts | sequel to american mcgee's alice |
| 5 | bighead bash | 2012 | none | spicy horse | none | side scrolling/battle multiplayer. (unreleased) |
| 6 | crazy fairies | 2012 | mobile, facebook | spicy horse | none | currently in the closed beta stage. (unreleased) |
| 7 | akaneiro: demon hunters | 2013 | browsers, tegra-powered tablets | spicy horse | spicy horse | a japanese/mcgee take on little red riding hood | | | | count ( "*" ) |
|---:|----------------:|
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select count ( date ) where attendance > 1145 col : week | date | opponent | results final score | results team record | venue | attendance row 1 : 1 | september 18 | washington redskins | l 24-21 | 0-1 | metropolitan stadium | 47,900 row 2 : 2 | september 24 | at detroit lions | w 34-10 | 1-1 | tiger stadium | 54,418 row 3 : 3 | october 1 | miami dolphins | l 16-14 | 1-2 | metropolitan stadium | 47,900 row 4 : 4 | october 8 | st. louis cardinals | l 19-17 | 1-3 | metropolitan stadium | 49,687 row 5 : 5 | october 15 | at denver broncos | w 23-20 | 2-3 | mile high stadium | 51,656 row 6 : 6 | october 23 | at chicago bears | l 13-10 | 2-4 | soldier field | 55,701 row 7 : 7 | october 29 | at green bay packers | w 27-13 | 3-4 | lambeau field | 56,263 row 8 : 8 | november 5 | new orleans saints | w 37-6 | 4-4 | metropolitan stadium | 49,784 row 9 : 9 | november 12 | detroit lions | w 16-14 | 5-4 | metropolitan stadium | 49,784 row 10 : 10 | november 19 | at los angeles rams | w 45-41 | 6-4 | los angeles memorial coliseum | 77,982 row 11 : 11 | november 26 | at pittsburgh steelers | l 23-10 | 6-5 | three rivers stadium | 50,348 row 12 : 12 | december 3 | chicago bears | w 23-10 | 7-5 | metropolitan stadium | 49,784 row 13 : 13 | december 10 | green bay packers | l 23-7 | 7-6 | metropolitan stadium | 49,784 row 14 : 14 | december 16 | at san francisco 49ers | l 20-17 | 7-7 | candlestick park | 61,214 | col : count ( "date" ) row 1 : 14 | select count ( date ) where attendance > 1145 <table_name> : table \begin{tabular}{llllllll}
\toprule
& week & date & opponent & results final score & results team record & venue & attendance \\
\midrule
0 & 1 & september 18 & washington redskins & l 24-21 & 0-1 & metropolitan stadium & 47,900 \\
1 & 2 & september 24 & at detroit lions & w 34-10 & 1-1 & tiger stadium & 54,418 \\
2 & 3 & october 1 & miami dolphins & l 16-14 & 1-2 & metropolitan stadium & 47,900 \\
3 & 4 & october 8 & st. louis cardinals & l 19-17 & 1-3 & metropolitan stadium & 49,687 \\
4 & 5 & october 15 & at denver broncos & w 23-20 & 2-3 & mile high stadium & 51,656 \\
5 & 6 & october 23 & at chicago bears & l 13-10 & 2-4 & soldier field & 55,701 \\
6 & 7 & october 29 & at green bay packers & w 27-13 & 3-4 & lambeau field & 56,263 \\
7 & 8 & november 5 & new orleans saints & w 37-6 & 4-4 & metropolitan stadium & 49,784 \\
8 & 9 & november 12 & detroit lions & w 16-14 & 5-4 & metropolitan stadium & 49,784 \\
9 & 10 & november 19 & at los angeles rams & w 45-41 & 6-4 & los angeles memorial coliseum & 77,982 \\
10 & 11 & november 26 & at pittsburgh steelers & l 23-10 & 6-5 & three rivers stadium & 50,348 \\
11 & 12 & december 3 & chicago bears & w 23-10 & 7-5 & metropolitan stadium & 49,784 \\
12 & 13 & december 10 & green bay packers & l 23-7 & 7-6 & metropolitan stadium & 49,784 \\
13 & 14 & december 16 & at san francisco 49ers & l 20-17 & 7-7 & candlestick park & 61,214 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "date" ) \\
\midrule
0 & 14 \\
\bottomrule
\end{tabular}
| select count ( date ) where attendance > 1145 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>opponent</th>
<th>results final score</th>
<th>results team record</th>
<th>venue</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>september 18</td>
<td>washington redskins</td>
<td>l 24-21</td>
<td>0-1</td>
<td>metropolitan stadium</td>
<td>47,900</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>september 24</td>
<td>at detroit lions</td>
<td>w 34-10</td>
<td>1-1</td>
<td>tiger stadium</td>
<td>54,418</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>october 1</td>
<td>miami dolphins</td>
<td>l 16-14</td>
<td>1-2</td>
<td>metropolitan stadium</td>
<td>47,900</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>october 8</td>
<td>st. louis cardinals</td>
<td>l 19-17</td>
<td>1-3</td>
<td>metropolitan stadium</td>
<td>49,687</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>october 15</td>
<td>at denver broncos</td>
<td>w 23-20</td>
<td>2-3</td>
<td>mile high stadium</td>
<td>51,656</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>october 23</td>
<td>at chicago bears</td>
<td>l 13-10</td>
<td>2-4</td>
<td>soldier field</td>
<td>55,701</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>october 29</td>
<td>at green bay packers</td>
<td>w 27-13</td>
<td>3-4</td>
<td>lambeau field</td>
<td>56,263</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>november 5</td>
<td>new orleans saints</td>
<td>w 37-6</td>
<td>4-4</td>
<td>metropolitan stadium</td>
<td>49,784</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>november 12</td>
<td>detroit lions</td>
<td>w 16-14</td>
<td>5-4</td>
<td>metropolitan stadium</td>
<td>49,784</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>november 19</td>
<td>at los angeles rams</td>
<td>w 45-41</td>
<td>6-4</td>
<td>los angeles memorial coliseum</td>
<td>77,982</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>november 26</td>
<td>at pittsburgh steelers</td>
<td>l 23-10</td>
<td>6-5</td>
<td>three rivers stadium</td>
<td>50,348</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>december 3</td>
<td>chicago bears</td>
<td>w 23-10</td>
<td>7-5</td>
<td>metropolitan stadium</td>
<td>49,784</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>december 10</td>
<td>green bay packers</td>
<td>l 23-7</td>
<td>7-6</td>
<td>metropolitan stadium</td>
<td>49,784</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>december 16</td>
<td>at san francisco 49ers</td>
<td>l 20-17</td>
<td>7-7</td>
<td>candlestick park</td>
<td>61,214</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "date" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>14</td>
</tr>
</tbody>
</table> | select count ( date ) where attendance > 1145 <table_name> : table | | week | date | opponent | results final score | results team record | venue | attendance |
|---:|-------:|:-------------|:-----------------------|:----------------------|:----------------------|:------------------------------|:-------------|
| 0 | 1 | september 18 | washington redskins | l 24-21 | 0-1 | metropolitan stadium | 47,900 |
| 1 | 2 | september 24 | at detroit lions | w 34-10 | 1-1 | tiger stadium | 54,418 |
| 2 | 3 | october 1 | miami dolphins | l 16-14 | 1-2 | metropolitan stadium | 47,900 |
| 3 | 4 | october 8 | st. louis cardinals | l 19-17 | 1-3 | metropolitan stadium | 49,687 |
| 4 | 5 | october 15 | at denver broncos | w 23-20 | 2-3 | mile high stadium | 51,656 |
| 5 | 6 | october 23 | at chicago bears | l 13-10 | 2-4 | soldier field | 55,701 |
| 6 | 7 | october 29 | at green bay packers | w 27-13 | 3-4 | lambeau field | 56,263 |
| 7 | 8 | november 5 | new orleans saints | w 37-6 | 4-4 | metropolitan stadium | 49,784 |
| 8 | 9 | november 12 | detroit lions | w 16-14 | 5-4 | metropolitan stadium | 49,784 |
| 9 | 10 | november 19 | at los angeles rams | w 45-41 | 6-4 | los angeles memorial coliseum | 77,982 |
| 10 | 11 | november 26 | at pittsburgh steelers | l 23-10 | 6-5 | three rivers stadium | 50,348 |
| 11 | 12 | december 3 | chicago bears | w 23-10 | 7-5 | metropolitan stadium | 49,784 |
| 12 | 13 | december 10 | green bay packers | l 23-7 | 7-6 | metropolitan stadium | 49,784 |
| 13 | 14 | december 16 | at san francisco 49ers | l 20-17 | 7-7 | candlestick park | 61,214 | | | | count ( "date" ) |
|---:|-------------------:|
| 0 | 14 | | [
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] |
select count ( club ) where club = 'malavan' col : # | club | winner | last win | runner-up | last losing final row 1 : 1 | esteghlal (taj) | 6 | 2012 | 3 | 2004 row 2 : 2 | persepolis | 5 | 2011 | 2 | 2013 row 3 : 3 | sepahan | 4 | 2013 | 0 | none row 4 : 4 | malavan | 3 | 1990 | 4 | 2011 row 5 : 5 | zob ahan | 2 | 2009 | 1 | 2001 row 6 : 6 | bahman | 1 | 1995 | 2 | 2000 row 7 : 6 | fajr sepasi | 1 | 2001 | 2 | 2003 row 8 : 6 | tractor sazi | 1 | 2014 | 2 | 1995 row 9 : 8 | bargh shiraz | 1 | 1997 | 1 | 1996 row 10 : 8 | saba qom (saba battery) | 1 | 2005 | 1 | 2007 row 11 : 10 | saipa | 1 | 1994 | 0 | none row 12 : 10 | shahin ahvaz | 1 | 1988 | 0 | none row 13 : 13 | homa | 0 | none | 1 | 1977 row 14 : 13 | kheibar khorramabad | 0 | none | 1 | 1986 row 15 : 13 | jonoob ahvaz | 0 | none | 1 | 1994 row 16 : 13 | aboomoslem | 0 | none | 1 | 2005 row 17 : 13 | damash (pegah) | 0 | none | 1 | 2008 row 18 : 13 | rah ahan | 0 | none | 1 | 2009 row 19 : 13 | gostaresh foolad | 0 | none | 1 | 2010 row 20 : 13 | shahin bushehr | 0 | none | 1 | 2012 row 21 : 13 | mes kerman | 0 | none | 1 | 2014 | col : count ( "club" ) row 1 : 1 | select count ( club ) where club = 'malavan' <table_name> : table \begin{tabular}{lllllll}
\toprule
& # & club & winner & last win & runner-up & last losing final \\
\midrule
0 & 1 & esteghlal (taj) & 6 & 2012 & 3 & 2004 \\
1 & 2 & persepolis & 5 & 2011 & 2 & 2013 \\
2 & 3 & sepahan & 4 & 2013 & 0 & none \\
3 & 4 & malavan & 3 & 1990 & 4 & 2011 \\
4 & 5 & zob ahan & 2 & 2009 & 1 & 2001 \\
5 & 6 & bahman & 1 & 1995 & 2 & 2000 \\
6 & 6 & fajr sepasi & 1 & 2001 & 2 & 2003 \\
7 & 6 & tractor sazi & 1 & 2014 & 2 & 1995 \\
8 & 8 & bargh shiraz & 1 & 1997 & 1 & 1996 \\
9 & 8 & saba qom (saba battery) & 1 & 2005 & 1 & 2007 \\
10 & 10 & saipa & 1 & 1994 & 0 & none \\
11 & 10 & shahin ahvaz & 1 & 1988 & 0 & none \\
12 & 13 & homa & 0 & none & 1 & 1977 \\
13 & 13 & kheibar khorramabad & 0 & none & 1 & 1986 \\
14 & 13 & jonoob ahvaz & 0 & none & 1 & 1994 \\
15 & 13 & aboomoslem & 0 & none & 1 & 2005 \\
16 & 13 & damash (pegah) & 0 & none & 1 & 2008 \\
17 & 13 & rah ahan & 0 & none & 1 & 2009 \\
18 & 13 & gostaresh foolad & 0 & none & 1 & 2010 \\
19 & 13 & shahin bushehr & 0 & none & 1 & 2012 \\
20 & 13 & mes kerman & 0 & none & 1 & 2014 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "club" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( club ) where club = 'malavan' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>club</th>
<th>winner</th>
<th>last win</th>
<th>runner-up</th>
<th>last losing final</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>esteghlal (taj)</td>
<td>6</td>
<td>2012</td>
<td>3</td>
<td>2004</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>persepolis</td>
<td>5</td>
<td>2011</td>
<td>2</td>
<td>2013</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>sepahan</td>
<td>4</td>
<td>2013</td>
<td>0</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>malavan</td>
<td>3</td>
<td>1990</td>
<td>4</td>
<td>2011</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>zob ahan</td>
<td>2</td>
<td>2009</td>
<td>1</td>
<td>2001</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>bahman</td>
<td>1</td>
<td>1995</td>
<td>2</td>
<td>2000</td>
</tr>
<tr>
<th>6</th>
<td>6</td>
<td>fajr sepasi</td>
<td>1</td>
<td>2001</td>
<td>2</td>
<td>2003</td>
</tr>
<tr>
<th>7</th>
<td>6</td>
<td>tractor sazi</td>
<td>1</td>
<td>2014</td>
<td>2</td>
<td>1995</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>bargh shiraz</td>
<td>1</td>
<td>1997</td>
<td>1</td>
<td>1996</td>
</tr>
<tr>
<th>9</th>
<td>8</td>
<td>saba qom (saba battery)</td>
<td>1</td>
<td>2005</td>
<td>1</td>
<td>2007</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>saipa</td>
<td>1</td>
<td>1994</td>
<td>0</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>10</td>
<td>shahin ahvaz</td>
<td>1</td>
<td>1988</td>
<td>0</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>homa</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>1977</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>kheibar khorramabad</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>1986</td>
</tr>
<tr>
<th>14</th>
<td>13</td>
<td>jonoob ahvaz</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>1994</td>
</tr>
<tr>
<th>15</th>
<td>13</td>
<td>aboomoslem</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>2005</td>
</tr>
<tr>
<th>16</th>
<td>13</td>
<td>damash (pegah)</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>2008</td>
</tr>
<tr>
<th>17</th>
<td>13</td>
<td>rah ahan</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>2009</td>
</tr>
<tr>
<th>18</th>
<td>13</td>
<td>gostaresh foolad</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>2010</td>
</tr>
<tr>
<th>19</th>
<td>13</td>
<td>shahin bushehr</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>2012</td>
</tr>
<tr>
<th>20</th>
<td>13</td>
<td>mes kerman</td>
<td>0</td>
<td>none</td>
<td>1</td>
<td>2014</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "club" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( club ) where club = 'malavan' <table_name> : table | | # | club | winner | last win | runner-up | last losing final |
|---:|----:|:------------------------|---------:|:-----------|------------:|:--------------------|
| 0 | 1 | esteghlal (taj) | 6 | 2012 | 3 | 2004 |
| 1 | 2 | persepolis | 5 | 2011 | 2 | 2013 |
| 2 | 3 | sepahan | 4 | 2013 | 0 | none |
| 3 | 4 | malavan | 3 | 1990 | 4 | 2011 |
| 4 | 5 | zob ahan | 2 | 2009 | 1 | 2001 |
| 5 | 6 | bahman | 1 | 1995 | 2 | 2000 |
| 6 | 6 | fajr sepasi | 1 | 2001 | 2 | 2003 |
| 7 | 6 | tractor sazi | 1 | 2014 | 2 | 1995 |
| 8 | 8 | bargh shiraz | 1 | 1997 | 1 | 1996 |
| 9 | 8 | saba qom (saba battery) | 1 | 2005 | 1 | 2007 |
| 10 | 10 | saipa | 1 | 1994 | 0 | none |
| 11 | 10 | shahin ahvaz | 1 | 1988 | 0 | none |
| 12 | 13 | homa | 0 | none | 1 | 1977 |
| 13 | 13 | kheibar khorramabad | 0 | none | 1 | 1986 |
| 14 | 13 | jonoob ahvaz | 0 | none | 1 | 1994 |
| 15 | 13 | aboomoslem | 0 | none | 1 | 2005 |
| 16 | 13 | damash (pegah) | 0 | none | 1 | 2008 |
| 17 | 13 | rah ahan | 0 | none | 1 | 2009 |
| 18 | 13 | gostaresh foolad | 0 | none | 1 | 2010 |
| 19 | 13 | shahin bushehr | 0 | none | 1 | 2012 |
| 20 | 13 | mes kerman | 0 | none | 1 | 2014 | | | | count ( "club" ) |
|---:|-------------------:|
| 0 | 1 | | [
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] |
select city where city = 'albino' order by city limit 492 col : pos. | city | population (ab) | surface (km2) | density (ab/km2) | altitude (mslm) row 1 : 1st | bergamo | 121.316 | 39.6 | 3064 | 249 row 2 : 2nd | treviglio | 29.334 | 31.54 | 930 | 125 row 3 : 3rd | seriate | 25.036 | 12.41 | 2017 | 247 row 4 : 4th | dalmine | 23.237 | 11.6 | 2003 | 207 row 5 : 5th | romano di lombardia | 19.472 | 18.03 | 1080 | 120 row 6 : 6th | albino | 18.232 | 31.32 | 582 | 342 row 7 : 7th | caravaggio | 16.258 | 32.81 | 496 | 111 row 8 : 8th | alzano lombardo | 13.821 | 13.43 | 1029 | 304 row 9 : 9th | stezzano | 12.999 | 9.25 | 1405 | 211 row 10 : 10th | osio sotto | 12.083 | 7.45 | 1622 | 182 | col : city row 1 : albino | select city where city = 'albino' order by city limit 492 <table_name> : table \begin{tabular}{lllllll}
\toprule
& pos. & city & population (ab) & surface (km2) & density (ab/km2) & altitude (mslm) \\
\midrule
0 & 1st & bergamo & 121.316 & 39.6 & 3064 & 249 \\
1 & 2nd & treviglio & 29.334 & 31.54 & 930 & 125 \\
2 & 3rd & seriate & 25.036 & 12.41 & 2017 & 247 \\
3 & 4th & dalmine & 23.237 & 11.6 & 2003 & 207 \\
4 & 5th & romano di lombardia & 19.472 & 18.03 & 1080 & 120 \\
5 & 6th & albino & 18.232 & 31.32 & 582 & 342 \\
6 & 7th & caravaggio & 16.258 & 32.81 & 496 & 111 \\
7 & 8th & alzano lombardo & 13.821 & 13.43 & 1029 & 304 \\
8 & 9th & stezzano & 12.999 & 9.25 & 1405 & 211 \\
9 & 10th & osio sotto & 12.083 & 7.45 & 1622 & 182 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& city \\
\midrule
0 & albino \\
\bottomrule
\end{tabular}
| select city where city = 'albino' order by city limit 492 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos.</th>
<th>city</th>
<th>population (ab)</th>
<th>surface (km2)</th>
<th>density (ab/km2)</th>
<th>altitude (mslm)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1st</td>
<td>bergamo</td>
<td>121.316</td>
<td>39.6</td>
<td>3064</td>
<td>249</td>
</tr>
<tr>
<th>1</th>
<td>2nd</td>
<td>treviglio</td>
<td>29.334</td>
<td>31.54</td>
<td>930</td>
<td>125</td>
</tr>
<tr>
<th>2</th>
<td>3rd</td>
<td>seriate</td>
<td>25.036</td>
<td>12.41</td>
<td>2017</td>
<td>247</td>
</tr>
<tr>
<th>3</th>
<td>4th</td>
<td>dalmine</td>
<td>23.237</td>
<td>11.6</td>
<td>2003</td>
<td>207</td>
</tr>
<tr>
<th>4</th>
<td>5th</td>
<td>romano di lombardia</td>
<td>19.472</td>
<td>18.03</td>
<td>1080</td>
<td>120</td>
</tr>
<tr>
<th>5</th>
<td>6th</td>
<td>albino</td>
<td>18.232</td>
<td>31.32</td>
<td>582</td>
<td>342</td>
</tr>
<tr>
<th>6</th>
<td>7th</td>
<td>caravaggio</td>
<td>16.258</td>
<td>32.81</td>
<td>496</td>
<td>111</td>
</tr>
<tr>
<th>7</th>
<td>8th</td>
<td>alzano lombardo</td>
<td>13.821</td>
<td>13.43</td>
<td>1029</td>
<td>304</td>
</tr>
<tr>
<th>8</th>
<td>9th</td>
<td>stezzano</td>
<td>12.999</td>
<td>9.25</td>
<td>1405</td>
<td>211</td>
</tr>
<tr>
<th>9</th>
<td>10th</td>
<td>osio sotto</td>
<td>12.083</td>
<td>7.45</td>
<td>1622</td>
<td>182</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>city</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>albino</td>
</tr>
</tbody>
</table> | select city where city = 'albino' order by city limit 492 <table_name> : table | | pos. | city | population (ab) | surface (km2) | density (ab/km2) | altitude (mslm) |
|---:|:-------|:--------------------|------------------:|----------------:|-------------------:|------------------:|
| 0 | 1st | bergamo | 121.316 | 39.6 | 3064 | 249 |
| 1 | 2nd | treviglio | 29.334 | 31.54 | 930 | 125 |
| 2 | 3rd | seriate | 25.036 | 12.41 | 2017 | 247 |
| 3 | 4th | dalmine | 23.237 | 11.6 | 2003 | 207 |
| 4 | 5th | romano di lombardia | 19.472 | 18.03 | 1080 | 120 |
| 5 | 6th | albino | 18.232 | 31.32 | 582 | 342 |
| 6 | 7th | caravaggio | 16.258 | 32.81 | 496 | 111 |
| 7 | 8th | alzano lombardo | 13.821 | 13.43 | 1029 | 304 |
| 8 | 9th | stezzano | 12.999 | 9.25 | 1405 | 211 |
| 9 | 10th | osio sotto | 12.083 | 7.45 | 1622 | 182 | | | | city |
|---:|:-------|
| 0 | albino | | [
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select count ( representative ) where district = 125 col : representative | party | home town/city | district row 1 : trey martinez fischer | d | san antonio | 116 row 2 : philip cortez | d | san antonio | 117 row 3 : joe farias | d | san antonio | 118 row 4 : roland gutierrez | d | san antonio | 119 row 5 : ruth mcclendon | d | san antonio | 120 row 6 : joe straus | r | san antonio | 121 row 7 : lyle larson | r | san antonio | 122 row 8 : mike villarreal | d | san antonio | 123 row 9 : jose menendez | d | san antonio | 124 row 10 : justin rodriguez | d | san antonio | 125 | col : count ( "representative" ) row 1 : 1 | select count ( representative ) where district = 125 <table_name> : table \begin{tabular}{lllll}
\toprule
& representative & party & home town/city & district \\
\midrule
0 & trey martinez fischer & d & san antonio & 116 \\
1 & philip cortez & d & san antonio & 117 \\
2 & joe farias & d & san antonio & 118 \\
3 & roland gutierrez & d & san antonio & 119 \\
4 & ruth mcclendon & d & san antonio & 120 \\
5 & joe straus & r & san antonio & 121 \\
6 & lyle larson & r & san antonio & 122 \\
7 & mike villarreal & d & san antonio & 123 \\
8 & jose menendez & d & san antonio & 124 \\
9 & justin rodriguez & d & san antonio & 125 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "representative" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( representative ) where district = 125 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>representative</th>
<th>party</th>
<th>home town/city</th>
<th>district</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>trey martinez fischer</td>
<td>d</td>
<td>san antonio</td>
<td>116</td>
</tr>
<tr>
<th>1</th>
<td>philip cortez</td>
<td>d</td>
<td>san antonio</td>
<td>117</td>
</tr>
<tr>
<th>2</th>
<td>joe farias</td>
<td>d</td>
<td>san antonio</td>
<td>118</td>
</tr>
<tr>
<th>3</th>
<td>roland gutierrez</td>
<td>d</td>
<td>san antonio</td>
<td>119</td>
</tr>
<tr>
<th>4</th>
<td>ruth mcclendon</td>
<td>d</td>
<td>san antonio</td>
<td>120</td>
</tr>
<tr>
<th>5</th>
<td>joe straus</td>
<td>r</td>
<td>san antonio</td>
<td>121</td>
</tr>
<tr>
<th>6</th>
<td>lyle larson</td>
<td>r</td>
<td>san antonio</td>
<td>122</td>
</tr>
<tr>
<th>7</th>
<td>mike villarreal</td>
<td>d</td>
<td>san antonio</td>
<td>123</td>
</tr>
<tr>
<th>8</th>
<td>jose menendez</td>
<td>d</td>
<td>san antonio</td>
<td>124</td>
</tr>
<tr>
<th>9</th>
<td>justin rodriguez</td>
<td>d</td>
<td>san antonio</td>
<td>125</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "representative" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( representative ) where district = 125 <table_name> : table | | representative | party | home town/city | district |
|---:|:----------------------|:--------|:-----------------|-----------:|
| 0 | trey martinez fischer | d | san antonio | 116 |
| 1 | philip cortez | d | san antonio | 117 |
| 2 | joe farias | d | san antonio | 118 |
| 3 | roland gutierrez | d | san antonio | 119 |
| 4 | ruth mcclendon | d | san antonio | 120 |
| 5 | joe straus | r | san antonio | 121 |
| 6 | lyle larson | r | san antonio | 122 |
| 7 | mike villarreal | d | san antonio | 123 |
| 8 | jose menendez | d | san antonio | 124 |
| 9 | justin rodriguez | d | san antonio | 125 | | | | count ( "representative" ) |
|---:|-----------------------------:|
| 0 | 1 | | [
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select count ( nation ) where gold = 2 col : rank | nation | gold | silver | bronze | total row 1 : 1 | japan | 18 | 8 | 8 | 34 row 2 : 2 | india | 4 | 5 | 6 | 15 row 3 : 3 | philippines | 4 | 3 | 3 | 10 row 4 : 4 | taiwan | 2 | 6 | 7 | 15 row 5 : 5 | south korea | 2 | 3 | 1 | 6 row 6 : 6 | thailand | 2 | 2 | 0 | 4 row 7 : 7 | pakistan | 2 | 1 | 0 | 3 row 8 : 8 | iran | 2 | 0 | 2 | 4 row 9 : 9 | israel | 1 | 0 | 1 | 2 row 10 : 10 | singapore | 0 | 4 | 4 | 8 row 11 : 11 | malaysia | 0 | 3 | 1 | 4 row 12 : 12 | iraq | 0 | 2 | 0 | 2 row 13 : 13 | kampuchea | 0 | 0 | 2 | 2 row 14 : 14 | nepal | 0 | 0 | 1 | 1 | col : count ( "nation" ) row 1 : 5 | select count ( nation ) where gold = 2 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & japan & 18 & 8 & 8 & 34 \\
1 & 2 & india & 4 & 5 & 6 & 15 \\
2 & 3 & philippines & 4 & 3 & 3 & 10 \\
3 & 4 & taiwan & 2 & 6 & 7 & 15 \\
4 & 5 & south korea & 2 & 3 & 1 & 6 \\
5 & 6 & thailand & 2 & 2 & 0 & 4 \\
6 & 7 & pakistan & 2 & 1 & 0 & 3 \\
7 & 8 & iran & 2 & 0 & 2 & 4 \\
8 & 9 & israel & 1 & 0 & 1 & 2 \\
9 & 10 & singapore & 0 & 4 & 4 & 8 \\
10 & 11 & malaysia & 0 & 3 & 1 & 4 \\
11 & 12 & iraq & 0 & 2 & 0 & 2 \\
12 & 13 & kampuchea & 0 & 0 & 2 & 2 \\
13 & 14 & nepal & 0 & 0 & 1 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "nation" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( nation ) where gold = 2 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>japan</td>
<td>18</td>
<td>8</td>
<td>8</td>
<td>34</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>india</td>
<td>4</td>
<td>5</td>
<td>6</td>
<td>15</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>philippines</td>
<td>4</td>
<td>3</td>
<td>3</td>
<td>10</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>taiwan</td>
<td>2</td>
<td>6</td>
<td>7</td>
<td>15</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>south korea</td>
<td>2</td>
<td>3</td>
<td>1</td>
<td>6</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>thailand</td>
<td>2</td>
<td>2</td>
<td>0</td>
<td>4</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>pakistan</td>
<td>2</td>
<td>1</td>
<td>0</td>
<td>3</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>iran</td>
<td>2</td>
<td>0</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>israel</td>
<td>1</td>
<td>0</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>singapore</td>
<td>0</td>
<td>4</td>
<td>4</td>
<td>8</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>malaysia</td>
<td>0</td>
<td>3</td>
<td>1</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>iraq</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>kampuchea</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>nepal</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "nation" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( nation ) where gold = 2 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:------------|-------:|---------:|---------:|--------:|
| 0 | 1 | japan | 18 | 8 | 8 | 34 |
| 1 | 2 | india | 4 | 5 | 6 | 15 |
| 2 | 3 | philippines | 4 | 3 | 3 | 10 |
| 3 | 4 | taiwan | 2 | 6 | 7 | 15 |
| 4 | 5 | south korea | 2 | 3 | 1 | 6 |
| 5 | 6 | thailand | 2 | 2 | 0 | 4 |
| 6 | 7 | pakistan | 2 | 1 | 0 | 3 |
| 7 | 8 | iran | 2 | 0 | 2 | 4 |
| 8 | 9 | israel | 1 | 0 | 1 | 2 |
| 9 | 10 | singapore | 0 | 4 | 4 | 8 |
| 10 | 11 | malaysia | 0 | 3 | 1 | 4 |
| 11 | 12 | iraq | 0 | 2 | 0 | 2 |
| 12 | 13 | kampuchea | 0 | 0 | 2 | 2 |
| 13 | 14 | nepal | 0 | 0 | 1 | 1 | | | | count ( "nation" ) |
|---:|---------------------:|
| 0 | 5 | | [
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select date where home team = 'birmingham solihull' col : date | competition | home team | score -1 | away team | score -2 row 1 : 2004-10-16 00:00:00 | powergen cup | bedford | none | tabard | none row 2 : 2005-02-15 00:00:00 | national division one | bedford | 26 | otley | 13 row 3 : 2005-02-19 00:00:00 | national division one | bedford | 16 | london welsh | 17 row 4 : 2005-02-26 00:00:00 | national division one | sedgley park | 12 | bedford | 23 row 5 : 2005-03-12 00:00:00 | national division one | bedford | 23 | cornish pirates | 28 row 6 : 2005-04-02 00:00:00 | national division one | bedford | 39 | plymouth albion | 21 row 7 : 2005-04-09 00:00:00 | national division one | birmingham solihull | 18 | bedford | 29 | col : date row 1 : 2005-04-09 00:00:00 | select date where home team = 'birmingham solihull' <table_name> : table \begin{tabular}{lllllll}
\toprule
& date & competition & home team & score -1 & away team & score -2 \\
\midrule
0 & 2004-10-16 00:00:00 & powergen cup & bedford & none & tabard & none \\
1 & 2005-02-15 00:00:00 & national division one & bedford & 26 & otley & 13 \\
2 & 2005-02-19 00:00:00 & national division one & bedford & 16 & london welsh & 17 \\
3 & 2005-02-26 00:00:00 & national division one & sedgley park & 12 & bedford & 23 \\
4 & 2005-03-12 00:00:00 & national division one & bedford & 23 & cornish pirates & 28 \\
5 & 2005-04-02 00:00:00 & national division one & bedford & 39 & plymouth albion & 21 \\
6 & 2005-04-09 00:00:00 & national division one & birmingham solihull & 18 & bedford & 29 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& date \\
\midrule
0 & 2005-04-09 00:00:00 \\
\bottomrule
\end{tabular}
| select date where home team = 'birmingham solihull' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>competition</th>
<th>home team</th>
<th>score -1</th>
<th>away team</th>
<th>score -2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2004-10-16 00:00:00</td>
<td>powergen cup</td>
<td>bedford</td>
<td>none</td>
<td>tabard</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2005-02-15 00:00:00</td>
<td>national division one</td>
<td>bedford</td>
<td>26</td>
<td>otley</td>
<td>13</td>
</tr>
<tr>
<th>2</th>
<td>2005-02-19 00:00:00</td>
<td>national division one</td>
<td>bedford</td>
<td>16</td>
<td>london welsh</td>
<td>17</td>
</tr>
<tr>
<th>3</th>
<td>2005-02-26 00:00:00</td>
<td>national division one</td>
<td>sedgley park</td>
<td>12</td>
<td>bedford</td>
<td>23</td>
</tr>
<tr>
<th>4</th>
<td>2005-03-12 00:00:00</td>
<td>national division one</td>
<td>bedford</td>
<td>23</td>
<td>cornish pirates</td>
<td>28</td>
</tr>
<tr>
<th>5</th>
<td>2005-04-02 00:00:00</td>
<td>national division one</td>
<td>bedford</td>
<td>39</td>
<td>plymouth albion</td>
<td>21</td>
</tr>
<tr>
<th>6</th>
<td>2005-04-09 00:00:00</td>
<td>national division one</td>
<td>birmingham solihull</td>
<td>18</td>
<td>bedford</td>
<td>29</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2005-04-09 00:00:00</td>
</tr>
</tbody>
</table> | select date where home team = 'birmingham solihull' <table_name> : table | | date | competition | home team | score -1 | away team | score -2 |
|---:|:--------------------|:----------------------|:--------------------|:-----------|:----------------|:-----------|
| 0 | 2004-10-16 00:00:00 | powergen cup | bedford | none | tabard | none |
| 1 | 2005-02-15 00:00:00 | national division one | bedford | 26 | otley | 13 |
| 2 | 2005-02-19 00:00:00 | national division one | bedford | 16 | london welsh | 17 |
| 3 | 2005-02-26 00:00:00 | national division one | sedgley park | 12 | bedford | 23 |
| 4 | 2005-03-12 00:00:00 | national division one | bedford | 23 | cornish pirates | 28 |
| 5 | 2005-04-02 00:00:00 | national division one | bedford | 39 | plymouth albion | 21 |
| 6 | 2005-04-09 00:00:00 | national division one | birmingham solihull | 18 | bedford | 29 | | | | date |
|---:|:--------------------|
| 0 | 2005-04-09 00:00:00 | | [
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] |
select count ( * ) where opponent = 'seattle seahawks' col : week | date | opponent | time | game site | tv | result/score | record | bye row 1 : 1 | september 6, 2007 | indianapolis colts | 8:30 pm edt | rca dome | nbc | l 41 - 10 | 0-1 | row 2 : 2 | september 16, 2007 | tampa bay buccaneers | 1:00 pm edt | raymond james stadium | fox | l 31 - 14 | 0-2 | row 3 : 3 | september 24, 2007 | tennessee titans | 8:30 pm edt | louisiana superdome | espn | l 31 - 14 | 0-3 | row 4 : 4 | none | none | none | none | none | none | none | row 5 : 5 | october 7, 2007 | carolina panthers | 1:00 pm edt | louisiana superdome | fox | l 16 - 13 | 0-4 | row 6 : 6 | october 14, 2007 | seattle seahawks | 8:15 pm edt | qwest field | nbc | w 28 - 17 | 1-4 | row 7 : 7 | october 21, 2007 | atlanta falcons | 1:00 pm edt | louisiana superdome | fox | w 22 - 16 | 2-4 | row 8 : 8 | october 28, 2007 | san francisco 49ers | 4:15 pm edt | monster park | fox | w 31 - 10 | 3-4 | row 9 : 9 | november 4, 2007 | jacksonville jaguars | 1:00 pm est | louisiana superdome | cbs | w 41 - 24 | 4-4 | row 10 : 10 | november 11, 2007 | st. louis rams | 1:00 pm est | louisiana superdome | fox | l 37 - 29 | 4-5 | row 11 : 11 | november 18, 2007 | houston texans | 1:00 pm est | reliant stadium | fox | l 23 - 10 | 4-6 | row 12 : 12 | november 25, 2007 | carolina panthers | 1:00 pm est | bank of america stadium | fox | w 31 - 6 | 5-6 | row 13 : 13 | december 2, 2007 | tampa bay buccaneers | 1:00 pm est | louisiana superdome | fox | l 27 - 23 | 5-7 | row 14 : 14 | december 10, 2007 | atlanta falcons | 8:30 pm est | georgia dome | espn | w 34 - 14 | 6-7 | row 15 : 15 | december 16, 2007 | arizona cardinals | 1:00 pm est | louisiana superdome | fox | w 31-24 | 7-7 | row 16 : 16 | december 23, 2007 | philadelphia eagles | 1:00 pm est | louisiana superdome | fox | l 38-23 | 7-8 | row 17 : 17 | december 30, 2007 | chicago bears | 1:00 pm est | soldier field | fox | l 33-25 | 7-9 | | col : count ( "*" ) row 1 : 1 | select count ( * ) where opponent = 'seattle seahawks' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& week & date & opponent & time & game site & tv & result/score & record & bye \\
\midrule
0 & 1 & september 6, 2007 & indianapolis colts & 8:30 pm edt & rca dome & nbc & l 41 - 10 & 0-1 & \\
1 & 2 & september 16, 2007 & tampa bay buccaneers & 1:00 pm edt & raymond james stadium & fox & l 31 - 14 & 0-2 & \\
2 & 3 & september 24, 2007 & tennessee titans & 8:30 pm edt & louisiana superdome & espn & l 31 - 14 & 0-3 & \\
3 & 4 & none & none & none & none & none & none & none & \\
4 & 5 & october 7, 2007 & carolina panthers & 1:00 pm edt & louisiana superdome & fox & l 16 - 13 & 0-4 & \\
5 & 6 & october 14, 2007 & seattle seahawks & 8:15 pm edt & qwest field & nbc & w 28 - 17 & 1-4 & \\
6 & 7 & october 21, 2007 & atlanta falcons & 1:00 pm edt & louisiana superdome & fox & w 22 - 16 & 2-4 & \\
7 & 8 & october 28, 2007 & san francisco 49ers & 4:15 pm edt & monster park & fox & w 31 - 10 & 3-4 & \\
8 & 9 & november 4, 2007 & jacksonville jaguars & 1:00 pm est & louisiana superdome & cbs & w 41 - 24 & 4-4 & \\
9 & 10 & november 11, 2007 & st. louis rams & 1:00 pm est & louisiana superdome & fox & l 37 - 29 & 4-5 & \\
10 & 11 & november 18, 2007 & houston texans & 1:00 pm est & reliant stadium & fox & l 23 - 10 & 4-6 & \\
11 & 12 & november 25, 2007 & carolina panthers & 1:00 pm est & bank of america stadium & fox & w 31 - 6 & 5-6 & \\
12 & 13 & december 2, 2007 & tampa bay buccaneers & 1:00 pm est & louisiana superdome & fox & l 27 - 23 & 5-7 & \\
13 & 14 & december 10, 2007 & atlanta falcons & 8:30 pm est & georgia dome & espn & w 34 - 14 & 6-7 & \\
14 & 15 & december 16, 2007 & arizona cardinals & 1:00 pm est & louisiana superdome & fox & w 31-24 & 7-7 & \\
15 & 16 & december 23, 2007 & philadelphia eagles & 1:00 pm est & louisiana superdome & fox & l 38-23 & 7-8 & \\
16 & 17 & december 30, 2007 & chicago bears & 1:00 pm est & soldier field & fox & l 33-25 & 7-9 | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where opponent = 'seattle seahawks' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>opponent</th>
<th>time</th>
<th>game site</th>
<th>tv</th>
<th>result/score</th>
<th>record</th>
<th>bye</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>september 6, 2007</td>
<td>indianapolis colts</td>
<td>8:30 pm edt</td>
<td>rca dome</td>
<td>nbc</td>
<td>l 41 - 10</td>
<td>0-1</td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>september 16, 2007</td>
<td>tampa bay buccaneers</td>
<td>1:00 pm edt</td>
<td>raymond james stadium</td>
<td>fox</td>
<td>l 31 - 14</td>
<td>0-2</td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>september 24, 2007</td>
<td>tennessee titans</td>
<td>8:30 pm edt</td>
<td>louisiana superdome</td>
<td>espn</td>
<td>l 31 - 14</td>
<td>0-3</td>
<td></td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>october 7, 2007</td>
<td>carolina panthers</td>
<td>1:00 pm edt</td>
<td>louisiana superdome</td>
<td>fox</td>
<td>l 16 - 13</td>
<td>0-4</td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>october 14, 2007</td>
<td>seattle seahawks</td>
<td>8:15 pm edt</td>
<td>qwest field</td>
<td>nbc</td>
<td>w 28 - 17</td>
<td>1-4</td>
<td></td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>october 21, 2007</td>
<td>atlanta falcons</td>
<td>1:00 pm edt</td>
<td>louisiana superdome</td>
<td>fox</td>
<td>w 22 - 16</td>
<td>2-4</td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>october 28, 2007</td>
<td>san francisco 49ers</td>
<td>4:15 pm edt</td>
<td>monster park</td>
<td>fox</td>
<td>w 31 - 10</td>
<td>3-4</td>
<td></td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>november 4, 2007</td>
<td>jacksonville jaguars</td>
<td>1:00 pm est</td>
<td>louisiana superdome</td>
<td>cbs</td>
<td>w 41 - 24</td>
<td>4-4</td>
<td></td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>november 11, 2007</td>
<td>st. louis rams</td>
<td>1:00 pm est</td>
<td>louisiana superdome</td>
<td>fox</td>
<td>l 37 - 29</td>
<td>4-5</td>
<td></td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>november 18, 2007</td>
<td>houston texans</td>
<td>1:00 pm est</td>
<td>reliant stadium</td>
<td>fox</td>
<td>l 23 - 10</td>
<td>4-6</td>
<td></td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>november 25, 2007</td>
<td>carolina panthers</td>
<td>1:00 pm est</td>
<td>bank of america stadium</td>
<td>fox</td>
<td>w 31 - 6</td>
<td>5-6</td>
<td></td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>december 2, 2007</td>
<td>tampa bay buccaneers</td>
<td>1:00 pm est</td>
<td>louisiana superdome</td>
<td>fox</td>
<td>l 27 - 23</td>
<td>5-7</td>
<td></td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>december 10, 2007</td>
<td>atlanta falcons</td>
<td>8:30 pm est</td>
<td>georgia dome</td>
<td>espn</td>
<td>w 34 - 14</td>
<td>6-7</td>
<td></td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>december 16, 2007</td>
<td>arizona cardinals</td>
<td>1:00 pm est</td>
<td>louisiana superdome</td>
<td>fox</td>
<td>w 31-24</td>
<td>7-7</td>
<td></td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>december 23, 2007</td>
<td>philadelphia eagles</td>
<td>1:00 pm est</td>
<td>louisiana superdome</td>
<td>fox</td>
<td>l 38-23</td>
<td>7-8</td>
<td></td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>december 30, 2007</td>
<td>chicago bears</td>
<td>1:00 pm est</td>
<td>soldier field</td>
<td>fox</td>
<td>l 33-25</td>
<td>7-9 |</td>
<td>None</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where opponent = 'seattle seahawks' <table_name> : table | | week | date | opponent | time | game site | tv | result/score | record | bye |
|---:|-------:|:-------------------|:---------------------|:------------|:------------------------|:-----|:---------------|:---------|:------|
| 0 | 1 | september 6, 2007 | indianapolis colts | 8:30 pm edt | rca dome | nbc | l 41 - 10 | 0-1 | |
| 1 | 2 | september 16, 2007 | tampa bay buccaneers | 1:00 pm edt | raymond james stadium | fox | l 31 - 14 | 0-2 | |
| 2 | 3 | september 24, 2007 | tennessee titans | 8:30 pm edt | louisiana superdome | espn | l 31 - 14 | 0-3 | |
| 3 | 4 | none | none | none | none | none | none | none | |
| 4 | 5 | october 7, 2007 | carolina panthers | 1:00 pm edt | louisiana superdome | fox | l 16 - 13 | 0-4 | |
| 5 | 6 | october 14, 2007 | seattle seahawks | 8:15 pm edt | qwest field | nbc | w 28 - 17 | 1-4 | |
| 6 | 7 | october 21, 2007 | atlanta falcons | 1:00 pm edt | louisiana superdome | fox | w 22 - 16 | 2-4 | |
| 7 | 8 | october 28, 2007 | san francisco 49ers | 4:15 pm edt | monster park | fox | w 31 - 10 | 3-4 | |
| 8 | 9 | november 4, 2007 | jacksonville jaguars | 1:00 pm est | louisiana superdome | cbs | w 41 - 24 | 4-4 | |
| 9 | 10 | november 11, 2007 | st. louis rams | 1:00 pm est | louisiana superdome | fox | l 37 - 29 | 4-5 | |
| 10 | 11 | november 18, 2007 | houston texans | 1:00 pm est | reliant stadium | fox | l 23 - 10 | 4-6 | |
| 11 | 12 | november 25, 2007 | carolina panthers | 1:00 pm est | bank of america stadium | fox | w 31 - 6 | 5-6 | |
| 12 | 13 | december 2, 2007 | tampa bay buccaneers | 1:00 pm est | louisiana superdome | fox | l 27 - 23 | 5-7 | |
| 13 | 14 | december 10, 2007 | atlanta falcons | 8:30 pm est | georgia dome | espn | w 34 - 14 | 6-7 | |
| 14 | 15 | december 16, 2007 | arizona cardinals | 1:00 pm est | louisiana superdome | fox | w 31-24 | 7-7 | |
| 15 | 16 | december 23, 2007 | philadelphia eagles | 1:00 pm est | louisiana superdome | fox | l 38-23 | 7-8 | |
| 16 | 17 | december 30, 2007 | chicago bears | 1:00 pm est | soldier field | fox | l 33-25 | 7-9 | | | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( term as a deputy judge ) where name < 358 col : nationality | name | term as a deputy judge | reason for termination row 1 : norway | frederik beichmann | 30 january 1920 - 6 december 1930 | not re-elected row 2 : china | wang ch'ung-hui | 30 january 1920 - 6 december 1930 | not re-elected row 3 : finland | rafael erich | 15 january 1931 - 1 february 1936 | post abolished row 4 : portugal | jose caeiro da matta | 15 january 1931 - 1 february 1936 | post abolished row 5 : romania | demetre negulesco | 30 january 1920 - 6 december 1930 | not re-elected row 6 : yugoslavia | mileta novakovic | 15 january 1931 - 1 february 1936 | post abolished row 7 : austria | josef redlich | 15 january 1931 - 1 february 1936 | post abolished row 8 : yugoslavia | mihajlo jovanovic | 30 january 1920 - 6 december 1930 | not re-elected | col : count ( "term as a deputy judge" ) row 1 : 0 | select count ( term as a deputy judge ) where name < 358 <table_name> : table \begin{tabular}{lllll}
\toprule
& nationality & name & term as a deputy judge & reason for termination \\
\midrule
0 & norway & frederik beichmann & 30 january 1920 - 6 december 1930 & not re-elected \\
1 & china & wang ch'ung-hui & 30 january 1920 - 6 december 1930 & not re-elected \\
2 & finland & rafael erich & 15 january 1931 - 1 february 1936 & post abolished \\
3 & portugal & jose caeiro da matta & 15 january 1931 - 1 february 1936 & post abolished \\
4 & romania & demetre negulesco & 30 january 1920 - 6 december 1930 & not re-elected \\
5 & yugoslavia & mileta novakovic & 15 january 1931 - 1 february 1936 & post abolished \\
6 & austria & josef redlich & 15 january 1931 - 1 february 1936 & post abolished \\
7 & yugoslavia & mihajlo jovanovic & 30 january 1920 - 6 december 1930 & not re-elected \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "term as a deputy judge" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( term as a deputy judge ) where name < 358 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nationality</th>
<th>name</th>
<th>term as a deputy judge</th>
<th>reason for termination</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>norway</td>
<td>frederik beichmann</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
<tr>
<th>1</th>
<td>china</td>
<td>wang ch'ung-hui</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
<tr>
<th>2</th>
<td>finland</td>
<td>rafael erich</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>3</th>
<td>portugal</td>
<td>jose caeiro da matta</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>4</th>
<td>romania</td>
<td>demetre negulesco</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
<tr>
<th>5</th>
<td>yugoslavia</td>
<td>mileta novakovic</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>6</th>
<td>austria</td>
<td>josef redlich</td>
<td>15 january 1931 - 1 february 1936</td>
<td>post abolished</td>
</tr>
<tr>
<th>7</th>
<td>yugoslavia</td>
<td>mihajlo jovanovic</td>
<td>30 january 1920 - 6 december 1930</td>
<td>not re-elected</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "term as a deputy judge" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( term as a deputy judge ) where name < 358 <table_name> : table | | nationality | name | term as a deputy judge | reason for termination |
|---:|:--------------|:---------------------|:----------------------------------|:-------------------------|
| 0 | norway | frederik beichmann | 30 january 1920 - 6 december 1930 | not re-elected |
| 1 | china | wang ch'ung-hui | 30 january 1920 - 6 december 1930 | not re-elected |
| 2 | finland | rafael erich | 15 january 1931 - 1 february 1936 | post abolished |
| 3 | portugal | jose caeiro da matta | 15 january 1931 - 1 february 1936 | post abolished |
| 4 | romania | demetre negulesco | 30 january 1920 - 6 december 1930 | not re-elected |
| 5 | yugoslavia | mileta novakovic | 15 january 1931 - 1 february 1936 | post abolished |
| 6 | austria | josef redlich | 15 january 1931 - 1 february 1936 | post abolished |
| 7 | yugoslavia | mihajlo jovanovic | 30 january 1920 - 6 december 1930 | not re-elected | | | | count ( "term as a deputy judge" ) |
|---:|-------------------------------------:|
| 0 | 0 | | [
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] |
select votes where candidate = 'george h. scott' col : party | candidate | votes row 1 : labour | james kinney | 5513 row 2 : labour | james east | 4847 row 3 : labour | rice sheppard | 4644 row 4 : citizens' committee | percy abbott | 4233 row 5 : citizens' committee | john bowen | 4093 row 6 : citizens' committee | george h. scott | 3835 row 7 : labour | james findlay | 3775 row 8 : labour | j. j. murray | 3696 row 9 : citizens' committee | valentine richards | 3524 row 10 : citizens' committee | charles grant | 3230 row 11 : independent | charles g. davidson | 2982 row 12 : independent | joseph adair | 2356 | col : votes row 1 : 3835 | select votes where candidate = 'george h. scott' <table_name> : table \begin{tabular}{llll}
\toprule
& party & candidate & votes \\
\midrule
0 & labour & james kinney & 5513 \\
1 & labour & james east & 4847 \\
2 & labour & rice sheppard & 4644 \\
3 & citizens' committee & percy abbott & 4233 \\
4 & citizens' committee & john bowen & 4093 \\
5 & citizens' committee & george h. scott & 3835 \\
6 & labour & james findlay & 3775 \\
7 & labour & j. j. murray & 3696 \\
8 & citizens' committee & valentine richards & 3524 \\
9 & citizens' committee & charles grant & 3230 \\
10 & independent & charles g. davidson & 2982 \\
11 & independent & joseph adair & 2356 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& votes \\
\midrule
0 & 3835 \\
\bottomrule
\end{tabular}
| select votes where candidate = 'george h. scott' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>candidate</th>
<th>votes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>labour</td>
<td>james kinney</td>
<td>5513</td>
</tr>
<tr>
<th>1</th>
<td>labour</td>
<td>james east</td>
<td>4847</td>
</tr>
<tr>
<th>2</th>
<td>labour</td>
<td>rice sheppard</td>
<td>4644</td>
</tr>
<tr>
<th>3</th>
<td>citizens' committee</td>
<td>percy abbott</td>
<td>4233</td>
</tr>
<tr>
<th>4</th>
<td>citizens' committee</td>
<td>john bowen</td>
<td>4093</td>
</tr>
<tr>
<th>5</th>
<td>citizens' committee</td>
<td>george h. scott</td>
<td>3835</td>
</tr>
<tr>
<th>6</th>
<td>labour</td>
<td>james findlay</td>
<td>3775</td>
</tr>
<tr>
<th>7</th>
<td>labour</td>
<td>j. j. murray</td>
<td>3696</td>
</tr>
<tr>
<th>8</th>
<td>citizens' committee</td>
<td>valentine richards</td>
<td>3524</td>
</tr>
<tr>
<th>9</th>
<td>citizens' committee</td>
<td>charles grant</td>
<td>3230</td>
</tr>
<tr>
<th>10</th>
<td>independent</td>
<td>charles g. davidson</td>
<td>2982</td>
</tr>
<tr>
<th>11</th>
<td>independent</td>
<td>joseph adair</td>
<td>2356</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>votes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3835</td>
</tr>
</tbody>
</table> | select votes where candidate = 'george h. scott' <table_name> : table | | party | candidate | votes |
|---:|:--------------------|:--------------------|--------:|
| 0 | labour | james kinney | 5513 |
| 1 | labour | james east | 4847 |
| 2 | labour | rice sheppard | 4644 |
| 3 | citizens' committee | percy abbott | 4233 |
| 4 | citizens' committee | john bowen | 4093 |
| 5 | citizens' committee | george h. scott | 3835 |
| 6 | labour | james findlay | 3775 |
| 7 | labour | j. j. murray | 3696 |
| 8 | citizens' committee | valentine richards | 3524 |
| 9 | citizens' committee | charles grant | 3230 |
| 10 | independent | charles g. davidson | 2982 |
| 11 | independent | joseph adair | 2356 | | | | votes |
|---:|--------:|
| 0 | 3835 | | [
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]
] |
select count ( location ) where net capacity (mwe) < 925 col : location | reactor type | status | net capacity (mwe) | gross capacity (mwe) row 1 : chernobyl-1 | rbmk-1000 | shut down in 1996 | 740 | 800 row 2 : chernobyl-2 | rbmk-1000 | shut down in 1991 | 925 | 1 row 3 : chernobyl-3 | rbmk-1000 | shut down in 2000 | 925 | 1 row 4 : chernobyl-4 | rbmk-1000 | destroyed in the 1986 accident | 925 | 1 row 5 : chernobyl-5 | rbmk-1000 | construction cancelled in 1988 | 950 | 1 row 6 : chernobyl-6 | rbmk-1000 | construction cancelled in 1988 | 950 | 1 row 7 : ignalina-1 | rbmk-1500 | shut down in 2004 | 1,185 | 1,3 row 8 : ignalina-2 | rbmk-1500 | shut down in 2009 | 1,185 | 1,3 row 9 : ignalina-3 | rbmk-1500 | construction cancelled in 1988 | 1,38 | 1,5 row 10 : ignalina-4 | rbmk-1500 | plan cancelled in 1988 | 1,38 | 1,5 row 11 : kostroma-1 | rbmk-1500 | construction cancelled in 1980s | 1,38 | 1,5 row 12 : kostroma-2 | rbmk-1500 | construction cancelled in 1980s | 1,38 | 1,5 row 13 : kursk-1 | rbmk-1000 | operational until 2021 | 925 | 1 row 14 : kursk-2 | rbmk-1000 | operational until 2024 | 925 | 1 row 15 : kursk-3 | rbmk-1000 | operational until march 2014 | 925 | 1 row 16 : kursk-4 | rbmk-1000 | operational until february 2016 | 925 | 1 row 17 : kursk-5 | mker-1000 | construction begin was 1985, since then shelved | 925 | 1 row 18 : kursk-6 | rbmk-1000 | construction cancelled in 1993 | 925 | 1 row 19 : leningrad-1 | rbmk-1000 | operational | 925 | 1 row 20 : leningrad-2 | rbmk-1000 | operational until 2021 | 925 | 1 row 21 : leningrad-3 | rbmk-1000 | operational until june 2025 | 925 | 1 row 22 : leningrad-4 | rbmk-1000 | operational until august 2026 | 925 | 1 row 23 : smolensk-1 | rbmk-1000 | operational until december 2022 | 925 | 1 row 24 : smolensk-2 | rbmk-1000 | operational until july 2015 | 925 | 1 row 25 : smolensk-3 | rbmk-1000 | operational until july 2023 | 925 | 1 row 26 : smolensk-4 | rbmk-1000 | construction cancelled in 1993 | 925 | 1 | col : count ( "location" ) row 1 : 7 | select count ( location ) where net capacity (mwe) < 925 <table_name> : table \begin{tabular}{llllll}
\toprule
& location & reactor type & status & net capacity (mwe) & gross capacity (mwe) \\
\midrule
0 & chernobyl-1 & rbmk-1000 & shut down in 1996 & 740 & 800 \\
1 & chernobyl-2 & rbmk-1000 & shut down in 1991 & 925 & 1 \\
2 & chernobyl-3 & rbmk-1000 & shut down in 2000 & 925 & 1 \\
3 & chernobyl-4 & rbmk-1000 & destroyed in the 1986 accident & 925 & 1 \\
4 & chernobyl-5 & rbmk-1000 & construction cancelled in 1988 & 950 & 1 \\
5 & chernobyl-6 & rbmk-1000 & construction cancelled in 1988 & 950 & 1 \\
6 & ignalina-1 & rbmk-1500 & shut down in 2004 & 1,185 & 1,3 \\
7 & ignalina-2 & rbmk-1500 & shut down in 2009 & 1,185 & 1,3 \\
8 & ignalina-3 & rbmk-1500 & construction cancelled in 1988 & 1,38 & 1,5 \\
9 & ignalina-4 & rbmk-1500 & plan cancelled in 1988 & 1,38 & 1,5 \\
10 & kostroma-1 & rbmk-1500 & construction cancelled in 1980s & 1,38 & 1,5 \\
11 & kostroma-2 & rbmk-1500 & construction cancelled in 1980s & 1,38 & 1,5 \\
12 & kursk-1 & rbmk-1000 & operational until 2021 & 925 & 1 \\
13 & kursk-2 & rbmk-1000 & operational until 2024 & 925 & 1 \\
14 & kursk-3 & rbmk-1000 & operational until march 2014 & 925 & 1 \\
15 & kursk-4 & rbmk-1000 & operational until february 2016 & 925 & 1 \\
16 & kursk-5 & mker-1000 & construction begin was 1985, since then shelved & 925 & 1 \\
17 & kursk-6 & rbmk-1000 & construction cancelled in 1993 & 925 & 1 \\
18 & leningrad-1 & rbmk-1000 & operational & 925 & 1 \\
19 & leningrad-2 & rbmk-1000 & operational until 2021 & 925 & 1 \\
20 & leningrad-3 & rbmk-1000 & operational until june 2025 & 925 & 1 \\
21 & leningrad-4 & rbmk-1000 & operational until august 2026 & 925 & 1 \\
22 & smolensk-1 & rbmk-1000 & operational until december 2022 & 925 & 1 \\
23 & smolensk-2 & rbmk-1000 & operational until july 2015 & 925 & 1 \\
24 & smolensk-3 & rbmk-1000 & operational until july 2023 & 925 & 1 \\
25 & smolensk-4 & rbmk-1000 & construction cancelled in 1993 & 925 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "location" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( location ) where net capacity (mwe) < 925 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>location</th>
<th>reactor type</th>
<th>status</th>
<th>net capacity (mwe)</th>
<th>gross capacity (mwe)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>chernobyl-1</td>
<td>rbmk-1000</td>
<td>shut down in 1996</td>
<td>740</td>
<td>800</td>
</tr>
<tr>
<th>1</th>
<td>chernobyl-2</td>
<td>rbmk-1000</td>
<td>shut down in 1991</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>2</th>
<td>chernobyl-3</td>
<td>rbmk-1000</td>
<td>shut down in 2000</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>3</th>
<td>chernobyl-4</td>
<td>rbmk-1000</td>
<td>destroyed in the 1986 accident</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>4</th>
<td>chernobyl-5</td>
<td>rbmk-1000</td>
<td>construction cancelled in 1988</td>
<td>950</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>chernobyl-6</td>
<td>rbmk-1000</td>
<td>construction cancelled in 1988</td>
<td>950</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>ignalina-1</td>
<td>rbmk-1500</td>
<td>shut down in 2004</td>
<td>1,185</td>
<td>1,3</td>
</tr>
<tr>
<th>7</th>
<td>ignalina-2</td>
<td>rbmk-1500</td>
<td>shut down in 2009</td>
<td>1,185</td>
<td>1,3</td>
</tr>
<tr>
<th>8</th>
<td>ignalina-3</td>
<td>rbmk-1500</td>
<td>construction cancelled in 1988</td>
<td>1,38</td>
<td>1,5</td>
</tr>
<tr>
<th>9</th>
<td>ignalina-4</td>
<td>rbmk-1500</td>
<td>plan cancelled in 1988</td>
<td>1,38</td>
<td>1,5</td>
</tr>
<tr>
<th>10</th>
<td>kostroma-1</td>
<td>rbmk-1500</td>
<td>construction cancelled in 1980s</td>
<td>1,38</td>
<td>1,5</td>
</tr>
<tr>
<th>11</th>
<td>kostroma-2</td>
<td>rbmk-1500</td>
<td>construction cancelled in 1980s</td>
<td>1,38</td>
<td>1,5</td>
</tr>
<tr>
<th>12</th>
<td>kursk-1</td>
<td>rbmk-1000</td>
<td>operational until 2021</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>13</th>
<td>kursk-2</td>
<td>rbmk-1000</td>
<td>operational until 2024</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>kursk-3</td>
<td>rbmk-1000</td>
<td>operational until march 2014</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>kursk-4</td>
<td>rbmk-1000</td>
<td>operational until february 2016</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>kursk-5</td>
<td>mker-1000</td>
<td>construction begin was 1985, since then shelved</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>17</th>
<td>kursk-6</td>
<td>rbmk-1000</td>
<td>construction cancelled in 1993</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>leningrad-1</td>
<td>rbmk-1000</td>
<td>operational</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>leningrad-2</td>
<td>rbmk-1000</td>
<td>operational until 2021</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>leningrad-3</td>
<td>rbmk-1000</td>
<td>operational until june 2025</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>leningrad-4</td>
<td>rbmk-1000</td>
<td>operational until august 2026</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>22</th>
<td>smolensk-1</td>
<td>rbmk-1000</td>
<td>operational until december 2022</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>23</th>
<td>smolensk-2</td>
<td>rbmk-1000</td>
<td>operational until july 2015</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>24</th>
<td>smolensk-3</td>
<td>rbmk-1000</td>
<td>operational until july 2023</td>
<td>925</td>
<td>1</td>
</tr>
<tr>
<th>25</th>
<td>smolensk-4</td>
<td>rbmk-1000</td>
<td>construction cancelled in 1993</td>
<td>925</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "location" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( location ) where net capacity (mwe) < 925 <table_name> : table | | location | reactor type | status | net capacity (mwe) | gross capacity (mwe) |
|---:|:------------|:---------------|:------------------------------------------------|:---------------------|:-----------------------|
| 0 | chernobyl-1 | rbmk-1000 | shut down in 1996 | 740 | 800 |
| 1 | chernobyl-2 | rbmk-1000 | shut down in 1991 | 925 | 1 |
| 2 | chernobyl-3 | rbmk-1000 | shut down in 2000 | 925 | 1 |
| 3 | chernobyl-4 | rbmk-1000 | destroyed in the 1986 accident | 925 | 1 |
| 4 | chernobyl-5 | rbmk-1000 | construction cancelled in 1988 | 950 | 1 |
| 5 | chernobyl-6 | rbmk-1000 | construction cancelled in 1988 | 950 | 1 |
| 6 | ignalina-1 | rbmk-1500 | shut down in 2004 | 1,185 | 1,3 |
| 7 | ignalina-2 | rbmk-1500 | shut down in 2009 | 1,185 | 1,3 |
| 8 | ignalina-3 | rbmk-1500 | construction cancelled in 1988 | 1,38 | 1,5 |
| 9 | ignalina-4 | rbmk-1500 | plan cancelled in 1988 | 1,38 | 1,5 |
| 10 | kostroma-1 | rbmk-1500 | construction cancelled in 1980s | 1,38 | 1,5 |
| 11 | kostroma-2 | rbmk-1500 | construction cancelled in 1980s | 1,38 | 1,5 |
| 12 | kursk-1 | rbmk-1000 | operational until 2021 | 925 | 1 |
| 13 | kursk-2 | rbmk-1000 | operational until 2024 | 925 | 1 |
| 14 | kursk-3 | rbmk-1000 | operational until march 2014 | 925 | 1 |
| 15 | kursk-4 | rbmk-1000 | operational until february 2016 | 925 | 1 |
| 16 | kursk-5 | mker-1000 | construction begin was 1985, since then shelved | 925 | 1 |
| 17 | kursk-6 | rbmk-1000 | construction cancelled in 1993 | 925 | 1 |
| 18 | leningrad-1 | rbmk-1000 | operational | 925 | 1 |
| 19 | leningrad-2 | rbmk-1000 | operational until 2021 | 925 | 1 |
| 20 | leningrad-3 | rbmk-1000 | operational until june 2025 | 925 | 1 |
| 21 | leningrad-4 | rbmk-1000 | operational until august 2026 | 925 | 1 |
| 22 | smolensk-1 | rbmk-1000 | operational until december 2022 | 925 | 1 |
| 23 | smolensk-2 | rbmk-1000 | operational until july 2015 | 925 | 1 |
| 24 | smolensk-3 | rbmk-1000 | operational until july 2023 | 925 | 1 |
| 25 | smolensk-4 | rbmk-1000 | construction cancelled in 1993 | 925 | 1 | | | | count ( "location" ) |
|---:|-----------------------:|
| 0 | 7 | | [
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select count ( * ) where title = 'fresh meat' col : title | character | broadcaster | episodes | date row 1 : rev | pip | bbc two | 1.0 | 2010 row 2 : the i.t. crowd | nikki | channel 4 | 1.0 | 2010 row 3 : eastenders: e20 | ava | bbc one | 15.0 | 2011 row 4 : fresh meat | caz | channel 4 | 1.0 | 2011 row 5 : phoneshop | daisy | channel 4 | 1.0 | 2011 row 6 : holby city | heidi hall | bbc one | 1.0 | 2012 row 7 : plebs | cynthia | itv2 | 6.0 | 2013 row 8 : blandings | valerie fanshawe | bbc | 2.5 | 2014 row 9 : death in paradise | helen walker | bbc | 3.4 | 2014 | col : count ( "*" ) row 1 : 1 | select count ( * ) where title = 'fresh meat' <table_name> : table \begin{tabular}{llllll}
\toprule
& title & character & broadcaster & episodes & date \\
\midrule
0 & rev & pip & bbc two & 1.0 & 2010 \\
1 & the i.t. crowd & nikki & channel 4 & 1.0 & 2010 \\
2 & eastenders: e20 & ava & bbc one & 15.0 & 2011 \\
3 & fresh meat & caz & channel 4 & 1.0 & 2011 \\
4 & phoneshop & daisy & channel 4 & 1.0 & 2011 \\
5 & holby city & heidi hall & bbc one & 1.0 & 2012 \\
6 & plebs & cynthia & itv2 & 6.0 & 2013 \\
7 & blandings & valerie fanshawe & bbc & 2.5 & 2014 \\
8 & death in paradise & helen walker & bbc & 3.4 & 2014 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where title = 'fresh meat' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>title</th>
<th>character</th>
<th>broadcaster</th>
<th>episodes</th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>rev</td>
<td>pip</td>
<td>bbc two</td>
<td>1.0</td>
<td>2010</td>
</tr>
<tr>
<th>1</th>
<td>the i.t. crowd</td>
<td>nikki</td>
<td>channel 4</td>
<td>1.0</td>
<td>2010</td>
</tr>
<tr>
<th>2</th>
<td>eastenders: e20</td>
<td>ava</td>
<td>bbc one</td>
<td>15.0</td>
<td>2011</td>
</tr>
<tr>
<th>3</th>
<td>fresh meat</td>
<td>caz</td>
<td>channel 4</td>
<td>1.0</td>
<td>2011</td>
</tr>
<tr>
<th>4</th>
<td>phoneshop</td>
<td>daisy</td>
<td>channel 4</td>
<td>1.0</td>
<td>2011</td>
</tr>
<tr>
<th>5</th>
<td>holby city</td>
<td>heidi hall</td>
<td>bbc one</td>
<td>1.0</td>
<td>2012</td>
</tr>
<tr>
<th>6</th>
<td>plebs</td>
<td>cynthia</td>
<td>itv2</td>
<td>6.0</td>
<td>2013</td>
</tr>
<tr>
<th>7</th>
<td>blandings</td>
<td>valerie fanshawe</td>
<td>bbc</td>
<td>2.5</td>
<td>2014</td>
</tr>
<tr>
<th>8</th>
<td>death in paradise</td>
<td>helen walker</td>
<td>bbc</td>
<td>3.4</td>
<td>2014</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where title = 'fresh meat' <table_name> : table | | title | character | broadcaster | episodes | date |
|---:|:------------------|:-----------------|:--------------|-----------:|-------:|
| 0 | rev | pip | bbc two | 1 | 2010 |
| 1 | the i.t. crowd | nikki | channel 4 | 1 | 2010 |
| 2 | eastenders: e20 | ava | bbc one | 15 | 2011 |
| 3 | fresh meat | caz | channel 4 | 1 | 2011 |
| 4 | phoneshop | daisy | channel 4 | 1 | 2011 |
| 5 | holby city | heidi hall | bbc one | 1 | 2012 |
| 6 | plebs | cynthia | itv2 | 6 | 2013 |
| 7 | blandings | valerie fanshawe | bbc | 2.5 | 2014 |
| 8 | death in paradise | helen walker | bbc | 3.4 | 2014 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select section where movements = 'relegated' col : season | level | division | section | position | movements row 1 : 1993 | tier 3 | division 2 | ostra svealand | 1st | promoted row 2 : 1994 | tier 2 | division 1 | norra | 11th | relegation playoffs row 3 : 1995 | tier 2 | division 1 | norra | 4th | none row 4 : 1996 | tier 2 | division 1 | norra | 11th | relegation playoffs - relegated row 5 : 1997 | tier 3 | division 2 | ostra svealand | 3rd | none row 6 : 1998 | tier 3 | division 2 | ostra svealand | 7th | none row 7 : 1999 | tier 3 | division 2 | ostra svealand | 3rd | none row 8 : 2000 | tier 3 | division 2 | ostra svealand | 9th | none row 9 : 2001 | tier 3 | division 2 | ostra svealand | 7th | none row 10 : 2002 | tier 3 | division 2 | ostra svealand | 2nd | none row 11 : 2003 | tier 3 | division 2 | ostra svealand | 3rd | none row 12 : 2004 | tier 3 | division 2 | ostra svealand | 6th | none row 13 : 2005 | tier 3 | division 2 | ostra svealand | 4th | promoted row 14 : 2006 | tier 3 | division 1 | norra | 5th | none row 15 : 2007 | tier 3 | division 1 | sodra | 14th | relegated | col : section row 1 : sodra | select section where movements = 'relegated' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & level & division & section & position & movements \\
\midrule
0 & 1993 & tier 3 & division 2 & ostra svealand & 1st & promoted \\
1 & 1994 & tier 2 & division 1 & norra & 11th & relegation playoffs \\
2 & 1995 & tier 2 & division 1 & norra & 4th & none \\
3 & 1996 & tier 2 & division 1 & norra & 11th & relegation playoffs - relegated \\
4 & 1997 & tier 3 & division 2 & ostra svealand & 3rd & none \\
5 & 1998 & tier 3 & division 2 & ostra svealand & 7th & none \\
6 & 1999 & tier 3 & division 2 & ostra svealand & 3rd & none \\
7 & 2000 & tier 3 & division 2 & ostra svealand & 9th & none \\
8 & 2001 & tier 3 & division 2 & ostra svealand & 7th & none \\
9 & 2002 & tier 3 & division 2 & ostra svealand & 2nd & none \\
10 & 2003 & tier 3 & division 2 & ostra svealand & 3rd & none \\
11 & 2004 & tier 3 & division 2 & ostra svealand & 6th & none \\
12 & 2005 & tier 3 & division 2 & ostra svealand & 4th & promoted \\
13 & 2006 & tier 3 & division 1 & norra & 5th & none \\
14 & 2007 & tier 3 & division 1 & sodra & 14th & relegated \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& section \\
\midrule
0 & sodra \\
\bottomrule
\end{tabular}
| select section where movements = 'relegated' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>level</th>
<th>division</th>
<th>section</th>
<th>position</th>
<th>movements</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1993</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>1st</td>
<td>promoted</td>
</tr>
<tr>
<th>1</th>
<td>1994</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>11th</td>
<td>relegation playoffs</td>
</tr>
<tr>
<th>2</th>
<td>1995</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>4th</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1996</td>
<td>tier 2</td>
<td>division 1</td>
<td>norra</td>
<td>11th</td>
<td>relegation playoffs - relegated</td>
</tr>
<tr>
<th>4</th>
<td>1997</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1998</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1999</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2000</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>9th</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2001</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2002</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>2004</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2005</td>
<td>tier 3</td>
<td>division 2</td>
<td>ostra svealand</td>
<td>4th</td>
<td>promoted</td>
</tr>
<tr>
<th>13</th>
<td>2006</td>
<td>tier 3</td>
<td>division 1</td>
<td>norra</td>
<td>5th</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>2007</td>
<td>tier 3</td>
<td>division 1</td>
<td>sodra</td>
<td>14th</td>
<td>relegated</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>section</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>sodra</td>
</tr>
</tbody>
</table> | select section where movements = 'relegated' <table_name> : table | | season | level | division | section | position | movements |
|---:|---------:|:--------|:-----------|:---------------|:-----------|:--------------------------------|
| 0 | 1993 | tier 3 | division 2 | ostra svealand | 1st | promoted |
| 1 | 1994 | tier 2 | division 1 | norra | 11th | relegation playoffs |
| 2 | 1995 | tier 2 | division 1 | norra | 4th | none |
| 3 | 1996 | tier 2 | division 1 | norra | 11th | relegation playoffs - relegated |
| 4 | 1997 | tier 3 | division 2 | ostra svealand | 3rd | none |
| 5 | 1998 | tier 3 | division 2 | ostra svealand | 7th | none |
| 6 | 1999 | tier 3 | division 2 | ostra svealand | 3rd | none |
| 7 | 2000 | tier 3 | division 2 | ostra svealand | 9th | none |
| 8 | 2001 | tier 3 | division 2 | ostra svealand | 7th | none |
| 9 | 2002 | tier 3 | division 2 | ostra svealand | 2nd | none |
| 10 | 2003 | tier 3 | division 2 | ostra svealand | 3rd | none |
| 11 | 2004 | tier 3 | division 2 | ostra svealand | 6th | none |
| 12 | 2005 | tier 3 | division 2 | ostra svealand | 4th | promoted |
| 13 | 2006 | tier 3 | division 1 | norra | 5th | none |
| 14 | 2007 | tier 3 | division 1 | sodra | 14th | relegated | | | | section |
|---:|:----------|
| 0 | sodra | | [
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select count ( date ) where home/away = 'away' col : match | date | round | home/away | opponent team | score | scorers row 1 : 1 | 2007-09-17 00:00:00 | group stage | home | benfica | 2-1 | pirlo 9', inzaghi 24' row 2 : 2 | 2007-10-03 00:00:00 | group stage | away | celtic | 2-1 | kaka 68' (pen.) row 3 : 3 | 2007-10-24 00:00:00 | group stage | home | shakhtar donetsk | 4-1 | gilardino 6', 14', seedorf 62', 69' row 4 : 4 | 2007-11-06 00:00:00 | group stage | away | shakhtar donetsk | 0-3 | inzaghi 66', 90+3', kaka 72' row 5 : 5 | 2007-11-28 00:00:00 | group stage | away | benfica | 1-1 | pirlo 15' row 6 : 6 | 2007-12-04 00:00:00 | group stage | home | celtic | 1-0 | inzaghi 70' row 7 : 7 | 2008-02-20 00:00:00 | round of 16 | away | arsenal | 0-0 | none row 8 : 8 | 2008-03-04 00:00:00 | round of 16 | home | arsenal | 0-2 | none | col : count ( "date" ) row 1 : 4 | select count ( date ) where home/away = 'away' <table_name> : table \begin{tabular}{llllllll}
\toprule
& match & date & round & home/away & opponent team & score & scorers \\
\midrule
0 & 1 & 2007-09-17 00:00:00 & group stage & home & benfica & 2-1 & pirlo 9', inzaghi 24' \\
1 & 2 & 2007-10-03 00:00:00 & group stage & away & celtic & 2-1 & kaka 68' (pen.) \\
2 & 3 & 2007-10-24 00:00:00 & group stage & home & shakhtar donetsk & 4-1 & gilardino 6', 14', seedorf 62', 69' \\
3 & 4 & 2007-11-06 00:00:00 & group stage & away & shakhtar donetsk & 0-3 & inzaghi 66', 90+3', kaka 72' \\
4 & 5 & 2007-11-28 00:00:00 & group stage & away & benfica & 1-1 & pirlo 15' \\
5 & 6 & 2007-12-04 00:00:00 & group stage & home & celtic & 1-0 & inzaghi 70' \\
6 & 7 & 2008-02-20 00:00:00 & round of 16 & away & arsenal & 0-0 & none \\
7 & 8 & 2008-03-04 00:00:00 & round of 16 & home & arsenal & 0-2 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "date" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( date ) where home/away = 'away' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>match</th>
<th>date</th>
<th>round</th>
<th>home/away</th>
<th>opponent team</th>
<th>score</th>
<th>scorers</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2007-09-17 00:00:00</td>
<td>group stage</td>
<td>home</td>
<td>benfica</td>
<td>2-1</td>
<td>pirlo 9', inzaghi 24'</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2007-10-03 00:00:00</td>
<td>group stage</td>
<td>away</td>
<td>celtic</td>
<td>2-1</td>
<td>kaka 68' (pen.)</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2007-10-24 00:00:00</td>
<td>group stage</td>
<td>home</td>
<td>shakhtar donetsk</td>
<td>4-1</td>
<td>gilardino 6', 14', seedorf 62', 69'</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2007-11-06 00:00:00</td>
<td>group stage</td>
<td>away</td>
<td>shakhtar donetsk</td>
<td>0-3</td>
<td>inzaghi 66', 90+3', kaka 72'</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2007-11-28 00:00:00</td>
<td>group stage</td>
<td>away</td>
<td>benfica</td>
<td>1-1</td>
<td>pirlo 15'</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2007-12-04 00:00:00</td>
<td>group stage</td>
<td>home</td>
<td>celtic</td>
<td>1-0</td>
<td>inzaghi 70'</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2008-02-20 00:00:00</td>
<td>round of 16</td>
<td>away</td>
<td>arsenal</td>
<td>0-0</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2008-03-04 00:00:00</td>
<td>round of 16</td>
<td>home</td>
<td>arsenal</td>
<td>0-2</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "date" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select count ( date ) where home/away = 'away' <table_name> : table | | match | date | round | home/away | opponent team | score | scorers |
|---:|--------:|:--------------------|:------------|:------------|:-----------------|:--------|:------------------------------------|
| 0 | 1 | 2007-09-17 00:00:00 | group stage | home | benfica | 2-1 | pirlo 9', inzaghi 24' |
| 1 | 2 | 2007-10-03 00:00:00 | group stage | away | celtic | 2-1 | kaka 68' (pen.) |
| 2 | 3 | 2007-10-24 00:00:00 | group stage | home | shakhtar donetsk | 4-1 | gilardino 6', 14', seedorf 62', 69' |
| 3 | 4 | 2007-11-06 00:00:00 | group stage | away | shakhtar donetsk | 0-3 | inzaghi 66', 90+3', kaka 72' |
| 4 | 5 | 2007-11-28 00:00:00 | group stage | away | benfica | 1-1 | pirlo 15' |
| 5 | 6 | 2007-12-04 00:00:00 | group stage | home | celtic | 1-0 | inzaghi 70' |
| 6 | 7 | 2008-02-20 00:00:00 | round of 16 | away | arsenal | 0-0 | none |
| 7 | 8 | 2008-03-04 00:00:00 | round of 16 | home | arsenal | 0-2 | none | | | | count ( "date" ) |
|---:|-------------------:|
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select color where pin (ring) > 20 order by pin (ring) limit 1 col : color -1 | pin (tip) | pin (ring) | color -2 row 1 : white/blue | 26 | 1 | blue/white row 2 : white/orange | 27 | 2 | orange/white row 3 : white/green | 28 | 3 | green/white row 4 : white/brown | 29 | 4 | brown/white row 5 : white/slate | 30 | 5 | slate/white row 6 : red/blue | 31 | 6 | blue/red row 7 : red/orange | 32 | 7 | orange/red row 8 : red/green | 33 | 8 | green/red row 9 : red/brown | 34 | 9 | brown/red row 10 : red/slate | 35 | 10 | slate/red row 11 : black/blue | 36 | 11 | blue/black row 12 : black/orange | 37 | 12 | orange/black row 13 : black/green | 38 | 13 | green/black row 14 : black/brown | 39 | 14 | brown/black row 15 : black/slate | 40 | 15 | slate/black row 16 : yellow/blue | 41 | 16 | blue/yellow row 17 : yellow/orange | 42 | 17 | orange/yellow row 18 : yellow/green | 43 | 18 | green/yellow row 19 : yellow/brown | 44 | 19 | brown/yellow row 20 : yellow/slate | 45 | 20 | slate/yellow row 21 : violet/blue | 46 | 21 | blue/violet row 22 : violet/orange | 47 | 22 | orange/violet row 23 : violet/green | 48 | 23 | green/violet row 24 : violet/brown | 49 | 24 | brown/violet row 25 : violet/slate | 50 | 25 | slate/violet | col : color row 1 : green/white row 2 : brown/white row 3 : slate/white row 4 : blue/red row 5 : orange/red row 6 : green/red row 7 : brown/red row 8 : blue/violet row 9 : orange/violet row 10 : green/violet row 11 : brown/violet row 12 : slate/violet | select color where pin (ring) > 20 order by pin (ring) limit 1 <table_name> : table \begin{tabular}{lllll}
\toprule
& color -1 & pin (tip) & pin (ring) & color -2 \\
\midrule
0 & white/blue & 26 & 1 & blue/white \\
1 & white/orange & 27 & 2 & orange/white \\
2 & white/green & 28 & 3 & green/white \\
3 & white/brown & 29 & 4 & brown/white \\
4 & white/slate & 30 & 5 & slate/white \\
5 & red/blue & 31 & 6 & blue/red \\
6 & red/orange & 32 & 7 & orange/red \\
7 & red/green & 33 & 8 & green/red \\
8 & red/brown & 34 & 9 & brown/red \\
9 & red/slate & 35 & 10 & slate/red \\
10 & black/blue & 36 & 11 & blue/black \\
11 & black/orange & 37 & 12 & orange/black \\
12 & black/green & 38 & 13 & green/black \\
13 & black/brown & 39 & 14 & brown/black \\
14 & black/slate & 40 & 15 & slate/black \\
15 & yellow/blue & 41 & 16 & blue/yellow \\
16 & yellow/orange & 42 & 17 & orange/yellow \\
17 & yellow/green & 43 & 18 & green/yellow \\
18 & yellow/brown & 44 & 19 & brown/yellow \\
19 & yellow/slate & 45 & 20 & slate/yellow \\
20 & violet/blue & 46 & 21 & blue/violet \\
21 & violet/orange & 47 & 22 & orange/violet \\
22 & violet/green & 48 & 23 & green/violet \\
23 & violet/brown & 49 & 24 & brown/violet \\
24 & violet/slate & 50 & 25 & slate/violet \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& color \\
\midrule
0 & green/white \\
1 & brown/white \\
2 & slate/white \\
3 & blue/red \\
4 & orange/red \\
5 & green/red \\
6 & brown/red \\
7 & blue/violet \\
8 & orange/violet \\
9 & green/violet \\
10 & brown/violet \\
11 & slate/violet \\
\bottomrule
\end{tabular}
| select color where pin (ring) > 20 order by pin (ring) limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>color -1</th>
<th>pin (tip)</th>
<th>pin (ring)</th>
<th>color -2</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>white/blue</td>
<td>26</td>
<td>1</td>
<td>blue/white</td>
</tr>
<tr>
<th>1</th>
<td>white/orange</td>
<td>27</td>
<td>2</td>
<td>orange/white</td>
</tr>
<tr>
<th>2</th>
<td>white/green</td>
<td>28</td>
<td>3</td>
<td>green/white</td>
</tr>
<tr>
<th>3</th>
<td>white/brown</td>
<td>29</td>
<td>4</td>
<td>brown/white</td>
</tr>
<tr>
<th>4</th>
<td>white/slate</td>
<td>30</td>
<td>5</td>
<td>slate/white</td>
</tr>
<tr>
<th>5</th>
<td>red/blue</td>
<td>31</td>
<td>6</td>
<td>blue/red</td>
</tr>
<tr>
<th>6</th>
<td>red/orange</td>
<td>32</td>
<td>7</td>
<td>orange/red</td>
</tr>
<tr>
<th>7</th>
<td>red/green</td>
<td>33</td>
<td>8</td>
<td>green/red</td>
</tr>
<tr>
<th>8</th>
<td>red/brown</td>
<td>34</td>
<td>9</td>
<td>brown/red</td>
</tr>
<tr>
<th>9</th>
<td>red/slate</td>
<td>35</td>
<td>10</td>
<td>slate/red</td>
</tr>
<tr>
<th>10</th>
<td>black/blue</td>
<td>36</td>
<td>11</td>
<td>blue/black</td>
</tr>
<tr>
<th>11</th>
<td>black/orange</td>
<td>37</td>
<td>12</td>
<td>orange/black</td>
</tr>
<tr>
<th>12</th>
<td>black/green</td>
<td>38</td>
<td>13</td>
<td>green/black</td>
</tr>
<tr>
<th>13</th>
<td>black/brown</td>
<td>39</td>
<td>14</td>
<td>brown/black</td>
</tr>
<tr>
<th>14</th>
<td>black/slate</td>
<td>40</td>
<td>15</td>
<td>slate/black</td>
</tr>
<tr>
<th>15</th>
<td>yellow/blue</td>
<td>41</td>
<td>16</td>
<td>blue/yellow</td>
</tr>
<tr>
<th>16</th>
<td>yellow/orange</td>
<td>42</td>
<td>17</td>
<td>orange/yellow</td>
</tr>
<tr>
<th>17</th>
<td>yellow/green</td>
<td>43</td>
<td>18</td>
<td>green/yellow</td>
</tr>
<tr>
<th>18</th>
<td>yellow/brown</td>
<td>44</td>
<td>19</td>
<td>brown/yellow</td>
</tr>
<tr>
<th>19</th>
<td>yellow/slate</td>
<td>45</td>
<td>20</td>
<td>slate/yellow</td>
</tr>
<tr>
<th>20</th>
<td>violet/blue</td>
<td>46</td>
<td>21</td>
<td>blue/violet</td>
</tr>
<tr>
<th>21</th>
<td>violet/orange</td>
<td>47</td>
<td>22</td>
<td>orange/violet</td>
</tr>
<tr>
<th>22</th>
<td>violet/green</td>
<td>48</td>
<td>23</td>
<td>green/violet</td>
</tr>
<tr>
<th>23</th>
<td>violet/brown</td>
<td>49</td>
<td>24</td>
<td>brown/violet</td>
</tr>
<tr>
<th>24</th>
<td>violet/slate</td>
<td>50</td>
<td>25</td>
<td>slate/violet</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>color</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>green/white</td>
</tr>
<tr>
<th>1</th>
<td>brown/white</td>
</tr>
<tr>
<th>2</th>
<td>slate/white</td>
</tr>
<tr>
<th>3</th>
<td>blue/red</td>
</tr>
<tr>
<th>4</th>
<td>orange/red</td>
</tr>
<tr>
<th>5</th>
<td>green/red</td>
</tr>
<tr>
<th>6</th>
<td>brown/red</td>
</tr>
<tr>
<th>7</th>
<td>blue/violet</td>
</tr>
<tr>
<th>8</th>
<td>orange/violet</td>
</tr>
<tr>
<th>9</th>
<td>green/violet</td>
</tr>
<tr>
<th>10</th>
<td>brown/violet</td>
</tr>
<tr>
<th>11</th>
<td>slate/violet</td>
</tr>
</tbody>
</table> | select color where pin (ring) > 20 order by pin (ring) limit 1 <table_name> : table | | color -1 | pin (tip) | pin (ring) | color -2 |
|---:|:--------------|------------:|-------------:|:--------------|
| 0 | white/blue | 26 | 1 | blue/white |
| 1 | white/orange | 27 | 2 | orange/white |
| 2 | white/green | 28 | 3 | green/white |
| 3 | white/brown | 29 | 4 | brown/white |
| 4 | white/slate | 30 | 5 | slate/white |
| 5 | red/blue | 31 | 6 | blue/red |
| 6 | red/orange | 32 | 7 | orange/red |
| 7 | red/green | 33 | 8 | green/red |
| 8 | red/brown | 34 | 9 | brown/red |
| 9 | red/slate | 35 | 10 | slate/red |
| 10 | black/blue | 36 | 11 | blue/black |
| 11 | black/orange | 37 | 12 | orange/black |
| 12 | black/green | 38 | 13 | green/black |
| 13 | black/brown | 39 | 14 | brown/black |
| 14 | black/slate | 40 | 15 | slate/black |
| 15 | yellow/blue | 41 | 16 | blue/yellow |
| 16 | yellow/orange | 42 | 17 | orange/yellow |
| 17 | yellow/green | 43 | 18 | green/yellow |
| 18 | yellow/brown | 44 | 19 | brown/yellow |
| 19 | yellow/slate | 45 | 20 | slate/yellow |
| 20 | violet/blue | 46 | 21 | blue/violet |
| 21 | violet/orange | 47 | 22 | orange/violet |
| 22 | violet/green | 48 | 23 | green/violet |
| 23 | violet/brown | 49 | 24 | brown/violet |
| 24 | violet/slate | 50 | 25 | slate/violet | | | | color |
|---:|:--------------|
| 0 | green/white |
| 1 | brown/white |
| 2 | slate/white |
| 3 | blue/red |
| 4 | orange/red |
| 5 | green/red |
| 6 | brown/red |
| 7 | blue/violet |
| 8 | orange/violet |
| 9 | green/violet |
| 10 | brown/violet |
| 11 | slate/violet | | [
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select town where school < town order by county desc limit 1 col : school | team name | town | county | enrollment (2010-11 & 2011-12) | primary mshsaa class* | football class row 1 : benton high school | (lady) cardinals | st. joseph | buchanan | 846 | 4 | 4 row 2 : bishop leblond high school | (lady) golden eagles | st. joseph | buchanan | 314 | 3 | 2 row 3 : cameron high school | (lady) dragons | cameron | clinton | 503 | 3 | 3 row 4 : chillicothe high school (missouri) | (lady) hornets | chillicothe | livingston | 638 | 4 | 3 row 5 : lafayette high school | fighting irish | st. joseph | buchanan | 801 | 4 | 4 row 6 : maryville high school | (lady) spoofhounds | maryville | nodaway | 473 | 3 | 2 row 7 : savannah high school | (lady) savages | savannah | andrew | 743 | 4 | 4 row 8 : smithville high school | (lady) warriors | smithville | clay | 727 | 4 | 4 | col : town row 1 : st. joseph row 2 : st. joseph row 3 : cameron row 4 : chillicothe row 5 : st. joseph row 6 : maryville row 7 : savannah row 8 : smithville | select town where school < town order by county desc limit 1 <table_name> : table \begin{tabular}{llllllll}
\toprule
& school & team name & town & county & enrollment (2010-11 & 2011-12) & primary mshsaa class* & football class \\
\midrule
0 & benton high school & (lady) cardinals & st. joseph & buchanan & 846 & 4 & 4 \\
1 & bishop leblond high school & (lady) golden eagles & st. joseph & buchanan & 314 & 3 & 2 \\
2 & cameron high school & (lady) dragons & cameron & clinton & 503 & 3 & 3 \\
3 & chillicothe high school (missouri) & (lady) hornets & chillicothe & livingston & 638 & 4 & 3 \\
4 & lafayette high school & fighting irish & st. joseph & buchanan & 801 & 4 & 4 \\
5 & maryville high school & (lady) spoofhounds & maryville & nodaway & 473 & 3 & 2 \\
6 & savannah high school & (lady) savages & savannah & andrew & 743 & 4 & 4 \\
7 & smithville high school & (lady) warriors & smithville & clay & 727 & 4 & 4 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& town \\
\midrule
0 & st. joseph \\
1 & st. joseph \\
2 & cameron \\
3 & chillicothe \\
4 & st. joseph \\
5 & maryville \\
6 & savannah \\
7 & smithville \\
\bottomrule
\end{tabular}
| select town where school < town order by county desc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>school</th>
<th>team name</th>
<th>town</th>
<th>county</th>
<th>enrollment (2010-11 & 2011-12)</th>
<th>primary mshsaa class*</th>
<th>football class</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>benton high school</td>
<td>(lady) cardinals</td>
<td>st. joseph</td>
<td>buchanan</td>
<td>846</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>1</th>
<td>bishop leblond high school</td>
<td>(lady) golden eagles</td>
<td>st. joseph</td>
<td>buchanan</td>
<td>314</td>
<td>3</td>
<td>2</td>
</tr>
<tr>
<th>2</th>
<td>cameron high school</td>
<td>(lady) dragons</td>
<td>cameron</td>
<td>clinton</td>
<td>503</td>
<td>3</td>
<td>3</td>
</tr>
<tr>
<th>3</th>
<td>chillicothe high school (missouri)</td>
<td>(lady) hornets</td>
<td>chillicothe</td>
<td>livingston</td>
<td>638</td>
<td>4</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>lafayette high school</td>
<td>fighting irish</td>
<td>st. joseph</td>
<td>buchanan</td>
<td>801</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>5</th>
<td>maryville high school</td>
<td>(lady) spoofhounds</td>
<td>maryville</td>
<td>nodaway</td>
<td>473</td>
<td>3</td>
<td>2</td>
</tr>
<tr>
<th>6</th>
<td>savannah high school</td>
<td>(lady) savages</td>
<td>savannah</td>
<td>andrew</td>
<td>743</td>
<td>4</td>
<td>4</td>
</tr>
<tr>
<th>7</th>
<td>smithville high school</td>
<td>(lady) warriors</td>
<td>smithville</td>
<td>clay</td>
<td>727</td>
<td>4</td>
<td>4</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>town</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>st. joseph</td>
</tr>
<tr>
<th>1</th>
<td>st. joseph</td>
</tr>
<tr>
<th>2</th>
<td>cameron</td>
</tr>
<tr>
<th>3</th>
<td>chillicothe</td>
</tr>
<tr>
<th>4</th>
<td>st. joseph</td>
</tr>
<tr>
<th>5</th>
<td>maryville</td>
</tr>
<tr>
<th>6</th>
<td>savannah</td>
</tr>
<tr>
<th>7</th>
<td>smithville</td>
</tr>
</tbody>
</table> | select town where school < town order by county desc limit 1 <table_name> : table | | school | team name | town | county | enrollment (2010-11 & 2011-12) | primary mshsaa class* | football class |
|---:|:-----------------------------------|:---------------------|:------------|:-----------|---------------------------------:|------------------------:|-----------------:|
| 0 | benton high school | (lady) cardinals | st. joseph | buchanan | 846 | 4 | 4 |
| 1 | bishop leblond high school | (lady) golden eagles | st. joseph | buchanan | 314 | 3 | 2 |
| 2 | cameron high school | (lady) dragons | cameron | clinton | 503 | 3 | 3 |
| 3 | chillicothe high school (missouri) | (lady) hornets | chillicothe | livingston | 638 | 4 | 3 |
| 4 | lafayette high school | fighting irish | st. joseph | buchanan | 801 | 4 | 4 |
| 5 | maryville high school | (lady) spoofhounds | maryville | nodaway | 473 | 3 | 2 |
| 6 | savannah high school | (lady) savages | savannah | andrew | 743 | 4 | 4 |
| 7 | smithville high school | (lady) warriors | smithville | clay | 727 | 4 | 4 | | | | town |
|---:|:------------|
| 0 | st. joseph |
| 1 | st. joseph |
| 2 | cameron |
| 3 | chillicothe |
| 4 | st. joseph |
| 5 | maryville |
| 6 | savannah |
| 7 | smithville | | [
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select count ( * ) where competition = 'uefa europa league' col : season | competition | round | club | home | away row 1 : 1985-86 | uefa cup winners' cup | 1r | hjk helsinki | 1-2 | 2-3 row 2 : 1986-87 | uefa cup | 1r | fc barcelona | 1-1 | 0-0 row 3 : 1987-88 | uefa cup | 1r | fk partizan beograd | 2-0 | 1-2 row 4 : 1987-88 | uefa cup | 2r | wismut aue | 2-0 | 0-1 row 5 : 1987-88 | uefa cup | 1/16 | fc barcelona | 1-0 | 1-4 row 6 : 1988-89 | uefa cup winners' cup | 1r | lech poznan | 2-3 | 0-1 row 7 : 1990-91 | uefa cup winners' cup | 1r | olympiacos piraeus | 0-2 | 1-3 row 8 : 1991-92 | uefa european cup | 1r | ifk goteborg | 1-1 | 0-0 row 9 : 1996-97 | uefa cup winners' cup | qr | humenne | 0-2 | 0-1 row 10 : 2009-10 | uefa europa league | 2qr | motherwell | 1-0 | 1-8 row 11 : 2011-12 | uefa europa league | 1qr | fk buducnost | 1-2 | 3-1 row 12 : none | none | 2qr | fk jablonec 97 | 0-2 | 1-5 row 13 : 2012-13 | uefa europa league | 1qr | budapest honved | 0-1 | 0-2 | col : count ( "*" ) row 1 : 3 | select count ( * ) where competition = 'uefa europa league' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & competition & round & club & home & away \\
\midrule
0 & 1985-86 & uefa cup winners' cup & 1r & hjk helsinki & 1-2 & 2-3 \\
1 & 1986-87 & uefa cup & 1r & fc barcelona & 1-1 & 0-0 \\
2 & 1987-88 & uefa cup & 1r & fk partizan beograd & 2-0 & 1-2 \\
3 & 1987-88 & uefa cup & 2r & wismut aue & 2-0 & 0-1 \\
4 & 1987-88 & uefa cup & 1/16 & fc barcelona & 1-0 & 1-4 \\
5 & 1988-89 & uefa cup winners' cup & 1r & lech poznan & 2-3 & 0-1 \\
6 & 1990-91 & uefa cup winners' cup & 1r & olympiacos piraeus & 0-2 & 1-3 \\
7 & 1991-92 & uefa european cup & 1r & ifk goteborg & 1-1 & 0-0 \\
8 & 1996-97 & uefa cup winners' cup & qr & humenne & 0-2 & 0-1 \\
9 & 2009-10 & uefa europa league & 2qr & motherwell & 1-0 & 1-8 \\
10 & 2011-12 & uefa europa league & 1qr & fk buducnost & 1-2 & 3-1 \\
11 & none & none & 2qr & fk jablonec 97 & 0-2 & 1-5 \\
12 & 2012-13 & uefa europa league & 1qr & budapest honved & 0-1 & 0-2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 3 \\
\bottomrule
\end{tabular}
| select count ( * ) where competition = 'uefa europa league' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>competition</th>
<th>round</th>
<th>club</th>
<th>home</th>
<th>away</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1985-86</td>
<td>uefa cup winners' cup</td>
<td>1r</td>
<td>hjk helsinki</td>
<td>1-2</td>
<td>2-3</td>
</tr>
<tr>
<th>1</th>
<td>1986-87</td>
<td>uefa cup</td>
<td>1r</td>
<td>fc barcelona</td>
<td>1-1</td>
<td>0-0</td>
</tr>
<tr>
<th>2</th>
<td>1987-88</td>
<td>uefa cup</td>
<td>1r</td>
<td>fk partizan beograd</td>
<td>2-0</td>
<td>1-2</td>
</tr>
<tr>
<th>3</th>
<td>1987-88</td>
<td>uefa cup</td>
<td>2r</td>
<td>wismut aue</td>
<td>2-0</td>
<td>0-1</td>
</tr>
<tr>
<th>4</th>
<td>1987-88</td>
<td>uefa cup</td>
<td>1/16</td>
<td>fc barcelona</td>
<td>1-0</td>
<td>1-4</td>
</tr>
<tr>
<th>5</th>
<td>1988-89</td>
<td>uefa cup winners' cup</td>
<td>1r</td>
<td>lech poznan</td>
<td>2-3</td>
<td>0-1</td>
</tr>
<tr>
<th>6</th>
<td>1990-91</td>
<td>uefa cup winners' cup</td>
<td>1r</td>
<td>olympiacos piraeus</td>
<td>0-2</td>
<td>1-3</td>
</tr>
<tr>
<th>7</th>
<td>1991-92</td>
<td>uefa european cup</td>
<td>1r</td>
<td>ifk goteborg</td>
<td>1-1</td>
<td>0-0</td>
</tr>
<tr>
<th>8</th>
<td>1996-97</td>
<td>uefa cup winners' cup</td>
<td>qr</td>
<td>humenne</td>
<td>0-2</td>
<td>0-1</td>
</tr>
<tr>
<th>9</th>
<td>2009-10</td>
<td>uefa europa league</td>
<td>2qr</td>
<td>motherwell</td>
<td>1-0</td>
<td>1-8</td>
</tr>
<tr>
<th>10</th>
<td>2011-12</td>
<td>uefa europa league</td>
<td>1qr</td>
<td>fk buducnost</td>
<td>1-2</td>
<td>3-1</td>
</tr>
<tr>
<th>11</th>
<td>none</td>
<td>none</td>
<td>2qr</td>
<td>fk jablonec 97</td>
<td>0-2</td>
<td>1-5</td>
</tr>
<tr>
<th>12</th>
<td>2012-13</td>
<td>uefa europa league</td>
<td>1qr</td>
<td>budapest honved</td>
<td>0-1</td>
<td>0-2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3</td>
</tr>
</tbody>
</table> | select count ( * ) where competition = 'uefa europa league' <table_name> : table | | season | competition | round | club | home | away |
|---:|:---------|:----------------------|:--------|:--------------------|:-------|:-------|
| 0 | 1985-86 | uefa cup winners' cup | 1r | hjk helsinki | 1-2 | 2-3 |
| 1 | 1986-87 | uefa cup | 1r | fc barcelona | 1-1 | 0-0 |
| 2 | 1987-88 | uefa cup | 1r | fk partizan beograd | 2-0 | 1-2 |
| 3 | 1987-88 | uefa cup | 2r | wismut aue | 2-0 | 0-1 |
| 4 | 1987-88 | uefa cup | 1/16 | fc barcelona | 1-0 | 1-4 |
| 5 | 1988-89 | uefa cup winners' cup | 1r | lech poznan | 2-3 | 0-1 |
| 6 | 1990-91 | uefa cup winners' cup | 1r | olympiacos piraeus | 0-2 | 1-3 |
| 7 | 1991-92 | uefa european cup | 1r | ifk goteborg | 1-1 | 0-0 |
| 8 | 1996-97 | uefa cup winners' cup | qr | humenne | 0-2 | 0-1 |
| 9 | 2009-10 | uefa europa league | 2qr | motherwell | 1-0 | 1-8 |
| 10 | 2011-12 | uefa europa league | 1qr | fk buducnost | 1-2 | 3-1 |
| 11 | none | none | 2qr | fk jablonec 97 | 0-2 | 1-5 |
| 12 | 2012-13 | uefa europa league | 1qr | budapest honved | 0-1 | 0-2 | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 3 | | [
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select count ( game site ) where week > 8 col : week | opponent | result | game site | tv | time | attendance | bye row 1 : 1 | at denver broncos | l 3-19 | mile high stadium | nbc | 4:15pm | 75600 | row 2 : 2 | at oakland raiders | w 28-27 | network associates coliseum | abc | 9:00pm | 61523 | row 3 : 3 | buffalo bills | w 22-16 | arrowhead stadium | nbc | 1:00pm | 78169 | row 4 : 4 | at carolina panthers | w 35-14 | bank of america stadium | nbc | 1:00pm | 67402 | row 5 : 5 | seattle seahawks | w 20-17 ot | arrowhead stadium | nbc | 4:15pm | 77877 | row 6 : 6 | at miami dolphins | l 14-17 | pro player stadium | nbc | 1:00pm | 71794 | row 7 : 7 | none | none | none | none | none | none | row 8 : 8 | san diego chargers | w 31-3 | arrowhead stadium | tnt | 8:00pm | 77195 | row 9 : 9 | at st. louis rams | w 28-20 | edward jones dome | nbc | 1:00pm | 64864 | row 10 : 10 | pittsburgh steelers | w 13-10 | arrowhead stadium | abc | 9:00pm | 78301 | row 11 : 11 | at jacksonville jaguars | l 14-24 | alltel stadium | nbc | 1:00pm | 70444 | row 12 : 12 | denver broncos | w 24-22 | arrowhead stadium | nbc | 1:00pm | 77963 | row 13 : 13 | at seattle seahawks | w 19-14 | kingdome | nbc | 4:15pm | 66264 | row 14 : 14 | san francisco 49ers | w 44-9 | arrowhead stadium | fox | 1:00pm | 77535 | row 15 : 15 | oakland raiders | w 30-0 | arrowhead stadium | nbc | 1:00pm | 76379 | row 16 : 16 | at san diego chargers | w 29-7 | qualcomm stadium | nbc | 4:15pm | 54594 | row 17 : 17 | new orleans saints | w 25-13 | arrowhead stadium | fox | 1:00pm | 66772 | row 18 : divisional playoff | denver broncos | l 10-14 | arrowhead stadium | nbc | 4:15pm | 76965 | | col : count ( "game site" ) row 1 : 2 | select count ( game site ) where week > 8 <table_name> : table \begin{tabular}{lllllllll}
\toprule
& week & opponent & result & game site & tv & time & attendance & bye \\
\midrule
0 & 1 & at denver broncos & l 3-19 & mile high stadium & nbc & 4:15pm & 75600 & \\
1 & 2 & at oakland raiders & w 28-27 & network associates coliseum & abc & 9:00pm & 61523 & \\
2 & 3 & buffalo bills & w 22-16 & arrowhead stadium & nbc & 1:00pm & 78169 & \\
3 & 4 & at carolina panthers & w 35-14 & bank of america stadium & nbc & 1:00pm & 67402 & \\
4 & 5 & seattle seahawks & w 20-17 ot & arrowhead stadium & nbc & 4:15pm & 77877 & \\
5 & 6 & at miami dolphins & l 14-17 & pro player stadium & nbc & 1:00pm & 71794 & \\
6 & 7 & none & none & none & none & none & none & \\
7 & 8 & san diego chargers & w 31-3 & arrowhead stadium & tnt & 8:00pm & 77195 & \\
8 & 9 & at st. louis rams & w 28-20 & edward jones dome & nbc & 1:00pm & 64864 & \\
9 & 10 & pittsburgh steelers & w 13-10 & arrowhead stadium & abc & 9:00pm & 78301 & \\
10 & 11 & at jacksonville jaguars & l 14-24 & alltel stadium & nbc & 1:00pm & 70444 & \\
11 & 12 & denver broncos & w 24-22 & arrowhead stadium & nbc & 1:00pm & 77963 & \\
12 & 13 & at seattle seahawks & w 19-14 & kingdome & nbc & 4:15pm & 66264 & \\
13 & 14 & san francisco 49ers & w 44-9 & arrowhead stadium & fox & 1:00pm & 77535 & \\
14 & 15 & oakland raiders & w 30-0 & arrowhead stadium & nbc & 1:00pm & 76379 & \\
15 & 16 & at san diego chargers & w 29-7 & qualcomm stadium & nbc & 4:15pm & 54594 & \\
16 & 17 & new orleans saints & w 25-13 & arrowhead stadium & fox & 1:00pm & 66772 & \\
17 & divisional playoff & denver broncos & l 10-14 & arrowhead stadium & nbc & 4:15pm & 76965 | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "game site" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( game site ) where week > 8 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>opponent</th>
<th>result</th>
<th>game site</th>
<th>tv</th>
<th>time</th>
<th>attendance</th>
<th>bye</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>at denver broncos</td>
<td>l 3-19</td>
<td>mile high stadium</td>
<td>nbc</td>
<td>4:15pm</td>
<td>75600</td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>at oakland raiders</td>
<td>w 28-27</td>
<td>network associates coliseum</td>
<td>abc</td>
<td>9:00pm</td>
<td>61523</td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>buffalo bills</td>
<td>w 22-16</td>
<td>arrowhead stadium</td>
<td>nbc</td>
<td>1:00pm</td>
<td>78169</td>
<td></td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>at carolina panthers</td>
<td>w 35-14</td>
<td>bank of america stadium</td>
<td>nbc</td>
<td>1:00pm</td>
<td>67402</td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>seattle seahawks</td>
<td>w 20-17 ot</td>
<td>arrowhead stadium</td>
<td>nbc</td>
<td>4:15pm</td>
<td>77877</td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>at miami dolphins</td>
<td>l 14-17</td>
<td>pro player stadium</td>
<td>nbc</td>
<td>1:00pm</td>
<td>71794</td>
<td></td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>san diego chargers</td>
<td>w 31-3</td>
<td>arrowhead stadium</td>
<td>tnt</td>
<td>8:00pm</td>
<td>77195</td>
<td></td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>at st. louis rams</td>
<td>w 28-20</td>
<td>edward jones dome</td>
<td>nbc</td>
<td>1:00pm</td>
<td>64864</td>
<td></td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>pittsburgh steelers</td>
<td>w 13-10</td>
<td>arrowhead stadium</td>
<td>abc</td>
<td>9:00pm</td>
<td>78301</td>
<td></td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>at jacksonville jaguars</td>
<td>l 14-24</td>
<td>alltel stadium</td>
<td>nbc</td>
<td>1:00pm</td>
<td>70444</td>
<td></td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>denver broncos</td>
<td>w 24-22</td>
<td>arrowhead stadium</td>
<td>nbc</td>
<td>1:00pm</td>
<td>77963</td>
<td></td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>at seattle seahawks</td>
<td>w 19-14</td>
<td>kingdome</td>
<td>nbc</td>
<td>4:15pm</td>
<td>66264</td>
<td></td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>san francisco 49ers</td>
<td>w 44-9</td>
<td>arrowhead stadium</td>
<td>fox</td>
<td>1:00pm</td>
<td>77535</td>
<td></td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>oakland raiders</td>
<td>w 30-0</td>
<td>arrowhead stadium</td>
<td>nbc</td>
<td>1:00pm</td>
<td>76379</td>
<td></td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>at san diego chargers</td>
<td>w 29-7</td>
<td>qualcomm stadium</td>
<td>nbc</td>
<td>4:15pm</td>
<td>54594</td>
<td></td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>new orleans saints</td>
<td>w 25-13</td>
<td>arrowhead stadium</td>
<td>fox</td>
<td>1:00pm</td>
<td>66772</td>
<td></td>
</tr>
<tr>
<th>17</th>
<td>divisional playoff</td>
<td>denver broncos</td>
<td>l 10-14</td>
<td>arrowhead stadium</td>
<td>nbc</td>
<td>4:15pm</td>
<td>76965 |</td>
<td>None</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "game site" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( game site ) where week > 8 <table_name> : table | | week | opponent | result | game site | tv | time | attendance | bye |
|---:|:-------------------|:------------------------|:-----------|:----------------------------|:-----|:-------|:-------------|:------|
| 0 | 1 | at denver broncos | l 3-19 | mile high stadium | nbc | 4:15pm | 75600 | |
| 1 | 2 | at oakland raiders | w 28-27 | network associates coliseum | abc | 9:00pm | 61523 | |
| 2 | 3 | buffalo bills | w 22-16 | arrowhead stadium | nbc | 1:00pm | 78169 | |
| 3 | 4 | at carolina panthers | w 35-14 | bank of america stadium | nbc | 1:00pm | 67402 | |
| 4 | 5 | seattle seahawks | w 20-17 ot | arrowhead stadium | nbc | 4:15pm | 77877 | |
| 5 | 6 | at miami dolphins | l 14-17 | pro player stadium | nbc | 1:00pm | 71794 | |
| 6 | 7 | none | none | none | none | none | none | |
| 7 | 8 | san diego chargers | w 31-3 | arrowhead stadium | tnt | 8:00pm | 77195 | |
| 8 | 9 | at st. louis rams | w 28-20 | edward jones dome | nbc | 1:00pm | 64864 | |
| 9 | 10 | pittsburgh steelers | w 13-10 | arrowhead stadium | abc | 9:00pm | 78301 | |
| 10 | 11 | at jacksonville jaguars | l 14-24 | alltel stadium | nbc | 1:00pm | 70444 | |
| 11 | 12 | denver broncos | w 24-22 | arrowhead stadium | nbc | 1:00pm | 77963 | |
| 12 | 13 | at seattle seahawks | w 19-14 | kingdome | nbc | 4:15pm | 66264 | |
| 13 | 14 | san francisco 49ers | w 44-9 | arrowhead stadium | fox | 1:00pm | 77535 | |
| 14 | 15 | oakland raiders | w 30-0 | arrowhead stadium | nbc | 1:00pm | 76379 | |
| 15 | 16 | at san diego chargers | w 29-7 | qualcomm stadium | nbc | 4:15pm | 54594 | |
| 16 | 17 | new orleans saints | w 25-13 | arrowhead stadium | fox | 1:00pm | 66772 | |
| 17 | divisional playoff | denver broncos | l 10-14 | arrowhead stadium | nbc | 4:15pm | 76965 | | | | | | count ( "game site" ) |
|---:|------------------------:|
| 0 | 2 | | [
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select distance (km) where japanese = '岡山' col : name | japanese | distance (km) | connections | location row 1 : okayama | 岡山 | 0.0 | sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line | kita-ku, okayama row 2 : bizen-mikado | 備前三門 | 1.9 | none | kita-ku, okayama row 3 : daianji | 大安寺 | 3.3 | none | kita-ku, okayama row 4 : bizen-ichinomiya | 備前一宮 | 6.5 | none | kita-ku, okayama row 5 : kibitsu | 吉備津 | 8.4 | none | kita-ku, okayama row 6 : bitchu-takamatsu | 備中高松 | 11.0 | none | kita-ku, okayama row 7 : ashimori | 足守 | 13.4 | none | kita-ku, okayama row 8 : hattori | 服部 | 16.2 | none | soja row 9 : higashi-soja | 東総社 | 18.8 | none | soja row 10 : soja | 総社 | 20.4 | hakubi line ibara railway ibara line | soja | col : distance (km) row 1 : 0 | select distance (km) where japanese = '岡山' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & japanese & distance (km) & connections & location \\
\midrule
0 & okayama & 岡山 & 0.0 & sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line & kita-ku, okayama \\
1 & bizen-mikado & 備前三門 & 1.9 & none & kita-ku, okayama \\
2 & daianji & 大安寺 & 3.3 & none & kita-ku, okayama \\
3 & bizen-ichinomiya & 備前一宮 & 6.5 & none & kita-ku, okayama \\
4 & kibitsu & 吉備津 & 8.4 & none & kita-ku, okayama \\
5 & bitchu-takamatsu & 備中高松 & 11.0 & none & kita-ku, okayama \\
6 & ashimori & 足守 & 13.4 & none & kita-ku, okayama \\
7 & hattori & 服部 & 16.2 & none & soja \\
8 & higashi-soja & 東総社 & 18.8 & none & soja \\
9 & soja & 総社 & 20.4 & hakubi line ibara railway ibara line & soja \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& distance (km) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select distance (km) where japanese = '岡山' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>japanese</th>
<th>distance (km)</th>
<th>connections</th>
<th>location</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>okayama</td>
<td>岡山</td>
<td>0.0</td>
<td>sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>1</th>
<td>bizen-mikado</td>
<td>備前三門</td>
<td>1.9</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>2</th>
<td>daianji</td>
<td>大安寺</td>
<td>3.3</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>3</th>
<td>bizen-ichinomiya</td>
<td>備前一宮</td>
<td>6.5</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>4</th>
<td>kibitsu</td>
<td>吉備津</td>
<td>8.4</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>5</th>
<td>bitchu-takamatsu</td>
<td>備中高松</td>
<td>11.0</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>6</th>
<td>ashimori</td>
<td>足守</td>
<td>13.4</td>
<td>none</td>
<td>kita-ku, okayama</td>
</tr>
<tr>
<th>7</th>
<td>hattori</td>
<td>服部</td>
<td>16.2</td>
<td>none</td>
<td>soja</td>
</tr>
<tr>
<th>8</th>
<td>higashi-soja</td>
<td>東総社</td>
<td>18.8</td>
<td>none</td>
<td>soja</td>
</tr>
<tr>
<th>9</th>
<td>soja</td>
<td>総社</td>
<td>20.4</td>
<td>hakubi line ibara railway ibara line</td>
<td>soja</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>distance (km)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select distance (km) where japanese = '岡山' <table_name> : table | | name | japanese | distance (km) | connections | location |
|---:|:-----------------|:-----------|----------------:|:----------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------|
| 0 | okayama | 岡山 | 0 | sanyo shinkansen, sanyo main line, ako line, hakubi line, uno line (seto-ohashi line), tsuyama line okayama electric tramway: higashiyama line, seikibashi line | kita-ku, okayama |
| 1 | bizen-mikado | 備前三門 | 1.9 | none | kita-ku, okayama |
| 2 | daianji | 大安寺 | 3.3 | none | kita-ku, okayama |
| 3 | bizen-ichinomiya | 備前一宮 | 6.5 | none | kita-ku, okayama |
| 4 | kibitsu | 吉備津 | 8.4 | none | kita-ku, okayama |
| 5 | bitchu-takamatsu | 備中高松 | 11 | none | kita-ku, okayama |
| 6 | ashimori | 足守 | 13.4 | none | kita-ku, okayama |
| 7 | hattori | 服部 | 16.2 | none | soja |
| 8 | higashi-soja | 東総社 | 18.8 | none | soja |
| 9 | soja | 総社 | 20.4 | hakubi line ibara railway ibara line | soja | | | | distance (km) |
|---:|----------------:|
| 0 | 0 | | [
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select count ( location ) where location = 'hsbc arena' col : game | date | opponent | location | score | ot | attendance | record row 1 : 1 | 2006-01-06 00:00:00 | philadelphia wings | xcel energy center | l 11-15 | none | 8024 | 0-1 row 2 : 2 | 2006-01-14 00:00:00 | @ philadelphia wings | wachovia center | w 13-10 | none | 11874 | 1-1 row 3 : 3 | 2006-01-20 00:00:00 | @ calgary roughnecks | pengrowth saddledome | w 12-8 | none | 10637 | 2-1 row 4 : 4 | 2006-01-21 00:00:00 | rochester knighthawks | xcel energy center | l 6-12 | none | 7124 | 2-2 row 5 : 5 | 2006-01-29 00:00:00 | rochester knighthawks | xcel energy center | l 9-10 | none | 7544 | 3-2 row 6 : 6 | 2006-02-03 00:00:00 | @ edmonton rush | rexall place | w 7-6 | none | 8745 | 3-3 row 7 : 7 | 2006-02-10 00:00:00 | philadelphia wings | xcel energy center | w 11-10 | none | 7524 | 4-3 row 8 : 8 | 2006-02-18 00:00:00 | @ buffalo bandits | hsbc arena | l 9-14 | none | 12458 | 4-4 row 9 : 9 | 2006-03-03 00:00:00 | @ toronto rock | air canada centre | l 8-13 | none | 15830 | 4-5 row 10 : 10 | 2006-03-04 00:00:00 | @ buffalo bandits | hsbc arena | w 11-8 | none | 10961 | 5-5 row 11 : 11 | 2006-03-17 00:00:00 | @ portland lumberjax | rose garden | w 14-12 | none | 5487 | 6-5 row 12 : 12 | 2006-03-24 00:00:00 | buffalo bandits | xcel energy center | l 11-13 | none | 9533 | 6-6 row 13 : 13 | 2006-04-01 00:00:00 | toronto rock | xcel energy center | w 10-9 | none | 10084 | 7-6 row 14 : 14 | 2006-04-08 00:00:00 | @ rochester knighthawks | blue cross arena | l 9-10 | none | 10352 | 7-7 row 15 : 15 | 2006-04-09 00:00:00 | san jose stealth | xcel energy center | w 9-8 | ot | 7044 | 8-7 row 16 : 16 | 2006-04-15 00:00:00 | portland lumberjax | xcel energy center | l 8-13 | none | 10104 | 8-8 | col : count ( "location" ) row 1 : 2 | select count ( location ) where location = 'hsbc arena' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& game & date & opponent & location & score & ot & attendance & record \\
\midrule
0 & 1 & 2006-01-06 00:00:00 & philadelphia wings & xcel energy center & l 11-15 & none & 8024 & 0-1 \\
1 & 2 & 2006-01-14 00:00:00 & @ philadelphia wings & wachovia center & w 13-10 & none & 11874 & 1-1 \\
2 & 3 & 2006-01-20 00:00:00 & @ calgary roughnecks & pengrowth saddledome & w 12-8 & none & 10637 & 2-1 \\
3 & 4 & 2006-01-21 00:00:00 & rochester knighthawks & xcel energy center & l 6-12 & none & 7124 & 2-2 \\
4 & 5 & 2006-01-29 00:00:00 & rochester knighthawks & xcel energy center & l 9-10 & none & 7544 & 3-2 \\
5 & 6 & 2006-02-03 00:00:00 & @ edmonton rush & rexall place & w 7-6 & none & 8745 & 3-3 \\
6 & 7 & 2006-02-10 00:00:00 & philadelphia wings & xcel energy center & w 11-10 & none & 7524 & 4-3 \\
7 & 8 & 2006-02-18 00:00:00 & @ buffalo bandits & hsbc arena & l 9-14 & none & 12458 & 4-4 \\
8 & 9 & 2006-03-03 00:00:00 & @ toronto rock & air canada centre & l 8-13 & none & 15830 & 4-5 \\
9 & 10 & 2006-03-04 00:00:00 & @ buffalo bandits & hsbc arena & w 11-8 & none & 10961 & 5-5 \\
10 & 11 & 2006-03-17 00:00:00 & @ portland lumberjax & rose garden & w 14-12 & none & 5487 & 6-5 \\
11 & 12 & 2006-03-24 00:00:00 & buffalo bandits & xcel energy center & l 11-13 & none & 9533 & 6-6 \\
12 & 13 & 2006-04-01 00:00:00 & toronto rock & xcel energy center & w 10-9 & none & 10084 & 7-6 \\
13 & 14 & 2006-04-08 00:00:00 & @ rochester knighthawks & blue cross arena & l 9-10 & none & 10352 & 7-7 \\
14 & 15 & 2006-04-09 00:00:00 & san jose stealth & xcel energy center & w 9-8 & ot & 7044 & 8-7 \\
15 & 16 & 2006-04-15 00:00:00 & portland lumberjax & xcel energy center & l 8-13 & none & 10104 & 8-8 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "location" ) \\
\midrule
0 & 2 \\
\bottomrule
\end{tabular}
| select count ( location ) where location = 'hsbc arena' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>date</th>
<th>opponent</th>
<th>location</th>
<th>score</th>
<th>ot</th>
<th>attendance</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2006-01-06 00:00:00</td>
<td>philadelphia wings</td>
<td>xcel energy center</td>
<td>l 11-15</td>
<td>none</td>
<td>8024</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2006-01-14 00:00:00</td>
<td>@ philadelphia wings</td>
<td>wachovia center</td>
<td>w 13-10</td>
<td>none</td>
<td>11874</td>
<td>1-1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2006-01-20 00:00:00</td>
<td>@ calgary roughnecks</td>
<td>pengrowth saddledome</td>
<td>w 12-8</td>
<td>none</td>
<td>10637</td>
<td>2-1</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2006-01-21 00:00:00</td>
<td>rochester knighthawks</td>
<td>xcel energy center</td>
<td>l 6-12</td>
<td>none</td>
<td>7124</td>
<td>2-2</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2006-01-29 00:00:00</td>
<td>rochester knighthawks</td>
<td>xcel energy center</td>
<td>l 9-10</td>
<td>none</td>
<td>7544</td>
<td>3-2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2006-02-03 00:00:00</td>
<td>@ edmonton rush</td>
<td>rexall place</td>
<td>w 7-6</td>
<td>none</td>
<td>8745</td>
<td>3-3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2006-02-10 00:00:00</td>
<td>philadelphia wings</td>
<td>xcel energy center</td>
<td>w 11-10</td>
<td>none</td>
<td>7524</td>
<td>4-3</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2006-02-18 00:00:00</td>
<td>@ buffalo bandits</td>
<td>hsbc arena</td>
<td>l 9-14</td>
<td>none</td>
<td>12458</td>
<td>4-4</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2006-03-03 00:00:00</td>
<td>@ toronto rock</td>
<td>air canada centre</td>
<td>l 8-13</td>
<td>none</td>
<td>15830</td>
<td>4-5</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2006-03-04 00:00:00</td>
<td>@ buffalo bandits</td>
<td>hsbc arena</td>
<td>w 11-8</td>
<td>none</td>
<td>10961</td>
<td>5-5</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2006-03-17 00:00:00</td>
<td>@ portland lumberjax</td>
<td>rose garden</td>
<td>w 14-12</td>
<td>none</td>
<td>5487</td>
<td>6-5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>2006-03-24 00:00:00</td>
<td>buffalo bandits</td>
<td>xcel energy center</td>
<td>l 11-13</td>
<td>none</td>
<td>9533</td>
<td>6-6</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>2006-04-01 00:00:00</td>
<td>toronto rock</td>
<td>xcel energy center</td>
<td>w 10-9</td>
<td>none</td>
<td>10084</td>
<td>7-6</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>2006-04-08 00:00:00</td>
<td>@ rochester knighthawks</td>
<td>blue cross arena</td>
<td>l 9-10</td>
<td>none</td>
<td>10352</td>
<td>7-7</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>2006-04-09 00:00:00</td>
<td>san jose stealth</td>
<td>xcel energy center</td>
<td>w 9-8</td>
<td>ot</td>
<td>7044</td>
<td>8-7</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>2006-04-15 00:00:00</td>
<td>portland lumberjax</td>
<td>xcel energy center</td>
<td>l 8-13</td>
<td>none</td>
<td>10104</td>
<td>8-8</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "location" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2</td>
</tr>
</tbody>
</table> | select count ( location ) where location = 'hsbc arena' <table_name> : table | | game | date | opponent | location | score | ot | attendance | record |
|---:|-------:|:--------------------|:------------------------|:---------------------|:--------|:-----|-------------:|:---------|
| 0 | 1 | 2006-01-06 00:00:00 | philadelphia wings | xcel energy center | l 11-15 | none | 8024 | 0-1 |
| 1 | 2 | 2006-01-14 00:00:00 | @ philadelphia wings | wachovia center | w 13-10 | none | 11874 | 1-1 |
| 2 | 3 | 2006-01-20 00:00:00 | @ calgary roughnecks | pengrowth saddledome | w 12-8 | none | 10637 | 2-1 |
| 3 | 4 | 2006-01-21 00:00:00 | rochester knighthawks | xcel energy center | l 6-12 | none | 7124 | 2-2 |
| 4 | 5 | 2006-01-29 00:00:00 | rochester knighthawks | xcel energy center | l 9-10 | none | 7544 | 3-2 |
| 5 | 6 | 2006-02-03 00:00:00 | @ edmonton rush | rexall place | w 7-6 | none | 8745 | 3-3 |
| 6 | 7 | 2006-02-10 00:00:00 | philadelphia wings | xcel energy center | w 11-10 | none | 7524 | 4-3 |
| 7 | 8 | 2006-02-18 00:00:00 | @ buffalo bandits | hsbc arena | l 9-14 | none | 12458 | 4-4 |
| 8 | 9 | 2006-03-03 00:00:00 | @ toronto rock | air canada centre | l 8-13 | none | 15830 | 4-5 |
| 9 | 10 | 2006-03-04 00:00:00 | @ buffalo bandits | hsbc arena | w 11-8 | none | 10961 | 5-5 |
| 10 | 11 | 2006-03-17 00:00:00 | @ portland lumberjax | rose garden | w 14-12 | none | 5487 | 6-5 |
| 11 | 12 | 2006-03-24 00:00:00 | buffalo bandits | xcel energy center | l 11-13 | none | 9533 | 6-6 |
| 12 | 13 | 2006-04-01 00:00:00 | toronto rock | xcel energy center | w 10-9 | none | 10084 | 7-6 |
| 13 | 14 | 2006-04-08 00:00:00 | @ rochester knighthawks | blue cross arena | l 9-10 | none | 10352 | 7-7 |
| 14 | 15 | 2006-04-09 00:00:00 | san jose stealth | xcel energy center | w 9-8 | ot | 7044 | 8-7 |
| 15 | 16 | 2006-04-15 00:00:00 | portland lumberjax | xcel energy center | l 8-13 | none | 10104 | 8-8 | | | | count ( "location" ) |
|---:|-----------------------:|
| 0 | 2 | | [
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select single where single = '"holding out for a hero"' order by single asc limit 1 col : year | single | chart | position row 1 : 1986 | "holding out for a hero" | irish singles chart (1985) | 1 row 2 : 1986 | "holding out for a hero" | uk singles chart (1985) | 2 row 3 : 1986 | "holding out for a hero" | euro charts (1985) | 12 row 4 : 1986 | "holding out for a hero" | german singles chart (1984) | 19 row 5 : 1986 | "holding out for a hero" | canadian singles chart (1984) | 19 row 6 : 1986 | "holding out for a hero" | austrian singles chart (1984) | 19 row 7 : 1986 | "holding out for a hero" | swedish singles chart (1984) | 19 row 8 : 1986 | "holding out for a hero" | italian singles chart (1984) | 30 row 9 : 1986 | "holding out for a hero" | new zealand singles chart (1984) | 33 row 10 : 1986 | "holding out for a hero" | u.s. billboard singles chart (1984) | 34 row 11 : 1986 | "holding out for a hero" | australian singles chart (1984) | 44 row 12 : 1986 | "holding out for a hero" | uk singles chart (1991) | 69 row 13 : 1986 | "holding out for a hero" | uk singles chart (1984) | 96 row 14 : 1986 | "if you were a woman and i was a man" | venezuela | 1 row 15 : 1986 | "if you were a woman and i was a man" | french snep singles chart | 6 row 16 : 1986 | "if you were a woman and i was a man" | swiss singles chart | 16 row 17 : 1986 | "if you were a woman and i was a man" | uk club chart | 16 row 18 : 1986 | "if you were a woman and i was a man" | new zealand | 20 row 19 : 1986 | "if you were a woman and i was a man" | german singles chart | 32 row 20 : 1986 | "if you were a woman and i was a man" | australia | 77 row 21 : 1986 | "if you were a woman and i was a man" | u.s. billboard singles chart | 77 row 22 : 1986 | "if you were a woman and i was a man" | uk singles chart | 78 row 23 : 1986 | "if you were a woman and i was a man" | canada rpm | 87 row 24 : 1986 | "loving you's a dirty job but somebody's gotta do it" | spain | 6 row 25 : 1986 | "loving you's a dirty job but somebody's gotta do it" | switzerland | 24 row 26 : 1986 | "loving you's a dirty job but somebody's gotta do it" | germany | 30 row 27 : 1986 | "loving you's a dirty job but somebody's gotta do it" | french | 34 row 28 : 1986 | "loving you's a dirty job but somebody's gotta do it" | uk | 73 row 29 : 1986 | "band of gold" | billboard hot dance breakouts singles sales | 6 row 30 : 1986 | "band of gold" | uk | 81 | col : single row 1 : "holding out for a hero" | select single where single = '"holding out for a hero"' order by single asc limit 1 <table_name> : table \begin{tabular}{lllll}
\toprule
& year & single & chart & position \\
\midrule
0 & 1986 & "holding out for a hero" & irish singles chart (1985) & 1 \\
1 & 1986 & "holding out for a hero" & uk singles chart (1985) & 2 \\
2 & 1986 & "holding out for a hero" & euro charts (1985) & 12 \\
3 & 1986 & "holding out for a hero" & german singles chart (1984) & 19 \\
4 & 1986 & "holding out for a hero" & canadian singles chart (1984) & 19 \\
5 & 1986 & "holding out for a hero" & austrian singles chart (1984) & 19 \\
6 & 1986 & "holding out for a hero" & swedish singles chart (1984) & 19 \\
7 & 1986 & "holding out for a hero" & italian singles chart (1984) & 30 \\
8 & 1986 & "holding out for a hero" & new zealand singles chart (1984) & 33 \\
9 & 1986 & "holding out for a hero" & u.s. billboard singles chart (1984) & 34 \\
10 & 1986 & "holding out for a hero" & australian singles chart (1984) & 44 \\
11 & 1986 & "holding out for a hero" & uk singles chart (1991) & 69 \\
12 & 1986 & "holding out for a hero" & uk singles chart (1984) & 96 \\
13 & 1986 & "if you were a woman and i was a man" & venezuela & 1 \\
14 & 1986 & "if you were a woman and i was a man" & french snep singles chart & 6 \\
15 & 1986 & "if you were a woman and i was a man" & swiss singles chart & 16 \\
16 & 1986 & "if you were a woman and i was a man" & uk club chart & 16 \\
17 & 1986 & "if you were a woman and i was a man" & new zealand & 20 \\
18 & 1986 & "if you were a woman and i was a man" & german singles chart & 32 \\
19 & 1986 & "if you were a woman and i was a man" & australia & 77 \\
20 & 1986 & "if you were a woman and i was a man" & u.s. billboard singles chart & 77 \\
21 & 1986 & "if you were a woman and i was a man" & uk singles chart & 78 \\
22 & 1986 & "if you were a woman and i was a man" & canada rpm & 87 \\
23 & 1986 & "loving you's a dirty job but somebody's gotta do it" & spain & 6 \\
24 & 1986 & "loving you's a dirty job but somebody's gotta do it" & switzerland & 24 \\
25 & 1986 & "loving you's a dirty job but somebody's gotta do it" & germany & 30 \\
26 & 1986 & "loving you's a dirty job but somebody's gotta do it" & french & 34 \\
27 & 1986 & "loving you's a dirty job but somebody's gotta do it" & uk & 73 \\
28 & 1986 & "band of gold" & billboard hot dance breakouts singles sales & 6 \\
29 & 1986 & "band of gold" & uk & 81 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& single \\
\midrule
0 & "holding out for a hero" \\
\bottomrule
\end{tabular}
| select single where single = '"holding out for a hero"' order by single asc limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>single</th>
<th>chart</th>
<th>position</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>irish singles chart (1985)</td>
<td>1</td>
</tr>
<tr>
<th>1</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>uk singles chart (1985)</td>
<td>2</td>
</tr>
<tr>
<th>2</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>euro charts (1985)</td>
<td>12</td>
</tr>
<tr>
<th>3</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>german singles chart (1984)</td>
<td>19</td>
</tr>
<tr>
<th>4</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>canadian singles chart (1984)</td>
<td>19</td>
</tr>
<tr>
<th>5</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>austrian singles chart (1984)</td>
<td>19</td>
</tr>
<tr>
<th>6</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>swedish singles chart (1984)</td>
<td>19</td>
</tr>
<tr>
<th>7</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>italian singles chart (1984)</td>
<td>30</td>
</tr>
<tr>
<th>8</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>new zealand singles chart (1984)</td>
<td>33</td>
</tr>
<tr>
<th>9</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>u.s. billboard singles chart (1984)</td>
<td>34</td>
</tr>
<tr>
<th>10</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>australian singles chart (1984)</td>
<td>44</td>
</tr>
<tr>
<th>11</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>uk singles chart (1991)</td>
<td>69</td>
</tr>
<tr>
<th>12</th>
<td>1986</td>
<td>"holding out for a hero"</td>
<td>uk singles chart (1984)</td>
<td>96</td>
</tr>
<tr>
<th>13</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>venezuela</td>
<td>1</td>
</tr>
<tr>
<th>14</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>french snep singles chart</td>
<td>6</td>
</tr>
<tr>
<th>15</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>swiss singles chart</td>
<td>16</td>
</tr>
<tr>
<th>16</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>uk club chart</td>
<td>16</td>
</tr>
<tr>
<th>17</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>new zealand</td>
<td>20</td>
</tr>
<tr>
<th>18</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>german singles chart</td>
<td>32</td>
</tr>
<tr>
<th>19</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>australia</td>
<td>77</td>
</tr>
<tr>
<th>20</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>u.s. billboard singles chart</td>
<td>77</td>
</tr>
<tr>
<th>21</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>uk singles chart</td>
<td>78</td>
</tr>
<tr>
<th>22</th>
<td>1986</td>
<td>"if you were a woman and i was a man"</td>
<td>canada rpm</td>
<td>87</td>
</tr>
<tr>
<th>23</th>
<td>1986</td>
<td>"loving you's a dirty job but somebody's gotta do it"</td>
<td>spain</td>
<td>6</td>
</tr>
<tr>
<th>24</th>
<td>1986</td>
<td>"loving you's a dirty job but somebody's gotta do it"</td>
<td>switzerland</td>
<td>24</td>
</tr>
<tr>
<th>25</th>
<td>1986</td>
<td>"loving you's a dirty job but somebody's gotta do it"</td>
<td>germany</td>
<td>30</td>
</tr>
<tr>
<th>26</th>
<td>1986</td>
<td>"loving you's a dirty job but somebody's gotta do it"</td>
<td>french</td>
<td>34</td>
</tr>
<tr>
<th>27</th>
<td>1986</td>
<td>"loving you's a dirty job but somebody's gotta do it"</td>
<td>uk</td>
<td>73</td>
</tr>
<tr>
<th>28</th>
<td>1986</td>
<td>"band of gold"</td>
<td>billboard hot dance breakouts singles sales</td>
<td>6</td>
</tr>
<tr>
<th>29</th>
<td>1986</td>
<td>"band of gold"</td>
<td>uk</td>
<td>81</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>single</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>"holding out for a hero"</td>
</tr>
</tbody>
</table> | select single where single = '"holding out for a hero"' order by single asc limit 1 <table_name> : table | | year | single | chart | position |
|---:|-------:|:------------------------------------------------------|:--------------------------------------------|-----------:|
| 0 | 1986 | "holding out for a hero" | irish singles chart (1985) | 1 |
| 1 | 1986 | "holding out for a hero" | uk singles chart (1985) | 2 |
| 2 | 1986 | "holding out for a hero" | euro charts (1985) | 12 |
| 3 | 1986 | "holding out for a hero" | german singles chart (1984) | 19 |
| 4 | 1986 | "holding out for a hero" | canadian singles chart (1984) | 19 |
| 5 | 1986 | "holding out for a hero" | austrian singles chart (1984) | 19 |
| 6 | 1986 | "holding out for a hero" | swedish singles chart (1984) | 19 |
| 7 | 1986 | "holding out for a hero" | italian singles chart (1984) | 30 |
| 8 | 1986 | "holding out for a hero" | new zealand singles chart (1984) | 33 |
| 9 | 1986 | "holding out for a hero" | u.s. billboard singles chart (1984) | 34 |
| 10 | 1986 | "holding out for a hero" | australian singles chart (1984) | 44 |
| 11 | 1986 | "holding out for a hero" | uk singles chart (1991) | 69 |
| 12 | 1986 | "holding out for a hero" | uk singles chart (1984) | 96 |
| 13 | 1986 | "if you were a woman and i was a man" | venezuela | 1 |
| 14 | 1986 | "if you were a woman and i was a man" | french snep singles chart | 6 |
| 15 | 1986 | "if you were a woman and i was a man" | swiss singles chart | 16 |
| 16 | 1986 | "if you were a woman and i was a man" | uk club chart | 16 |
| 17 | 1986 | "if you were a woman and i was a man" | new zealand | 20 |
| 18 | 1986 | "if you were a woman and i was a man" | german singles chart | 32 |
| 19 | 1986 | "if you were a woman and i was a man" | australia | 77 |
| 20 | 1986 | "if you were a woman and i was a man" | u.s. billboard singles chart | 77 |
| 21 | 1986 | "if you were a woman and i was a man" | uk singles chart | 78 |
| 22 | 1986 | "if you were a woman and i was a man" | canada rpm | 87 |
| 23 | 1986 | "loving you's a dirty job but somebody's gotta do it" | spain | 6 |
| 24 | 1986 | "loving you's a dirty job but somebody's gotta do it" | switzerland | 24 |
| 25 | 1986 | "loving you's a dirty job but somebody's gotta do it" | germany | 30 |
| 26 | 1986 | "loving you's a dirty job but somebody's gotta do it" | french | 34 |
| 27 | 1986 | "loving you's a dirty job but somebody's gotta do it" | uk | 73 |
| 28 | 1986 | "band of gold" | billboard hot dance breakouts singles sales | 6 |
| 29 | 1986 | "band of gold" | uk | 81 | | | | single |
|---:|:-------------------------|
| 0 | "holding out for a hero" | | [
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select count ( * ) where fate = 'sunk at 57°24′n 11°21′w / 57.400°n 11.350°w' col : date | name of ship | nationality | tonnage | fate row 1 : 1940-06-05 00:00:00 | ss stancor | united kingdom | 798 | sunk at 58°48′n 08°45′w / 58.800°n 8.750°w row 2 : 1940-06-07 00:00:00 | ss frances massey | united kingdom | 4212 | sunk at 55°33′n 08°26′w / 55.550°n 8.433°w row 3 : 1940-06-07 00:00:00 | ss eros | united kingdom | 5888 | damaged at 55°33′n 08°26′w / 55.550°n 8.433°w row 4 : 1940-06-11 00:00:00 | ss violando n goulandris | greece | 2375 | sunk at 44°04′n 12°30′w / 44.067°n 12.500°w row 5 : 1940-06-19 00:00:00 | mv tudor | norway | 6607 | sunk at 45°10′n 11°50′w / 45.167°n 11.833°w row 6 : 1940-06-19 00:00:00 | ss baron loudoun | united kingdom | 3164 | sunk at 45°00′n 11°21′w / 45.000°n 11.350°w row 7 : 1940-06-19 00:00:00 | ss british monarch | united kingdom | 5661 | sunk at 45°00′n 11°21′w / 45.000°n 11.350°w row 8 : 1940-06-20 00:00:00 | mv moerdrecht | netherlands | 7493 | sunk at 43°34′n 14°20′w / 43.567°n 14.333°w row 9 : 1940-08-16 00:00:00 | ss hedrun | sweden | 2325 | sunk at 57°10′n 16°37′w / 57.167°n 16.617°w row 10 : 1940-08-19 00:00:00 | ss ville de gand | belgium | 7590 | sunk at 55°28′n 15°10′w / 55.467°n 15.167°w row 11 : 1940-08-24 00:00:00 | ss la brea | united kingdom | 6666 | sunk at 57°24′n 11°21′w / 57.400°n 11.350°w row 12 : 1940-08-25 00:00:00 | ss empire merlin | united kingdom | 5763 | sunk at 58°30′n 10°15′w / 58.500°n 10.250°w row 13 : 1940-08-25 00:00:00 | mv athelcrest | united kingdom | 6825 | sunk at 58°24′n 11°25′w / 58.400°n 11.417°w | col : count ( "*" ) row 1 : 1 | select count ( * ) where fate = 'sunk at 57°24′n 11°21′w / 57.400°n 11.350°w' <table_name> : table \begin{tabular}{llllll}
\toprule
& date & name of ship & nationality & tonnage & fate \\
\midrule
0 & 1940-06-05 00:00:00 & ss stancor & united kingdom & 798 & sunk at 58°48′n 08°45′w / 58.800°n 8.750°w \\
1 & 1940-06-07 00:00:00 & ss frances massey & united kingdom & 4212 & sunk at 55°33′n 08°26′w / 55.550°n 8.433°w \\
2 & 1940-06-07 00:00:00 & ss eros & united kingdom & 5888 & damaged at 55°33′n 08°26′w / 55.550°n 8.433°w \\
3 & 1940-06-11 00:00:00 & ss violando n goulandris & greece & 2375 & sunk at 44°04′n 12°30′w / 44.067°n 12.500°w \\
4 & 1940-06-19 00:00:00 & mv tudor & norway & 6607 & sunk at 45°10′n 11°50′w / 45.167°n 11.833°w \\
5 & 1940-06-19 00:00:00 & ss baron loudoun & united kingdom & 3164 & sunk at 45°00′n 11°21′w / 45.000°n 11.350°w \\
6 & 1940-06-19 00:00:00 & ss british monarch & united kingdom & 5661 & sunk at 45°00′n 11°21′w / 45.000°n 11.350°w \\
7 & 1940-06-20 00:00:00 & mv moerdrecht & netherlands & 7493 & sunk at 43°34′n 14°20′w / 43.567°n 14.333°w \\
8 & 1940-08-16 00:00:00 & ss hedrun & sweden & 2325 & sunk at 57°10′n 16°37′w / 57.167°n 16.617°w \\
9 & 1940-08-19 00:00:00 & ss ville de gand & belgium & 7590 & sunk at 55°28′n 15°10′w / 55.467°n 15.167°w \\
10 & 1940-08-24 00:00:00 & ss la brea & united kingdom & 6666 & sunk at 57°24′n 11°21′w / 57.400°n 11.350°w \\
11 & 1940-08-25 00:00:00 & ss empire merlin & united kingdom & 5763 & sunk at 58°30′n 10°15′w / 58.500°n 10.250°w \\
12 & 1940-08-25 00:00:00 & mv athelcrest & united kingdom & 6825 & sunk at 58°24′n 11°25′w / 58.400°n 11.417°w \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where fate = 'sunk at 57°24′n 11°21′w / 57.400°n 11.350°w' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>name of ship</th>
<th>nationality</th>
<th>tonnage</th>
<th>fate</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1940-06-05 00:00:00</td>
<td>ss stancor</td>
<td>united kingdom</td>
<td>798</td>
<td>sunk at 58°48′n 08°45′w / 58.800°n 8.750°w</td>
</tr>
<tr>
<th>1</th>
<td>1940-06-07 00:00:00</td>
<td>ss frances massey</td>
<td>united kingdom</td>
<td>4212</td>
<td>sunk at 55°33′n 08°26′w / 55.550°n 8.433°w</td>
</tr>
<tr>
<th>2</th>
<td>1940-06-07 00:00:00</td>
<td>ss eros</td>
<td>united kingdom</td>
<td>5888</td>
<td>damaged at 55°33′n 08°26′w / 55.550°n 8.433°w</td>
</tr>
<tr>
<th>3</th>
<td>1940-06-11 00:00:00</td>
<td>ss violando n goulandris</td>
<td>greece</td>
<td>2375</td>
<td>sunk at 44°04′n 12°30′w / 44.067°n 12.500°w</td>
</tr>
<tr>
<th>4</th>
<td>1940-06-19 00:00:00</td>
<td>mv tudor</td>
<td>norway</td>
<td>6607</td>
<td>sunk at 45°10′n 11°50′w / 45.167°n 11.833°w</td>
</tr>
<tr>
<th>5</th>
<td>1940-06-19 00:00:00</td>
<td>ss baron loudoun</td>
<td>united kingdom</td>
<td>3164</td>
<td>sunk at 45°00′n 11°21′w / 45.000°n 11.350°w</td>
</tr>
<tr>
<th>6</th>
<td>1940-06-19 00:00:00</td>
<td>ss british monarch</td>
<td>united kingdom</td>
<td>5661</td>
<td>sunk at 45°00′n 11°21′w / 45.000°n 11.350°w</td>
</tr>
<tr>
<th>7</th>
<td>1940-06-20 00:00:00</td>
<td>mv moerdrecht</td>
<td>netherlands</td>
<td>7493</td>
<td>sunk at 43°34′n 14°20′w / 43.567°n 14.333°w</td>
</tr>
<tr>
<th>8</th>
<td>1940-08-16 00:00:00</td>
<td>ss hedrun</td>
<td>sweden</td>
<td>2325</td>
<td>sunk at 57°10′n 16°37′w / 57.167°n 16.617°w</td>
</tr>
<tr>
<th>9</th>
<td>1940-08-19 00:00:00</td>
<td>ss ville de gand</td>
<td>belgium</td>
<td>7590</td>
<td>sunk at 55°28′n 15°10′w / 55.467°n 15.167°w</td>
</tr>
<tr>
<th>10</th>
<td>1940-08-24 00:00:00</td>
<td>ss la brea</td>
<td>united kingdom</td>
<td>6666</td>
<td>sunk at 57°24′n 11°21′w / 57.400°n 11.350°w</td>
</tr>
<tr>
<th>11</th>
<td>1940-08-25 00:00:00</td>
<td>ss empire merlin</td>
<td>united kingdom</td>
<td>5763</td>
<td>sunk at 58°30′n 10°15′w / 58.500°n 10.250°w</td>
</tr>
<tr>
<th>12</th>
<td>1940-08-25 00:00:00</td>
<td>mv athelcrest</td>
<td>united kingdom</td>
<td>6825</td>
<td>sunk at 58°24′n 11°25′w / 58.400°n 11.417°w</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where fate = 'sunk at 57°24′n 11°21′w / 57.400°n 11.350°w' <table_name> : table | | date | name of ship | nationality | tonnage | fate |
|---:|:--------------------|:-------------------------|:---------------|----------:|:----------------------------------------------|
| 0 | 1940-06-05 00:00:00 | ss stancor | united kingdom | 798 | sunk at 58°48′n 08°45′w / 58.800°n 8.750°w |
| 1 | 1940-06-07 00:00:00 | ss frances massey | united kingdom | 4212 | sunk at 55°33′n 08°26′w / 55.550°n 8.433°w |
| 2 | 1940-06-07 00:00:00 | ss eros | united kingdom | 5888 | damaged at 55°33′n 08°26′w / 55.550°n 8.433°w |
| 3 | 1940-06-11 00:00:00 | ss violando n goulandris | greece | 2375 | sunk at 44°04′n 12°30′w / 44.067°n 12.500°w |
| 4 | 1940-06-19 00:00:00 | mv tudor | norway | 6607 | sunk at 45°10′n 11°50′w / 45.167°n 11.833°w |
| 5 | 1940-06-19 00:00:00 | ss baron loudoun | united kingdom | 3164 | sunk at 45°00′n 11°21′w / 45.000°n 11.350°w |
| 6 | 1940-06-19 00:00:00 | ss british monarch | united kingdom | 5661 | sunk at 45°00′n 11°21′w / 45.000°n 11.350°w |
| 7 | 1940-06-20 00:00:00 | mv moerdrecht | netherlands | 7493 | sunk at 43°34′n 14°20′w / 43.567°n 14.333°w |
| 8 | 1940-08-16 00:00:00 | ss hedrun | sweden | 2325 | sunk at 57°10′n 16°37′w / 57.167°n 16.617°w |
| 9 | 1940-08-19 00:00:00 | ss ville de gand | belgium | 7590 | sunk at 55°28′n 15°10′w / 55.467°n 15.167°w |
| 10 | 1940-08-24 00:00:00 | ss la brea | united kingdom | 6666 | sunk at 57°24′n 11°21′w / 57.400°n 11.350°w |
| 11 | 1940-08-25 00:00:00 | ss empire merlin | united kingdom | 5763 | sunk at 58°30′n 10°15′w / 58.500°n 10.250°w |
| 12 | 1940-08-25 00:00:00 | mv athelcrest | united kingdom | 6825 | sunk at 58°24′n 11°25′w / 58.400°n 11.417°w | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( co-driver ) where driver = 'jose camacho' col : pos. | driver | co-driver | car | time row 1 : 1 | giandomenico basso | lorenzo granai | peugeot 207 s2000 | 2h28m50.8s row 2 : 2 | bruno magalhaes | nuno r. silva | peugeot 207 s2000 | +07.3s row 3 : 3 | miguel nunes | joao paulo | mitsubishi lancer x r4 | + 3m30.8s row 4 : 4 | pedro meireles | mario castro | skoda fabia s2000 | +3m42.5s row 5 : 5 | luca betti | francesco pezzoli | ford fiesta s2000 | +4m04.1s row 6 : 6 | filipe freitas | daniel figueiroa | mitsubishi lancer x r4 | +5m36s row 7 : 7 | filipe pires | vasco rodrigues | mitsubishi lancer x | +9m11.2s row 8 : 8 | luis serrado | joao sousa | peugeot 206 s1600 | +10m53.7s row 9 : 9 | jose camacho | fernando spinola | peugeot 206 s1600 | +13m08.3s row 10 : 10 | rui conceicao | duarte coelho | ford escort cosworth | +16m50.1s | col : count ( "co-driver" ) row 1 : 1 | select count ( co-driver ) where driver = 'jose camacho' <table_name> : table \begin{tabular}{llllll}
\toprule
& pos. & driver & co-driver & car & time \\
\midrule
0 & 1 & giandomenico basso & lorenzo granai & peugeot 207 s2000 & 2h28m50.8s \\
1 & 2 & bruno magalhaes & nuno r. silva & peugeot 207 s2000 & +07.3s \\
2 & 3 & miguel nunes & joao paulo & mitsubishi lancer x r4 & + 3m30.8s \\
3 & 4 & pedro meireles & mario castro & skoda fabia s2000 & +3m42.5s \\
4 & 5 & luca betti & francesco pezzoli & ford fiesta s2000 & +4m04.1s \\
5 & 6 & filipe freitas & daniel figueiroa & mitsubishi lancer x r4 & +5m36s \\
6 & 7 & filipe pires & vasco rodrigues & mitsubishi lancer x & +9m11.2s \\
7 & 8 & luis serrado & joao sousa & peugeot 206 s1600 & +10m53.7s \\
8 & 9 & jose camacho & fernando spinola & peugeot 206 s1600 & +13m08.3s \\
9 & 10 & rui conceicao & duarte coelho & ford escort cosworth & +16m50.1s \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "co-driver" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( co-driver ) where driver = 'jose camacho' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos.</th>
<th>driver</th>
<th>co-driver</th>
<th>car</th>
<th>time</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>giandomenico basso</td>
<td>lorenzo granai</td>
<td>peugeot 207 s2000</td>
<td>2h28m50.8s</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>bruno magalhaes</td>
<td>nuno r. silva</td>
<td>peugeot 207 s2000</td>
<td>+07.3s</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>miguel nunes</td>
<td>joao paulo</td>
<td>mitsubishi lancer x r4</td>
<td>+ 3m30.8s</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>pedro meireles</td>
<td>mario castro</td>
<td>skoda fabia s2000</td>
<td>+3m42.5s</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>luca betti</td>
<td>francesco pezzoli</td>
<td>ford fiesta s2000</td>
<td>+4m04.1s</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>filipe freitas</td>
<td>daniel figueiroa</td>
<td>mitsubishi lancer x r4</td>
<td>+5m36s</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>filipe pires</td>
<td>vasco rodrigues</td>
<td>mitsubishi lancer x</td>
<td>+9m11.2s</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>luis serrado</td>
<td>joao sousa</td>
<td>peugeot 206 s1600</td>
<td>+10m53.7s</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>jose camacho</td>
<td>fernando spinola</td>
<td>peugeot 206 s1600</td>
<td>+13m08.3s</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>rui conceicao</td>
<td>duarte coelho</td>
<td>ford escort cosworth</td>
<td>+16m50.1s</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "co-driver" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( co-driver ) where driver = 'jose camacho' <table_name> : table | | pos. | driver | co-driver | car | time |
|---:|-------:|:-------------------|:------------------|:-----------------------|:-----------|
| 0 | 1 | giandomenico basso | lorenzo granai | peugeot 207 s2000 | 2h28m50.8s |
| 1 | 2 | bruno magalhaes | nuno r. silva | peugeot 207 s2000 | +07.3s |
| 2 | 3 | miguel nunes | joao paulo | mitsubishi lancer x r4 | + 3m30.8s |
| 3 | 4 | pedro meireles | mario castro | skoda fabia s2000 | +3m42.5s |
| 4 | 5 | luca betti | francesco pezzoli | ford fiesta s2000 | +4m04.1s |
| 5 | 6 | filipe freitas | daniel figueiroa | mitsubishi lancer x r4 | +5m36s |
| 6 | 7 | filipe pires | vasco rodrigues | mitsubishi lancer x | +9m11.2s |
| 7 | 8 | luis serrado | joao sousa | peugeot 206 s1600 | +10m53.7s |
| 8 | 9 | jose camacho | fernando spinola | peugeot 206 s1600 | +13m08.3s |
| 9 | 10 | rui conceicao | duarte coelho | ford escort cosworth | +16m50.1s | | | | count ( "co-driver" ) |
|---:|------------------------:|
| 0 | 1 | | [
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select count ( * ) where massif = 'svydovets' and region != '7' col : # | massif | region | type of nature reserve | preserved area | buffer zone row 1 : 1 | chornohora | zakarpattia | carpathian biosphere reserve | 2476.8 ha | 12925 ha row 2 : 2 | uholka / wide meadow | zakarpattia | carpathian biosphere reserve | 11860 ha | 3301 ha row 3 : 3 | svydovets | zakarpattia | carpathian biosphere reserve | 3030.5 ha | 5639.5 ha row 4 : 4 | maramoros | zakarpattia | carpathian biosphere reserve | 2243.6 ha | 6230.4 ha row 5 : 5 | kuziy / trybushany | zakarpattia | carpathian biosphere reserve | 1369.6 ha | 3163.4 ha row 6 : 6 | stuzhytsia / uzhok | zakarpattia | uzh national nature park | 2532 ha | 3615 ha row 7 : 7 | stuzica / bukovske vrchy | presov | poloniny national park | 2950 ha | 11300 ha row 8 : 8 | rozok | presov | presov preserved areas | 67.1 ha | 41.4 ha row 9 : 9 | vihorlat | presov | presov preserved areas | 2578 ha | 2413 ha row 10 : 10 | havesova | presov | presov preserved areas | 171.3 ha | 63.9 ha row 11 : 11 | jasmund | mecklenburg-vorpommern | jasmund national park | 492.5 ha | 2510.5 ha row 12 : 12 | serrahn | mecklenburg-vorpommern | muritz national park | 268.1 ha | 2568 ha row 13 : 13 | grumsiner forest | brandenburg | grumsiner forest nature reserve | 590.1 ha | 274.3 ha row 14 : 14 | hainich | thuringia | hainich national park | 1573.4 ha | 4085.4 ha row 15 : 15 | kellerwald | hesse | kellerwald-edersee national park | 1467.1 ha | 4271.4 ha | col : count ( "*" ) row 1 : 0 | select count ( * ) where massif = 'svydovets' and region != '7' <table_name> : table \begin{tabular}{lllllll}
\toprule
& # & massif & region & type of nature reserve & preserved area & buffer zone \\
\midrule
0 & 1 & chornohora & zakarpattia & carpathian biosphere reserve & 2476.8 ha & 12925 ha \\
1 & 2 & uholka / wide meadow & zakarpattia & carpathian biosphere reserve & 11860 ha & 3301 ha \\
2 & 3 & svydovets & zakarpattia & carpathian biosphere reserve & 3030.5 ha & 5639.5 ha \\
3 & 4 & maramoros & zakarpattia & carpathian biosphere reserve & 2243.6 ha & 6230.4 ha \\
4 & 5 & kuziy / trybushany & zakarpattia & carpathian biosphere reserve & 1369.6 ha & 3163.4 ha \\
5 & 6 & stuzhytsia / uzhok & zakarpattia & uzh national nature park & 2532 ha & 3615 ha \\
6 & 7 & stuzica / bukovske vrchy & presov & poloniny national park & 2950 ha & 11300 ha \\
7 & 8 & rozok & presov & presov preserved areas & 67.1 ha & 41.4 ha \\
8 & 9 & vihorlat & presov & presov preserved areas & 2578 ha & 2413 ha \\
9 & 10 & havesova & presov & presov preserved areas & 171.3 ha & 63.9 ha \\
10 & 11 & jasmund & mecklenburg-vorpommern & jasmund national park & 492.5 ha & 2510.5 ha \\
11 & 12 & serrahn & mecklenburg-vorpommern & muritz national park & 268.1 ha & 2568 ha \\
12 & 13 & grumsiner forest & brandenburg & grumsiner forest nature reserve & 590.1 ha & 274.3 ha \\
13 & 14 & hainich & thuringia & hainich national park & 1573.4 ha & 4085.4 ha \\
14 & 15 & kellerwald & hesse & kellerwald-edersee national park & 1467.1 ha & 4271.4 ha \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where massif = 'svydovets' and region != '7' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>massif</th>
<th>region</th>
<th>type of nature reserve</th>
<th>preserved area</th>
<th>buffer zone</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>chornohora</td>
<td>zakarpattia</td>
<td>carpathian biosphere reserve</td>
<td>2476.8 ha</td>
<td>12925 ha</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>uholka / wide meadow</td>
<td>zakarpattia</td>
<td>carpathian biosphere reserve</td>
<td>11860 ha</td>
<td>3301 ha</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>svydovets</td>
<td>zakarpattia</td>
<td>carpathian biosphere reserve</td>
<td>3030.5 ha</td>
<td>5639.5 ha</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>maramoros</td>
<td>zakarpattia</td>
<td>carpathian biosphere reserve</td>
<td>2243.6 ha</td>
<td>6230.4 ha</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>kuziy / trybushany</td>
<td>zakarpattia</td>
<td>carpathian biosphere reserve</td>
<td>1369.6 ha</td>
<td>3163.4 ha</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>stuzhytsia / uzhok</td>
<td>zakarpattia</td>
<td>uzh national nature park</td>
<td>2532 ha</td>
<td>3615 ha</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>stuzica / bukovske vrchy</td>
<td>presov</td>
<td>poloniny national park</td>
<td>2950 ha</td>
<td>11300 ha</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>rozok</td>
<td>presov</td>
<td>presov preserved areas</td>
<td>67.1 ha</td>
<td>41.4 ha</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>vihorlat</td>
<td>presov</td>
<td>presov preserved areas</td>
<td>2578 ha</td>
<td>2413 ha</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>havesova</td>
<td>presov</td>
<td>presov preserved areas</td>
<td>171.3 ha</td>
<td>63.9 ha</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>jasmund</td>
<td>mecklenburg-vorpommern</td>
<td>jasmund national park</td>
<td>492.5 ha</td>
<td>2510.5 ha</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>serrahn</td>
<td>mecklenburg-vorpommern</td>
<td>muritz national park</td>
<td>268.1 ha</td>
<td>2568 ha</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>grumsiner forest</td>
<td>brandenburg</td>
<td>grumsiner forest nature reserve</td>
<td>590.1 ha</td>
<td>274.3 ha</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>hainich</td>
<td>thuringia</td>
<td>hainich national park</td>
<td>1573.4 ha</td>
<td>4085.4 ha</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>kellerwald</td>
<td>hesse</td>
<td>kellerwald-edersee national park</td>
<td>1467.1 ha</td>
<td>4271.4 ha</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where massif = 'svydovets' and region != '7' <table_name> : table | | # | massif | region | type of nature reserve | preserved area | buffer zone |
|---:|----:|:-------------------------|:-----------------------|:---------------------------------|:-----------------|:--------------|
| 0 | 1 | chornohora | zakarpattia | carpathian biosphere reserve | 2476.8 ha | 12925 ha |
| 1 | 2 | uholka / wide meadow | zakarpattia | carpathian biosphere reserve | 11860 ha | 3301 ha |
| 2 | 3 | svydovets | zakarpattia | carpathian biosphere reserve | 3030.5 ha | 5639.5 ha |
| 3 | 4 | maramoros | zakarpattia | carpathian biosphere reserve | 2243.6 ha | 6230.4 ha |
| 4 | 5 | kuziy / trybushany | zakarpattia | carpathian biosphere reserve | 1369.6 ha | 3163.4 ha |
| 5 | 6 | stuzhytsia / uzhok | zakarpattia | uzh national nature park | 2532 ha | 3615 ha |
| 6 | 7 | stuzica / bukovske vrchy | presov | poloniny national park | 2950 ha | 11300 ha |
| 7 | 8 | rozok | presov | presov preserved areas | 67.1 ha | 41.4 ha |
| 8 | 9 | vihorlat | presov | presov preserved areas | 2578 ha | 2413 ha |
| 9 | 10 | havesova | presov | presov preserved areas | 171.3 ha | 63.9 ha |
| 10 | 11 | jasmund | mecklenburg-vorpommern | jasmund national park | 492.5 ha | 2510.5 ha |
| 11 | 12 | serrahn | mecklenburg-vorpommern | muritz national park | 268.1 ha | 2568 ha |
| 12 | 13 | grumsiner forest | brandenburg | grumsiner forest nature reserve | 590.1 ha | 274.3 ha |
| 13 | 14 | hainich | thuringia | hainich national park | 1573.4 ha | 4085.4 ha |
| 14 | 15 | kellerwald | hesse | kellerwald-edersee national park | 1467.1 ha | 4271.4 ha | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select attendance where score = 'l 9-10' col : game | date | opponent | location | score | ot | attendance | record row 1 : 1 | 2006-01-06 00:00:00 | philadelphia wings | xcel energy center | l 11-15 | none | 8024 | 0-1 row 2 : 2 | 2006-01-14 00:00:00 | @ philadelphia wings | wachovia center | w 13-10 | none | 11874 | 1-1 row 3 : 3 | 2006-01-20 00:00:00 | @ calgary roughnecks | pengrowth saddledome | w 12-8 | none | 10637 | 2-1 row 4 : 4 | 2006-01-21 00:00:00 | rochester knighthawks | xcel energy center | l 6-12 | none | 7124 | 2-2 row 5 : 5 | 2006-01-29 00:00:00 | rochester knighthawks | xcel energy center | l 9-10 | none | 7544 | 3-2 row 6 : 6 | 2006-02-03 00:00:00 | @ edmonton rush | rexall place | w 7-6 | none | 8745 | 3-3 row 7 : 7 | 2006-02-10 00:00:00 | philadelphia wings | xcel energy center | w 11-10 | none | 7524 | 4-3 row 8 : 8 | 2006-02-18 00:00:00 | @ buffalo bandits | hsbc arena | l 9-14 | none | 12458 | 4-4 row 9 : 9 | 2006-03-03 00:00:00 | @ toronto rock | air canada centre | l 8-13 | none | 15830 | 4-5 row 10 : 10 | 2006-03-04 00:00:00 | @ buffalo bandits | hsbc arena | w 11-8 | none | 10961 | 5-5 row 11 : 11 | 2006-03-17 00:00:00 | @ portland lumberjax | rose garden | w 14-12 | none | 5487 | 6-5 row 12 : 12 | 2006-03-24 00:00:00 | buffalo bandits | xcel energy center | l 11-13 | none | 9533 | 6-6 row 13 : 13 | 2006-04-01 00:00:00 | toronto rock | xcel energy center | w 10-9 | none | 10084 | 7-6 row 14 : 14 | 2006-04-08 00:00:00 | @ rochester knighthawks | blue cross arena | l 9-10 | none | 10352 | 7-7 row 15 : 15 | 2006-04-09 00:00:00 | san jose stealth | xcel energy center | w 9-8 | ot | 7044 | 8-7 row 16 : 16 | 2006-04-15 00:00:00 | portland lumberjax | xcel energy center | l 8-13 | none | 10104 | 8-8 | col : attendance row 1 : 7544 row 2 : 10352 | select attendance where score = 'l 9-10' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& game & date & opponent & location & score & ot & attendance & record \\
\midrule
0 & 1 & 2006-01-06 00:00:00 & philadelphia wings & xcel energy center & l 11-15 & none & 8024 & 0-1 \\
1 & 2 & 2006-01-14 00:00:00 & @ philadelphia wings & wachovia center & w 13-10 & none & 11874 & 1-1 \\
2 & 3 & 2006-01-20 00:00:00 & @ calgary roughnecks & pengrowth saddledome & w 12-8 & none & 10637 & 2-1 \\
3 & 4 & 2006-01-21 00:00:00 & rochester knighthawks & xcel energy center & l 6-12 & none & 7124 & 2-2 \\
4 & 5 & 2006-01-29 00:00:00 & rochester knighthawks & xcel energy center & l 9-10 & none & 7544 & 3-2 \\
5 & 6 & 2006-02-03 00:00:00 & @ edmonton rush & rexall place & w 7-6 & none & 8745 & 3-3 \\
6 & 7 & 2006-02-10 00:00:00 & philadelphia wings & xcel energy center & w 11-10 & none & 7524 & 4-3 \\
7 & 8 & 2006-02-18 00:00:00 & @ buffalo bandits & hsbc arena & l 9-14 & none & 12458 & 4-4 \\
8 & 9 & 2006-03-03 00:00:00 & @ toronto rock & air canada centre & l 8-13 & none & 15830 & 4-5 \\
9 & 10 & 2006-03-04 00:00:00 & @ buffalo bandits & hsbc arena & w 11-8 & none & 10961 & 5-5 \\
10 & 11 & 2006-03-17 00:00:00 & @ portland lumberjax & rose garden & w 14-12 & none & 5487 & 6-5 \\
11 & 12 & 2006-03-24 00:00:00 & buffalo bandits & xcel energy center & l 11-13 & none & 9533 & 6-6 \\
12 & 13 & 2006-04-01 00:00:00 & toronto rock & xcel energy center & w 10-9 & none & 10084 & 7-6 \\
13 & 14 & 2006-04-08 00:00:00 & @ rochester knighthawks & blue cross arena & l 9-10 & none & 10352 & 7-7 \\
14 & 15 & 2006-04-09 00:00:00 & san jose stealth & xcel energy center & w 9-8 & ot & 7044 & 8-7 \\
15 & 16 & 2006-04-15 00:00:00 & portland lumberjax & xcel energy center & l 8-13 & none & 10104 & 8-8 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& attendance \\
\midrule
0 & 7544 \\
1 & 10352 \\
\bottomrule
\end{tabular}
| select attendance where score = 'l 9-10' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>date</th>
<th>opponent</th>
<th>location</th>
<th>score</th>
<th>ot</th>
<th>attendance</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>2006-01-06 00:00:00</td>
<td>philadelphia wings</td>
<td>xcel energy center</td>
<td>l 11-15</td>
<td>none</td>
<td>8024</td>
<td>0-1</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2006-01-14 00:00:00</td>
<td>@ philadelphia wings</td>
<td>wachovia center</td>
<td>w 13-10</td>
<td>none</td>
<td>11874</td>
<td>1-1</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>2006-01-20 00:00:00</td>
<td>@ calgary roughnecks</td>
<td>pengrowth saddledome</td>
<td>w 12-8</td>
<td>none</td>
<td>10637</td>
<td>2-1</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>2006-01-21 00:00:00</td>
<td>rochester knighthawks</td>
<td>xcel energy center</td>
<td>l 6-12</td>
<td>none</td>
<td>7124</td>
<td>2-2</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>2006-01-29 00:00:00</td>
<td>rochester knighthawks</td>
<td>xcel energy center</td>
<td>l 9-10</td>
<td>none</td>
<td>7544</td>
<td>3-2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>2006-02-03 00:00:00</td>
<td>@ edmonton rush</td>
<td>rexall place</td>
<td>w 7-6</td>
<td>none</td>
<td>8745</td>
<td>3-3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>2006-02-10 00:00:00</td>
<td>philadelphia wings</td>
<td>xcel energy center</td>
<td>w 11-10</td>
<td>none</td>
<td>7524</td>
<td>4-3</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>2006-02-18 00:00:00</td>
<td>@ buffalo bandits</td>
<td>hsbc arena</td>
<td>l 9-14</td>
<td>none</td>
<td>12458</td>
<td>4-4</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>2006-03-03 00:00:00</td>
<td>@ toronto rock</td>
<td>air canada centre</td>
<td>l 8-13</td>
<td>none</td>
<td>15830</td>
<td>4-5</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>2006-03-04 00:00:00</td>
<td>@ buffalo bandits</td>
<td>hsbc arena</td>
<td>w 11-8</td>
<td>none</td>
<td>10961</td>
<td>5-5</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>2006-03-17 00:00:00</td>
<td>@ portland lumberjax</td>
<td>rose garden</td>
<td>w 14-12</td>
<td>none</td>
<td>5487</td>
<td>6-5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>2006-03-24 00:00:00</td>
<td>buffalo bandits</td>
<td>xcel energy center</td>
<td>l 11-13</td>
<td>none</td>
<td>9533</td>
<td>6-6</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>2006-04-01 00:00:00</td>
<td>toronto rock</td>
<td>xcel energy center</td>
<td>w 10-9</td>
<td>none</td>
<td>10084</td>
<td>7-6</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>2006-04-08 00:00:00</td>
<td>@ rochester knighthawks</td>
<td>blue cross arena</td>
<td>l 9-10</td>
<td>none</td>
<td>10352</td>
<td>7-7</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>2006-04-09 00:00:00</td>
<td>san jose stealth</td>
<td>xcel energy center</td>
<td>w 9-8</td>
<td>ot</td>
<td>7044</td>
<td>8-7</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>2006-04-15 00:00:00</td>
<td>portland lumberjax</td>
<td>xcel energy center</td>
<td>l 8-13</td>
<td>none</td>
<td>10104</td>
<td>8-8</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7544</td>
</tr>
<tr>
<th>1</th>
<td>10352</td>
</tr>
</tbody>
</table> | select attendance where score = 'l 9-10' <table_name> : table | | game | date | opponent | location | score | ot | attendance | record |
|---:|-------:|:--------------------|:------------------------|:---------------------|:--------|:-----|-------------:|:---------|
| 0 | 1 | 2006-01-06 00:00:00 | philadelphia wings | xcel energy center | l 11-15 | none | 8024 | 0-1 |
| 1 | 2 | 2006-01-14 00:00:00 | @ philadelphia wings | wachovia center | w 13-10 | none | 11874 | 1-1 |
| 2 | 3 | 2006-01-20 00:00:00 | @ calgary roughnecks | pengrowth saddledome | w 12-8 | none | 10637 | 2-1 |
| 3 | 4 | 2006-01-21 00:00:00 | rochester knighthawks | xcel energy center | l 6-12 | none | 7124 | 2-2 |
| 4 | 5 | 2006-01-29 00:00:00 | rochester knighthawks | xcel energy center | l 9-10 | none | 7544 | 3-2 |
| 5 | 6 | 2006-02-03 00:00:00 | @ edmonton rush | rexall place | w 7-6 | none | 8745 | 3-3 |
| 6 | 7 | 2006-02-10 00:00:00 | philadelphia wings | xcel energy center | w 11-10 | none | 7524 | 4-3 |
| 7 | 8 | 2006-02-18 00:00:00 | @ buffalo bandits | hsbc arena | l 9-14 | none | 12458 | 4-4 |
| 8 | 9 | 2006-03-03 00:00:00 | @ toronto rock | air canada centre | l 8-13 | none | 15830 | 4-5 |
| 9 | 10 | 2006-03-04 00:00:00 | @ buffalo bandits | hsbc arena | w 11-8 | none | 10961 | 5-5 |
| 10 | 11 | 2006-03-17 00:00:00 | @ portland lumberjax | rose garden | w 14-12 | none | 5487 | 6-5 |
| 11 | 12 | 2006-03-24 00:00:00 | buffalo bandits | xcel energy center | l 11-13 | none | 9533 | 6-6 |
| 12 | 13 | 2006-04-01 00:00:00 | toronto rock | xcel energy center | w 10-9 | none | 10084 | 7-6 |
| 13 | 14 | 2006-04-08 00:00:00 | @ rochester knighthawks | blue cross arena | l 9-10 | none | 10352 | 7-7 |
| 14 | 15 | 2006-04-09 00:00:00 | san jose stealth | xcel energy center | w 9-8 | ot | 7044 | 8-7 |
| 15 | 16 | 2006-04-15 00:00:00 | portland lumberjax | xcel energy center | l 8-13 | none | 10104 | 8-8 | | | | attendance |
|---:|-------------:|
| 0 | 7544 |
| 1 | 10352 | | [
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select count ( silver ) where silver = 15 col : rank | nation | gold | silver | bronze | total row 1 : 1 | netherlands | 20 | 9 | 0 | 29 row 2 : 2 | italy | 10 | 15 | 3 | 28 row 3 : 3 | belgium | 1 | 2 | 6 | 9 row 4 : 4 | spain | 1 | 1 | 13 | 15 row 5 : 5 | great britain | 0 | 2 | 0 | 2 row 6 : 6 | germany | 0 | 1 | 7 | 8 row 7 : 7 | greece | 0 | 1 | 0 | 1 row 8 : 7 | russia | 0 | 1 | 0 | 1 row 9 : 9 | sweden | 0 | 0 | 2 | 2 row 10 : 10 | france | 0 | 0 | 1 | 1 | col : count ( "silver" ) row 1 : 1 | select count ( silver ) where silver = 15 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & netherlands & 20 & 9 & 0 & 29 \\
1 & 2 & italy & 10 & 15 & 3 & 28 \\
2 & 3 & belgium & 1 & 2 & 6 & 9 \\
3 & 4 & spain & 1 & 1 & 13 & 15 \\
4 & 5 & great britain & 0 & 2 & 0 & 2 \\
5 & 6 & germany & 0 & 1 & 7 & 8 \\
6 & 7 & greece & 0 & 1 & 0 & 1 \\
7 & 7 & russia & 0 & 1 & 0 & 1 \\
8 & 9 & sweden & 0 & 0 & 2 & 2 \\
9 & 10 & france & 0 & 0 & 1 & 1 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "silver" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( silver ) where silver = 15 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>netherlands</td>
<td>20</td>
<td>9</td>
<td>0</td>
<td>29</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>italy</td>
<td>10</td>
<td>15</td>
<td>3</td>
<td>28</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>belgium</td>
<td>1</td>
<td>2</td>
<td>6</td>
<td>9</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>spain</td>
<td>1</td>
<td>1</td>
<td>13</td>
<td>15</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>great britain</td>
<td>0</td>
<td>2</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>germany</td>
<td>0</td>
<td>1</td>
<td>7</td>
<td>8</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>greece</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>russia</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>sweden</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>france</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "silver" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( silver ) where silver = 15 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|-------:|:--------------|-------:|---------:|---------:|--------:|
| 0 | 1 | netherlands | 20 | 9 | 0 | 29 |
| 1 | 2 | italy | 10 | 15 | 3 | 28 |
| 2 | 3 | belgium | 1 | 2 | 6 | 9 |
| 3 | 4 | spain | 1 | 1 | 13 | 15 |
| 4 | 5 | great britain | 0 | 2 | 0 | 2 |
| 5 | 6 | germany | 0 | 1 | 7 | 8 |
| 6 | 7 | greece | 0 | 1 | 0 | 1 |
| 7 | 7 | russia | 0 | 1 | 0 | 1 |
| 8 | 9 | sweden | 0 | 0 | 2 | 2 |
| 9 | 10 | france | 0 | 0 | 1 | 1 | | | | count ( "silver" ) |
|---:|---------------------:|
| 0 | 1 | | [
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select count ( notes ) where name = 578 col : rank | name | nationality | time | notes row 1 : 1 | janelle atkinson | jamaica | 4:16.89 | q row 2 : 2 | none | none | none | q row 3 : 3 | kaitlin sandeno | united states | 4:18.97 | q row 4 : 4 | julia stowers | united states | 4:19.84 | q row 5 : 5 | none | none | none | q row 6 : 6 | none | none | none | q row 7 : 7 | none | none | none | q row 8 : 8 | none | none | none | q | col : count ( "notes" ) row 1 : 0 | select count ( notes ) where name = 578 <table_name> : table \begin{tabular}{llllll}
\toprule
& rank & name & nationality & time & notes \\
\midrule
0 & 1 & janelle atkinson & jamaica & 4:16.89 & q \\
1 & 2 & none & none & none & q \\
2 & 3 & kaitlin sandeno & united states & 4:18.97 & q \\
3 & 4 & julia stowers & united states & 4:19.84 & q \\
4 & 5 & none & none & none & q \\
5 & 6 & none & none & none & q \\
6 & 7 & none & none & none & q \\
7 & 8 & none & none & none & q \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "notes" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( notes ) where name = 578 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>name</th>
<th>nationality</th>
<th>time</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>janelle atkinson</td>
<td>jamaica</td>
<td>4:16.89</td>
<td>q</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>q</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>kaitlin sandeno</td>
<td>united states</td>
<td>4:18.97</td>
<td>q</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>julia stowers</td>
<td>united states</td>
<td>4:19.84</td>
<td>q</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>q</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>q</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>q</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>q</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "notes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( notes ) where name = 578 <table_name> : table | | rank | name | nationality | time | notes |
|---:|-------:|:-----------------|:--------------|:--------|:--------|
| 0 | 1 | janelle atkinson | jamaica | 4:16.89 | q |
| 1 | 2 | none | none | none | q |
| 2 | 3 | kaitlin sandeno | united states | 4:18.97 | q |
| 3 | 4 | julia stowers | united states | 4:19.84 | q |
| 4 | 5 | none | none | none | q |
| 5 | 6 | none | none | none | q |
| 6 | 7 | none | none | none | q |
| 7 | 8 | none | none | none | q | | | | count ( "notes" ) |
|---:|--------------------:|
| 0 | 0 | | [
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select year where finish = '1st' col : year | record | finish | manager | playoffs row 1 : 1961 | 68-86 | 6th | tommy heath / bill werle | none row 2 : 1962 | 77-76 | 5th | irv noren | none row 3 : 1963 | 81-77 | 4th | irv noren | none row 4 : 1964 | 60-98 | 10th | bob lemon | none row 5 : 1965 | 75-72 | 6th (t) | george case | none row 6 : 1966 | 63-84 | 10th | george case | none row 7 : 1967 | 60-87 | 12th | wayne terwilliger | none row 8 : 1968 | 78-69 | 3rd | bill adair | none row 9 : 1969 | 74-72 | 4th | chuck tanner | none row 10 : 1970 | 98-48 | 1st | chuck tanner | lost league finals row 11 : 1971 | 73-73 | 4th (t) | bill adair | none row 12 : 1972 | 74-74 | 5th | rocky bridges | none row 13 : 1973 | 70-74 | 5th | rocky bridges / warren hacker / roy hartsfield | none row 14 : 1974 | 67-77 | 6th | roy hartsfield | none row 15 : 1975 | 88-56 | 1st | roy hartsfield | league champs row 16 : 1976 | 77-68 | 2nd | roy hartsfield | league champs row 17 : 1977 | 79-67 | 2nd | dick phillips | lost league finals row 18 : 1978 | 56-82 | 8th | dick phillips | none row 19 : 1979 | 72-76 | 8th | dick phillips | lost league finals row 20 : 1980 | 76-65 | 5th | doug rader | lost league finals row 21 : 1981 | 72-65 | 3rd (t) | doug rader | lost in 1st round row 22 : 1982 | 73-71 | 5th | doug rader | none row 23 : 1983 | 72-71 | 5th | tom trebelhorn | none row 24 : 1984 | 87-53 | 1st | tommy sandt | lost league finals row 25 : 1985 | 84-59 | 1st | tommy sandt | lost in 1st round row 26 : 1986 | 65-79 | 9th | tommy sandt | none row 27 : 1987 | 65-75 | 9th | bob bailey | none | col : year row 1 : 1970 row 2 : 1975 row 3 : 1984 row 4 : 1985 | select year where finish = '1st' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & record & finish & manager & playoffs \\
\midrule
0 & 1961 & 68-86 & 6th & tommy heath / bill werle & none \\
1 & 1962 & 77-76 & 5th & irv noren & none \\
2 & 1963 & 81-77 & 4th & irv noren & none \\
3 & 1964 & 60-98 & 10th & bob lemon & none \\
4 & 1965 & 75-72 & 6th (t) & george case & none \\
5 & 1966 & 63-84 & 10th & george case & none \\
6 & 1967 & 60-87 & 12th & wayne terwilliger & none \\
7 & 1968 & 78-69 & 3rd & bill adair & none \\
8 & 1969 & 74-72 & 4th & chuck tanner & none \\
9 & 1970 & 98-48 & 1st & chuck tanner & lost league finals \\
10 & 1971 & 73-73 & 4th (t) & bill adair & none \\
11 & 1972 & 74-74 & 5th & rocky bridges & none \\
12 & 1973 & 70-74 & 5th & rocky bridges / warren hacker / roy hartsfield & none \\
13 & 1974 & 67-77 & 6th & roy hartsfield & none \\
14 & 1975 & 88-56 & 1st & roy hartsfield & league champs \\
15 & 1976 & 77-68 & 2nd & roy hartsfield & league champs \\
16 & 1977 & 79-67 & 2nd & dick phillips & lost league finals \\
17 & 1978 & 56-82 & 8th & dick phillips & none \\
18 & 1979 & 72-76 & 8th & dick phillips & lost league finals \\
19 & 1980 & 76-65 & 5th & doug rader & lost league finals \\
20 & 1981 & 72-65 & 3rd (t) & doug rader & lost in 1st round \\
21 & 1982 & 73-71 & 5th & doug rader & none \\
22 & 1983 & 72-71 & 5th & tom trebelhorn & none \\
23 & 1984 & 87-53 & 1st & tommy sandt & lost league finals \\
24 & 1985 & 84-59 & 1st & tommy sandt & lost in 1st round \\
25 & 1986 & 65-79 & 9th & tommy sandt & none \\
26 & 1987 & 65-75 & 9th & bob bailey & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1970 \\
1 & 1975 \\
2 & 1984 \\
3 & 1985 \\
\bottomrule
\end{tabular}
| select year where finish = '1st' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>record</th>
<th>finish</th>
<th>manager</th>
<th>playoffs</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1961</td>
<td>68-86</td>
<td>6th</td>
<td>tommy heath / bill werle</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1962</td>
<td>77-76</td>
<td>5th</td>
<td>irv noren</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1963</td>
<td>81-77</td>
<td>4th</td>
<td>irv noren</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1964</td>
<td>60-98</td>
<td>10th</td>
<td>bob lemon</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1965</td>
<td>75-72</td>
<td>6th (t)</td>
<td>george case</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1966</td>
<td>63-84</td>
<td>10th</td>
<td>george case</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1967</td>
<td>60-87</td>
<td>12th</td>
<td>wayne terwilliger</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>1968</td>
<td>78-69</td>
<td>3rd</td>
<td>bill adair</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1969</td>
<td>74-72</td>
<td>4th</td>
<td>chuck tanner</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1970</td>
<td>98-48</td>
<td>1st</td>
<td>chuck tanner</td>
<td>lost league finals</td>
</tr>
<tr>
<th>10</th>
<td>1971</td>
<td>73-73</td>
<td>4th (t)</td>
<td>bill adair</td>
<td>none</td>
</tr>
<tr>
<th>11</th>
<td>1972</td>
<td>74-74</td>
<td>5th</td>
<td>rocky bridges</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>1973</td>
<td>70-74</td>
<td>5th</td>
<td>rocky bridges / warren hacker / roy hartsfield</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>1974</td>
<td>67-77</td>
<td>6th</td>
<td>roy hartsfield</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>1975</td>
<td>88-56</td>
<td>1st</td>
<td>roy hartsfield</td>
<td>league champs</td>
</tr>
<tr>
<th>15</th>
<td>1976</td>
<td>77-68</td>
<td>2nd</td>
<td>roy hartsfield</td>
<td>league champs</td>
</tr>
<tr>
<th>16</th>
<td>1977</td>
<td>79-67</td>
<td>2nd</td>
<td>dick phillips</td>
<td>lost league finals</td>
</tr>
<tr>
<th>17</th>
<td>1978</td>
<td>56-82</td>
<td>8th</td>
<td>dick phillips</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>1979</td>
<td>72-76</td>
<td>8th</td>
<td>dick phillips</td>
<td>lost league finals</td>
</tr>
<tr>
<th>19</th>
<td>1980</td>
<td>76-65</td>
<td>5th</td>
<td>doug rader</td>
<td>lost league finals</td>
</tr>
<tr>
<th>20</th>
<td>1981</td>
<td>72-65</td>
<td>3rd (t)</td>
<td>doug rader</td>
<td>lost in 1st round</td>
</tr>
<tr>
<th>21</th>
<td>1982</td>
<td>73-71</td>
<td>5th</td>
<td>doug rader</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>1983</td>
<td>72-71</td>
<td>5th</td>
<td>tom trebelhorn</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>1984</td>
<td>87-53</td>
<td>1st</td>
<td>tommy sandt</td>
<td>lost league finals</td>
</tr>
<tr>
<th>24</th>
<td>1985</td>
<td>84-59</td>
<td>1st</td>
<td>tommy sandt</td>
<td>lost in 1st round</td>
</tr>
<tr>
<th>25</th>
<td>1986</td>
<td>65-79</td>
<td>9th</td>
<td>tommy sandt</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>1987</td>
<td>65-75</td>
<td>9th</td>
<td>bob bailey</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1970</td>
</tr>
<tr>
<th>1</th>
<td>1975</td>
</tr>
<tr>
<th>2</th>
<td>1984</td>
</tr>
<tr>
<th>3</th>
<td>1985</td>
</tr>
</tbody>
</table> | select year where finish = '1st' <table_name> : table | | year | record | finish | manager | playoffs |
|---:|-------:|:---------|:---------|:-----------------------------------------------|:-------------------|
| 0 | 1961 | 68-86 | 6th | tommy heath / bill werle | none |
| 1 | 1962 | 77-76 | 5th | irv noren | none |
| 2 | 1963 | 81-77 | 4th | irv noren | none |
| 3 | 1964 | 60-98 | 10th | bob lemon | none |
| 4 | 1965 | 75-72 | 6th (t) | george case | none |
| 5 | 1966 | 63-84 | 10th | george case | none |
| 6 | 1967 | 60-87 | 12th | wayne terwilliger | none |
| 7 | 1968 | 78-69 | 3rd | bill adair | none |
| 8 | 1969 | 74-72 | 4th | chuck tanner | none |
| 9 | 1970 | 98-48 | 1st | chuck tanner | lost league finals |
| 10 | 1971 | 73-73 | 4th (t) | bill adair | none |
| 11 | 1972 | 74-74 | 5th | rocky bridges | none |
| 12 | 1973 | 70-74 | 5th | rocky bridges / warren hacker / roy hartsfield | none |
| 13 | 1974 | 67-77 | 6th | roy hartsfield | none |
| 14 | 1975 | 88-56 | 1st | roy hartsfield | league champs |
| 15 | 1976 | 77-68 | 2nd | roy hartsfield | league champs |
| 16 | 1977 | 79-67 | 2nd | dick phillips | lost league finals |
| 17 | 1978 | 56-82 | 8th | dick phillips | none |
| 18 | 1979 | 72-76 | 8th | dick phillips | lost league finals |
| 19 | 1980 | 76-65 | 5th | doug rader | lost league finals |
| 20 | 1981 | 72-65 | 3rd (t) | doug rader | lost in 1st round |
| 21 | 1982 | 73-71 | 5th | doug rader | none |
| 22 | 1983 | 72-71 | 5th | tom trebelhorn | none |
| 23 | 1984 | 87-53 | 1st | tommy sandt | lost league finals |
| 24 | 1985 | 84-59 | 1st | tommy sandt | lost in 1st round |
| 25 | 1986 | 65-79 | 9th | tommy sandt | none |
| 26 | 1987 | 65-75 | 9th | bob bailey | none | | | | year |
|---:|-------:|
| 0 | 1970 |
| 1 | 1975 |
| 2 | 1984 |
| 3 | 1985 | | [
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select division where division = '2ab' col : season | tier | division | place row 1 : 1988/89 | 4 | 3a | 3rd row 2 : 1989/90 | 4 | 3a | 1st row 3 : 1990/91 | 3 | 2ab | 6th row 4 : 1991/92 | 3 | 2ab | 12th row 5 : 1992/93 | 3 | 2ab | 4th row 6 : 1993/94 | 3 | 2ab | 15th row 7 : 1994/95 | 3 | 2ab | 9th row 8 : 1995/96 | 3 | 2ab | 19th row 9 : 1996/97 | 4 | 3a | 2nd row 10 : 1997/98 | 4 | 3a | 1st row 11 : 1998/99 | 4 | 3a | 6th | col : division row 1 : 2ab row 2 : 2ab row 3 : 2ab row 4 : 2ab row 5 : 2ab row 6 : 2ab | select division where division = '2ab' <table_name> : table \begin{tabular}{lllll}
\toprule
& season & tier & division & place \\
\midrule
0 & 1988/89 & 4 & 3a & 3rd \\
1 & 1989/90 & 4 & 3a & 1st \\
2 & 1990/91 & 3 & 2ab & 6th \\
3 & 1991/92 & 3 & 2ab & 12th \\
4 & 1992/93 & 3 & 2ab & 4th \\
5 & 1993/94 & 3 & 2ab & 15th \\
6 & 1994/95 & 3 & 2ab & 9th \\
7 & 1995/96 & 3 & 2ab & 19th \\
8 & 1996/97 & 4 & 3a & 2nd \\
9 & 1997/98 & 4 & 3a & 1st \\
10 & 1998/99 & 4 & 3a & 6th \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& division \\
\midrule
0 & 2ab \\
1 & 2ab \\
2 & 2ab \\
3 & 2ab \\
4 & 2ab \\
5 & 2ab \\
\bottomrule
\end{tabular}
| select division where division = '2ab' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>tier</th>
<th>division</th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1988/89</td>
<td>4</td>
<td>3a</td>
<td>3rd</td>
</tr>
<tr>
<th>1</th>
<td>1989/90</td>
<td>4</td>
<td>3a</td>
<td>1st</td>
</tr>
<tr>
<th>2</th>
<td>1990/91</td>
<td>3</td>
<td>2ab</td>
<td>6th</td>
</tr>
<tr>
<th>3</th>
<td>1991/92</td>
<td>3</td>
<td>2ab</td>
<td>12th</td>
</tr>
<tr>
<th>4</th>
<td>1992/93</td>
<td>3</td>
<td>2ab</td>
<td>4th</td>
</tr>
<tr>
<th>5</th>
<td>1993/94</td>
<td>3</td>
<td>2ab</td>
<td>15th</td>
</tr>
<tr>
<th>6</th>
<td>1994/95</td>
<td>3</td>
<td>2ab</td>
<td>9th</td>
</tr>
<tr>
<th>7</th>
<td>1995/96</td>
<td>3</td>
<td>2ab</td>
<td>19th</td>
</tr>
<tr>
<th>8</th>
<td>1996/97</td>
<td>4</td>
<td>3a</td>
<td>2nd</td>
</tr>
<tr>
<th>9</th>
<td>1997/98</td>
<td>4</td>
<td>3a</td>
<td>1st</td>
</tr>
<tr>
<th>10</th>
<td>1998/99</td>
<td>4</td>
<td>3a</td>
<td>6th</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>division</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2ab</td>
</tr>
<tr>
<th>1</th>
<td>2ab</td>
</tr>
<tr>
<th>2</th>
<td>2ab</td>
</tr>
<tr>
<th>3</th>
<td>2ab</td>
</tr>
<tr>
<th>4</th>
<td>2ab</td>
</tr>
<tr>
<th>5</th>
<td>2ab</td>
</tr>
</tbody>
</table> | select division where division = '2ab' <table_name> : table | | season | tier | division | place |
|---:|:---------|-------:|:-----------|:--------|
| 0 | 1988/89 | 4 | 3a | 3rd |
| 1 | 1989/90 | 4 | 3a | 1st |
| 2 | 1990/91 | 3 | 2ab | 6th |
| 3 | 1991/92 | 3 | 2ab | 12th |
| 4 | 1992/93 | 3 | 2ab | 4th |
| 5 | 1993/94 | 3 | 2ab | 15th |
| 6 | 1994/95 | 3 | 2ab | 9th |
| 7 | 1995/96 | 3 | 2ab | 19th |
| 8 | 1996/97 | 4 | 3a | 2nd |
| 9 | 1997/98 | 4 | 3a | 1st |
| 10 | 1998/99 | 4 | 3a | 6th | | | | division |
|---:|:-----------|
| 0 | 2ab |
| 1 | 2ab |
| 2 | 2ab |
| 3 | 2ab |
| 4 | 2ab |
| 5 | 2ab | | [
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select district where representative = 'jose menendez' col : representative | party | home town/city | district row 1 : trey martinez fischer | d | san antonio | 116 row 2 : philip cortez | d | san antonio | 117 row 3 : joe farias | d | san antonio | 118 row 4 : roland gutierrez | d | san antonio | 119 row 5 : ruth mcclendon | d | san antonio | 120 row 6 : joe straus | r | san antonio | 121 row 7 : lyle larson | r | san antonio | 122 row 8 : mike villarreal | d | san antonio | 123 row 9 : jose menendez | d | san antonio | 124 row 10 : justin rodriguez | d | san antonio | 125 | col : district row 1 : 124 | select district where representative = 'jose menendez' <table_name> : table \begin{tabular}{lllll}
\toprule
& representative & party & home town/city & district \\
\midrule
0 & trey martinez fischer & d & san antonio & 116 \\
1 & philip cortez & d & san antonio & 117 \\
2 & joe farias & d & san antonio & 118 \\
3 & roland gutierrez & d & san antonio & 119 \\
4 & ruth mcclendon & d & san antonio & 120 \\
5 & joe straus & r & san antonio & 121 \\
6 & lyle larson & r & san antonio & 122 \\
7 & mike villarreal & d & san antonio & 123 \\
8 & jose menendez & d & san antonio & 124 \\
9 & justin rodriguez & d & san antonio & 125 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& district \\
\midrule
0 & 124 \\
\bottomrule
\end{tabular}
| select district where representative = 'jose menendez' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>representative</th>
<th>party</th>
<th>home town/city</th>
<th>district</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>trey martinez fischer</td>
<td>d</td>
<td>san antonio</td>
<td>116</td>
</tr>
<tr>
<th>1</th>
<td>philip cortez</td>
<td>d</td>
<td>san antonio</td>
<td>117</td>
</tr>
<tr>
<th>2</th>
<td>joe farias</td>
<td>d</td>
<td>san antonio</td>
<td>118</td>
</tr>
<tr>
<th>3</th>
<td>roland gutierrez</td>
<td>d</td>
<td>san antonio</td>
<td>119</td>
</tr>
<tr>
<th>4</th>
<td>ruth mcclendon</td>
<td>d</td>
<td>san antonio</td>
<td>120</td>
</tr>
<tr>
<th>5</th>
<td>joe straus</td>
<td>r</td>
<td>san antonio</td>
<td>121</td>
</tr>
<tr>
<th>6</th>
<td>lyle larson</td>
<td>r</td>
<td>san antonio</td>
<td>122</td>
</tr>
<tr>
<th>7</th>
<td>mike villarreal</td>
<td>d</td>
<td>san antonio</td>
<td>123</td>
</tr>
<tr>
<th>8</th>
<td>jose menendez</td>
<td>d</td>
<td>san antonio</td>
<td>124</td>
</tr>
<tr>
<th>9</th>
<td>justin rodriguez</td>
<td>d</td>
<td>san antonio</td>
<td>125</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>district</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>124</td>
</tr>
</tbody>
</table> | select district where representative = 'jose menendez' <table_name> : table | | representative | party | home town/city | district |
|---:|:----------------------|:--------|:-----------------|-----------:|
| 0 | trey martinez fischer | d | san antonio | 116 |
| 1 | philip cortez | d | san antonio | 117 |
| 2 | joe farias | d | san antonio | 118 |
| 3 | roland gutierrez | d | san antonio | 119 |
| 4 | ruth mcclendon | d | san antonio | 120 |
| 5 | joe straus | r | san antonio | 121 |
| 6 | lyle larson | r | san antonio | 122 |
| 7 | mike villarreal | d | san antonio | 123 |
| 8 | jose menendez | d | san antonio | 124 |
| 9 | justin rodriguez | d | san antonio | 125 | | | | district |
|---:|-----------:|
| 0 | 124 | | [
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select network where air date = 'may 26, 1993' order by network limit 1 col : no. | air date | network | household rating | viewers (millions) row 1 : 18th | june 27, 1991 | cbs | 13.5 | 18.9 row 2 : 19th | june 23, 1992 | nbc | 15.3 | 20.2 row 3 : 20th | may 26, 1993 | abc | 16.4 | 22 row 4 : 21st | may 25, 1994 | abc | 14.1 | 18.9 row 5 : 22nd | may 19, 1995 | nbc | 10.2 | 13.7 row 6 : 23rd | may 22, 1996 | cbs | 11.4 | 15.1 row 7 : 24th | may 21, 1997 | abc | 11.8 | 15.9 row 8 : 25th | may 15, 1998 | nbc | 10.2 | 13 row 9 : 26th | may 21, 1999 | cbs | 10.4 | 14.2 row 10 : 27th | may 19, 2000 | abc | 9.1 | 13 row 11 : 28th | may 18, 2001 | nbc | 7.9 | 10.3 row 12 : 29th | may 17, 2002 | cbs | 6.9 | 10.1 row 13 : 30th | may 16, 2003 | abc | 6.3 | 8.6 row 14 : 31st | may 21, 2004 | nbc | 6 | 8.4 row 15 : 32nd | may 20, 2005 | cbs | 5.5 | 7.6 row 16 : 33rd | april 28, 2006 | abc | 4.5 | 6.1 row 17 : 34th | june 15, 2007 | cbs | 5.9 | 8.3 row 18 : 35th | june 20, 2008 | abc | 4 | 5.4 row 19 : 36th | august 30, 2009 | cw | 2 | 2.7 row 20 : 37th | june 27, 2010 | cbs | 3.8 | 5.6 row 21 : 38th | june 19, 2011 | cbs | 3.7 | 5.5 row 22 : 39th | june 23, 2012 | hln | none | 2 (5 broadcasts) | col : network row 1 : abc | select network where air date = 'may 26, 1993' order by network limit 1 <table_name> : table \begin{tabular}{llllll}
\toprule
& no. & air date & network & household rating & viewers (millions) \\
\midrule
0 & 18th & june 27, 1991 & cbs & 13.5 & 18.9 \\
1 & 19th & june 23, 1992 & nbc & 15.3 & 20.2 \\
2 & 20th & may 26, 1993 & abc & 16.4 & 22 \\
3 & 21st & may 25, 1994 & abc & 14.1 & 18.9 \\
4 & 22nd & may 19, 1995 & nbc & 10.2 & 13.7 \\
5 & 23rd & may 22, 1996 & cbs & 11.4 & 15.1 \\
6 & 24th & may 21, 1997 & abc & 11.8 & 15.9 \\
7 & 25th & may 15, 1998 & nbc & 10.2 & 13 \\
8 & 26th & may 21, 1999 & cbs & 10.4 & 14.2 \\
9 & 27th & may 19, 2000 & abc & 9.1 & 13 \\
10 & 28th & may 18, 2001 & nbc & 7.9 & 10.3 \\
11 & 29th & may 17, 2002 & cbs & 6.9 & 10.1 \\
12 & 30th & may 16, 2003 & abc & 6.3 & 8.6 \\
13 & 31st & may 21, 2004 & nbc & 6 & 8.4 \\
14 & 32nd & may 20, 2005 & cbs & 5.5 & 7.6 \\
15 & 33rd & april 28, 2006 & abc & 4.5 & 6.1 \\
16 & 34th & june 15, 2007 & cbs & 5.9 & 8.3 \\
17 & 35th & june 20, 2008 & abc & 4 & 5.4 \\
18 & 36th & august 30, 2009 & cw & 2 & 2.7 \\
19 & 37th & june 27, 2010 & cbs & 3.8 & 5.6 \\
20 & 38th & june 19, 2011 & cbs & 3.7 & 5.5 \\
21 & 39th & june 23, 2012 & hln & none & 2 (5 broadcasts) \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& network \\
\midrule
0 & abc \\
\bottomrule
\end{tabular}
| select network where air date = 'may 26, 1993' order by network limit 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no.</th>
<th>air date</th>
<th>network</th>
<th>household rating</th>
<th>viewers (millions)</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>18th</td>
<td>june 27, 1991</td>
<td>cbs</td>
<td>13.5</td>
<td>18.9</td>
</tr>
<tr>
<th>1</th>
<td>19th</td>
<td>june 23, 1992</td>
<td>nbc</td>
<td>15.3</td>
<td>20.2</td>
</tr>
<tr>
<th>2</th>
<td>20th</td>
<td>may 26, 1993</td>
<td>abc</td>
<td>16.4</td>
<td>22</td>
</tr>
<tr>
<th>3</th>
<td>21st</td>
<td>may 25, 1994</td>
<td>abc</td>
<td>14.1</td>
<td>18.9</td>
</tr>
<tr>
<th>4</th>
<td>22nd</td>
<td>may 19, 1995</td>
<td>nbc</td>
<td>10.2</td>
<td>13.7</td>
</tr>
<tr>
<th>5</th>
<td>23rd</td>
<td>may 22, 1996</td>
<td>cbs</td>
<td>11.4</td>
<td>15.1</td>
</tr>
<tr>
<th>6</th>
<td>24th</td>
<td>may 21, 1997</td>
<td>abc</td>
<td>11.8</td>
<td>15.9</td>
</tr>
<tr>
<th>7</th>
<td>25th</td>
<td>may 15, 1998</td>
<td>nbc</td>
<td>10.2</td>
<td>13</td>
</tr>
<tr>
<th>8</th>
<td>26th</td>
<td>may 21, 1999</td>
<td>cbs</td>
<td>10.4</td>
<td>14.2</td>
</tr>
<tr>
<th>9</th>
<td>27th</td>
<td>may 19, 2000</td>
<td>abc</td>
<td>9.1</td>
<td>13</td>
</tr>
<tr>
<th>10</th>
<td>28th</td>
<td>may 18, 2001</td>
<td>nbc</td>
<td>7.9</td>
<td>10.3</td>
</tr>
<tr>
<th>11</th>
<td>29th</td>
<td>may 17, 2002</td>
<td>cbs</td>
<td>6.9</td>
<td>10.1</td>
</tr>
<tr>
<th>12</th>
<td>30th</td>
<td>may 16, 2003</td>
<td>abc</td>
<td>6.3</td>
<td>8.6</td>
</tr>
<tr>
<th>13</th>
<td>31st</td>
<td>may 21, 2004</td>
<td>nbc</td>
<td>6</td>
<td>8.4</td>
</tr>
<tr>
<th>14</th>
<td>32nd</td>
<td>may 20, 2005</td>
<td>cbs</td>
<td>5.5</td>
<td>7.6</td>
</tr>
<tr>
<th>15</th>
<td>33rd</td>
<td>april 28, 2006</td>
<td>abc</td>
<td>4.5</td>
<td>6.1</td>
</tr>
<tr>
<th>16</th>
<td>34th</td>
<td>june 15, 2007</td>
<td>cbs</td>
<td>5.9</td>
<td>8.3</td>
</tr>
<tr>
<th>17</th>
<td>35th</td>
<td>june 20, 2008</td>
<td>abc</td>
<td>4</td>
<td>5.4</td>
</tr>
<tr>
<th>18</th>
<td>36th</td>
<td>august 30, 2009</td>
<td>cw</td>
<td>2</td>
<td>2.7</td>
</tr>
<tr>
<th>19</th>
<td>37th</td>
<td>june 27, 2010</td>
<td>cbs</td>
<td>3.8</td>
<td>5.6</td>
</tr>
<tr>
<th>20</th>
<td>38th</td>
<td>june 19, 2011</td>
<td>cbs</td>
<td>3.7</td>
<td>5.5</td>
</tr>
<tr>
<th>21</th>
<td>39th</td>
<td>june 23, 2012</td>
<td>hln</td>
<td>none</td>
<td>2 (5 broadcasts)</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>network</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>abc</td>
</tr>
</tbody>
</table> | select network where air date = 'may 26, 1993' order by network limit 1 <table_name> : table | | no. | air date | network | household rating | viewers (millions) |
|---:|:------|:----------------|:----------|:-------------------|:---------------------|
| 0 | 18th | june 27, 1991 | cbs | 13.5 | 18.9 |
| 1 | 19th | june 23, 1992 | nbc | 15.3 | 20.2 |
| 2 | 20th | may 26, 1993 | abc | 16.4 | 22 |
| 3 | 21st | may 25, 1994 | abc | 14.1 | 18.9 |
| 4 | 22nd | may 19, 1995 | nbc | 10.2 | 13.7 |
| 5 | 23rd | may 22, 1996 | cbs | 11.4 | 15.1 |
| 6 | 24th | may 21, 1997 | abc | 11.8 | 15.9 |
| 7 | 25th | may 15, 1998 | nbc | 10.2 | 13 |
| 8 | 26th | may 21, 1999 | cbs | 10.4 | 14.2 |
| 9 | 27th | may 19, 2000 | abc | 9.1 | 13 |
| 10 | 28th | may 18, 2001 | nbc | 7.9 | 10.3 |
| 11 | 29th | may 17, 2002 | cbs | 6.9 | 10.1 |
| 12 | 30th | may 16, 2003 | abc | 6.3 | 8.6 |
| 13 | 31st | may 21, 2004 | nbc | 6 | 8.4 |
| 14 | 32nd | may 20, 2005 | cbs | 5.5 | 7.6 |
| 15 | 33rd | april 28, 2006 | abc | 4.5 | 6.1 |
| 16 | 34th | june 15, 2007 | cbs | 5.9 | 8.3 |
| 17 | 35th | june 20, 2008 | abc | 4 | 5.4 |
| 18 | 36th | august 30, 2009 | cw | 2 | 2.7 |
| 19 | 37th | june 27, 2010 | cbs | 3.8 | 5.6 |
| 20 | 38th | june 19, 2011 | cbs | 3.7 | 5.5 |
| 21 | 39th | june 23, 2012 | hln | none | 2 (5 broadcasts) | | | | network |
|---:|:----------|
| 0 | abc | | [
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select date where opponent = 'pittsburgh steelers' col : week | date | opponent | result | attendance row 1 : 1 | 1981-09-06 00:00:00 | new orleans saints | w 27-0 | 57,406 row 2 : 2 | 1981-09-13 00:00:00 | at green bay packers | w 31-17 | 55,382 row 3 : 3 | 1981-09-20 00:00:00 | san francisco 49ers | w 34-17 | 56,653 row 4 : 4 | 1981-09-27 00:00:00 | at cleveland browns | l 28-17 | 78,283 row 5 : 5 | 1981-10-05 00:00:00 | at philadelphia eagles | l 16-13 | 71,488 row 6 : 6 | 1981-10-11 00:00:00 | los angeles rams | l 37-35 | 57,841 row 7 : 7 | 1981-10-18 00:00:00 | st. louis cardinals | w 41-20 | 51,428 row 8 : 8 | 1981-10-25 00:00:00 | new york giants | l 27-24 | 48,410 row 9 : 9 | 1981-11-01 00:00:00 | at new orleans saints | w 41-10 | 63,637 row 10 : 10 | 1981-11-08 00:00:00 | at san francisco 49ers | l 17-14 | 59,127 row 11 : 11 | 1981-11-15 00:00:00 | pittsburgh steelers | l 34-20 | 57,485 row 12 : 12 | 1981-11-23 00:00:00 | minnesota vikings | w 31-30 | 54,086 row 13 : 13 | 1981-11-29 00:00:00 | at houston oilers | w 31-27 | 40,201 row 14 : 14 | 1981-12-06 00:00:00 | at tampa bay buccaneers | l 24-23 | 69,221 row 15 : 15 | 1981-12-14 00:00:00 | at los angeles rams | l 21-16 | 57,054 row 16 : 16 | 1981-12-20 00:00:00 | cincinnati bengals | l 30-28 | 35,972 | col : date row 1 : 1981-11-15 00:00:00 | select date where opponent = 'pittsburgh steelers' <table_name> : table \begin{tabular}{llllll}
\toprule
& week & date & opponent & result & attendance \\
\midrule
0 & 1 & 1981-09-06 00:00:00 & new orleans saints & w 27-0 & 57,406 \\
1 & 2 & 1981-09-13 00:00:00 & at green bay packers & w 31-17 & 55,382 \\
2 & 3 & 1981-09-20 00:00:00 & san francisco 49ers & w 34-17 & 56,653 \\
3 & 4 & 1981-09-27 00:00:00 & at cleveland browns & l 28-17 & 78,283 \\
4 & 5 & 1981-10-05 00:00:00 & at philadelphia eagles & l 16-13 & 71,488 \\
5 & 6 & 1981-10-11 00:00:00 & los angeles rams & l 37-35 & 57,841 \\
6 & 7 & 1981-10-18 00:00:00 & st. louis cardinals & w 41-20 & 51,428 \\
7 & 8 & 1981-10-25 00:00:00 & new york giants & l 27-24 & 48,410 \\
8 & 9 & 1981-11-01 00:00:00 & at new orleans saints & w 41-10 & 63,637 \\
9 & 10 & 1981-11-08 00:00:00 & at san francisco 49ers & l 17-14 & 59,127 \\
10 & 11 & 1981-11-15 00:00:00 & pittsburgh steelers & l 34-20 & 57,485 \\
11 & 12 & 1981-11-23 00:00:00 & minnesota vikings & w 31-30 & 54,086 \\
12 & 13 & 1981-11-29 00:00:00 & at houston oilers & w 31-27 & 40,201 \\
13 & 14 & 1981-12-06 00:00:00 & at tampa bay buccaneers & l 24-23 & 69,221 \\
14 & 15 & 1981-12-14 00:00:00 & at los angeles rams & l 21-16 & 57,054 \\
15 & 16 & 1981-12-20 00:00:00 & cincinnati bengals & l 30-28 & 35,972 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& date \\
\midrule
0 & 1981-11-15 00:00:00 \\
\bottomrule
\end{tabular}
| select date where opponent = 'pittsburgh steelers' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>opponent</th>
<th>result</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1981-09-06 00:00:00</td>
<td>new orleans saints</td>
<td>w 27-0</td>
<td>57,406</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>1981-09-13 00:00:00</td>
<td>at green bay packers</td>
<td>w 31-17</td>
<td>55,382</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1981-09-20 00:00:00</td>
<td>san francisco 49ers</td>
<td>w 34-17</td>
<td>56,653</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>1981-09-27 00:00:00</td>
<td>at cleveland browns</td>
<td>l 28-17</td>
<td>78,283</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>1981-10-05 00:00:00</td>
<td>at philadelphia eagles</td>
<td>l 16-13</td>
<td>71,488</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>1981-10-11 00:00:00</td>
<td>los angeles rams</td>
<td>l 37-35</td>
<td>57,841</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>1981-10-18 00:00:00</td>
<td>st. louis cardinals</td>
<td>w 41-20</td>
<td>51,428</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>1981-10-25 00:00:00</td>
<td>new york giants</td>
<td>l 27-24</td>
<td>48,410</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>1981-11-01 00:00:00</td>
<td>at new orleans saints</td>
<td>w 41-10</td>
<td>63,637</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>1981-11-08 00:00:00</td>
<td>at san francisco 49ers</td>
<td>l 17-14</td>
<td>59,127</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>1981-11-15 00:00:00</td>
<td>pittsburgh steelers</td>
<td>l 34-20</td>
<td>57,485</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>1981-11-23 00:00:00</td>
<td>minnesota vikings</td>
<td>w 31-30</td>
<td>54,086</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>1981-11-29 00:00:00</td>
<td>at houston oilers</td>
<td>w 31-27</td>
<td>40,201</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>1981-12-06 00:00:00</td>
<td>at tampa bay buccaneers</td>
<td>l 24-23</td>
<td>69,221</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>1981-12-14 00:00:00</td>
<td>at los angeles rams</td>
<td>l 21-16</td>
<td>57,054</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>1981-12-20 00:00:00</td>
<td>cincinnati bengals</td>
<td>l 30-28</td>
<td>35,972</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1981-11-15 00:00:00</td>
</tr>
</tbody>
</table> | select date where opponent = 'pittsburgh steelers' <table_name> : table | | week | date | opponent | result | attendance |
|---:|-------:|:--------------------|:------------------------|:---------|:-------------|
| 0 | 1 | 1981-09-06 00:00:00 | new orleans saints | w 27-0 | 57,406 |
| 1 | 2 | 1981-09-13 00:00:00 | at green bay packers | w 31-17 | 55,382 |
| 2 | 3 | 1981-09-20 00:00:00 | san francisco 49ers | w 34-17 | 56,653 |
| 3 | 4 | 1981-09-27 00:00:00 | at cleveland browns | l 28-17 | 78,283 |
| 4 | 5 | 1981-10-05 00:00:00 | at philadelphia eagles | l 16-13 | 71,488 |
| 5 | 6 | 1981-10-11 00:00:00 | los angeles rams | l 37-35 | 57,841 |
| 6 | 7 | 1981-10-18 00:00:00 | st. louis cardinals | w 41-20 | 51,428 |
| 7 | 8 | 1981-10-25 00:00:00 | new york giants | l 27-24 | 48,410 |
| 8 | 9 | 1981-11-01 00:00:00 | at new orleans saints | w 41-10 | 63,637 |
| 9 | 10 | 1981-11-08 00:00:00 | at san francisco 49ers | l 17-14 | 59,127 |
| 10 | 11 | 1981-11-15 00:00:00 | pittsburgh steelers | l 34-20 | 57,485 |
| 11 | 12 | 1981-11-23 00:00:00 | minnesota vikings | w 31-30 | 54,086 |
| 12 | 13 | 1981-11-29 00:00:00 | at houston oilers | w 31-27 | 40,201 |
| 13 | 14 | 1981-12-06 00:00:00 | at tampa bay buccaneers | l 24-23 | 69,221 |
| 14 | 15 | 1981-12-14 00:00:00 | at los angeles rams | l 21-16 | 57,054 |
| 15 | 16 | 1981-12-20 00:00:00 | cincinnati bengals | l 30-28 | 35,972 | | | | date |
|---:|:--------------------|
| 0 | 1981-11-15 00:00:00 | | [
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select count ( 2.15 ) where 2.26 = 'xxx' col : rank | group | name | nationality | 2.05 | 2.15 | 2.19 | 2.23 | 2.26 | result | notes row 1 : 1 | a | nicola ciotti | italy | none | o | o | o | o | 2.26 | q row 2 : 1 | a | linus thornblad | sweden | none | o | o | o | o | 2.26 | q row 3 : 1 | a | tomas janku | czech republic | none | o | o | o | o | 2.26 | q row 4 : 1 | b | oskari frosen | finland | none | o | o | o | o | 2.26 | q row 5 : 1 | b | stefan holm | sweden | none | o | o | o | o | 2.26 | q row 6 : 1 | b | svatoslav ton | czech republic | none | o | o | o | o | 2.26 | q row 7 : 7 | a | niki palli | israel | o | o | o | o | xo | 2.26 | q row 8 : 7 | b | yaroslav rybakov | russia | none | o | o | o | xo | 2.26 | q row 9 : 9 | b | giulio ciotti | italy | none | o | xo | o | xo | 2.26 | q row 10 : 10 | a | andrey silnov | russia | none | o | o | o | xxo | 2.26 | q row 11 : 11 | a | ivan ukhov | russia | none | none | none | o | none | 2.23 | q row 12 : 11 | a | andrea bettinelli | italy | none | o | o | o | xxx | 2.23 | q row 13 : 11 | b | wilbert pennings | netherlands | none | o | o | o | xxx | 2.23 | q row 14 : 14 | a | martyn bernard | united kingdom | none | o | xxo | xo | xxx | 2.23 | none row 15 : 15 | b | peter horak | slovakia | none | o | o | xxo | xxx | 2.23 | none row 16 : 15 | b | normunds pupols | latvia | none | o | o | xxo | xxx | 2.23 | none row 17 : 17 | a | germaine mason | united kingdom | none | o | o | xxx | none | 2.19 | none row 18 : 17 | b | rozle prezelj | slovenia | o | o | o | xxx | none | 2.19 | none row 19 : 19 | a | heikki taneli | finland | none | xo | o | xxx | none | 2.19 | none row 20 : 19 | b | andriy sokolovskyy | ukraine | none | xo | o | xxx | none | 2.19 | none row 21 : 21 | b | mickael hanany | france | none | xo | xo | xxx | none | 2.19 | none row 22 : 22 | b | javier bermejo | spain | o | o | xxx | none | none | 2.15 | none row 23 : 23 | a | osku torro | finland | none | xo | x- | x | none | 2.15 | none row 24 : 24 | a | jan-peter larsen | netherlands | o | xxx | none | none | none | 2.05 | none row 25 : none | b | adam scarr | united kingdom | none | xxx | none | none | none | nm | none | col : count ( "2.15" ) row 1 : 5 | select count ( 2.15 ) where 2.26 = 'xxx' <table_name> : table \begin{tabular}{llllllllllll}
\toprule
& rank & group & name & nationality & 2.05 & 2.15 & 2.19 & 2.23 & 2.26 & result & notes \\
\midrule
0 & 1 & a & nicola ciotti & italy & none & o & o & o & o & 2.26 & q \\
1 & 1 & a & linus thornblad & sweden & none & o & o & o & o & 2.26 & q \\
2 & 1 & a & tomas janku & czech republic & none & o & o & o & o & 2.26 & q \\
3 & 1 & b & oskari frosen & finland & none & o & o & o & o & 2.26 & q \\
4 & 1 & b & stefan holm & sweden & none & o & o & o & o & 2.26 & q \\
5 & 1 & b & svatoslav ton & czech republic & none & o & o & o & o & 2.26 & q \\
6 & 7 & a & niki palli & israel & o & o & o & o & xo & 2.26 & q \\
7 & 7 & b & yaroslav rybakov & russia & none & o & o & o & xo & 2.26 & q \\
8 & 9 & b & giulio ciotti & italy & none & o & xo & o & xo & 2.26 & q \\
9 & 10 & a & andrey silnov & russia & none & o & o & o & xxo & 2.26 & q \\
10 & 11 & a & ivan ukhov & russia & none & none & none & o & none & 2.23 & q \\
11 & 11 & a & andrea bettinelli & italy & none & o & o & o & xxx & 2.23 & q \\
12 & 11 & b & wilbert pennings & netherlands & none & o & o & o & xxx & 2.23 & q \\
13 & 14 & a & martyn bernard & united kingdom & none & o & xxo & xo & xxx & 2.23 & none \\
14 & 15 & b & peter horak & slovakia & none & o & o & xxo & xxx & 2.23 & none \\
15 & 15 & b & normunds pupols & latvia & none & o & o & xxo & xxx & 2.23 & none \\
16 & 17 & a & germaine mason & united kingdom & none & o & o & xxx & none & 2.19 & none \\
17 & 17 & b & rozle prezelj & slovenia & o & o & o & xxx & none & 2.19 & none \\
18 & 19 & a & heikki taneli & finland & none & xo & o & xxx & none & 2.19 & none \\
19 & 19 & b & andriy sokolovskyy & ukraine & none & xo & o & xxx & none & 2.19 & none \\
20 & 21 & b & mickael hanany & france & none & xo & xo & xxx & none & 2.19 & none \\
21 & 22 & b & javier bermejo & spain & o & o & xxx & none & none & 2.15 & none \\
22 & 23 & a & osku torro & finland & none & xo & x- & x & none & 2.15 & none \\
23 & 24 & a & jan-peter larsen & netherlands & o & xxx & none & none & none & 2.05 & none \\
24 & none & b & adam scarr & united kingdom & none & xxx & none & none & none & nm & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "2.15" ) \\
\midrule
0 & 5 \\
\bottomrule
\end{tabular}
| select count ( 2.15 ) where 2.26 = 'xxx' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>group</th>
<th>name</th>
<th>nationality</th>
<th>2.05</th>
<th>2.15</th>
<th>2.19</th>
<th>2.23</th>
<th>2.26</th>
<th>result</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>a</td>
<td>nicola ciotti</td>
<td>italy</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>1</th>
<td>1</td>
<td>a</td>
<td>linus thornblad</td>
<td>sweden</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>2</th>
<td>1</td>
<td>a</td>
<td>tomas janku</td>
<td>czech republic</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>3</th>
<td>1</td>
<td>b</td>
<td>oskari frosen</td>
<td>finland</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>4</th>
<td>1</td>
<td>b</td>
<td>stefan holm</td>
<td>sweden</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>5</th>
<td>1</td>
<td>b</td>
<td>svatoslav ton</td>
<td>czech republic</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>a</td>
<td>niki palli</td>
<td>israel</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>xo</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>b</td>
<td>yaroslav rybakov</td>
<td>russia</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>xo</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>b</td>
<td>giulio ciotti</td>
<td>italy</td>
<td>none</td>
<td>o</td>
<td>xo</td>
<td>o</td>
<td>xo</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>a</td>
<td>andrey silnov</td>
<td>russia</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>xxo</td>
<td>2.26</td>
<td>q</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>a</td>
<td>ivan ukhov</td>
<td>russia</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>o</td>
<td>none</td>
<td>2.23</td>
<td>q</td>
</tr>
<tr>
<th>11</th>
<td>11</td>
<td>a</td>
<td>andrea bettinelli</td>
<td>italy</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>xxx</td>
<td>2.23</td>
<td>q</td>
</tr>
<tr>
<th>12</th>
<td>11</td>
<td>b</td>
<td>wilbert pennings</td>
<td>netherlands</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>xxx</td>
<td>2.23</td>
<td>q</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>a</td>
<td>martyn bernard</td>
<td>united kingdom</td>
<td>none</td>
<td>o</td>
<td>xxo</td>
<td>xo</td>
<td>xxx</td>
<td>2.23</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>b</td>
<td>peter horak</td>
<td>slovakia</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>xxo</td>
<td>xxx</td>
<td>2.23</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>15</td>
<td>b</td>
<td>normunds pupols</td>
<td>latvia</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>xxo</td>
<td>xxx</td>
<td>2.23</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>a</td>
<td>germaine mason</td>
<td>united kingdom</td>
<td>none</td>
<td>o</td>
<td>o</td>
<td>xxx</td>
<td>none</td>
<td>2.19</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>17</td>
<td>b</td>
<td>rozle prezelj</td>
<td>slovenia</td>
<td>o</td>
<td>o</td>
<td>o</td>
<td>xxx</td>
<td>none</td>
<td>2.19</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>a</td>
<td>heikki taneli</td>
<td>finland</td>
<td>none</td>
<td>xo</td>
<td>o</td>
<td>xxx</td>
<td>none</td>
<td>2.19</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>19</td>
<td>b</td>
<td>andriy sokolovskyy</td>
<td>ukraine</td>
<td>none</td>
<td>xo</td>
<td>o</td>
<td>xxx</td>
<td>none</td>
<td>2.19</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>b</td>
<td>mickael hanany</td>
<td>france</td>
<td>none</td>
<td>xo</td>
<td>xo</td>
<td>xxx</td>
<td>none</td>
<td>2.19</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>b</td>
<td>javier bermejo</td>
<td>spain</td>
<td>o</td>
<td>o</td>
<td>xxx</td>
<td>none</td>
<td>none</td>
<td>2.15</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>a</td>
<td>osku torro</td>
<td>finland</td>
<td>none</td>
<td>xo</td>
<td>x-</td>
<td>x</td>
<td>none</td>
<td>2.15</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>a</td>
<td>jan-peter larsen</td>
<td>netherlands</td>
<td>o</td>
<td>xxx</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>2.05</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>none</td>
<td>b</td>
<td>adam scarr</td>
<td>united kingdom</td>
<td>none</td>
<td>xxx</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>nm</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "2.15" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>5</td>
</tr>
</tbody>
</table> | select count ( 2.15 ) where 2.26 = 'xxx' <table_name> : table | | rank | group | name | nationality | 2.05 | 2.15 | 2.19 | 2.23 | 2.26 | result | notes |
|---:|:-------|:--------|:-------------------|:---------------|:-------|:-------|:-------|:-------|:-------|:---------|:--------|
| 0 | 1 | a | nicola ciotti | italy | none | o | o | o | o | 2.26 | q |
| 1 | 1 | a | linus thornblad | sweden | none | o | o | o | o | 2.26 | q |
| 2 | 1 | a | tomas janku | czech republic | none | o | o | o | o | 2.26 | q |
| 3 | 1 | b | oskari frosen | finland | none | o | o | o | o | 2.26 | q |
| 4 | 1 | b | stefan holm | sweden | none | o | o | o | o | 2.26 | q |
| 5 | 1 | b | svatoslav ton | czech republic | none | o | o | o | o | 2.26 | q |
| 6 | 7 | a | niki palli | israel | o | o | o | o | xo | 2.26 | q |
| 7 | 7 | b | yaroslav rybakov | russia | none | o | o | o | xo | 2.26 | q |
| 8 | 9 | b | giulio ciotti | italy | none | o | xo | o | xo | 2.26 | q |
| 9 | 10 | a | andrey silnov | russia | none | o | o | o | xxo | 2.26 | q |
| 10 | 11 | a | ivan ukhov | russia | none | none | none | o | none | 2.23 | q |
| 11 | 11 | a | andrea bettinelli | italy | none | o | o | o | xxx | 2.23 | q |
| 12 | 11 | b | wilbert pennings | netherlands | none | o | o | o | xxx | 2.23 | q |
| 13 | 14 | a | martyn bernard | united kingdom | none | o | xxo | xo | xxx | 2.23 | none |
| 14 | 15 | b | peter horak | slovakia | none | o | o | xxo | xxx | 2.23 | none |
| 15 | 15 | b | normunds pupols | latvia | none | o | o | xxo | xxx | 2.23 | none |
| 16 | 17 | a | germaine mason | united kingdom | none | o | o | xxx | none | 2.19 | none |
| 17 | 17 | b | rozle prezelj | slovenia | o | o | o | xxx | none | 2.19 | none |
| 18 | 19 | a | heikki taneli | finland | none | xo | o | xxx | none | 2.19 | none |
| 19 | 19 | b | andriy sokolovskyy | ukraine | none | xo | o | xxx | none | 2.19 | none |
| 20 | 21 | b | mickael hanany | france | none | xo | xo | xxx | none | 2.19 | none |
| 21 | 22 | b | javier bermejo | spain | o | o | xxx | none | none | 2.15 | none |
| 22 | 23 | a | osku torro | finland | none | xo | x- | x | none | 2.15 | none |
| 23 | 24 | a | jan-peter larsen | netherlands | o | xxx | none | none | none | 2.05 | none |
| 24 | none | b | adam scarr | united kingdom | none | xxx | none | none | none | nm | none | | | | count ( "2.15" ) |
|---:|-------------------:|
| 0 | 5 | | [
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select number where number = 1 col : number | builder | type | date | length | notes row 1 : 51 | american car company | motor | 1904 | 47'9" | retired 1933 row 2 : 53 | american car company | motor | 1904 | 47'9" | retired 1933 row 3 : 55 | american car company | motor | 1904 | 47'9" | became inspection car in 1932 retired 1941 row 4 : 57 | american car company | motor | 1904 | 47'9" | became inspection car in 1932 retired 1941 row 5 : 59 | w. l. holman car company | motor | 1904 | 44' | retired 1932 row 6 : 61 | w. l. holman car company | motor | 1904 | 44' | retired 1932 row 7 : 63 | w. l. holman car company | motor | 1904 | 44' | retired 1932 preserved western railway museum row 8 : 65 | w. l. holman car company | motor | 1904 | 44' | retired 1932 row 9 : 67 | w. l. holman car company | motor | 1904 | 44' | retired 1932 row 10 : 69 | w. l. holman car company | motor | 1904 | 44' | converted to express trailer in 1919 retired 1932 row 11 : 71 | w. l. holman car company | trailer | 1905 | 44' | retired 1929 row 12 : 73 | w. l. holman car company | trailer | 1905 | 44' | retired 1929 row 13 : 1 | w. l. holman car company | express trailer | 1916 | none | built as #8 express motor demotorized 1917 designated express trailer 1920 retired 1933 | col : number row 1 : 1 | select number where number = 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& number & builder & type & date & length & notes \\
\midrule
0 & 51 & american car company & motor & 1904 & 47'9" & retired 1933 \\
1 & 53 & american car company & motor & 1904 & 47'9" & retired 1933 \\
2 & 55 & american car company & motor & 1904 & 47'9" & became inspection car in 1932 retired 1941 \\
3 & 57 & american car company & motor & 1904 & 47'9" & became inspection car in 1932 retired 1941 \\
4 & 59 & w. l. holman car company & motor & 1904 & 44' & retired 1932 \\
5 & 61 & w. l. holman car company & motor & 1904 & 44' & retired 1932 \\
6 & 63 & w. l. holman car company & motor & 1904 & 44' & retired 1932 preserved western railway museum \\
7 & 65 & w. l. holman car company & motor & 1904 & 44' & retired 1932 \\
8 & 67 & w. l. holman car company & motor & 1904 & 44' & retired 1932 \\
9 & 69 & w. l. holman car company & motor & 1904 & 44' & converted to express trailer in 1919 retired 1932 \\
10 & 71 & w. l. holman car company & trailer & 1905 & 44' & retired 1929 \\
11 & 73 & w. l. holman car company & trailer & 1905 & 44' & retired 1929 \\
12 & 1 & w. l. holman car company & express trailer & 1916 & none & built as #8 express motor demotorized 1917 designated express trailer 1920 retired 1933 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& number \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select number where number = 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>number</th>
<th>builder</th>
<th>type</th>
<th>date</th>
<th>length</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>51</td>
<td>american car company</td>
<td>motor</td>
<td>1904</td>
<td>47'9"</td>
<td>retired 1933</td>
</tr>
<tr>
<th>1</th>
<td>53</td>
<td>american car company</td>
<td>motor</td>
<td>1904</td>
<td>47'9"</td>
<td>retired 1933</td>
</tr>
<tr>
<th>2</th>
<td>55</td>
<td>american car company</td>
<td>motor</td>
<td>1904</td>
<td>47'9"</td>
<td>became inspection car in 1932 retired 1941</td>
</tr>
<tr>
<th>3</th>
<td>57</td>
<td>american car company</td>
<td>motor</td>
<td>1904</td>
<td>47'9"</td>
<td>became inspection car in 1932 retired 1941</td>
</tr>
<tr>
<th>4</th>
<td>59</td>
<td>w. l. holman car company</td>
<td>motor</td>
<td>1904</td>
<td>44'</td>
<td>retired 1932</td>
</tr>
<tr>
<th>5</th>
<td>61</td>
<td>w. l. holman car company</td>
<td>motor</td>
<td>1904</td>
<td>44'</td>
<td>retired 1932</td>
</tr>
<tr>
<th>6</th>
<td>63</td>
<td>w. l. holman car company</td>
<td>motor</td>
<td>1904</td>
<td>44'</td>
<td>retired 1932 preserved western railway museum</td>
</tr>
<tr>
<th>7</th>
<td>65</td>
<td>w. l. holman car company</td>
<td>motor</td>
<td>1904</td>
<td>44'</td>
<td>retired 1932</td>
</tr>
<tr>
<th>8</th>
<td>67</td>
<td>w. l. holman car company</td>
<td>motor</td>
<td>1904</td>
<td>44'</td>
<td>retired 1932</td>
</tr>
<tr>
<th>9</th>
<td>69</td>
<td>w. l. holman car company</td>
<td>motor</td>
<td>1904</td>
<td>44'</td>
<td>converted to express trailer in 1919 retired 1932</td>
</tr>
<tr>
<th>10</th>
<td>71</td>
<td>w. l. holman car company</td>
<td>trailer</td>
<td>1905</td>
<td>44'</td>
<td>retired 1929</td>
</tr>
<tr>
<th>11</th>
<td>73</td>
<td>w. l. holman car company</td>
<td>trailer</td>
<td>1905</td>
<td>44'</td>
<td>retired 1929</td>
</tr>
<tr>
<th>12</th>
<td>1</td>
<td>w. l. holman car company</td>
<td>express trailer</td>
<td>1916</td>
<td>none</td>
<td>built as #8 express motor demotorized 1917 designated express trailer 1920 retired 1933</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>number</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select number where number = 1 <table_name> : table | | number | builder | type | date | length | notes |
|---:|---------:|:-------------------------|:----------------|-------:|:---------|:----------------------------------------------------------------------------------------|
| 0 | 51 | american car company | motor | 1904 | 47'9" | retired 1933 |
| 1 | 53 | american car company | motor | 1904 | 47'9" | retired 1933 |
| 2 | 55 | american car company | motor | 1904 | 47'9" | became inspection car in 1932 retired 1941 |
| 3 | 57 | american car company | motor | 1904 | 47'9" | became inspection car in 1932 retired 1941 |
| 4 | 59 | w. l. holman car company | motor | 1904 | 44' | retired 1932 |
| 5 | 61 | w. l. holman car company | motor | 1904 | 44' | retired 1932 |
| 6 | 63 | w. l. holman car company | motor | 1904 | 44' | retired 1932 preserved western railway museum |
| 7 | 65 | w. l. holman car company | motor | 1904 | 44' | retired 1932 |
| 8 | 67 | w. l. holman car company | motor | 1904 | 44' | retired 1932 |
| 9 | 69 | w. l. holman car company | motor | 1904 | 44' | converted to express trailer in 1919 retired 1932 |
| 10 | 71 | w. l. holman car company | trailer | 1905 | 44' | retired 1929 |
| 11 | 73 | w. l. holman car company | trailer | 1905 | 44' | retired 1929 |
| 12 | 1 | w. l. holman car company | express trailer | 1916 | none | built as #8 express motor demotorized 1917 designated express trailer 1920 retired 1933 | | | | number |
|---:|---------:|
| 0 | 1 | | [
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select titles where team = 'hapoel holon' col : place | team | titles | runners-up | winning years row 1 : 1 | maccabi tel aviv | 5 | 1 | 2007, 2010, 2011, 2012, 2013 row 2 : 2 | hapoel jerusalem | 2 | 3 | 2008, 2009 row 3 : 3 | ironi ashkelon | 1 | 0 | 2006 row 4 : 4 | maccabi rishon lezion | 0 | 1 | none row 5 : 4 | ironi nahariya | 0 | 1 | none row 6 : 4 | hapoel holon | 0 | 1 | none row 7 : 4 | maccabi ashdod | 0 | 1 | none | col : titles row 1 : 0 | select titles where team = 'hapoel holon' <table_name> : table \begin{tabular}{llllll}
\toprule
& place & team & titles & runners-up & winning years \\
\midrule
0 & 1 & maccabi tel aviv & 5 & 1 & 2007, 2010, 2011, 2012, 2013 \\
1 & 2 & hapoel jerusalem & 2 & 3 & 2008, 2009 \\
2 & 3 & ironi ashkelon & 1 & 0 & 2006 \\
3 & 4 & maccabi rishon lezion & 0 & 1 & none \\
4 & 4 & ironi nahariya & 0 & 1 & none \\
5 & 4 & hapoel holon & 0 & 1 & none \\
6 & 4 & maccabi ashdod & 0 & 1 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& titles \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select titles where team = 'hapoel holon' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>team</th>
<th>titles</th>
<th>runners-up</th>
<th>winning years</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>maccabi tel aviv</td>
<td>5</td>
<td>1</td>
<td>2007, 2010, 2011, 2012, 2013</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>hapoel jerusalem</td>
<td>2</td>
<td>3</td>
<td>2008, 2009</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>ironi ashkelon</td>
<td>1</td>
<td>0</td>
<td>2006</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>maccabi rishon lezion</td>
<td>0</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>ironi nahariya</td>
<td>0</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>hapoel holon</td>
<td>0</td>
<td>1</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>4</td>
<td>maccabi ashdod</td>
<td>0</td>
<td>1</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>titles</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select titles where team = 'hapoel holon' <table_name> : table | | place | team | titles | runners-up | winning years |
|---:|--------:|:----------------------|---------:|-------------:|:-----------------------------|
| 0 | 1 | maccabi tel aviv | 5 | 1 | 2007, 2010, 2011, 2012, 2013 |
| 1 | 2 | hapoel jerusalem | 2 | 3 | 2008, 2009 |
| 2 | 3 | ironi ashkelon | 1 | 0 | 2006 |
| 3 | 4 | maccabi rishon lezion | 0 | 1 | none |
| 4 | 4 | ironi nahariya | 0 | 1 | none |
| 5 | 4 | hapoel holon | 0 | 1 | none |
| 6 | 4 | maccabi ashdod | 0 | 1 | none | | | | titles |
|---:|---------:|
| 0 | 0 | | [
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select count ( result ) where year > 0 col : year | nominated work | award | category | result row 1 : 1984 | what becomes a semi-legend most? | grammy award | best comedy album | nominated row 2 : 1990 | the joan rivers show | daytime emmy award | outstanding talk show host | won row 3 : 1991 | the joan rivers show | daytime emmy award | outstanding talk show host | nominated row 4 : 1992 | the joan rivers show | daytime emmy award | outstanding writing - special class | nominated row 5 : 1992 | the joan rivers show | daytime emmy award | outstanding talk show host | nominated row 6 : 1993 | the joan rivers show | daytime emmy award | outstanding writing - special class | nominated row 7 : 1993 | the joan rivers show | daytime emmy award | outstanding talk show host | nominated row 8 : 1994 | sally marr...and her escorts | tony award | best actress in a play | nominated row 9 : 2009 | arthur | daytime emmy award | outstanding performer in an animated program | nominated | col : count ( "result" ) row 1 : 9 | select count ( result ) where year > 0 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & nominated work & award & category & result \\
\midrule
0 & 1984 & what becomes a semi-legend most? & grammy award & best comedy album & nominated \\
1 & 1990 & the joan rivers show & daytime emmy award & outstanding talk show host & won \\
2 & 1991 & the joan rivers show & daytime emmy award & outstanding talk show host & nominated \\
3 & 1992 & the joan rivers show & daytime emmy award & outstanding writing - special class & nominated \\
4 & 1992 & the joan rivers show & daytime emmy award & outstanding talk show host & nominated \\
5 & 1993 & the joan rivers show & daytime emmy award & outstanding writing - special class & nominated \\
6 & 1993 & the joan rivers show & daytime emmy award & outstanding talk show host & nominated \\
7 & 1994 & sally marr...and her escorts & tony award & best actress in a play & nominated \\
8 & 2009 & arthur & daytime emmy award & outstanding performer in an animated program & nominated \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "result" ) \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select count ( result ) where year > 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>nominated work</th>
<th>award</th>
<th>category</th>
<th>result</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1984</td>
<td>what becomes a semi-legend most?</td>
<td>grammy award</td>
<td>best comedy album</td>
<td>nominated</td>
</tr>
<tr>
<th>1</th>
<td>1990</td>
<td>the joan rivers show</td>
<td>daytime emmy award</td>
<td>outstanding talk show host</td>
<td>won</td>
</tr>
<tr>
<th>2</th>
<td>1991</td>
<td>the joan rivers show</td>
<td>daytime emmy award</td>
<td>outstanding talk show host</td>
<td>nominated</td>
</tr>
<tr>
<th>3</th>
<td>1992</td>
<td>the joan rivers show</td>
<td>daytime emmy award</td>
<td>outstanding writing - special class</td>
<td>nominated</td>
</tr>
<tr>
<th>4</th>
<td>1992</td>
<td>the joan rivers show</td>
<td>daytime emmy award</td>
<td>outstanding talk show host</td>
<td>nominated</td>
</tr>
<tr>
<th>5</th>
<td>1993</td>
<td>the joan rivers show</td>
<td>daytime emmy award</td>
<td>outstanding writing - special class</td>
<td>nominated</td>
</tr>
<tr>
<th>6</th>
<td>1993</td>
<td>the joan rivers show</td>
<td>daytime emmy award</td>
<td>outstanding talk show host</td>
<td>nominated</td>
</tr>
<tr>
<th>7</th>
<td>1994</td>
<td>sally marr...and her escorts</td>
<td>tony award</td>
<td>best actress in a play</td>
<td>nominated</td>
</tr>
<tr>
<th>8</th>
<td>2009</td>
<td>arthur</td>
<td>daytime emmy award</td>
<td>outstanding performer in an animated program</td>
<td>nominated</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "result" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select count ( result ) where year > 0 <table_name> : table | | year | nominated work | award | category | result |
|---:|-------:|:---------------------------------|:-------------------|:---------------------------------------------|:----------|
| 0 | 1984 | what becomes a semi-legend most? | grammy award | best comedy album | nominated |
| 1 | 1990 | the joan rivers show | daytime emmy award | outstanding talk show host | won |
| 2 | 1991 | the joan rivers show | daytime emmy award | outstanding talk show host | nominated |
| 3 | 1992 | the joan rivers show | daytime emmy award | outstanding writing - special class | nominated |
| 4 | 1992 | the joan rivers show | daytime emmy award | outstanding talk show host | nominated |
| 5 | 1993 | the joan rivers show | daytime emmy award | outstanding writing - special class | nominated |
| 6 | 1993 | the joan rivers show | daytime emmy award | outstanding talk show host | nominated |
| 7 | 1994 | sally marr...and her escorts | tony award | best actress in a play | nominated |
| 8 | 2009 | arthur | daytime emmy award | outstanding performer in an animated program | nominated | | | | count ( "result" ) |
|---:|---------------------:|
| 0 | 9 | | [
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select sum ( discs ) where dvd release region 4 = 2013 col : dvd title | discs | year | no. of ep. | dvd release region 2 | dvd release region 4 row 1 : complete series 1 | 2 | 1971 | 8 | 30 april 2007 | 4 july 2007 row 2 : complete series 2 | 2 | 1972 | 8 | 2 july 2007 | 8 may 2008 row 3 : complete series 3 | 2 | 1973-1974 | 8 | 17 march 2008 | 5 march 2009 row 4 : complete series 4 | 2 | 1975 | 8 | 19 may 2008 | 6 august 2009 row 5 : complete series 5 | 2 | 1976 | 8 | 15 june 2009 | 4 march 2010 row 6 : complete series 6 | 2 | 1977-1978 | 8 | 22 february 2010 | 5 august 2010 row 7 : complete series 7 | 2 | 1978-1979 | 8 | 17 may 2010 | 3 march 2011 row 8 : complete series 8 | 2 | 1980 | 8 | 6 september 2010 | 2 june 2011 row 9 : complete series 9 | 2 | 1981-1982 | 8 | 28 february 2011 | 1 march 2012 row 10 : complete series 10 | 2 | 1983-1984 | 6 | 9 may 2011 | 5 september 2012 row 11 : complete series 11 | 2 | 1985 | 5 | 25 july 2011 | 3 april 2013 row 12 : complete series 12 | 2 | 1985-1986 | 6 | 26 september 2011 | 7 august 2013 row 13 : the christmas specials | 2 | 1973-1982-1984-1987 | 4 | 29 october 2007 | 6 november 2008 row 14 : the complete collection | 27 | 1971-1987, 2010 | 96 | 24 september 2012 | 2013 row 15 : two ronnies in australia | 2 | 1986 | 6 | none | 28 june 2008 row 16 : the best of...volume 1 | 1 | 1971-1984 | 1 compilation | 1 october 2001 | 4 march 2002 row 17 : the best of...volume 2 | 1 | 1971-1985 | 1 compilation | 29 september 2003 | 17 march 2003 | col : sum ( "discs" ) row 1 : 27 | select sum ( discs ) where dvd release region 4 = 2013 <table_name> : table \begin{tabular}{lllllll}
\toprule
& dvd title & discs & year & no. of ep. & dvd release region 2 & dvd release region 4 \\
\midrule
0 & complete series 1 & 2 & 1971 & 8 & 30 april 2007 & 4 july 2007 \\
1 & complete series 2 & 2 & 1972 & 8 & 2 july 2007 & 8 may 2008 \\
2 & complete series 3 & 2 & 1973-1974 & 8 & 17 march 2008 & 5 march 2009 \\
3 & complete series 4 & 2 & 1975 & 8 & 19 may 2008 & 6 august 2009 \\
4 & complete series 5 & 2 & 1976 & 8 & 15 june 2009 & 4 march 2010 \\
5 & complete series 6 & 2 & 1977-1978 & 8 & 22 february 2010 & 5 august 2010 \\
6 & complete series 7 & 2 & 1978-1979 & 8 & 17 may 2010 & 3 march 2011 \\
7 & complete series 8 & 2 & 1980 & 8 & 6 september 2010 & 2 june 2011 \\
8 & complete series 9 & 2 & 1981-1982 & 8 & 28 february 2011 & 1 march 2012 \\
9 & complete series 10 & 2 & 1983-1984 & 6 & 9 may 2011 & 5 september 2012 \\
10 & complete series 11 & 2 & 1985 & 5 & 25 july 2011 & 3 april 2013 \\
11 & complete series 12 & 2 & 1985-1986 & 6 & 26 september 2011 & 7 august 2013 \\
12 & the christmas specials & 2 & 1973-1982-1984-1987 & 4 & 29 october 2007 & 6 november 2008 \\
13 & the complete collection & 27 & 1971-1987, 2010 & 96 & 24 september 2012 & 2013 \\
14 & two ronnies in australia & 2 & 1986 & 6 & none & 28 june 2008 \\
15 & the best of...volume 1 & 1 & 1971-1984 & 1 compilation & 1 october 2001 & 4 march 2002 \\
16 & the best of...volume 2 & 1 & 1971-1985 & 1 compilation & 29 september 2003 & 17 march 2003 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& sum ( "discs" ) \\
\midrule
0 & 27 \\
\bottomrule
\end{tabular}
| select sum ( discs ) where dvd release region 4 = 2013 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>dvd title</th>
<th>discs</th>
<th>year</th>
<th>no. of ep.</th>
<th>dvd release region 2</th>
<th>dvd release region 4</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>complete series 1</td>
<td>2</td>
<td>1971</td>
<td>8</td>
<td>30 april 2007</td>
<td>4 july 2007</td>
</tr>
<tr>
<th>1</th>
<td>complete series 2</td>
<td>2</td>
<td>1972</td>
<td>8</td>
<td>2 july 2007</td>
<td>8 may 2008</td>
</tr>
<tr>
<th>2</th>
<td>complete series 3</td>
<td>2</td>
<td>1973-1974</td>
<td>8</td>
<td>17 march 2008</td>
<td>5 march 2009</td>
</tr>
<tr>
<th>3</th>
<td>complete series 4</td>
<td>2</td>
<td>1975</td>
<td>8</td>
<td>19 may 2008</td>
<td>6 august 2009</td>
</tr>
<tr>
<th>4</th>
<td>complete series 5</td>
<td>2</td>
<td>1976</td>
<td>8</td>
<td>15 june 2009</td>
<td>4 march 2010</td>
</tr>
<tr>
<th>5</th>
<td>complete series 6</td>
<td>2</td>
<td>1977-1978</td>
<td>8</td>
<td>22 february 2010</td>
<td>5 august 2010</td>
</tr>
<tr>
<th>6</th>
<td>complete series 7</td>
<td>2</td>
<td>1978-1979</td>
<td>8</td>
<td>17 may 2010</td>
<td>3 march 2011</td>
</tr>
<tr>
<th>7</th>
<td>complete series 8</td>
<td>2</td>
<td>1980</td>
<td>8</td>
<td>6 september 2010</td>
<td>2 june 2011</td>
</tr>
<tr>
<th>8</th>
<td>complete series 9</td>
<td>2</td>
<td>1981-1982</td>
<td>8</td>
<td>28 february 2011</td>
<td>1 march 2012</td>
</tr>
<tr>
<th>9</th>
<td>complete series 10</td>
<td>2</td>
<td>1983-1984</td>
<td>6</td>
<td>9 may 2011</td>
<td>5 september 2012</td>
</tr>
<tr>
<th>10</th>
<td>complete series 11</td>
<td>2</td>
<td>1985</td>
<td>5</td>
<td>25 july 2011</td>
<td>3 april 2013</td>
</tr>
<tr>
<th>11</th>
<td>complete series 12</td>
<td>2</td>
<td>1985-1986</td>
<td>6</td>
<td>26 september 2011</td>
<td>7 august 2013</td>
</tr>
<tr>
<th>12</th>
<td>the christmas specials</td>
<td>2</td>
<td>1973-1982-1984-1987</td>
<td>4</td>
<td>29 october 2007</td>
<td>6 november 2008</td>
</tr>
<tr>
<th>13</th>
<td>the complete collection</td>
<td>27</td>
<td>1971-1987, 2010</td>
<td>96</td>
<td>24 september 2012</td>
<td>2013</td>
</tr>
<tr>
<th>14</th>
<td>two ronnies in australia</td>
<td>2</td>
<td>1986</td>
<td>6</td>
<td>none</td>
<td>28 june 2008</td>
</tr>
<tr>
<th>15</th>
<td>the best of...volume 1</td>
<td>1</td>
<td>1971-1984</td>
<td>1 compilation</td>
<td>1 october 2001</td>
<td>4 march 2002</td>
</tr>
<tr>
<th>16</th>
<td>the best of...volume 2</td>
<td>1</td>
<td>1971-1985</td>
<td>1 compilation</td>
<td>29 september 2003</td>
<td>17 march 2003</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>sum ( "discs" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>27</td>
</tr>
</tbody>
</table> | select sum ( discs ) where dvd release region 4 = 2013 <table_name> : table | | dvd title | discs | year | no. of ep. | dvd release region 2 | dvd release region 4 |
|---:|:-------------------------|--------:|:--------------------|:--------------|:-----------------------|:-----------------------|
| 0 | complete series 1 | 2 | 1971 | 8 | 30 april 2007 | 4 july 2007 |
| 1 | complete series 2 | 2 | 1972 | 8 | 2 july 2007 | 8 may 2008 |
| 2 | complete series 3 | 2 | 1973-1974 | 8 | 17 march 2008 | 5 march 2009 |
| 3 | complete series 4 | 2 | 1975 | 8 | 19 may 2008 | 6 august 2009 |
| 4 | complete series 5 | 2 | 1976 | 8 | 15 june 2009 | 4 march 2010 |
| 5 | complete series 6 | 2 | 1977-1978 | 8 | 22 february 2010 | 5 august 2010 |
| 6 | complete series 7 | 2 | 1978-1979 | 8 | 17 may 2010 | 3 march 2011 |
| 7 | complete series 8 | 2 | 1980 | 8 | 6 september 2010 | 2 june 2011 |
| 8 | complete series 9 | 2 | 1981-1982 | 8 | 28 february 2011 | 1 march 2012 |
| 9 | complete series 10 | 2 | 1983-1984 | 6 | 9 may 2011 | 5 september 2012 |
| 10 | complete series 11 | 2 | 1985 | 5 | 25 july 2011 | 3 april 2013 |
| 11 | complete series 12 | 2 | 1985-1986 | 6 | 26 september 2011 | 7 august 2013 |
| 12 | the christmas specials | 2 | 1973-1982-1984-1987 | 4 | 29 october 2007 | 6 november 2008 |
| 13 | the complete collection | 27 | 1971-1987, 2010 | 96 | 24 september 2012 | 2013 |
| 14 | two ronnies in australia | 2 | 1986 | 6 | none | 28 june 2008 |
| 15 | the best of...volume 1 | 1 | 1971-1984 | 1 compilation | 1 october 2001 | 4 march 2002 |
| 16 | the best of...volume 2 | 1 | 1971-1985 | 1 compilation | 29 september 2003 | 17 march 2003 | | | | sum ( "discs" ) |
|---:|------------------:|
| 0 | 27 | | [
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select place where population = 10304 col : place | code | area (km2) | population | most spoken language row 1 : beatrix mine | 40701 | 0.17 | 2492 | sotho row 2 : boipatong | 40702 | 0.31 | 1501 | sotho row 3 : brandfort | 40703 | 3.2 | 1516 | afrikaans row 4 : fora | 40704 | 0.05 | 530 | sotho row 5 : ikgomotseng | 40705 | 1.07 | 2254 | tswana row 6 : joel mine | 40706 | 0.11 | 728 | sotho row 7 : lusaka | 40707 | 1.4 | 6110 | sotho row 8 : majwemasweu | 40708 | 2.5 | 10328 | sotho row 9 : makeleketla | 40709 | 1.35 | 6629 | sotho row 10 : masilo | 40710 | 3.02 | 14903 | sotho row 11 : star diamond mine | 40712 | 0.11 | 212 | sotho row 12 : theunissen | 40713 | 15.11 | 1667 | afrikaans row 13 : tshepong | 40714 | 0.54 | 1710 | sotho row 14 : verkeerdevlei | 40715 | 1.22 | 151 | afrikaans row 15 : winburg | 40716 | 70.22 | 3371 | sotho row 16 : remainder of the municipality | 40711 | 6696.44 | 10304 | sotho | col : place row 1 : remainder of the municipality | select place where population = 10304 <table_name> : table \begin{tabular}{llllll}
\toprule
& place & code & area (km2) & population & most spoken language \\
\midrule
0 & beatrix mine & 40701 & 0.17 & 2492 & sotho \\
1 & boipatong & 40702 & 0.31 & 1501 & sotho \\
2 & brandfort & 40703 & 3.2 & 1516 & afrikaans \\
3 & fora & 40704 & 0.05 & 530 & sotho \\
4 & ikgomotseng & 40705 & 1.07 & 2254 & tswana \\
5 & joel mine & 40706 & 0.11 & 728 & sotho \\
6 & lusaka & 40707 & 1.4 & 6110 & sotho \\
7 & majwemasweu & 40708 & 2.5 & 10328 & sotho \\
8 & makeleketla & 40709 & 1.35 & 6629 & sotho \\
9 & masilo & 40710 & 3.02 & 14903 & sotho \\
10 & star diamond mine & 40712 & 0.11 & 212 & sotho \\
11 & theunissen & 40713 & 15.11 & 1667 & afrikaans \\
12 & tshepong & 40714 & 0.54 & 1710 & sotho \\
13 & verkeerdevlei & 40715 & 1.22 & 151 & afrikaans \\
14 & winburg & 40716 & 70.22 & 3371 & sotho \\
15 & remainder of the municipality & 40711 & 6696.44 & 10304 & sotho \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& place \\
\midrule
0 & remainder of the municipality \\
\bottomrule
\end{tabular}
| select place where population = 10304 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>code</th>
<th>area (km2)</th>
<th>population</th>
<th>most spoken language</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>beatrix mine</td>
<td>40701</td>
<td>0.17</td>
<td>2492</td>
<td>sotho</td>
</tr>
<tr>
<th>1</th>
<td>boipatong</td>
<td>40702</td>
<td>0.31</td>
<td>1501</td>
<td>sotho</td>
</tr>
<tr>
<th>2</th>
<td>brandfort</td>
<td>40703</td>
<td>3.2</td>
<td>1516</td>
<td>afrikaans</td>
</tr>
<tr>
<th>3</th>
<td>fora</td>
<td>40704</td>
<td>0.05</td>
<td>530</td>
<td>sotho</td>
</tr>
<tr>
<th>4</th>
<td>ikgomotseng</td>
<td>40705</td>
<td>1.07</td>
<td>2254</td>
<td>tswana</td>
</tr>
<tr>
<th>5</th>
<td>joel mine</td>
<td>40706</td>
<td>0.11</td>
<td>728</td>
<td>sotho</td>
</tr>
<tr>
<th>6</th>
<td>lusaka</td>
<td>40707</td>
<td>1.4</td>
<td>6110</td>
<td>sotho</td>
</tr>
<tr>
<th>7</th>
<td>majwemasweu</td>
<td>40708</td>
<td>2.5</td>
<td>10328</td>
<td>sotho</td>
</tr>
<tr>
<th>8</th>
<td>makeleketla</td>
<td>40709</td>
<td>1.35</td>
<td>6629</td>
<td>sotho</td>
</tr>
<tr>
<th>9</th>
<td>masilo</td>
<td>40710</td>
<td>3.02</td>
<td>14903</td>
<td>sotho</td>
</tr>
<tr>
<th>10</th>
<td>star diamond mine</td>
<td>40712</td>
<td>0.11</td>
<td>212</td>
<td>sotho</td>
</tr>
<tr>
<th>11</th>
<td>theunissen</td>
<td>40713</td>
<td>15.11</td>
<td>1667</td>
<td>afrikaans</td>
</tr>
<tr>
<th>12</th>
<td>tshepong</td>
<td>40714</td>
<td>0.54</td>
<td>1710</td>
<td>sotho</td>
</tr>
<tr>
<th>13</th>
<td>verkeerdevlei</td>
<td>40715</td>
<td>1.22</td>
<td>151</td>
<td>afrikaans</td>
</tr>
<tr>
<th>14</th>
<td>winburg</td>
<td>40716</td>
<td>70.22</td>
<td>3371</td>
<td>sotho</td>
</tr>
<tr>
<th>15</th>
<td>remainder of the municipality</td>
<td>40711</td>
<td>6696.44</td>
<td>10304</td>
<td>sotho</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>remainder of the municipality</td>
</tr>
</tbody>
</table> | select place where population = 10304 <table_name> : table | | place | code | area (km2) | population | most spoken language |
|---:|:------------------------------|-------:|-------------:|-------------:|:-----------------------|
| 0 | beatrix mine | 40701 | 0.17 | 2492 | sotho |
| 1 | boipatong | 40702 | 0.31 | 1501 | sotho |
| 2 | brandfort | 40703 | 3.2 | 1516 | afrikaans |
| 3 | fora | 40704 | 0.05 | 530 | sotho |
| 4 | ikgomotseng | 40705 | 1.07 | 2254 | tswana |
| 5 | joel mine | 40706 | 0.11 | 728 | sotho |
| 6 | lusaka | 40707 | 1.4 | 6110 | sotho |
| 7 | majwemasweu | 40708 | 2.5 | 10328 | sotho |
| 8 | makeleketla | 40709 | 1.35 | 6629 | sotho |
| 9 | masilo | 40710 | 3.02 | 14903 | sotho |
| 10 | star diamond mine | 40712 | 0.11 | 212 | sotho |
| 11 | theunissen | 40713 | 15.11 | 1667 | afrikaans |
| 12 | tshepong | 40714 | 0.54 | 1710 | sotho |
| 13 | verkeerdevlei | 40715 | 1.22 | 151 | afrikaans |
| 14 | winburg | 40716 | 70.22 | 3371 | sotho |
| 15 | remainder of the municipality | 40711 | 6696.44 | 10304 | sotho | | | | place |
|---:|:------------------------------|
| 0 | remainder of the municipality | | [
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] |
select count ( coordinates ) where comments = 'none' col : site | municipality | comments | coordinates | type | ref. row 1 : kikkawa motoharu fortified residence gardens 吉川元春館跡庭園 kikkawa motoharu yakata ato teien | kitahiroshima | none | 34°43′01′′n 132°27′58′′e / 34.71697004°n 132.46599393°e | 1 | row 2 : former mantoku-in gardens 旧万徳院庭園 kyu-mantokuin teien | kitahiroshima | none | 34°43′27′′n 132°28′22′′e / 34.72423174°n 132.47265069°e | 1 | row 3 : itsukushima 厳島 itsukushima | hatsukaichi | also a special historic site; itsukushima jinja is inscribed on the unesco world heritage list | 34°16′16′′n 132°18′22′′e / 34.27116774°n 132.30612348°e | 8 | row 4 : sandan-kyo 三段峡 sandan-kyo | akiota/kitahiroshima | none | 34°36′57′′n 132°11′44′′e / 34.61573328°n 132.19561853°e | 3, 5, 6 | row 5 : shukkei-en 縮景園 shukukei-en | hiroshima | none | 34°24′02′′n 132°28′04′′e / 34.40050182°n 132.46770735°e | 1 | row 6 : jodo-ji gardens 浄土寺庭園 jodoji teien | onomichi | none | 34°24′44′′n 133°12′36′′e / 34.41222952°n 133.21012266°e | 1 | row 7 : taishaku-kyo 帝釈川の谷 (帝釈峡) taishaku-gawa no tani (taishaku-kyo) | shobara/jinsekikogen | none | 34°50′58′′n 133°13′23′′e / 34.8493628°n 133.2231609°e | 5, 6 | row 8 : peace memorial park 平和記念公園 heiwa kinen koen | hiroshima | the hiroshima peace memorial (genbaku dome) is inscribed on the unesco world heritage list | 34°23′34′′n 132°27′09′′e / 34.39284707°n 132.45251203°e | 1 | row 9 : tomo park 鞆公園 tomo koen | fukuyama | none | 34°23′01′′n 133°23′48′′e / 34.3835209°n 133.39662133°e | 1, 8 | | col : count ( "coordinates" ) row 1 : 7 | select count ( coordinates ) where comments = 'none' <table_name> : table \begin{tabular}{lllllll}
\toprule
& site & municipality & comments & coordinates & type & ref. \\
\midrule
0 & kikkawa motoharu fortified residence gardens 吉川元春館跡庭園 kikkawa motoharu yakata ato teien & kitahiroshima & none & 34°43′01′′n 132°27′58′′e / 34.71697004°n 132.46599393°e & 1 & \\
1 & former mantoku-in gardens 旧万徳院庭園 kyu-mantokuin teien & kitahiroshima & none & 34°43′27′′n 132°28′22′′e / 34.72423174°n 132.47265069°e & 1 & \\
2 & itsukushima 厳島 itsukushima & hatsukaichi & also a special historic site; itsukushima jinja is inscribed on the unesco world heritage list & 34°16′16′′n 132°18′22′′e / 34.27116774°n 132.30612348°e & 8 & \\
3 & sandan-kyo 三段峡 sandan-kyo & akiota/kitahiroshima & none & 34°36′57′′n 132°11′44′′e / 34.61573328°n 132.19561853°e & 3, 5, 6 & \\
4 & shukkei-en 縮景園 shukukei-en & hiroshima & none & 34°24′02′′n 132°28′04′′e / 34.40050182°n 132.46770735°e & 1 & \\
5 & jodo-ji gardens 浄土寺庭園 jodoji teien & onomichi & none & 34°24′44′′n 133°12′36′′e / 34.41222952°n 133.21012266°e & 1 & \\
6 & taishaku-kyo 帝釈川の谷 (帝釈峡) taishaku-gawa no tani (taishaku-kyo) & shobara/jinsekikogen & none & 34°50′58′′n 133°13′23′′e / 34.8493628°n 133.2231609°e & 5, 6 & \\
7 & peace memorial park 平和記念公園 heiwa kinen koen & hiroshima & the hiroshima peace memorial (genbaku dome) is inscribed on the unesco world heritage list & 34°23′34′′n 132°27′09′′e / 34.39284707°n 132.45251203°e & 1 & \\
8 & tomo park 鞆公園 tomo koen & fukuyama & none & 34°23′01′′n 133°23′48′′e / 34.3835209°n 133.39662133°e & 1, 8 | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "coordinates" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( coordinates ) where comments = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>site</th>
<th>municipality</th>
<th>comments</th>
<th>coordinates</th>
<th>type</th>
<th>ref.</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>kikkawa motoharu fortified residence gardens 吉川元春館跡庭園 kikkawa motoharu yakata ato teien</td>
<td>kitahiroshima</td>
<td>none</td>
<td>34°43′01′′n 132°27′58′′e / 34.71697004°n 132.46599393°e</td>
<td>1</td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>former mantoku-in gardens 旧万徳院庭園 kyu-mantokuin teien</td>
<td>kitahiroshima</td>
<td>none</td>
<td>34°43′27′′n 132°28′22′′e / 34.72423174°n 132.47265069°e</td>
<td>1</td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>itsukushima 厳島 itsukushima</td>
<td>hatsukaichi</td>
<td>also a special historic site; itsukushima jinja is inscribed on the unesco world heritage list</td>
<td>34°16′16′′n 132°18′22′′e / 34.27116774°n 132.30612348°e</td>
<td>8</td>
<td></td>
</tr>
<tr>
<th>3</th>
<td>sandan-kyo 三段峡 sandan-kyo</td>
<td>akiota/kitahiroshima</td>
<td>none</td>
<td>34°36′57′′n 132°11′44′′e / 34.61573328°n 132.19561853°e</td>
<td>3, 5, 6</td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>shukkei-en 縮景園 shukukei-en</td>
<td>hiroshima</td>
<td>none</td>
<td>34°24′02′′n 132°28′04′′e / 34.40050182°n 132.46770735°e</td>
<td>1</td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>jodo-ji gardens 浄土寺庭園 jodoji teien</td>
<td>onomichi</td>
<td>none</td>
<td>34°24′44′′n 133°12′36′′e / 34.41222952°n 133.21012266°e</td>
<td>1</td>
<td></td>
</tr>
<tr>
<th>6</th>
<td>taishaku-kyo 帝釈川の谷 (帝釈峡) taishaku-gawa no tani (taishaku-kyo)</td>
<td>shobara/jinsekikogen</td>
<td>none</td>
<td>34°50′58′′n 133°13′23′′e / 34.8493628°n 133.2231609°e</td>
<td>5, 6</td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>peace memorial park 平和記念公園 heiwa kinen koen</td>
<td>hiroshima</td>
<td>the hiroshima peace memorial (genbaku dome) is inscribed on the unesco world heritage list</td>
<td>34°23′34′′n 132°27′09′′e / 34.39284707°n 132.45251203°e</td>
<td>1</td>
<td></td>
</tr>
<tr>
<th>8</th>
<td>tomo park 鞆公園 tomo koen</td>
<td>fukuyama</td>
<td>none</td>
<td>34°23′01′′n 133°23′48′′e / 34.3835209°n 133.39662133°e</td>
<td>1, 8 |</td>
<td>None</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "coordinates" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( coordinates ) where comments = 'none' <table_name> : table | | site | municipality | comments | coordinates | type | ref. |
|---:|:------------------------------------------------------------------------------------------------|:---------------------|:-----------------------------------------------------------------------------------------------|:--------------------------------------------------------|:--------|:-------|
| 0 | kikkawa motoharu fortified residence gardens 吉川元春館跡庭園 kikkawa motoharu yakata ato teien | kitahiroshima | none | 34°43′01′′n 132°27′58′′e / 34.71697004°n 132.46599393°e | 1 | |
| 1 | former mantoku-in gardens 旧万徳院庭園 kyu-mantokuin teien | kitahiroshima | none | 34°43′27′′n 132°28′22′′e / 34.72423174°n 132.47265069°e | 1 | |
| 2 | itsukushima 厳島 itsukushima | hatsukaichi | also a special historic site; itsukushima jinja is inscribed on the unesco world heritage list | 34°16′16′′n 132°18′22′′e / 34.27116774°n 132.30612348°e | 8 | |
| 3 | sandan-kyo 三段峡 sandan-kyo | akiota/kitahiroshima | none | 34°36′57′′n 132°11′44′′e / 34.61573328°n 132.19561853°e | 3, 5, 6 | |
| 4 | shukkei-en 縮景園 shukukei-en | hiroshima | none | 34°24′02′′n 132°28′04′′e / 34.40050182°n 132.46770735°e | 1 | |
| 5 | jodo-ji gardens 浄土寺庭園 jodoji teien | onomichi | none | 34°24′44′′n 133°12′36′′e / 34.41222952°n 133.21012266°e | 1 | |
| 6 | taishaku-kyo 帝釈川の谷 (帝釈峡) taishaku-gawa no tani (taishaku-kyo) | shobara/jinsekikogen | none | 34°50′58′′n 133°13′23′′e / 34.8493628°n 133.2231609°e | 5, 6 | |
| 7 | peace memorial park 平和記念公園 heiwa kinen koen | hiroshima | the hiroshima peace memorial (genbaku dome) is inscribed on the unesco world heritage list | 34°23′34′′n 132°27′09′′e / 34.39284707°n 132.45251203°e | 1 | |
| 8 | tomo park 鞆公園 tomo koen | fukuyama | none | 34°23′01′′n 133°23′48′′e / 34.3835209°n 133.39662133°e | 1, 8 | | | | | | count ( "coordinates" ) |
|---:|--------------------------:|
| 0 | 7 | | [
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] |
select nation where nation = 'germany (ger)' col : rank | nation | gold | silver | bronze | total row 1 : 1 | russia (rus) | 3 | 1 | 1 | 5 row 2 : 2 | canada (can) | 2 | 0 | 0 | 2 row 3 : 3 | germany (ger) | 1 | 3 | 2 | 6 row 4 : 4 | france (fra) | 0 | 1 | 2 | 3 row 5 : 5 | belarus (blr) | 0 | 1 | 0 | 1 row 6 : 6 | ukraine (ukr) | 0 | 0 | 1 | 1 row 7 : none | total | 6 | 6 | 6 | 18 | col : nation row 1 : germany (ger) | select nation where nation = 'germany (ger)' <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & russia (rus) & 3 & 1 & 1 & 5 \\
1 & 2 & canada (can) & 2 & 0 & 0 & 2 \\
2 & 3 & germany (ger) & 1 & 3 & 2 & 6 \\
3 & 4 & france (fra) & 0 & 1 & 2 & 3 \\
4 & 5 & belarus (blr) & 0 & 1 & 0 & 1 \\
5 & 6 & ukraine (ukr) & 0 & 0 & 1 & 1 \\
6 & none & total & 6 & 6 & 6 & 18 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & germany (ger) \\
\bottomrule
\end{tabular}
| select nation where nation = 'germany (ger)' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>russia (rus)</td>
<td>3</td>
<td>1</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>canada (can)</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>germany (ger)</td>
<td>1</td>
<td>3</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>france (fra)</td>
<td>0</td>
<td>1</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>belarus (blr)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>ukraine (ukr)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
<td>total</td>
<td>6</td>
<td>6</td>
<td>6</td>
<td>18</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>germany (ger)</td>
</tr>
</tbody>
</table> | select nation where nation = 'germany (ger)' <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:--------------|-------:|---------:|---------:|--------:|
| 0 | 1 | russia (rus) | 3 | 1 | 1 | 5 |
| 1 | 2 | canada (can) | 2 | 0 | 0 | 2 |
| 2 | 3 | germany (ger) | 1 | 3 | 2 | 6 |
| 3 | 4 | france (fra) | 0 | 1 | 2 | 3 |
| 4 | 5 | belarus (blr) | 0 | 1 | 0 | 1 |
| 5 | 6 | ukraine (ukr) | 0 | 0 | 1 | 1 |
| 6 | none | total | 6 | 6 | 6 | 18 | | | | nation |
|---:|:--------------|
| 0 | germany (ger) | | [
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select count ( * ) where hangul = '런닝맨' col : year | title | hangul | network | further info row 1 : 2008 | pretty boys: a wrong situation | 꽃미남 아롱사태 | mnet | none row 2 : 2009 | let's go dream team! season 2 | 출발 드림팀2 | kbs2 | variety show row 3 : 2009-10 | music bank | 뮤직뱅크 | kbs2 | music show, as mc row 4 : 2010-11 | running man | 런닝맨 | sbs | variety show row 5 : 2011 | i'm real: song joong-ki | i'm real 송중기 | qtv | none row 6 : 2011 | everyone dramatic | 에브리원 드라마틱 | mbc | none row 7 : 2011 | made in u | 메이드 인 유 | jtbc | audition show, as mc row 8 : 2011-12 | tears of the antarctic | 남극의 눈물 | mbc | documentary, as narrator | col : count ( "*" ) row 1 : 1 | select count ( * ) where hangul = '런닝맨' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & title & hangul & network & further info \\
\midrule
0 & 2008 & pretty boys: a wrong situation & 꽃미남 아롱사태 & mnet & none \\
1 & 2009 & let's go dream team! season 2 & 출발 드림팀2 & kbs2 & variety show \\
2 & 2009-10 & music bank & 뮤직뱅크 & kbs2 & music show, as mc \\
3 & 2010-11 & running man & 런닝맨 & sbs & variety show \\
4 & 2011 & i'm real: song joong-ki & i'm real 송중기 & qtv & none \\
5 & 2011 & everyone dramatic & 에브리원 드라마틱 & mbc & none \\
6 & 2011 & made in u & 메이드 인 유 & jtbc & audition show, as mc \\
7 & 2011-12 & tears of the antarctic & 남극의 눈물 & mbc & documentary, as narrator \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where hangul = '런닝맨' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>title</th>
<th>hangul</th>
<th>network</th>
<th>further info</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2008</td>
<td>pretty boys: a wrong situation</td>
<td>꽃미남 아롱사태</td>
<td>mnet</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2009</td>
<td>let's go dream team! season 2</td>
<td>출발 드림팀2</td>
<td>kbs2</td>
<td>variety show</td>
</tr>
<tr>
<th>2</th>
<td>2009-10</td>
<td>music bank</td>
<td>뮤직뱅크</td>
<td>kbs2</td>
<td>music show, as mc</td>
</tr>
<tr>
<th>3</th>
<td>2010-11</td>
<td>running man</td>
<td>런닝맨</td>
<td>sbs</td>
<td>variety show</td>
</tr>
<tr>
<th>4</th>
<td>2011</td>
<td>i'm real: song joong-ki</td>
<td>i'm real 송중기</td>
<td>qtv</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2011</td>
<td>everyone dramatic</td>
<td>에브리원 드라마틱</td>
<td>mbc</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>2011</td>
<td>made in u</td>
<td>메이드 인 유</td>
<td>jtbc</td>
<td>audition show, as mc</td>
</tr>
<tr>
<th>7</th>
<td>2011-12</td>
<td>tears of the antarctic</td>
<td>남극의 눈물</td>
<td>mbc</td>
<td>documentary, as narrator</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where hangul = '런닝맨' <table_name> : table | | year | title | hangul | network | further info |
|---:|:--------|:-------------------------------|:------------------|:----------|:-------------------------|
| 0 | 2008 | pretty boys: a wrong situation | 꽃미남 아롱사태 | mnet | none |
| 1 | 2009 | let's go dream team! season 2 | 출발 드림팀2 | kbs2 | variety show |
| 2 | 2009-10 | music bank | 뮤직뱅크 | kbs2 | music show, as mc |
| 3 | 2010-11 | running man | 런닝맨 | sbs | variety show |
| 4 | 2011 | i'm real: song joong-ki | i'm real 송중기 | qtv | none |
| 5 | 2011 | everyone dramatic | 에브리원 드라마틱 | mbc | none |
| 6 | 2011 | made in u | 메이드 인 유 | jtbc | audition show, as mc |
| 7 | 2011-12 | tears of the antarctic | 남극의 눈물 | mbc | documentary, as narrator | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select nation where nation = 'hungary' col : place | nation | 5 hoops | 3 balls, 2 ribbons | total row 1 : 1 | bulgaria | 19.800 (1) | 19.800 (1) | 39.6 row 2 : 2 | spain | 19.700 (3) | 19.700 (2) | 39.4 row 3 : 3 | belarus | 19.733 (2) | 19.600 (3) | 39.333 row 4 : 4 | russia | 19.600 (4) | 19.566 (4) | 39.166 row 5 : 5 | ukraine | 19.366 (5) | 15.500 (5) | 38.866 row 6 : 6 | japan | 19.166 (6) | 19.333 (7) | 38.499 row 7 : 7 | italy | 19.066 (7) | 19.400 (6) | 38.466 row 8 : 8 | hungary | 18.766 (8) | 19.166 (8) | 37.932 | col : nation row 1 : hungary | select nation where nation = 'hungary' <table_name> : table \begin{tabular}{llllll}
\toprule
& place & nation & 5 hoops & 3 balls, 2 ribbons & total \\
\midrule
0 & 1 & bulgaria & 19.800 (1) & 19.800 (1) & 39.6 \\
1 & 2 & spain & 19.700 (3) & 19.700 (2) & 39.4 \\
2 & 3 & belarus & 19.733 (2) & 19.600 (3) & 39.333 \\
3 & 4 & russia & 19.600 (4) & 19.566 (4) & 39.166 \\
4 & 5 & ukraine & 19.366 (5) & 15.500 (5) & 38.866 \\
5 & 6 & japan & 19.166 (6) & 19.333 (7) & 38.499 \\
6 & 7 & italy & 19.066 (7) & 19.400 (6) & 38.466 \\
7 & 8 & hungary & 18.766 (8) & 19.166 (8) & 37.932 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& nation \\
\midrule
0 & hungary \\
\bottomrule
\end{tabular}
| select nation where nation = 'hungary' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>place</th>
<th>nation</th>
<th>5 hoops</th>
<th>3 balls, 2 ribbons</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>bulgaria</td>
<td>19.800 (1)</td>
<td>19.800 (1)</td>
<td>39.6</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>spain</td>
<td>19.700 (3)</td>
<td>19.700 (2)</td>
<td>39.4</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>belarus</td>
<td>19.733 (2)</td>
<td>19.600 (3)</td>
<td>39.333</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>russia</td>
<td>19.600 (4)</td>
<td>19.566 (4)</td>
<td>39.166</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>ukraine</td>
<td>19.366 (5)</td>
<td>15.500 (5)</td>
<td>38.866</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>japan</td>
<td>19.166 (6)</td>
<td>19.333 (7)</td>
<td>38.499</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>italy</td>
<td>19.066 (7)</td>
<td>19.400 (6)</td>
<td>38.466</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>hungary</td>
<td>18.766 (8)</td>
<td>19.166 (8)</td>
<td>37.932</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>nation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>hungary</td>
</tr>
</tbody>
</table> | select nation where nation = 'hungary' <table_name> : table | | place | nation | 5 hoops | 3 balls, 2 ribbons | total |
|---:|--------:|:---------|:-----------|:---------------------|--------:|
| 0 | 1 | bulgaria | 19.800 (1) | 19.800 (1) | 39.6 |
| 1 | 2 | spain | 19.700 (3) | 19.700 (2) | 39.4 |
| 2 | 3 | belarus | 19.733 (2) | 19.600 (3) | 39.333 |
| 3 | 4 | russia | 19.600 (4) | 19.566 (4) | 39.166 |
| 4 | 5 | ukraine | 19.366 (5) | 15.500 (5) | 38.866 |
| 5 | 6 | japan | 19.166 (6) | 19.333 (7) | 38.499 |
| 6 | 7 | italy | 19.066 (7) | 19.400 (6) | 38.466 |
| 7 | 8 | hungary | 18.766 (8) | 19.166 (8) | 37.932 | | | | nation |
|---:|:---------|
| 0 | hungary | | [
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select count ( season ) where score = 'central fc' col : season | winner | score | runners-up | venue row 1 : 2000 | san juan jabloteh | 1-0 | defence force | marvin lee stadium row 2 : 2001 | w connection | 1-0 | caledonia aia | manny ramjohn stadium row 3 : 2002 | defence force | 2-0 | w connection | hasely crawford stadium row 4 : 2003 | san juan jabloteh | 1-1 | w connection | manny ramjohn stadium row 5 : 2004 | w connection | 2-2 | defence force | manny ramjohn stadium row 6 : 2005 | w connection | 3-1 | san juan jabloteh | manny ramjohn stadium row 7 : 2006 | w connection | 3-1 | north east stars | manny ramjohn stadium row 8 : 2007 | w connection | 2-0 | caledonia aia | manny ramjohn stadium row 9 : 2008 | w connection | 2-2 | joe public | manny ramjohn stadium row 10 : 2009 | defence force | 1-0 | joe public | marvin lee stadium row 11 : 2010 | joe public | 1-1 | defence force | marvin lee stadium row 12 : 2011 | caledonia aia | 2-1 | t&tec | hasely crawford stadium row 13 : 2012 | caledonia aia | 2-1 | defence force | hasely crawford stadium row 14 : 2013 | central fc | 2-1 | defence force | hasely crawford stadium | col : count ( "season" ) row 1 : 0 | select count ( season ) where score = 'central fc' <table_name> : table \begin{tabular}{llllll}
\toprule
& season & winner & score & runners-up & venue \\
\midrule
0 & 2000 & san juan jabloteh & 1-0 & defence force & marvin lee stadium \\
1 & 2001 & w connection & 1-0 & caledonia aia & manny ramjohn stadium \\
2 & 2002 & defence force & 2-0 & w connection & hasely crawford stadium \\
3 & 2003 & san juan jabloteh & 1-1 & w connection & manny ramjohn stadium \\
4 & 2004 & w connection & 2-2 & defence force & manny ramjohn stadium \\
5 & 2005 & w connection & 3-1 & san juan jabloteh & manny ramjohn stadium \\
6 & 2006 & w connection & 3-1 & north east stars & manny ramjohn stadium \\
7 & 2007 & w connection & 2-0 & caledonia aia & manny ramjohn stadium \\
8 & 2008 & w connection & 2-2 & joe public & manny ramjohn stadium \\
9 & 2009 & defence force & 1-0 & joe public & marvin lee stadium \\
10 & 2010 & joe public & 1-1 & defence force & marvin lee stadium \\
11 & 2011 & caledonia aia & 2-1 & t&tec & hasely crawford stadium \\
12 & 2012 & caledonia aia & 2-1 & defence force & hasely crawford stadium \\
13 & 2013 & central fc & 2-1 & defence force & hasely crawford stadium \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "season" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( season ) where score = 'central fc' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>winner</th>
<th>score</th>
<th>runners-up</th>
<th>venue</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2000</td>
<td>san juan jabloteh</td>
<td>1-0</td>
<td>defence force</td>
<td>marvin lee stadium</td>
</tr>
<tr>
<th>1</th>
<td>2001</td>
<td>w connection</td>
<td>1-0</td>
<td>caledonia aia</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>2</th>
<td>2002</td>
<td>defence force</td>
<td>2-0</td>
<td>w connection</td>
<td>hasely crawford stadium</td>
</tr>
<tr>
<th>3</th>
<td>2003</td>
<td>san juan jabloteh</td>
<td>1-1</td>
<td>w connection</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>w connection</td>
<td>2-2</td>
<td>defence force</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>5</th>
<td>2005</td>
<td>w connection</td>
<td>3-1</td>
<td>san juan jabloteh</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>6</th>
<td>2006</td>
<td>w connection</td>
<td>3-1</td>
<td>north east stars</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>7</th>
<td>2007</td>
<td>w connection</td>
<td>2-0</td>
<td>caledonia aia</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>8</th>
<td>2008</td>
<td>w connection</td>
<td>2-2</td>
<td>joe public</td>
<td>manny ramjohn stadium</td>
</tr>
<tr>
<th>9</th>
<td>2009</td>
<td>defence force</td>
<td>1-0</td>
<td>joe public</td>
<td>marvin lee stadium</td>
</tr>
<tr>
<th>10</th>
<td>2010</td>
<td>joe public</td>
<td>1-1</td>
<td>defence force</td>
<td>marvin lee stadium</td>
</tr>
<tr>
<th>11</th>
<td>2011</td>
<td>caledonia aia</td>
<td>2-1</td>
<td>t&tec</td>
<td>hasely crawford stadium</td>
</tr>
<tr>
<th>12</th>
<td>2012</td>
<td>caledonia aia</td>
<td>2-1</td>
<td>defence force</td>
<td>hasely crawford stadium</td>
</tr>
<tr>
<th>13</th>
<td>2013</td>
<td>central fc</td>
<td>2-1</td>
<td>defence force</td>
<td>hasely crawford stadium</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "season" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( season ) where score = 'central fc' <table_name> : table | | season | winner | score | runners-up | venue |
|---:|---------:|:------------------|:--------|:------------------|:------------------------|
| 0 | 2000 | san juan jabloteh | 1-0 | defence force | marvin lee stadium |
| 1 | 2001 | w connection | 1-0 | caledonia aia | manny ramjohn stadium |
| 2 | 2002 | defence force | 2-0 | w connection | hasely crawford stadium |
| 3 | 2003 | san juan jabloteh | 1-1 | w connection | manny ramjohn stadium |
| 4 | 2004 | w connection | 2-2 | defence force | manny ramjohn stadium |
| 5 | 2005 | w connection | 3-1 | san juan jabloteh | manny ramjohn stadium |
| 6 | 2006 | w connection | 3-1 | north east stars | manny ramjohn stadium |
| 7 | 2007 | w connection | 2-0 | caledonia aia | manny ramjohn stadium |
| 8 | 2008 | w connection | 2-2 | joe public | manny ramjohn stadium |
| 9 | 2009 | defence force | 1-0 | joe public | marvin lee stadium |
| 10 | 2010 | joe public | 1-1 | defence force | marvin lee stadium |
| 11 | 2011 | caledonia aia | 2-1 | t&tec | hasely crawford stadium |
| 12 | 2012 | caledonia aia | 2-1 | defence force | hasely crawford stadium |
| 13 | 2013 | central fc | 2-1 | defence force | hasely crawford stadium | | | | count ( "season" ) |
|---:|---------------------:|
| 0 | 0 | | [
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select catalog where format = 'lp' col : region | date | label | format | catalog row 1 : united kingdom | 1985-06-10 00:00:00 | i.r.s | vinyl lp | mirf1003 row 2 : united states | 1985-06-11 00:00:00 | i.r.s | lp | irs-5592 row 3 : united states | 1985-06-11 00:00:00 | i.r.s | cassette tape | irsc-5592 row 4 : united states | 1985-06-11 00:00:00 | i.r.s | compact disc | irsd-5592 row 5 : greece | 1985-01-01 00:00:00 | illegal | lp | 26525 row 6 : australia | 1985-01-01 00:00:00 | i.r.s./epic | lp | elps 4495 row 7 : the netherlands | 1985-01-01 00:00:00 | i.r.s | lp | 26525 row 8 : worldwide | 1990-01-01 00:00:00 | mca | compact disc | 5592 row 9 : worldwide | 1990-01-01 00:00:00 | i.r.s | cassette tape | irsc-5592 row 10 : the netherlands | 1992-08-06 00:00:00 | emi | compact disc | 7 13160 2 9 row 11 : united kingdom | 1992-01-01 00:00:00 | simply vinyl | 180-gram vinyl lp | svlp151 row 12 : worldwide | 1998-01-01 00:00:00 | capitol | compact disc | 93479 row 13 : europe | 1998-01-01 00:00:00 | emi | compact disc | 13160 row 14 : worldwide | 1999-01-01 00:00:00 | i.r.s | compact disc | 19016 row 15 : united states | 1999-01-01 00:00:00 | simply vinyl | lp | 151 row 16 : europe | 2000-01-01 00:00:00 | i.r.s | compact disc | 7131602 | col : catalog row 1 : irs-5592 row 2 : 26525 row 3 : elps 4495 row 4 : 26525 row 5 : 151 | select catalog where format = 'lp' <table_name> : table \begin{tabular}{llllll}
\toprule
& region & date & label & format & catalog \\
\midrule
0 & united kingdom & 1985-06-10 00:00:00 & i.r.s & vinyl lp & mirf1003 \\
1 & united states & 1985-06-11 00:00:00 & i.r.s & lp & irs-5592 \\
2 & united states & 1985-06-11 00:00:00 & i.r.s & cassette tape & irsc-5592 \\
3 & united states & 1985-06-11 00:00:00 & i.r.s & compact disc & irsd-5592 \\
4 & greece & 1985-01-01 00:00:00 & illegal & lp & 26525 \\
5 & australia & 1985-01-01 00:00:00 & i.r.s./epic & lp & elps 4495 \\
6 & the netherlands & 1985-01-01 00:00:00 & i.r.s & lp & 26525 \\
7 & worldwide & 1990-01-01 00:00:00 & mca & compact disc & 5592 \\
8 & worldwide & 1990-01-01 00:00:00 & i.r.s & cassette tape & irsc-5592 \\
9 & the netherlands & 1992-08-06 00:00:00 & emi & compact disc & 7 13160 2 9 \\
10 & united kingdom & 1992-01-01 00:00:00 & simply vinyl & 180-gram vinyl lp & svlp151 \\
11 & worldwide & 1998-01-01 00:00:00 & capitol & compact disc & 93479 \\
12 & europe & 1998-01-01 00:00:00 & emi & compact disc & 13160 \\
13 & worldwide & 1999-01-01 00:00:00 & i.r.s & compact disc & 19016 \\
14 & united states & 1999-01-01 00:00:00 & simply vinyl & lp & 151 \\
15 & europe & 2000-01-01 00:00:00 & i.r.s & compact disc & 7131602 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& catalog \\
\midrule
0 & irs-5592 \\
1 & 26525 \\
2 & elps 4495 \\
3 & 26525 \\
4 & 151 \\
\bottomrule
\end{tabular}
| select catalog where format = 'lp' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>region</th>
<th>date</th>
<th>label</th>
<th>format</th>
<th>catalog</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>united kingdom</td>
<td>1985-06-10 00:00:00</td>
<td>i.r.s</td>
<td>vinyl lp</td>
<td>mirf1003</td>
</tr>
<tr>
<th>1</th>
<td>united states</td>
<td>1985-06-11 00:00:00</td>
<td>i.r.s</td>
<td>lp</td>
<td>irs-5592</td>
</tr>
<tr>
<th>2</th>
<td>united states</td>
<td>1985-06-11 00:00:00</td>
<td>i.r.s</td>
<td>cassette tape</td>
<td>irsc-5592</td>
</tr>
<tr>
<th>3</th>
<td>united states</td>
<td>1985-06-11 00:00:00</td>
<td>i.r.s</td>
<td>compact disc</td>
<td>irsd-5592</td>
</tr>
<tr>
<th>4</th>
<td>greece</td>
<td>1985-01-01 00:00:00</td>
<td>illegal</td>
<td>lp</td>
<td>26525</td>
</tr>
<tr>
<th>5</th>
<td>australia</td>
<td>1985-01-01 00:00:00</td>
<td>i.r.s./epic</td>
<td>lp</td>
<td>elps 4495</td>
</tr>
<tr>
<th>6</th>
<td>the netherlands</td>
<td>1985-01-01 00:00:00</td>
<td>i.r.s</td>
<td>lp</td>
<td>26525</td>
</tr>
<tr>
<th>7</th>
<td>worldwide</td>
<td>1990-01-01 00:00:00</td>
<td>mca</td>
<td>compact disc</td>
<td>5592</td>
</tr>
<tr>
<th>8</th>
<td>worldwide</td>
<td>1990-01-01 00:00:00</td>
<td>i.r.s</td>
<td>cassette tape</td>
<td>irsc-5592</td>
</tr>
<tr>
<th>9</th>
<td>the netherlands</td>
<td>1992-08-06 00:00:00</td>
<td>emi</td>
<td>compact disc</td>
<td>7 13160 2 9</td>
</tr>
<tr>
<th>10</th>
<td>united kingdom</td>
<td>1992-01-01 00:00:00</td>
<td>simply vinyl</td>
<td>180-gram vinyl lp</td>
<td>svlp151</td>
</tr>
<tr>
<th>11</th>
<td>worldwide</td>
<td>1998-01-01 00:00:00</td>
<td>capitol</td>
<td>compact disc</td>
<td>93479</td>
</tr>
<tr>
<th>12</th>
<td>europe</td>
<td>1998-01-01 00:00:00</td>
<td>emi</td>
<td>compact disc</td>
<td>13160</td>
</tr>
<tr>
<th>13</th>
<td>worldwide</td>
<td>1999-01-01 00:00:00</td>
<td>i.r.s</td>
<td>compact disc</td>
<td>19016</td>
</tr>
<tr>
<th>14</th>
<td>united states</td>
<td>1999-01-01 00:00:00</td>
<td>simply vinyl</td>
<td>lp</td>
<td>151</td>
</tr>
<tr>
<th>15</th>
<td>europe</td>
<td>2000-01-01 00:00:00</td>
<td>i.r.s</td>
<td>compact disc</td>
<td>7131602</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>catalog</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>irs-5592</td>
</tr>
<tr>
<th>1</th>
<td>26525</td>
</tr>
<tr>
<th>2</th>
<td>elps 4495</td>
</tr>
<tr>
<th>3</th>
<td>26525</td>
</tr>
<tr>
<th>4</th>
<td>151</td>
</tr>
</tbody>
</table> | select catalog where format = 'lp' <table_name> : table | | region | date | label | format | catalog |
|---:|:----------------|:--------------------|:-------------|:------------------|:------------|
| 0 | united kingdom | 1985-06-10 00:00:00 | i.r.s | vinyl lp | mirf1003 |
| 1 | united states | 1985-06-11 00:00:00 | i.r.s | lp | irs-5592 |
| 2 | united states | 1985-06-11 00:00:00 | i.r.s | cassette tape | irsc-5592 |
| 3 | united states | 1985-06-11 00:00:00 | i.r.s | compact disc | irsd-5592 |
| 4 | greece | 1985-01-01 00:00:00 | illegal | lp | 26525 |
| 5 | australia | 1985-01-01 00:00:00 | i.r.s./epic | lp | elps 4495 |
| 6 | the netherlands | 1985-01-01 00:00:00 | i.r.s | lp | 26525 |
| 7 | worldwide | 1990-01-01 00:00:00 | mca | compact disc | 5592 |
| 8 | worldwide | 1990-01-01 00:00:00 | i.r.s | cassette tape | irsc-5592 |
| 9 | the netherlands | 1992-08-06 00:00:00 | emi | compact disc | 7 13160 2 9 |
| 10 | united kingdom | 1992-01-01 00:00:00 | simply vinyl | 180-gram vinyl lp | svlp151 |
| 11 | worldwide | 1998-01-01 00:00:00 | capitol | compact disc | 93479 |
| 12 | europe | 1998-01-01 00:00:00 | emi | compact disc | 13160 |
| 13 | worldwide | 1999-01-01 00:00:00 | i.r.s | compact disc | 19016 |
| 14 | united states | 1999-01-01 00:00:00 | simply vinyl | lp | 151 |
| 15 | europe | 2000-01-01 00:00:00 | i.r.s | compact disc | 7131602 | | | | catalog |
|---:|:----------|
| 0 | irs-5592 |
| 1 | 26525 |
| 2 | elps 4495 |
| 3 | 26525 |
| 4 | 151 | | [
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select operator where notes = 'mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon' col : route number | terminals -1 | terminals -2 | via | operator | notes row 1 : 310 310a 311 | waltham cross bus station | hertford bus station | cheshunt, broxbourne, ware | arriva shires & essex, centrebus | mon-sat (310), mon-fri peaks (310a) row 2 : 323 | broxbourne station | essex road industrial estate | hoddesdon | sm coaches | mon-fri peak hours. herts cc contract. times row 3 : 392 | harlow town station | rye park old highway | nazeing, broxbourne | network harlow | mon-sat. essex cc contract. times row 4 : 641 | broxbourne station | hatfield business park | hertford, university of hertfordshire | uno | mon-fri university term time only row 5 : c3/c3a | waltham cross | harlow bus station | cheshunt, broxbourne | trustybus | mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon row 6 : c4 | waltham cross bus station | hertford bus station | cheshunt, ware | trustybus | sundays | col : operator row 1 : trustybus | select operator where notes = 'mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon' <table_name> : table \begin{tabular}{lllllll}
\toprule
& route number & terminals -1 & terminals -2 & via & operator & notes \\
\midrule
0 & 310 310a 311 & waltham cross bus station & hertford bus station & cheshunt, broxbourne, ware & arriva shires & essex, centrebus & mon-sat (310), mon-fri peaks (310a) \\
1 & 323 & broxbourne station & essex road industrial estate & hoddesdon & sm coaches & mon-fri peak hours. herts cc contract. times \\
2 & 392 & harlow town station & rye park old highway & nazeing, broxbourne & network harlow & mon-sat. essex cc contract. times \\
3 & 641 & broxbourne station & hatfield business park & hertford, university of hertfordshire & uno & mon-fri university term time only \\
4 & c3/c3a & waltham cross & harlow bus station & cheshunt, broxbourne & trustybus & mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon \\
5 & c4 & waltham cross bus station & hertford bus station & cheshunt, ware & trustybus & sundays \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& operator \\
\midrule
0 & trustybus \\
\bottomrule
\end{tabular}
| select operator where notes = 'mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>route number</th>
<th>terminals -1</th>
<th>terminals -2</th>
<th>via</th>
<th>operator</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>310 310a 311</td>
<td>waltham cross bus station</td>
<td>hertford bus station</td>
<td>cheshunt, broxbourne, ware</td>
<td>arriva shires & essex, centrebus</td>
<td>mon-sat (310), mon-fri peaks (310a)</td>
</tr>
<tr>
<th>1</th>
<td>323</td>
<td>broxbourne station</td>
<td>essex road industrial estate</td>
<td>hoddesdon</td>
<td>sm coaches</td>
<td>mon-fri peak hours. herts cc contract. times</td>
</tr>
<tr>
<th>2</th>
<td>392</td>
<td>harlow town station</td>
<td>rye park old highway</td>
<td>nazeing, broxbourne</td>
<td>network harlow</td>
<td>mon-sat. essex cc contract. times</td>
</tr>
<tr>
<th>3</th>
<td>641</td>
<td>broxbourne station</td>
<td>hatfield business park</td>
<td>hertford, university of hertfordshire</td>
<td>uno</td>
<td>mon-fri university term time only</td>
</tr>
<tr>
<th>4</th>
<td>c3/c3a</td>
<td>waltham cross</td>
<td>harlow bus station</td>
<td>cheshunt, broxbourne</td>
<td>trustybus</td>
<td>mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon</td>
</tr>
<tr>
<th>5</th>
<td>c4</td>
<td>waltham cross bus station</td>
<td>hertford bus station</td>
<td>cheshunt, ware</td>
<td>trustybus</td>
<td>sundays</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>operator</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>trustybus</td>
</tr>
</tbody>
</table> | select operator where notes = 'mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon' <table_name> : table | | route number | terminals -1 | terminals -2 | via | operator | notes |
|---:|:---------------|:--------------------------|:-----------------------------|:--------------------------------------|:---------------------------------|:--------------------------------------------------------------------------------------|
| 0 | 310 310a 311 | waltham cross bus station | hertford bus station | cheshunt, broxbourne, ware | arriva shires & essex, centrebus | mon-sat (310), mon-fri peaks (310a) |
| 1 | 323 | broxbourne station | essex road industrial estate | hoddesdon | sm coaches | mon-fri peak hours. herts cc contract. times |
| 2 | 392 | harlow town station | rye park old highway | nazeing, broxbourne | network harlow | mon-sat. essex cc contract. times |
| 3 | 641 | broxbourne station | hatfield business park | hertford, university of hertfordshire | uno | mon-fri university term time only |
| 4 | c3/c3a | waltham cross | harlow bus station | cheshunt, broxbourne | trustybus | mon-fri. 2 buses per hour operate to harlow. sat 1 bus per hour to harlow via hunsdon |
| 5 | c4 | waltham cross bus station | hertford bus station | cheshunt, ware | trustybus | sundays | | | | operator |
|---:|:-----------|
| 0 | trustybus | | [
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select kickoff where date = 'november 10' col : game | day | date | kickoff | opponent | results score | results record | location | attendance row 1 : 1 | sunday | november 10 | 3:05pm | at las vegas legends | l 3-7 | 0-1 | orleans arena | 1836 row 2 : 2 | sunday | november 17 | 1:05pm | monterrey flash | l 6-10 | 0-2 | unisantos park | 363 row 3 : 3 | saturday | november 23 | 7:05pm | at bay area rosal | w 10-7 | 1-2 | cabernet indoor sports | 652 row 4 : 4 | sunday | december 1 | 1:05pm | ontario fury | w 18-4 | 2-2 | unisantos park | 207 row 5 : 5 | saturday | december 14 | 7:05pm | at sacramento surge | w 7-6 (ot) | 3-2 | estadio azteca soccer arena | 215 row 6 : 6 | sunday | december 15 | 6:00pm | at bay area rosal | l 8-9 (ot) | 3-3 | cabernet indoor sports | 480 row 7 : 7 | sunday | december 22 | 1:05pm | turlock express | w 16-8 | 4-3 | unisantos park | 218 row 8 : 8 | saturday | january 4 | 7:05pm | at ontario fury | l 5-12 | 4-4 | citizens business bank arena | 2653 row 9 : 9 | sunday | january 5 | 1:05pm | san diego sockers | l 7-12 | 4-5 | unisantos park | 388 row 10 : 10 | sunday | january 12 | 1:05pm | las vegas legends | w 10-7 | 5-5 | unisantos park | 343 row 11 : 11 | sunday | january 19 | 1:05pm | bay area rosal | w 17-7 | 6-5 | unisantos park | 219 row 12 : 12 | sunday | january 26 | 1:05pm | sacramento surge | w 20-6 | 7-5 | unisantos park | 224 row 13 : 13 | saturday | february 1 | 7:05pm | at san diego sockers | l 5-6 | 7-6 | valley view casino center | 4954 row 14 : 14 | friday | february 7 | 7:05pm | at turlock express | l 6-9 | 7-7 | turlock soccer complex | 673 row 15 : 15 | saturday | february 8 | 7:05pm | at sacramento surge | w 10-6 | 8-7 | estadio azteca soccer arena | 323 row 16 : 16 | saturday | february 15 | 5:05pm | bay area rosal | w 27-2 | 9-7 | unisantos park | 118 | col : kickoff row 1 : 3:05pm | select kickoff where date = 'november 10' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& game & day & date & kickoff & opponent & results score & results record & location & attendance \\
\midrule
0 & 1 & sunday & november 10 & 3:05pm & at las vegas legends & l 3-7 & 0-1 & orleans arena & 1836 \\
1 & 2 & sunday & november 17 & 1:05pm & monterrey flash & l 6-10 & 0-2 & unisantos park & 363 \\
2 & 3 & saturday & november 23 & 7:05pm & at bay area rosal & w 10-7 & 1-2 & cabernet indoor sports & 652 \\
3 & 4 & sunday & december 1 & 1:05pm & ontario fury & w 18-4 & 2-2 & unisantos park & 207 \\
4 & 5 & saturday & december 14 & 7:05pm & at sacramento surge & w 7-6 (ot) & 3-2 & estadio azteca soccer arena & 215 \\
5 & 6 & sunday & december 15 & 6:00pm & at bay area rosal & l 8-9 (ot) & 3-3 & cabernet indoor sports & 480 \\
6 & 7 & sunday & december 22 & 1:05pm & turlock express & w 16-8 & 4-3 & unisantos park & 218 \\
7 & 8 & saturday & january 4 & 7:05pm & at ontario fury & l 5-12 & 4-4 & citizens business bank arena & 2653 \\
8 & 9 & sunday & january 5 & 1:05pm & san diego sockers & l 7-12 & 4-5 & unisantos park & 388 \\
9 & 10 & sunday & january 12 & 1:05pm & las vegas legends & w 10-7 & 5-5 & unisantos park & 343 \\
10 & 11 & sunday & january 19 & 1:05pm & bay area rosal & w 17-7 & 6-5 & unisantos park & 219 \\
11 & 12 & sunday & january 26 & 1:05pm & sacramento surge & w 20-6 & 7-5 & unisantos park & 224 \\
12 & 13 & saturday & february 1 & 7:05pm & at san diego sockers & l 5-6 & 7-6 & valley view casino center & 4954 \\
13 & 14 & friday & february 7 & 7:05pm & at turlock express & l 6-9 & 7-7 & turlock soccer complex & 673 \\
14 & 15 & saturday & february 8 & 7:05pm & at sacramento surge & w 10-6 & 8-7 & estadio azteca soccer arena & 323 \\
15 & 16 & saturday & february 15 & 5:05pm & bay area rosal & w 27-2 & 9-7 & unisantos park & 118 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& kickoff \\
\midrule
0 & 3:05pm \\
\bottomrule
\end{tabular}
| select kickoff where date = 'november 10' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>game</th>
<th>day</th>
<th>date</th>
<th>kickoff</th>
<th>opponent</th>
<th>results score</th>
<th>results record</th>
<th>location</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>sunday</td>
<td>november 10</td>
<td>3:05pm</td>
<td>at las vegas legends</td>
<td>l 3-7</td>
<td>0-1</td>
<td>orleans arena</td>
<td>1836</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>sunday</td>
<td>november 17</td>
<td>1:05pm</td>
<td>monterrey flash</td>
<td>l 6-10</td>
<td>0-2</td>
<td>unisantos park</td>
<td>363</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>saturday</td>
<td>november 23</td>
<td>7:05pm</td>
<td>at bay area rosal</td>
<td>w 10-7</td>
<td>1-2</td>
<td>cabernet indoor sports</td>
<td>652</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>sunday</td>
<td>december 1</td>
<td>1:05pm</td>
<td>ontario fury</td>
<td>w 18-4</td>
<td>2-2</td>
<td>unisantos park</td>
<td>207</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>saturday</td>
<td>december 14</td>
<td>7:05pm</td>
<td>at sacramento surge</td>
<td>w 7-6 (ot)</td>
<td>3-2</td>
<td>estadio azteca soccer arena</td>
<td>215</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>sunday</td>
<td>december 15</td>
<td>6:00pm</td>
<td>at bay area rosal</td>
<td>l 8-9 (ot)</td>
<td>3-3</td>
<td>cabernet indoor sports</td>
<td>480</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>sunday</td>
<td>december 22</td>
<td>1:05pm</td>
<td>turlock express</td>
<td>w 16-8</td>
<td>4-3</td>
<td>unisantos park</td>
<td>218</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>saturday</td>
<td>january 4</td>
<td>7:05pm</td>
<td>at ontario fury</td>
<td>l 5-12</td>
<td>4-4</td>
<td>citizens business bank arena</td>
<td>2653</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>sunday</td>
<td>january 5</td>
<td>1:05pm</td>
<td>san diego sockers</td>
<td>l 7-12</td>
<td>4-5</td>
<td>unisantos park</td>
<td>388</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>sunday</td>
<td>january 12</td>
<td>1:05pm</td>
<td>las vegas legends</td>
<td>w 10-7</td>
<td>5-5</td>
<td>unisantos park</td>
<td>343</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>sunday</td>
<td>january 19</td>
<td>1:05pm</td>
<td>bay area rosal</td>
<td>w 17-7</td>
<td>6-5</td>
<td>unisantos park</td>
<td>219</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>sunday</td>
<td>january 26</td>
<td>1:05pm</td>
<td>sacramento surge</td>
<td>w 20-6</td>
<td>7-5</td>
<td>unisantos park</td>
<td>224</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>saturday</td>
<td>february 1</td>
<td>7:05pm</td>
<td>at san diego sockers</td>
<td>l 5-6</td>
<td>7-6</td>
<td>valley view casino center</td>
<td>4954</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>friday</td>
<td>february 7</td>
<td>7:05pm</td>
<td>at turlock express</td>
<td>l 6-9</td>
<td>7-7</td>
<td>turlock soccer complex</td>
<td>673</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>saturday</td>
<td>february 8</td>
<td>7:05pm</td>
<td>at sacramento surge</td>
<td>w 10-6</td>
<td>8-7</td>
<td>estadio azteca soccer arena</td>
<td>323</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>saturday</td>
<td>february 15</td>
<td>5:05pm</td>
<td>bay area rosal</td>
<td>w 27-2</td>
<td>9-7</td>
<td>unisantos park</td>
<td>118</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>kickoff</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>3:05pm</td>
</tr>
</tbody>
</table> | select kickoff where date = 'november 10' <table_name> : table | | game | day | date | kickoff | opponent | results score | results record | location | attendance |
|---:|-------:|:---------|:------------|:----------|:---------------------|:----------------|:-----------------|:-----------------------------|-------------:|
| 0 | 1 | sunday | november 10 | 3:05pm | at las vegas legends | l 3-7 | 0-1 | orleans arena | 1836 |
| 1 | 2 | sunday | november 17 | 1:05pm | monterrey flash | l 6-10 | 0-2 | unisantos park | 363 |
| 2 | 3 | saturday | november 23 | 7:05pm | at bay area rosal | w 10-7 | 1-2 | cabernet indoor sports | 652 |
| 3 | 4 | sunday | december 1 | 1:05pm | ontario fury | w 18-4 | 2-2 | unisantos park | 207 |
| 4 | 5 | saturday | december 14 | 7:05pm | at sacramento surge | w 7-6 (ot) | 3-2 | estadio azteca soccer arena | 215 |
| 5 | 6 | sunday | december 15 | 6:00pm | at bay area rosal | l 8-9 (ot) | 3-3 | cabernet indoor sports | 480 |
| 6 | 7 | sunday | december 22 | 1:05pm | turlock express | w 16-8 | 4-3 | unisantos park | 218 |
| 7 | 8 | saturday | january 4 | 7:05pm | at ontario fury | l 5-12 | 4-4 | citizens business bank arena | 2653 |
| 8 | 9 | sunday | january 5 | 1:05pm | san diego sockers | l 7-12 | 4-5 | unisantos park | 388 |
| 9 | 10 | sunday | january 12 | 1:05pm | las vegas legends | w 10-7 | 5-5 | unisantos park | 343 |
| 10 | 11 | sunday | january 19 | 1:05pm | bay area rosal | w 17-7 | 6-5 | unisantos park | 219 |
| 11 | 12 | sunday | january 26 | 1:05pm | sacramento surge | w 20-6 | 7-5 | unisantos park | 224 |
| 12 | 13 | saturday | february 1 | 7:05pm | at san diego sockers | l 5-6 | 7-6 | valley view casino center | 4954 |
| 13 | 14 | friday | february 7 | 7:05pm | at turlock express | l 6-9 | 7-7 | turlock soccer complex | 673 |
| 14 | 15 | saturday | february 8 | 7:05pm | at sacramento surge | w 10-6 | 8-7 | estadio azteca soccer arena | 323 |
| 15 | 16 | saturday | february 15 | 5:05pm | bay area rosal | w 27-2 | 9-7 | unisantos park | 118 | | | | kickoff |
|---:|:----------|
| 0 | 3:05pm | | [
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] |
select count ( * ) where unsung hero = 'none' col : year | mvp | defensive player of the year | unsung hero | newcomer of the year row 1 : 1993 | patrice ferri | none | none | none row 2 : 1994 | jean harbor | none | none | none row 3 : 1995 | lloyd barker | none | none | none row 4 : 1996 | paolo ceccarelli | none | none | none row 5 : 1997 | mauro biello | none | none | none row 6 : 1998 | mauro biello | none | none | none row 7 : 1999 | none | none | none | none row 8 : 2000 | jim larkin | none | none | none row 9 : 2001 | mauro biello | none | none | none row 10 : 2002 | eduardo sebrango | gabriel gervais | jason ditullio | ze roberto row 11 : 2003 | greg sutton | gabriel gervais | david fronimadis | martin nash row 12 : 2004 | gabriel gervais | greg sutton | ze roberto | sandro grande row 13 : 2005 | mauro biello | nevio pizzolitto | mauricio vincello | masahiro fukazawa row 14 : 2006 | mauricio vincello | gabriel gervais | andrew weber | leonardo di lorenzo row 15 : 2007 | leonardo di lorenzo | mauricio vincello | simon gatti | matt jordan row 16 : 2008 | matt jordan | nevio pizzolitto | joey gjertsen | stefano pesoli row 17 : 2009 | david testo | nevio pizzolitto | adam braz | stephen deroux row 18 : 2010 | philippe billy | philippe billy | tony donatelli | ali gerba row 19 : 2011 | hassoun camara | evan bush | simon gatti | ian westlake / sinisa ubiparipovic | col : count ( "*" ) row 1 : 9 | select count ( * ) where unsung hero = 'none' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & mvp & defensive player of the year & unsung hero & newcomer of the year \\
\midrule
0 & 1993 & patrice ferri & none & none & none \\
1 & 1994 & jean harbor & none & none & none \\
2 & 1995 & lloyd barker & none & none & none \\
3 & 1996 & paolo ceccarelli & none & none & none \\
4 & 1997 & mauro biello & none & none & none \\
5 & 1998 & mauro biello & none & none & none \\
6 & 1999 & none & none & none & none \\
7 & 2000 & jim larkin & none & none & none \\
8 & 2001 & mauro biello & none & none & none \\
9 & 2002 & eduardo sebrango & gabriel gervais & jason ditullio & ze roberto \\
10 & 2003 & greg sutton & gabriel gervais & david fronimadis & martin nash \\
11 & 2004 & gabriel gervais & greg sutton & ze roberto & sandro grande \\
12 & 2005 & mauro biello & nevio pizzolitto & mauricio vincello & masahiro fukazawa \\
13 & 2006 & mauricio vincello & gabriel gervais & andrew weber & leonardo di lorenzo \\
14 & 2007 & leonardo di lorenzo & mauricio vincello & simon gatti & matt jordan \\
15 & 2008 & matt jordan & nevio pizzolitto & joey gjertsen & stefano pesoli \\
16 & 2009 & david testo & nevio pizzolitto & adam braz & stephen deroux \\
17 & 2010 & philippe billy & philippe billy & tony donatelli & ali gerba \\
18 & 2011 & hassoun camara & evan bush & simon gatti & ian westlake / sinisa ubiparipovic \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 9 \\
\bottomrule
\end{tabular}
| select count ( * ) where unsung hero = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>mvp</th>
<th>defensive player of the year</th>
<th>unsung hero</th>
<th>newcomer of the year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1993</td>
<td>patrice ferri</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1994</td>
<td>jean harbor</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1995</td>
<td>lloyd barker</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>1996</td>
<td>paolo ceccarelli</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>1997</td>
<td>mauro biello</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1998</td>
<td>mauro biello</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1999</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>2000</td>
<td>jim larkin</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2001</td>
<td>mauro biello</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2002</td>
<td>eduardo sebrango</td>
<td>gabriel gervais</td>
<td>jason ditullio</td>
<td>ze roberto</td>
</tr>
<tr>
<th>10</th>
<td>2003</td>
<td>greg sutton</td>
<td>gabriel gervais</td>
<td>david fronimadis</td>
<td>martin nash</td>
</tr>
<tr>
<th>11</th>
<td>2004</td>
<td>gabriel gervais</td>
<td>greg sutton</td>
<td>ze roberto</td>
<td>sandro grande</td>
</tr>
<tr>
<th>12</th>
<td>2005</td>
<td>mauro biello</td>
<td>nevio pizzolitto</td>
<td>mauricio vincello</td>
<td>masahiro fukazawa</td>
</tr>
<tr>
<th>13</th>
<td>2006</td>
<td>mauricio vincello</td>
<td>gabriel gervais</td>
<td>andrew weber</td>
<td>leonardo di lorenzo</td>
</tr>
<tr>
<th>14</th>
<td>2007</td>
<td>leonardo di lorenzo</td>
<td>mauricio vincello</td>
<td>simon gatti</td>
<td>matt jordan</td>
</tr>
<tr>
<th>15</th>
<td>2008</td>
<td>matt jordan</td>
<td>nevio pizzolitto</td>
<td>joey gjertsen</td>
<td>stefano pesoli</td>
</tr>
<tr>
<th>16</th>
<td>2009</td>
<td>david testo</td>
<td>nevio pizzolitto</td>
<td>adam braz</td>
<td>stephen deroux</td>
</tr>
<tr>
<th>17</th>
<td>2010</td>
<td>philippe billy</td>
<td>philippe billy</td>
<td>tony donatelli</td>
<td>ali gerba</td>
</tr>
<tr>
<th>18</th>
<td>2011</td>
<td>hassoun camara</td>
<td>evan bush</td>
<td>simon gatti</td>
<td>ian westlake / sinisa ubiparipovic</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>9</td>
</tr>
</tbody>
</table> | select count ( * ) where unsung hero = 'none' <table_name> : table | | year | mvp | defensive player of the year | unsung hero | newcomer of the year |
|---:|-------:|:--------------------|:-------------------------------|:------------------|:-----------------------------------|
| 0 | 1993 | patrice ferri | none | none | none |
| 1 | 1994 | jean harbor | none | none | none |
| 2 | 1995 | lloyd barker | none | none | none |
| 3 | 1996 | paolo ceccarelli | none | none | none |
| 4 | 1997 | mauro biello | none | none | none |
| 5 | 1998 | mauro biello | none | none | none |
| 6 | 1999 | none | none | none | none |
| 7 | 2000 | jim larkin | none | none | none |
| 8 | 2001 | mauro biello | none | none | none |
| 9 | 2002 | eduardo sebrango | gabriel gervais | jason ditullio | ze roberto |
| 10 | 2003 | greg sutton | gabriel gervais | david fronimadis | martin nash |
| 11 | 2004 | gabriel gervais | greg sutton | ze roberto | sandro grande |
| 12 | 2005 | mauro biello | nevio pizzolitto | mauricio vincello | masahiro fukazawa |
| 13 | 2006 | mauricio vincello | gabriel gervais | andrew weber | leonardo di lorenzo |
| 14 | 2007 | leonardo di lorenzo | mauricio vincello | simon gatti | matt jordan |
| 15 | 2008 | matt jordan | nevio pizzolitto | joey gjertsen | stefano pesoli |
| 16 | 2009 | david testo | nevio pizzolitto | adam braz | stephen deroux |
| 17 | 2010 | philippe billy | philippe billy | tony donatelli | ali gerba |
| 18 | 2011 | hassoun camara | evan bush | simon gatti | ian westlake / sinisa ubiparipovic | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 9 | | [
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select count ( * ) where name = 'kirkby' and status = 'civil parish' col : name | status | population | district | former local authority row 1 : cronton | civil parish | 1379 | knowsley | whiston rural district row 2 : halewood | town | 20309 | knowsley | whiston rural district row 3 : huyton with roby | unparished area | 49859 | knowsley | huyton with roby urban district row 4 : kirkby | unparished area | 40374 | knowsley | kirkby urban district row 5 : knowsley | civil parish | 11343 | knowsley | whiston rural district row 6 : prescot | town | 11184 | knowsley | prescot urban district row 7 : tarbock | civil parish | 2382 | knowsley | whiston rural district row 8 : whiston | town | 13629 | knowsley | whiston rural district row 9 : liverpool | unparished area | 439473 | liverpool | liverpool county borough row 10 : aintree village | civil parish | 7126 | sefton | west lancashire rural district row 11 : bootle | unparished area | 59011 | sefton | bootle county borough row 12 : crosby | unparished area | 45872 | sefton | crosby municipal borough row 13 : formby | civil parish | 23586 | sefton | formby urban district row 14 : hightown | civil parish | 2247 | sefton | crosby municipal borough row 15 : ince blundell | civil parish | 518 | sefton | west lancashire rural district row 16 : litherland | unparished area | 18629 | sefton | litherland urban district row 17 : little altcar | civil parish | 892 | sefton | west lancashire rural district row 18 : lydiate | civil parish | 6672 | sefton | west lancashire rural district row 19 : maghull | town | 22225 | sefton | west lancashire rural district row 20 : melling | civil parish | 2810 | sefton | west lancashire rural district row 21 : sefton | civil parish | 772 | sefton | west lancashire rural district row 22 : southport | unparished area | 90336 | sefton | southport county borough row 23 : thornton | civil parish | 2262 | sefton | west lancashire rural district row 24 : billinge chapel end | civil parish | 6554 | st helens | billinge and winstanley urban district row 25 : bold | civil parish | 2283 | st helens | whiston rural district row 26 : eccleston | civil parish | 10528 | st helens | whiston rural district row 27 : haydock | unparished area | 15684 | st helens | haydock urban district row 28 : newton le willows | unparished area | 21418 | st helens | newton le willows urban district row 29 : rainford | civil parish | 8344 | st helens | rainford urban district row 30 : rainhill | civil parish | 11913 | st helens | whiston rural district row 31 : seneley green | civil parish | 6163 | st helens | ashton in makerfield urban district row 32 : st helens | unparished area | 91414 | st helens | st helens county borough row 33 : windle | civil parish | 2542 | st helens | whiston rural district row 34 : bebington | unparished area | 58226 | wirral | bebington municipal borough row 35 : birkenhead | unparished area | 103206 | wirral | birkenhead county borough row 36 : heswall | unparished area | 29977 | wirral | wirral urban district row 37 : hoylake | unparished area | 35655 | wirral | hoylake urban district row 38 : wallasey | unparished area | 84348 | wirral | wallasey county borough | col : count ( "*" ) row 1 : 0 | select count ( * ) where name = 'kirkby' and status = 'civil parish' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & status & population & district & former local authority \\
\midrule
0 & cronton & civil parish & 1379 & knowsley & whiston rural district \\
1 & halewood & town & 20309 & knowsley & whiston rural district \\
2 & huyton with roby & unparished area & 49859 & knowsley & huyton with roby urban district \\
3 & kirkby & unparished area & 40374 & knowsley & kirkby urban district \\
4 & knowsley & civil parish & 11343 & knowsley & whiston rural district \\
5 & prescot & town & 11184 & knowsley & prescot urban district \\
6 & tarbock & civil parish & 2382 & knowsley & whiston rural district \\
7 & whiston & town & 13629 & knowsley & whiston rural district \\
8 & liverpool & unparished area & 439473 & liverpool & liverpool county borough \\
9 & aintree village & civil parish & 7126 & sefton & west lancashire rural district \\
10 & bootle & unparished area & 59011 & sefton & bootle county borough \\
11 & crosby & unparished area & 45872 & sefton & crosby municipal borough \\
12 & formby & civil parish & 23586 & sefton & formby urban district \\
13 & hightown & civil parish & 2247 & sefton & crosby municipal borough \\
14 & ince blundell & civil parish & 518 & sefton & west lancashire rural district \\
15 & litherland & unparished area & 18629 & sefton & litherland urban district \\
16 & little altcar & civil parish & 892 & sefton & west lancashire rural district \\
17 & lydiate & civil parish & 6672 & sefton & west lancashire rural district \\
18 & maghull & town & 22225 & sefton & west lancashire rural district \\
19 & melling & civil parish & 2810 & sefton & west lancashire rural district \\
20 & sefton & civil parish & 772 & sefton & west lancashire rural district \\
21 & southport & unparished area & 90336 & sefton & southport county borough \\
22 & thornton & civil parish & 2262 & sefton & west lancashire rural district \\
23 & billinge chapel end & civil parish & 6554 & st helens & billinge and winstanley urban district \\
24 & bold & civil parish & 2283 & st helens & whiston rural district \\
25 & eccleston & civil parish & 10528 & st helens & whiston rural district \\
26 & haydock & unparished area & 15684 & st helens & haydock urban district \\
27 & newton le willows & unparished area & 21418 & st helens & newton le willows urban district \\
28 & rainford & civil parish & 8344 & st helens & rainford urban district \\
29 & rainhill & civil parish & 11913 & st helens & whiston rural district \\
30 & seneley green & civil parish & 6163 & st helens & ashton in makerfield urban district \\
31 & st helens & unparished area & 91414 & st helens & st helens county borough \\
32 & windle & civil parish & 2542 & st helens & whiston rural district \\
33 & bebington & unparished area & 58226 & wirral & bebington municipal borough \\
34 & birkenhead & unparished area & 103206 & wirral & birkenhead county borough \\
35 & heswall & unparished area & 29977 & wirral & wirral urban district \\
36 & hoylake & unparished area & 35655 & wirral & hoylake urban district \\
37 & wallasey & unparished area & 84348 & wirral & wallasey county borough \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( * ) where name = 'kirkby' and status = 'civil parish' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>status</th>
<th>population</th>
<th>district</th>
<th>former local authority</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>cronton</td>
<td>civil parish</td>
<td>1379</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>1</th>
<td>halewood</td>
<td>town</td>
<td>20309</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>2</th>
<td>huyton with roby</td>
<td>unparished area</td>
<td>49859</td>
<td>knowsley</td>
<td>huyton with roby urban district</td>
</tr>
<tr>
<th>3</th>
<td>kirkby</td>
<td>unparished area</td>
<td>40374</td>
<td>knowsley</td>
<td>kirkby urban district</td>
</tr>
<tr>
<th>4</th>
<td>knowsley</td>
<td>civil parish</td>
<td>11343</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>5</th>
<td>prescot</td>
<td>town</td>
<td>11184</td>
<td>knowsley</td>
<td>prescot urban district</td>
</tr>
<tr>
<th>6</th>
<td>tarbock</td>
<td>civil parish</td>
<td>2382</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>7</th>
<td>whiston</td>
<td>town</td>
<td>13629</td>
<td>knowsley</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>8</th>
<td>liverpool</td>
<td>unparished area</td>
<td>439473</td>
<td>liverpool</td>
<td>liverpool county borough</td>
</tr>
<tr>
<th>9</th>
<td>aintree village</td>
<td>civil parish</td>
<td>7126</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>10</th>
<td>bootle</td>
<td>unparished area</td>
<td>59011</td>
<td>sefton</td>
<td>bootle county borough</td>
</tr>
<tr>
<th>11</th>
<td>crosby</td>
<td>unparished area</td>
<td>45872</td>
<td>sefton</td>
<td>crosby municipal borough</td>
</tr>
<tr>
<th>12</th>
<td>formby</td>
<td>civil parish</td>
<td>23586</td>
<td>sefton</td>
<td>formby urban district</td>
</tr>
<tr>
<th>13</th>
<td>hightown</td>
<td>civil parish</td>
<td>2247</td>
<td>sefton</td>
<td>crosby municipal borough</td>
</tr>
<tr>
<th>14</th>
<td>ince blundell</td>
<td>civil parish</td>
<td>518</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>15</th>
<td>litherland</td>
<td>unparished area</td>
<td>18629</td>
<td>sefton</td>
<td>litherland urban district</td>
</tr>
<tr>
<th>16</th>
<td>little altcar</td>
<td>civil parish</td>
<td>892</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>17</th>
<td>lydiate</td>
<td>civil parish</td>
<td>6672</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>18</th>
<td>maghull</td>
<td>town</td>
<td>22225</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>19</th>
<td>melling</td>
<td>civil parish</td>
<td>2810</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>20</th>
<td>sefton</td>
<td>civil parish</td>
<td>772</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>21</th>
<td>southport</td>
<td>unparished area</td>
<td>90336</td>
<td>sefton</td>
<td>southport county borough</td>
</tr>
<tr>
<th>22</th>
<td>thornton</td>
<td>civil parish</td>
<td>2262</td>
<td>sefton</td>
<td>west lancashire rural district</td>
</tr>
<tr>
<th>23</th>
<td>billinge chapel end</td>
<td>civil parish</td>
<td>6554</td>
<td>st helens</td>
<td>billinge and winstanley urban district</td>
</tr>
<tr>
<th>24</th>
<td>bold</td>
<td>civil parish</td>
<td>2283</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>25</th>
<td>eccleston</td>
<td>civil parish</td>
<td>10528</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>26</th>
<td>haydock</td>
<td>unparished area</td>
<td>15684</td>
<td>st helens</td>
<td>haydock urban district</td>
</tr>
<tr>
<th>27</th>
<td>newton le willows</td>
<td>unparished area</td>
<td>21418</td>
<td>st helens</td>
<td>newton le willows urban district</td>
</tr>
<tr>
<th>28</th>
<td>rainford</td>
<td>civil parish</td>
<td>8344</td>
<td>st helens</td>
<td>rainford urban district</td>
</tr>
<tr>
<th>29</th>
<td>rainhill</td>
<td>civil parish</td>
<td>11913</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>30</th>
<td>seneley green</td>
<td>civil parish</td>
<td>6163</td>
<td>st helens</td>
<td>ashton in makerfield urban district</td>
</tr>
<tr>
<th>31</th>
<td>st helens</td>
<td>unparished area</td>
<td>91414</td>
<td>st helens</td>
<td>st helens county borough</td>
</tr>
<tr>
<th>32</th>
<td>windle</td>
<td>civil parish</td>
<td>2542</td>
<td>st helens</td>
<td>whiston rural district</td>
</tr>
<tr>
<th>33</th>
<td>bebington</td>
<td>unparished area</td>
<td>58226</td>
<td>wirral</td>
<td>bebington municipal borough</td>
</tr>
<tr>
<th>34</th>
<td>birkenhead</td>
<td>unparished area</td>
<td>103206</td>
<td>wirral</td>
<td>birkenhead county borough</td>
</tr>
<tr>
<th>35</th>
<td>heswall</td>
<td>unparished area</td>
<td>29977</td>
<td>wirral</td>
<td>wirral urban district</td>
</tr>
<tr>
<th>36</th>
<td>hoylake</td>
<td>unparished area</td>
<td>35655</td>
<td>wirral</td>
<td>hoylake urban district</td>
</tr>
<tr>
<th>37</th>
<td>wallasey</td>
<td>unparished area</td>
<td>84348</td>
<td>wirral</td>
<td>wallasey county borough</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( * ) where name = 'kirkby' and status = 'civil parish' <table_name> : table | | name | status | population | district | former local authority |
|---:|:--------------------|:----------------|-------------:|:-----------|:---------------------------------------|
| 0 | cronton | civil parish | 1379 | knowsley | whiston rural district |
| 1 | halewood | town | 20309 | knowsley | whiston rural district |
| 2 | huyton with roby | unparished area | 49859 | knowsley | huyton with roby urban district |
| 3 | kirkby | unparished area | 40374 | knowsley | kirkby urban district |
| 4 | knowsley | civil parish | 11343 | knowsley | whiston rural district |
| 5 | prescot | town | 11184 | knowsley | prescot urban district |
| 6 | tarbock | civil parish | 2382 | knowsley | whiston rural district |
| 7 | whiston | town | 13629 | knowsley | whiston rural district |
| 8 | liverpool | unparished area | 439473 | liverpool | liverpool county borough |
| 9 | aintree village | civil parish | 7126 | sefton | west lancashire rural district |
| 10 | bootle | unparished area | 59011 | sefton | bootle county borough |
| 11 | crosby | unparished area | 45872 | sefton | crosby municipal borough |
| 12 | formby | civil parish | 23586 | sefton | formby urban district |
| 13 | hightown | civil parish | 2247 | sefton | crosby municipal borough |
| 14 | ince blundell | civil parish | 518 | sefton | west lancashire rural district |
| 15 | litherland | unparished area | 18629 | sefton | litherland urban district |
| 16 | little altcar | civil parish | 892 | sefton | west lancashire rural district |
| 17 | lydiate | civil parish | 6672 | sefton | west lancashire rural district |
| 18 | maghull | town | 22225 | sefton | west lancashire rural district |
| 19 | melling | civil parish | 2810 | sefton | west lancashire rural district |
| 20 | sefton | civil parish | 772 | sefton | west lancashire rural district |
| 21 | southport | unparished area | 90336 | sefton | southport county borough |
| 22 | thornton | civil parish | 2262 | sefton | west lancashire rural district |
| 23 | billinge chapel end | civil parish | 6554 | st helens | billinge and winstanley urban district |
| 24 | bold | civil parish | 2283 | st helens | whiston rural district |
| 25 | eccleston | civil parish | 10528 | st helens | whiston rural district |
| 26 | haydock | unparished area | 15684 | st helens | haydock urban district |
| 27 | newton le willows | unparished area | 21418 | st helens | newton le willows urban district |
| 28 | rainford | civil parish | 8344 | st helens | rainford urban district |
| 29 | rainhill | civil parish | 11913 | st helens | whiston rural district |
| 30 | seneley green | civil parish | 6163 | st helens | ashton in makerfield urban district |
| 31 | st helens | unparished area | 91414 | st helens | st helens county borough |
| 32 | windle | civil parish | 2542 | st helens | whiston rural district |
| 33 | bebington | unparished area | 58226 | wirral | bebington municipal borough |
| 34 | birkenhead | unparished area | 103206 | wirral | birkenhead county borough |
| 35 | heswall | unparished area | 29977 | wirral | wirral urban district |
| 36 | hoylake | unparished area | 35655 | wirral | hoylake urban district |
| 37 | wallasey | unparished area | 84348 | wirral | wallasey county borough | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 0 | | [
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select year where company = 'at&t' col : year | company | number of members affected | duration of strike | notes row 1 : 1955 | southern bell telephone co | 50000 | 72 days | strike was in answer to management's effort to prohibit workers from striking row 2 : 1968 | at&t | 200000 | 18 days | wage increases to compensate for cost of living, and medical benefits won row 3 : 1971 | bell system | 400000 | 1 week | cost of living allowance (cola) won for workers row 4 : 1983 | bell system | 600000 | 22 days | last contract with the bell system before its breakup. bell system sought givebacks. the contract resulted in wage increases, employment security, pension, and health improvements row 5 : 1986 | at&t | 175000 | 25 days | cola clause suspended in contract - former bell system contracts vary substantially from the at&t contract row 6 : 1989 | at&t | 175000 | none | child and elder care benefits added to contract. cola clause removed from contract row 7 : 1989 | nynex | 175000 | 17 weeks | strike was due to major health care cuts by nynex row 8 : 1998 | us west | 34000 | 15 day | strike was due to mandatory overtime demands and forced pay-for-performance plan. overtime caps were won row 9 : 2000 | verizon | 80000 | 3 weeks | strike was due to mandatory overtime demands. provisions for stress were won row 10 : 2011 | verizon | 45000 | 13 days | strike was due to major wage and health care cuts by verizon, a forced pay-for-performance plan and movement-of-work job security provisions. contract extended row 11 : 2012 | at&t | 20000 | 2 days | at&t west; california, nevada, and at&t east; connecticut - unfair labor practice strike during contract negotiations | col : year row 1 : 1968 row 2 : 1986 row 3 : 1989 row 4 : 2012 | select year where company = 'at&t' <table_name> : table \begin{tabular}{llllll}
\toprule
& year & company & number of members affected & duration of strike & notes \\
\midrule
0 & 1955 & southern bell telephone co & 50000 & 72 days & strike was in answer to management's effort to prohibit workers from striking \\
1 & 1968 & at&t & 200000 & 18 days & wage increases to compensate for cost of living, and medical benefits won \\
2 & 1971 & bell system & 400000 & 1 week & cost of living allowance (cola) won for workers \\
3 & 1983 & bell system & 600000 & 22 days & last contract with the bell system before its breakup. bell system sought givebacks. the contract resulted in wage increases, employment security, pension, and health improvements \\
4 & 1986 & at&t & 175000 & 25 days & cola clause suspended in contract - former bell system contracts vary substantially from the at&t contract \\
5 & 1989 & at&t & 175000 & none & child and elder care benefits added to contract. cola clause removed from contract \\
6 & 1989 & nynex & 175000 & 17 weeks & strike was due to major health care cuts by nynex \\
7 & 1998 & us west & 34000 & 15 day & strike was due to mandatory overtime demands and forced pay-for-performance plan. overtime caps were won \\
8 & 2000 & verizon & 80000 & 3 weeks & strike was due to mandatory overtime demands. provisions for stress were won \\
9 & 2011 & verizon & 45000 & 13 days & strike was due to major wage and health care cuts by verizon, a forced pay-for-performance plan and movement-of-work job security provisions. contract extended \\
10 & 2012 & at&t & 20000 & 2 days & at&t west; california, nevada, and at&t east; connecticut - unfair labor practice strike during contract negotiations \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1968 \\
1 & 1986 \\
2 & 1989 \\
3 & 2012 \\
\bottomrule
\end{tabular}
| select year where company = 'at&t' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>company</th>
<th>number of members affected</th>
<th>duration of strike</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1955</td>
<td>southern bell telephone co</td>
<td>50000</td>
<td>72 days</td>
<td>strike was in answer to management's effort to prohibit workers from striking</td>
</tr>
<tr>
<th>1</th>
<td>1968</td>
<td>at&t</td>
<td>200000</td>
<td>18 days</td>
<td>wage increases to compensate for cost of living, and medical benefits won</td>
</tr>
<tr>
<th>2</th>
<td>1971</td>
<td>bell system</td>
<td>400000</td>
<td>1 week</td>
<td>cost of living allowance (cola) won for workers</td>
</tr>
<tr>
<th>3</th>
<td>1983</td>
<td>bell system</td>
<td>600000</td>
<td>22 days</td>
<td>last contract with the bell system before its breakup. bell system sought givebacks. the contract resulted in wage increases, employment security, pension, and health improvements</td>
</tr>
<tr>
<th>4</th>
<td>1986</td>
<td>at&t</td>
<td>175000</td>
<td>25 days</td>
<td>cola clause suspended in contract - former bell system contracts vary substantially from the at&t contract</td>
</tr>
<tr>
<th>5</th>
<td>1989</td>
<td>at&t</td>
<td>175000</td>
<td>none</td>
<td>child and elder care benefits added to contract. cola clause removed from contract</td>
</tr>
<tr>
<th>6</th>
<td>1989</td>
<td>nynex</td>
<td>175000</td>
<td>17 weeks</td>
<td>strike was due to major health care cuts by nynex</td>
</tr>
<tr>
<th>7</th>
<td>1998</td>
<td>us west</td>
<td>34000</td>
<td>15 day</td>
<td>strike was due to mandatory overtime demands and forced pay-for-performance plan. overtime caps were won</td>
</tr>
<tr>
<th>8</th>
<td>2000</td>
<td>verizon</td>
<td>80000</td>
<td>3 weeks</td>
<td>strike was due to mandatory overtime demands. provisions for stress were won</td>
</tr>
<tr>
<th>9</th>
<td>2011</td>
<td>verizon</td>
<td>45000</td>
<td>13 days</td>
<td>strike was due to major wage and health care cuts by verizon, a forced pay-for-performance plan and movement-of-work job security provisions. contract extended</td>
</tr>
<tr>
<th>10</th>
<td>2012</td>
<td>at&t</td>
<td>20000</td>
<td>2 days</td>
<td>at&t west; california, nevada, and at&t east; connecticut - unfair labor practice strike during contract negotiations</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1968</td>
</tr>
<tr>
<th>1</th>
<td>1986</td>
</tr>
<tr>
<th>2</th>
<td>1989</td>
</tr>
<tr>
<th>3</th>
<td>2012</td>
</tr>
</tbody>
</table> | select year where company = 'at&t' <table_name> : table | | year | company | number of members affected | duration of strike | notes |
|---:|-------:|:---------------------------|-----------------------------:|:---------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | 1955 | southern bell telephone co | 50000 | 72 days | strike was in answer to management's effort to prohibit workers from striking |
| 1 | 1968 | at&t | 200000 | 18 days | wage increases to compensate for cost of living, and medical benefits won |
| 2 | 1971 | bell system | 400000 | 1 week | cost of living allowance (cola) won for workers |
| 3 | 1983 | bell system | 600000 | 22 days | last contract with the bell system before its breakup. bell system sought givebacks. the contract resulted in wage increases, employment security, pension, and health improvements |
| 4 | 1986 | at&t | 175000 | 25 days | cola clause suspended in contract - former bell system contracts vary substantially from the at&t contract |
| 5 | 1989 | at&t | 175000 | none | child and elder care benefits added to contract. cola clause removed from contract |
| 6 | 1989 | nynex | 175000 | 17 weeks | strike was due to major health care cuts by nynex |
| 7 | 1998 | us west | 34000 | 15 day | strike was due to mandatory overtime demands and forced pay-for-performance plan. overtime caps were won |
| 8 | 2000 | verizon | 80000 | 3 weeks | strike was due to mandatory overtime demands. provisions for stress were won |
| 9 | 2011 | verizon | 45000 | 13 days | strike was due to major wage and health care cuts by verizon, a forced pay-for-performance plan and movement-of-work job security provisions. contract extended |
| 10 | 2012 | at&t | 20000 | 2 days | at&t west; california, nevada, and at&t east; connecticut - unfair labor practice strike during contract negotiations | | | | year |
|---:|-------:|
| 0 | 1968 |
| 1 | 1986 |
| 2 | 1989 |
| 3 | 2012 | | [
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select sum ( isolation ) where rank = 12 col : rank | mountain peak | nation | province | elevation | prominence | isolation row 1 : 1 | volcan tajumulco pb | guatemala | san marcos | 4220 m 13,845 ft | 3980 m 13,058 ft | 722 km 448 mi row 2 : 2 | chirripo grande pb | costa rica | cartago limon san jose | 3819 m 12,530 ft | 3726 m 12,224 ft | 864 km 537 mi row 3 : 3 | montana de santa barbara pb | honduras | santa barbara | 2744 m 9,003 ft | 2084 m 6,837 ft | 74 km 46 mi row 4 : 4 | cerro las minas pb | honduras | lempira | 2849 m 9,347 ft | 2069 m 6,788 ft | 130 km 81 mi row 5 : 5 | volcan de agua pb | guatemala | escuintla sacatepequez | 3761 m 12,339 ft | 1981 m 6,499 ft | 16 km 10 mi row 6 : 6 | alto cuchumatanes pb | guatemala | huehuetenango | 3837 m 12,589 ft | 1877 m 6,158 ft | 65 km 40 mi row 7 : 7 | volcan irazu pb | costa rica | cartago san jose | 3402 m 11,161 ft | 1872 m 6,142 ft | 48 km 30 mi row 8 : 8 | montanas pena blanca high point pb | guatemala | huehuetenango | 3518 m 11,542 ft | 1858 m 6,096 ft | 42 km 26 mi row 9 : 9 | volcan acatenango pb | guatemala | chimaltenango sacatepequez | 3975 m 13,041 ft | 1835 m 6,020 ft | 126 km 78 mi row 10 : 10 | volcan san miguel pb | el salvador | san miguel | 2131 m 6,991 ft | 1831 m 6,007 ft | 64 km 40 mi row 11 : 11 | cerro tacarcuna pb | panama | darien | 1875 m 6,152 ft | 1770 m 5,807 ft | 99 km 61 mi row 12 : 12 | volcan atitlan pb | guatemala | solola | 3537 m 11,604 ft | 1754 m 5,755 ft | 35 km 21 mi row 13 : 13 | pico bonito pb | honduras | atlantida | 2450 m 8,038 ft | 1710 m 5,610 ft | 152 km 95 mi row 14 : 14 | montana san ildefonso pb | honduras | cortes | 2242 m 7,356 ft | 1702 m 5,584 ft | 68 km 42 mi row 15 : 15 | volcan san cristobal pb | nicaragua | chinandega | 1745 m 5,725 ft | 1665 m 5,463 ft | 134 km 83 mi | col : sum ( "isolation" ) row 1 : 35 | select sum ( isolation ) where rank = 12 <table_name> : table \begin{tabular}{llllllll}
\toprule
& rank & mountain peak & nation & province & elevation & prominence & isolation \\
\midrule
0 & 1 & volcan tajumulco pb & guatemala & san marcos & 4220 m 13,845 ft & 3980 m 13,058 ft & 722 km 448 mi \\
1 & 2 & chirripo grande pb & costa rica & cartago limon san jose & 3819 m 12,530 ft & 3726 m 12,224 ft & 864 km 537 mi \\
2 & 3 & montana de santa barbara pb & honduras & santa barbara & 2744 m 9,003 ft & 2084 m 6,837 ft & 74 km 46 mi \\
3 & 4 & cerro las minas pb & honduras & lempira & 2849 m 9,347 ft & 2069 m 6,788 ft & 130 km 81 mi \\
4 & 5 & volcan de agua pb & guatemala & escuintla sacatepequez & 3761 m 12,339 ft & 1981 m 6,499 ft & 16 km 10 mi \\
5 & 6 & alto cuchumatanes pb & guatemala & huehuetenango & 3837 m 12,589 ft & 1877 m 6,158 ft & 65 km 40 mi \\
6 & 7 & volcan irazu pb & costa rica & cartago san jose & 3402 m 11,161 ft & 1872 m 6,142 ft & 48 km 30 mi \\
7 & 8 & montanas pena blanca high point pb & guatemala & huehuetenango & 3518 m 11,542 ft & 1858 m 6,096 ft & 42 km 26 mi \\
8 & 9 & volcan acatenango pb & guatemala & chimaltenango sacatepequez & 3975 m 13,041 ft & 1835 m 6,020 ft & 126 km 78 mi \\
9 & 10 & volcan san miguel pb & el salvador & san miguel & 2131 m 6,991 ft & 1831 m 6,007 ft & 64 km 40 mi \\
10 & 11 & cerro tacarcuna pb & panama & darien & 1875 m 6,152 ft & 1770 m 5,807 ft & 99 km 61 mi \\
11 & 12 & volcan atitlan pb & guatemala & solola & 3537 m 11,604 ft & 1754 m 5,755 ft & 35 km 21 mi \\
12 & 13 & pico bonito pb & honduras & atlantida & 2450 m 8,038 ft & 1710 m 5,610 ft & 152 km 95 mi \\
13 & 14 & montana san ildefonso pb & honduras & cortes & 2242 m 7,356 ft & 1702 m 5,584 ft & 68 km 42 mi \\
14 & 15 & volcan san cristobal pb & nicaragua & chinandega & 1745 m 5,725 ft & 1665 m 5,463 ft & 134 km 83 mi \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& sum ( "isolation" ) \\
\midrule
0 & 35 \\
\bottomrule
\end{tabular}
| select sum ( isolation ) where rank = 12 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>mountain peak</th>
<th>nation</th>
<th>province</th>
<th>elevation</th>
<th>prominence</th>
<th>isolation</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>volcan tajumulco pb</td>
<td>guatemala</td>
<td>san marcos</td>
<td>4220 m 13,845 ft</td>
<td>3980 m 13,058 ft</td>
<td>722 km 448 mi</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>chirripo grande pb</td>
<td>costa rica</td>
<td>cartago limon san jose</td>
<td>3819 m 12,530 ft</td>
<td>3726 m 12,224 ft</td>
<td>864 km 537 mi</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>montana de santa barbara pb</td>
<td>honduras</td>
<td>santa barbara</td>
<td>2744 m 9,003 ft</td>
<td>2084 m 6,837 ft</td>
<td>74 km 46 mi</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>cerro las minas pb</td>
<td>honduras</td>
<td>lempira</td>
<td>2849 m 9,347 ft</td>
<td>2069 m 6,788 ft</td>
<td>130 km 81 mi</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>volcan de agua pb</td>
<td>guatemala</td>
<td>escuintla sacatepequez</td>
<td>3761 m 12,339 ft</td>
<td>1981 m 6,499 ft</td>
<td>16 km 10 mi</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>alto cuchumatanes pb</td>
<td>guatemala</td>
<td>huehuetenango</td>
<td>3837 m 12,589 ft</td>
<td>1877 m 6,158 ft</td>
<td>65 km 40 mi</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>volcan irazu pb</td>
<td>costa rica</td>
<td>cartago san jose</td>
<td>3402 m 11,161 ft</td>
<td>1872 m 6,142 ft</td>
<td>48 km 30 mi</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>montanas pena blanca high point pb</td>
<td>guatemala</td>
<td>huehuetenango</td>
<td>3518 m 11,542 ft</td>
<td>1858 m 6,096 ft</td>
<td>42 km 26 mi</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>volcan acatenango pb</td>
<td>guatemala</td>
<td>chimaltenango sacatepequez</td>
<td>3975 m 13,041 ft</td>
<td>1835 m 6,020 ft</td>
<td>126 km 78 mi</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>volcan san miguel pb</td>
<td>el salvador</td>
<td>san miguel</td>
<td>2131 m 6,991 ft</td>
<td>1831 m 6,007 ft</td>
<td>64 km 40 mi</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>cerro tacarcuna pb</td>
<td>panama</td>
<td>darien</td>
<td>1875 m 6,152 ft</td>
<td>1770 m 5,807 ft</td>
<td>99 km 61 mi</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>volcan atitlan pb</td>
<td>guatemala</td>
<td>solola</td>
<td>3537 m 11,604 ft</td>
<td>1754 m 5,755 ft</td>
<td>35 km 21 mi</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>pico bonito pb</td>
<td>honduras</td>
<td>atlantida</td>
<td>2450 m 8,038 ft</td>
<td>1710 m 5,610 ft</td>
<td>152 km 95 mi</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>montana san ildefonso pb</td>
<td>honduras</td>
<td>cortes</td>
<td>2242 m 7,356 ft</td>
<td>1702 m 5,584 ft</td>
<td>68 km 42 mi</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>volcan san cristobal pb</td>
<td>nicaragua</td>
<td>chinandega</td>
<td>1745 m 5,725 ft</td>
<td>1665 m 5,463 ft</td>
<td>134 km 83 mi</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>sum ( "isolation" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>35</td>
</tr>
</tbody>
</table> | select sum ( isolation ) where rank = 12 <table_name> : table | | rank | mountain peak | nation | province | elevation | prominence | isolation |
|---:|-------:|:-----------------------------------|:------------|:---------------------------|:-----------------|:-----------------|:--------------|
| 0 | 1 | volcan tajumulco pb | guatemala | san marcos | 4220 m 13,845 ft | 3980 m 13,058 ft | 722 km 448 mi |
| 1 | 2 | chirripo grande pb | costa rica | cartago limon san jose | 3819 m 12,530 ft | 3726 m 12,224 ft | 864 km 537 mi |
| 2 | 3 | montana de santa barbara pb | honduras | santa barbara | 2744 m 9,003 ft | 2084 m 6,837 ft | 74 km 46 mi |
| 3 | 4 | cerro las minas pb | honduras | lempira | 2849 m 9,347 ft | 2069 m 6,788 ft | 130 km 81 mi |
| 4 | 5 | volcan de agua pb | guatemala | escuintla sacatepequez | 3761 m 12,339 ft | 1981 m 6,499 ft | 16 km 10 mi |
| 5 | 6 | alto cuchumatanes pb | guatemala | huehuetenango | 3837 m 12,589 ft | 1877 m 6,158 ft | 65 km 40 mi |
| 6 | 7 | volcan irazu pb | costa rica | cartago san jose | 3402 m 11,161 ft | 1872 m 6,142 ft | 48 km 30 mi |
| 7 | 8 | montanas pena blanca high point pb | guatemala | huehuetenango | 3518 m 11,542 ft | 1858 m 6,096 ft | 42 km 26 mi |
| 8 | 9 | volcan acatenango pb | guatemala | chimaltenango sacatepequez | 3975 m 13,041 ft | 1835 m 6,020 ft | 126 km 78 mi |
| 9 | 10 | volcan san miguel pb | el salvador | san miguel | 2131 m 6,991 ft | 1831 m 6,007 ft | 64 km 40 mi |
| 10 | 11 | cerro tacarcuna pb | panama | darien | 1875 m 6,152 ft | 1770 m 5,807 ft | 99 km 61 mi |
| 11 | 12 | volcan atitlan pb | guatemala | solola | 3537 m 11,604 ft | 1754 m 5,755 ft | 35 km 21 mi |
| 12 | 13 | pico bonito pb | honduras | atlantida | 2450 m 8,038 ft | 1710 m 5,610 ft | 152 km 95 mi |
| 13 | 14 | montana san ildefonso pb | honduras | cortes | 2242 m 7,356 ft | 1702 m 5,584 ft | 68 km 42 mi |
| 14 | 15 | volcan san cristobal pb | nicaragua | chinandega | 1745 m 5,725 ft | 1665 m 5,463 ft | 134 km 83 mi | | | | sum ( "isolation" ) |
|---:|----------------------:|
| 0 | 35 | | [
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select rider where pos = 1 col : pos | rider | manufacturer | time/retired | grid | points row 1 : 1 | roberto rolfo | honda | 45:14.ret3 | 8 | 25 row 2 : 2 | anthony west | aprilia | 14.04 | 11 | 20 row 3 : 3 | fonsi nieto | aprilia | 33.511 | 5 | 16 row 4 : 4 | franco battaini | aprilia | 54.252 | 3 | 13 row 5 : 5 | alex debon | honda | +1:06.895 | 13 | 11 row 6 : 6 | naoki matsudo | yamaha | +1:06.943 | 9 | 10 row 7 : 7 | erwan nigon | aprilia | +1:13.421 | 12 | 9 row 8 : 8 | jaroslav hules | yamaha | +1:22.119 | 10 | 8 row 9 : 9 | manuel poggiali | aprilia | +1:22.163 | 7 | 7 row 10 : 10 | johann stigefelt | aprilia | +1:25.303 | 22 | 6 row 11 : 11 | toni elias | aprilia | +1:41.591 | 1 | 5 row 12 : 12 | lukas pesek | yamaha | +2:49.682 | 18 | 4 row 13 : 13 | dirk heidolf | aprilia | +1 lap | 17 | 3 row 14 : 14 | hugo marchand | aprilia | +1 lap | 19 | 2 row 15 : 15 | chaz davies | aprilia | +1 lap | 15 | 1 row 16 : 16 | hector faubel | aprilia | +1 lap | 16 | none row 17 : 17 | henk vd lagemaat | honda | +2 laps | 25 | none row 18 : 18 | joan olive | aprilia | +3 laps | 20 | none row 19 : ret | randy de puniet | aprilia | retirement | 4 | none row 20 : ret | christian gemmel | honda | retirement | 23 | none row 21 : ret | eric bataille | honda | retirement | 14 | none row 22 : ret | sebastian porto | honda | retirement | 2 | none row 23 : ret | katja poensgen | honda | retirement | 24 | none row 24 : ret | geoff hardcastle | yamaha | retirement | 26 | none row 25 : ret | alex baldolini | aprilia | retirement | 21 | none row 26 : ret | sylvain guintoli | aprilia | retirement | 6 | none | col : rider row 1 : roberto rolfo | select rider where pos = 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& pos & rider & manufacturer & time/retired & grid & points \\
\midrule
0 & 1 & roberto rolfo & honda & 45:14.ret3 & 8 & 25 \\
1 & 2 & anthony west & aprilia & 14.04 & 11 & 20 \\
2 & 3 & fonsi nieto & aprilia & 33.511 & 5 & 16 \\
3 & 4 & franco battaini & aprilia & 54.252 & 3 & 13 \\
4 & 5 & alex debon & honda & +1:06.895 & 13 & 11 \\
5 & 6 & naoki matsudo & yamaha & +1:06.943 & 9 & 10 \\
6 & 7 & erwan nigon & aprilia & +1:13.421 & 12 & 9 \\
7 & 8 & jaroslav hules & yamaha & +1:22.119 & 10 & 8 \\
8 & 9 & manuel poggiali & aprilia & +1:22.163 & 7 & 7 \\
9 & 10 & johann stigefelt & aprilia & +1:25.303 & 22 & 6 \\
10 & 11 & toni elias & aprilia & +1:41.591 & 1 & 5 \\
11 & 12 & lukas pesek & yamaha & +2:49.682 & 18 & 4 \\
12 & 13 & dirk heidolf & aprilia & +1 lap & 17 & 3 \\
13 & 14 & hugo marchand & aprilia & +1 lap & 19 & 2 \\
14 & 15 & chaz davies & aprilia & +1 lap & 15 & 1 \\
15 & 16 & hector faubel & aprilia & +1 lap & 16 & none \\
16 & 17 & henk vd lagemaat & honda & +2 laps & 25 & none \\
17 & 18 & joan olive & aprilia & +3 laps & 20 & none \\
18 & ret & randy de puniet & aprilia & retirement & 4 & none \\
19 & ret & christian gemmel & honda & retirement & 23 & none \\
20 & ret & eric bataille & honda & retirement & 14 & none \\
21 & ret & sebastian porto & honda & retirement & 2 & none \\
22 & ret & katja poensgen & honda & retirement & 24 & none \\
23 & ret & geoff hardcastle & yamaha & retirement & 26 & none \\
24 & ret & alex baldolini & aprilia & retirement & 21 & none \\
25 & ret & sylvain guintoli & aprilia & retirement & 6 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& rider \\
\midrule
0 & roberto rolfo \\
\bottomrule
\end{tabular}
| select rider where pos = 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>rider</th>
<th>manufacturer</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>roberto rolfo</td>
<td>honda</td>
<td>45:14.ret3</td>
<td>8</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>anthony west</td>
<td>aprilia</td>
<td>14.04</td>
<td>11</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>fonsi nieto</td>
<td>aprilia</td>
<td>33.511</td>
<td>5</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>franco battaini</td>
<td>aprilia</td>
<td>54.252</td>
<td>3</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>alex debon</td>
<td>honda</td>
<td>+1:06.895</td>
<td>13</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>naoki matsudo</td>
<td>yamaha</td>
<td>+1:06.943</td>
<td>9</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>erwan nigon</td>
<td>aprilia</td>
<td>+1:13.421</td>
<td>12</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>jaroslav hules</td>
<td>yamaha</td>
<td>+1:22.119</td>
<td>10</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>manuel poggiali</td>
<td>aprilia</td>
<td>+1:22.163</td>
<td>7</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>johann stigefelt</td>
<td>aprilia</td>
<td>+1:25.303</td>
<td>22</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>toni elias</td>
<td>aprilia</td>
<td>+1:41.591</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>lukas pesek</td>
<td>yamaha</td>
<td>+2:49.682</td>
<td>18</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>dirk heidolf</td>
<td>aprilia</td>
<td>+1 lap</td>
<td>17</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>hugo marchand</td>
<td>aprilia</td>
<td>+1 lap</td>
<td>19</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>chaz davies</td>
<td>aprilia</td>
<td>+1 lap</td>
<td>15</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>hector faubel</td>
<td>aprilia</td>
<td>+1 lap</td>
<td>16</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>henk vd lagemaat</td>
<td>honda</td>
<td>+2 laps</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>joan olive</td>
<td>aprilia</td>
<td>+3 laps</td>
<td>20</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>ret</td>
<td>randy de puniet</td>
<td>aprilia</td>
<td>retirement</td>
<td>4</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>christian gemmel</td>
<td>honda</td>
<td>retirement</td>
<td>23</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>eric bataille</td>
<td>honda</td>
<td>retirement</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>sebastian porto</td>
<td>honda</td>
<td>retirement</td>
<td>2</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>ret</td>
<td>katja poensgen</td>
<td>honda</td>
<td>retirement</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>geoff hardcastle</td>
<td>yamaha</td>
<td>retirement</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>alex baldolini</td>
<td>aprilia</td>
<td>retirement</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>sylvain guintoli</td>
<td>aprilia</td>
<td>retirement</td>
<td>6</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rider</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>roberto rolfo</td>
</tr>
</tbody>
</table> | select rider where pos = 1 <table_name> : table | | pos | rider | manufacturer | time/retired | grid | points |
|---:|:------|:-----------------|:---------------|:---------------|-------:|:---------|
| 0 | 1 | roberto rolfo | honda | 45:14.ret3 | 8 | 25 |
| 1 | 2 | anthony west | aprilia | 14.04 | 11 | 20 |
| 2 | 3 | fonsi nieto | aprilia | 33.511 | 5 | 16 |
| 3 | 4 | franco battaini | aprilia | 54.252 | 3 | 13 |
| 4 | 5 | alex debon | honda | +1:06.895 | 13 | 11 |
| 5 | 6 | naoki matsudo | yamaha | +1:06.943 | 9 | 10 |
| 6 | 7 | erwan nigon | aprilia | +1:13.421 | 12 | 9 |
| 7 | 8 | jaroslav hules | yamaha | +1:22.119 | 10 | 8 |
| 8 | 9 | manuel poggiali | aprilia | +1:22.163 | 7 | 7 |
| 9 | 10 | johann stigefelt | aprilia | +1:25.303 | 22 | 6 |
| 10 | 11 | toni elias | aprilia | +1:41.591 | 1 | 5 |
| 11 | 12 | lukas pesek | yamaha | +2:49.682 | 18 | 4 |
| 12 | 13 | dirk heidolf | aprilia | +1 lap | 17 | 3 |
| 13 | 14 | hugo marchand | aprilia | +1 lap | 19 | 2 |
| 14 | 15 | chaz davies | aprilia | +1 lap | 15 | 1 |
| 15 | 16 | hector faubel | aprilia | +1 lap | 16 | none |
| 16 | 17 | henk vd lagemaat | honda | +2 laps | 25 | none |
| 17 | 18 | joan olive | aprilia | +3 laps | 20 | none |
| 18 | ret | randy de puniet | aprilia | retirement | 4 | none |
| 19 | ret | christian gemmel | honda | retirement | 23 | none |
| 20 | ret | eric bataille | honda | retirement | 14 | none |
| 21 | ret | sebastian porto | honda | retirement | 2 | none |
| 22 | ret | katja poensgen | honda | retirement | 24 | none |
| 23 | ret | geoff hardcastle | yamaha | retirement | 26 | none |
| 24 | ret | alex baldolini | aprilia | retirement | 21 | none |
| 25 | ret | sylvain guintoli | aprilia | retirement | 6 | none | | | | rider |
|---:|:--------------|
| 0 | roberto rolfo | | [
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select max ( votes ) where percentage < 332 col : party | candidate(s) | votes | percentage row 1 : uup | peter weir alan mcfarland roy bradford john shields irene cree | 9270 | 25.6 row 2 : uk unionist | robert mccartney valerie kinghan patricia watson | 7579 | 20.9 row 3 : dup | st clair mcalister ruby cooling cecil noble | 6699 | 18.5 row 4 : alliance | oliver napier brian wilson eileen bell larry thompson jane copeland | 6186 | 17.1 row 5 : sdlp | owen adams john burke | 1798 | 5.0 row 6 : pup | victor ash samuel curry neil mehaffy kenneth sterrit | 1694 | 4.7 row 7 : ulster democratic | james mccullough thomas lindsay | 651 | 1.8 row 8 : ni women's coalition | emma mcguigan ann marie foster jane morrice | 496 | 1.4 row 9 : conservative | ann thompson bruce mulligan | 444 | 1.2 row 10 : independent chambers | alan chambers james arbuthnot robert irvine | 334 | 0.9 row 11 : green (ni) | paddy mcevoy mary ringland | 283 | 0.8 row 12 : sinn fein | mairtin o mulleoir john smith | 275 | 0.8 row 13 : labour coalition | john magennis sean mcgouran | 171 | 0.5 row 14 : independent dup | thomas o'brien william baxter | 97 | 0.3 row 15 : democratic left | daryl armitage tim davis | 95 | 0.3 row 16 : workers' party | dessie o'hagan colum mullan | 60 | 0.2 row 17 : ulster independence | geoffrey watson glenn pollock | 49 | 0.1 row 18 : independent voice | christopher carter fidelma carter | 49 | 0.1 row 19 : natural law | peter mcgowan thomas mullins | 15 | 0.0 | col : max ( "votes" ) row 1 : 97 | select max ( votes ) where percentage < 332 <table_name> : table \begin{tabular}{lllll}
\toprule
& party & candidate(s) & votes & percentage \\
\midrule
0 & uup & peter weir alan mcfarland roy bradford john shields irene cree & 9270 & 25.6 \\
1 & uk unionist & robert mccartney valerie kinghan patricia watson & 7579 & 20.9 \\
2 & dup & st clair mcalister ruby cooling cecil noble & 6699 & 18.5 \\
3 & alliance & oliver napier brian wilson eileen bell larry thompson jane copeland & 6186 & 17.1 \\
4 & sdlp & owen adams john burke & 1798 & 5.0 \\
5 & pup & victor ash samuel curry neil mehaffy kenneth sterrit & 1694 & 4.7 \\
6 & ulster democratic & james mccullough thomas lindsay & 651 & 1.8 \\
7 & ni women's coalition & emma mcguigan ann marie foster jane morrice & 496 & 1.4 \\
8 & conservative & ann thompson bruce mulligan & 444 & 1.2 \\
9 & independent chambers & alan chambers james arbuthnot robert irvine & 334 & 0.9 \\
10 & green (ni) & paddy mcevoy mary ringland & 283 & 0.8 \\
11 & sinn fein & mairtin o mulleoir john smith & 275 & 0.8 \\
12 & labour coalition & john magennis sean mcgouran & 171 & 0.5 \\
13 & independent dup & thomas o'brien william baxter & 97 & 0.3 \\
14 & democratic left & daryl armitage tim davis & 95 & 0.3 \\
15 & workers' party & dessie o'hagan colum mullan & 60 & 0.2 \\
16 & ulster independence & geoffrey watson glenn pollock & 49 & 0.1 \\
17 & independent voice & christopher carter fidelma carter & 49 & 0.1 \\
18 & natural law & peter mcgowan thomas mullins & 15 & 0.0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& max ( "votes" ) \\
\midrule
0 & 97 \\
\bottomrule
\end{tabular}
| select max ( votes ) where percentage < 332 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>candidate(s)</th>
<th>votes</th>
<th>percentage</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>uup</td>
<td>peter weir alan mcfarland roy bradford john shields irene cree</td>
<td>9270</td>
<td>25.6</td>
</tr>
<tr>
<th>1</th>
<td>uk unionist</td>
<td>robert mccartney valerie kinghan patricia watson</td>
<td>7579</td>
<td>20.9</td>
</tr>
<tr>
<th>2</th>
<td>dup</td>
<td>st clair mcalister ruby cooling cecil noble</td>
<td>6699</td>
<td>18.5</td>
</tr>
<tr>
<th>3</th>
<td>alliance</td>
<td>oliver napier brian wilson eileen bell larry thompson jane copeland</td>
<td>6186</td>
<td>17.1</td>
</tr>
<tr>
<th>4</th>
<td>sdlp</td>
<td>owen adams john burke</td>
<td>1798</td>
<td>5.0</td>
</tr>
<tr>
<th>5</th>
<td>pup</td>
<td>victor ash samuel curry neil mehaffy kenneth sterrit</td>
<td>1694</td>
<td>4.7</td>
</tr>
<tr>
<th>6</th>
<td>ulster democratic</td>
<td>james mccullough thomas lindsay</td>
<td>651</td>
<td>1.8</td>
</tr>
<tr>
<th>7</th>
<td>ni women's coalition</td>
<td>emma mcguigan ann marie foster jane morrice</td>
<td>496</td>
<td>1.4</td>
</tr>
<tr>
<th>8</th>
<td>conservative</td>
<td>ann thompson bruce mulligan</td>
<td>444</td>
<td>1.2</td>
</tr>
<tr>
<th>9</th>
<td>independent chambers</td>
<td>alan chambers james arbuthnot robert irvine</td>
<td>334</td>
<td>0.9</td>
</tr>
<tr>
<th>10</th>
<td>green (ni)</td>
<td>paddy mcevoy mary ringland</td>
<td>283</td>
<td>0.8</td>
</tr>
<tr>
<th>11</th>
<td>sinn fein</td>
<td>mairtin o mulleoir john smith</td>
<td>275</td>
<td>0.8</td>
</tr>
<tr>
<th>12</th>
<td>labour coalition</td>
<td>john magennis sean mcgouran</td>
<td>171</td>
<td>0.5</td>
</tr>
<tr>
<th>13</th>
<td>independent dup</td>
<td>thomas o'brien william baxter</td>
<td>97</td>
<td>0.3</td>
</tr>
<tr>
<th>14</th>
<td>democratic left</td>
<td>daryl armitage tim davis</td>
<td>95</td>
<td>0.3</td>
</tr>
<tr>
<th>15</th>
<td>workers' party</td>
<td>dessie o'hagan colum mullan</td>
<td>60</td>
<td>0.2</td>
</tr>
<tr>
<th>16</th>
<td>ulster independence</td>
<td>geoffrey watson glenn pollock</td>
<td>49</td>
<td>0.1</td>
</tr>
<tr>
<th>17</th>
<td>independent voice</td>
<td>christopher carter fidelma carter</td>
<td>49</td>
<td>0.1</td>
</tr>
<tr>
<th>18</th>
<td>natural law</td>
<td>peter mcgowan thomas mullins</td>
<td>15</td>
<td>0.0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>max ( "votes" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>97</td>
</tr>
</tbody>
</table> | select max ( votes ) where percentage < 332 <table_name> : table | | party | candidate(s) | votes | percentage |
|---:|:---------------------|:--------------------------------------------------------------------|--------:|-------------:|
| 0 | uup | peter weir alan mcfarland roy bradford john shields irene cree | 9270 | 25.6 |
| 1 | uk unionist | robert mccartney valerie kinghan patricia watson | 7579 | 20.9 |
| 2 | dup | st clair mcalister ruby cooling cecil noble | 6699 | 18.5 |
| 3 | alliance | oliver napier brian wilson eileen bell larry thompson jane copeland | 6186 | 17.1 |
| 4 | sdlp | owen adams john burke | 1798 | 5 |
| 5 | pup | victor ash samuel curry neil mehaffy kenneth sterrit | 1694 | 4.7 |
| 6 | ulster democratic | james mccullough thomas lindsay | 651 | 1.8 |
| 7 | ni women's coalition | emma mcguigan ann marie foster jane morrice | 496 | 1.4 |
| 8 | conservative | ann thompson bruce mulligan | 444 | 1.2 |
| 9 | independent chambers | alan chambers james arbuthnot robert irvine | 334 | 0.9 |
| 10 | green (ni) | paddy mcevoy mary ringland | 283 | 0.8 |
| 11 | sinn fein | mairtin o mulleoir john smith | 275 | 0.8 |
| 12 | labour coalition | john magennis sean mcgouran | 171 | 0.5 |
| 13 | independent dup | thomas o'brien william baxter | 97 | 0.3 |
| 14 | democratic left | daryl armitage tim davis | 95 | 0.3 |
| 15 | workers' party | dessie o'hagan colum mullan | 60 | 0.2 |
| 16 | ulster independence | geoffrey watson glenn pollock | 49 | 0.1 |
| 17 | independent voice | christopher carter fidelma carter | 49 | 0.1 |
| 18 | natural law | peter mcgowan thomas mullins | 15 | 0 | | | | max ( "votes" ) |
|---:|------------------:|
| 0 | 97 | | [
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select count ( * ) where school/club team = 'wisconsin-eau claire' col : round | pick | player | position | nationality | school/club team row 1 : 1 | 15 | reggie johnson | pf/c | united states | tennessee row 2 : 2 | 39 | michael miley | none | united states | california state-long beach row 3 : 3 | 60 | lavon mercer | none | united states | georgia row 4 : 3 | 61 | rich yonakor | none | united states | north carolina row 5 : 4 | 83 | calvin roberts | none | united states | california state-fullerton row 6 : 5 | 107 | gib hinz | none | united states | wisconsin-eau claire row 7 : 6 | 129 | dean uthoff | none | united states | iowa state row 8 : 7 | 153 | allan zahn | none | united states | arkansas row 9 : 8 | 172 | bill bailey | none | united states | texas pan-american row 10 : 9 | 192 | al williams | none | united states | north texas state row 11 : 10 | 209 | steve schall | none | united states | arkansas | col : count ( "*" ) row 1 : 1 | select count ( * ) where school/club team = 'wisconsin-eau claire' <table_name> : table \begin{tabular}{lllllll}
\toprule
& round & pick & player & position & nationality & school/club team \\
\midrule
0 & 1 & 15 & reggie johnson & pf/c & united states & tennessee \\
1 & 2 & 39 & michael miley & none & united states & california state-long beach \\
2 & 3 & 60 & lavon mercer & none & united states & georgia \\
3 & 3 & 61 & rich yonakor & none & united states & north carolina \\
4 & 4 & 83 & calvin roberts & none & united states & california state-fullerton \\
5 & 5 & 107 & gib hinz & none & united states & wisconsin-eau claire \\
6 & 6 & 129 & dean uthoff & none & united states & iowa state \\
7 & 7 & 153 & allan zahn & none & united states & arkansas \\
8 & 8 & 172 & bill bailey & none & united states & texas pan-american \\
9 & 9 & 192 & al williams & none & united states & north texas state \\
10 & 10 & 209 & steve schall & none & united states & arkansas \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where school/club team = 'wisconsin-eau claire' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>round</th>
<th>pick</th>
<th>player</th>
<th>position</th>
<th>nationality</th>
<th>school/club team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>15</td>
<td>reggie johnson</td>
<td>pf/c</td>
<td>united states</td>
<td>tennessee</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>39</td>
<td>michael miley</td>
<td>none</td>
<td>united states</td>
<td>california state-long beach</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>60</td>
<td>lavon mercer</td>
<td>none</td>
<td>united states</td>
<td>georgia</td>
</tr>
<tr>
<th>3</th>
<td>3</td>
<td>61</td>
<td>rich yonakor</td>
<td>none</td>
<td>united states</td>
<td>north carolina</td>
</tr>
<tr>
<th>4</th>
<td>4</td>
<td>83</td>
<td>calvin roberts</td>
<td>none</td>
<td>united states</td>
<td>california state-fullerton</td>
</tr>
<tr>
<th>5</th>
<td>5</td>
<td>107</td>
<td>gib hinz</td>
<td>none</td>
<td>united states</td>
<td>wisconsin-eau claire</td>
</tr>
<tr>
<th>6</th>
<td>6</td>
<td>129</td>
<td>dean uthoff</td>
<td>none</td>
<td>united states</td>
<td>iowa state</td>
</tr>
<tr>
<th>7</th>
<td>7</td>
<td>153</td>
<td>allan zahn</td>
<td>none</td>
<td>united states</td>
<td>arkansas</td>
</tr>
<tr>
<th>8</th>
<td>8</td>
<td>172</td>
<td>bill bailey</td>
<td>none</td>
<td>united states</td>
<td>texas pan-american</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>192</td>
<td>al williams</td>
<td>none</td>
<td>united states</td>
<td>north texas state</td>
</tr>
<tr>
<th>10</th>
<td>10</td>
<td>209</td>
<td>steve schall</td>
<td>none</td>
<td>united states</td>
<td>arkansas</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where school/club team = 'wisconsin-eau claire' <table_name> : table | | round | pick | player | position | nationality | school/club team |
|---:|--------:|-------:|:---------------|:-----------|:--------------|:----------------------------|
| 0 | 1 | 15 | reggie johnson | pf/c | united states | tennessee |
| 1 | 2 | 39 | michael miley | none | united states | california state-long beach |
| 2 | 3 | 60 | lavon mercer | none | united states | georgia |
| 3 | 3 | 61 | rich yonakor | none | united states | north carolina |
| 4 | 4 | 83 | calvin roberts | none | united states | california state-fullerton |
| 5 | 5 | 107 | gib hinz | none | united states | wisconsin-eau claire |
| 6 | 6 | 129 | dean uthoff | none | united states | iowa state |
| 7 | 7 | 153 | allan zahn | none | united states | arkansas |
| 8 | 8 | 172 | bill bailey | none | united states | texas pan-american |
| 9 | 9 | 192 | al williams | none | united states | north texas state |
| 10 | 10 | 209 | steve schall | none | united states | arkansas | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select seats where % = '2.70%' col : party/electoral alliance | seats | change | votes | % row 1 : radical civic union (ucr) | 98 | 6 | 618411 | 42.70% row 2 : independent socialist | 15 | 9 | 110792 | 7.70% row 3 : conservative | 12 | -2 | 153826 | 10.60% row 4 : democratic (cordoba province) | 7 | 1 | none | none row 5 : unified ucr (santa fe province) | 4 | -7 | 53221 | 3.70% row 6 : liberal (tucuman province) | 4 | -2 | 39543 | 2.70% row 7 : democratic progressive | 3 | 3 | 136121 | 9.40% row 8 : antipersonalist ucr | 3 | -2 | 47891 | 3.30% row 9 : autonomist party of corrientes | 2 | -3 | 17152 | 1.20% row 10 : lencinist ucr (mendoza province) | 1 | none | 19375 | 1.30% row 11 : socialist | 1 | -3 | 123734 | 8.50% row 12 : others | 4 | none | 127601 | 8.60% row 13 : invalid votes | 4 | none | 39868 | 2.70% row 14 : total | 158 | none | 1487535 | 100.00% | col : seats row 1 : 4 row 2 : 4 | select seats where % = '2.70%' <table_name> : table \begin{tabular}{llllll}
\toprule
& party/electoral alliance & seats & change & votes & % \\
\midrule
0 & radical civic union (ucr) & 98 & 6 & 618411 & 42.70% \\
1 & independent socialist & 15 & 9 & 110792 & 7.70% \\
2 & conservative & 12 & -2 & 153826 & 10.60% \\
3 & democratic (cordoba province) & 7 & 1 & none & none \\
4 & unified ucr (santa fe province) & 4 & -7 & 53221 & 3.70% \\
5 & liberal (tucuman province) & 4 & -2 & 39543 & 2.70% \\
6 & democratic progressive & 3 & 3 & 136121 & 9.40% \\
7 & antipersonalist ucr & 3 & -2 & 47891 & 3.30% \\
8 & autonomist party of corrientes & 2 & -3 & 17152 & 1.20% \\
9 & lencinist ucr (mendoza province) & 1 & none & 19375 & 1.30% \\
10 & socialist & 1 & -3 & 123734 & 8.50% \\
11 & others & 4 & none & 127601 & 8.60% \\
12 & invalid votes & 4 & none & 39868 & 2.70% \\
13 & total & 158 & none & 1487535 & 100.00% \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& seats \\
\midrule
0 & 4 \\
1 & 4 \\
\bottomrule
\end{tabular}
| select seats where % = '2.70%' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party/electoral alliance</th>
<th>seats</th>
<th>change</th>
<th>votes</th>
<th>%</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>radical civic union (ucr)</td>
<td>98</td>
<td>6</td>
<td>618411</td>
<td>42.70%</td>
</tr>
<tr>
<th>1</th>
<td>independent socialist</td>
<td>15</td>
<td>9</td>
<td>110792</td>
<td>7.70%</td>
</tr>
<tr>
<th>2</th>
<td>conservative</td>
<td>12</td>
<td>-2</td>
<td>153826</td>
<td>10.60%</td>
</tr>
<tr>
<th>3</th>
<td>democratic (cordoba province)</td>
<td>7</td>
<td>1</td>
<td>none</td>
<td>none</td>
</tr>
<tr>
<th>4</th>
<td>unified ucr (santa fe province)</td>
<td>4</td>
<td>-7</td>
<td>53221</td>
<td>3.70%</td>
</tr>
<tr>
<th>5</th>
<td>liberal (tucuman province)</td>
<td>4</td>
<td>-2</td>
<td>39543</td>
<td>2.70%</td>
</tr>
<tr>
<th>6</th>
<td>democratic progressive</td>
<td>3</td>
<td>3</td>
<td>136121</td>
<td>9.40%</td>
</tr>
<tr>
<th>7</th>
<td>antipersonalist ucr</td>
<td>3</td>
<td>-2</td>
<td>47891</td>
<td>3.30%</td>
</tr>
<tr>
<th>8</th>
<td>autonomist party of corrientes</td>
<td>2</td>
<td>-3</td>
<td>17152</td>
<td>1.20%</td>
</tr>
<tr>
<th>9</th>
<td>lencinist ucr (mendoza province)</td>
<td>1</td>
<td>none</td>
<td>19375</td>
<td>1.30%</td>
</tr>
<tr>
<th>10</th>
<td>socialist</td>
<td>1</td>
<td>-3</td>
<td>123734</td>
<td>8.50%</td>
</tr>
<tr>
<th>11</th>
<td>others</td>
<td>4</td>
<td>none</td>
<td>127601</td>
<td>8.60%</td>
</tr>
<tr>
<th>12</th>
<td>invalid votes</td>
<td>4</td>
<td>none</td>
<td>39868</td>
<td>2.70%</td>
</tr>
<tr>
<th>13</th>
<td>total</td>
<td>158</td>
<td>none</td>
<td>1487535</td>
<td>100.00%</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>seats</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
<tr>
<th>1</th>
<td>4</td>
</tr>
</tbody>
</table> | select seats where % = '2.70%' <table_name> : table | | party/electoral alliance | seats | change | votes | % |
|---:|:---------------------------------|--------:|:---------|:--------|:--------|
| 0 | radical civic union (ucr) | 98 | 6 | 618411 | 42.70% |
| 1 | independent socialist | 15 | 9 | 110792 | 7.70% |
| 2 | conservative | 12 | -2 | 153826 | 10.60% |
| 3 | democratic (cordoba province) | 7 | 1 | none | none |
| 4 | unified ucr (santa fe province) | 4 | -7 | 53221 | 3.70% |
| 5 | liberal (tucuman province) | 4 | -2 | 39543 | 2.70% |
| 6 | democratic progressive | 3 | 3 | 136121 | 9.40% |
| 7 | antipersonalist ucr | 3 | -2 | 47891 | 3.30% |
| 8 | autonomist party of corrientes | 2 | -3 | 17152 | 1.20% |
| 9 | lencinist ucr (mendoza province) | 1 | none | 19375 | 1.30% |
| 10 | socialist | 1 | -3 | 123734 | 8.50% |
| 11 | others | 4 | none | 127601 | 8.60% |
| 12 | invalid votes | 4 | none | 39868 | 2.70% |
| 13 | total | 158 | none | 1487535 | 100.00% | | | | seats |
|---:|--------:|
| 0 | 4 |
| 1 | 4 | | [
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select year where year = 1949 col : year | english title | chinese title | director | role row 1 : 1933 | twenty-four hours in shanghai | 上海二十四小时 | shen xiling | none row 2 : 1937 | street angel | 马路天使 | yuan muzhi | xiao chen row 3 : 1937 | crossroads | 十字街头 | shen xiling | zhao row 4 : 1947 | far away love | 遙遠的愛 | chen liting | xiao yuanxi row 5 : 1947 | rhapsody of happiness | 幸福狂想曲 | chen liting | none row 6 : 1949 | crows and sparrows | 烏鴉与麻雀 | zheng junli | little broadcast row 7 : 1949 | women side by side | 丽人行 | chen liting | zhang yuliang row 8 : 1950 | the life of wu xun | 武训传 | sun yu | wu xun row 9 : 1951 | the married couple | 我们夫妇之间 | zheng junli | none row 10 : 1956 | li shizhen | 李时珍 | shen fu | li shizhen row 11 : 1958 | lin zexu | 林则徐 | zheng junli | lin zexu row 12 : 1959 | nie er | 聂耳 | zheng junli | nie er | col : year row 1 : 1949 row 2 : 1949 | select year where year = 1949 <table_name> : table \begin{tabular}{llllll}
\toprule
& year & english title & chinese title & director & role \\
\midrule
0 & 1933 & twenty-four hours in shanghai & 上海二十四小时 & shen xiling & none \\
1 & 1937 & street angel & 马路天使 & yuan muzhi & xiao chen \\
2 & 1937 & crossroads & 十字街头 & shen xiling & zhao \\
3 & 1947 & far away love & 遙遠的愛 & chen liting & xiao yuanxi \\
4 & 1947 & rhapsody of happiness & 幸福狂想曲 & chen liting & none \\
5 & 1949 & crows and sparrows & 烏鴉与麻雀 & zheng junli & little broadcast \\
6 & 1949 & women side by side & 丽人行 & chen liting & zhang yuliang \\
7 & 1950 & the life of wu xun & 武训传 & sun yu & wu xun \\
8 & 1951 & the married couple & 我们夫妇之间 & zheng junli & none \\
9 & 1956 & li shizhen & 李时珍 & shen fu & li shizhen \\
10 & 1958 & lin zexu & 林则徐 & zheng junli & lin zexu \\
11 & 1959 & nie er & 聂耳 & zheng junli & nie er \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& year \\
\midrule
0 & 1949 \\
1 & 1949 \\
\bottomrule
\end{tabular}
| select year where year = 1949 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>english title</th>
<th>chinese title</th>
<th>director</th>
<th>role</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1933</td>
<td>twenty-four hours in shanghai</td>
<td>上海二十四小时</td>
<td>shen xiling</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>1937</td>
<td>street angel</td>
<td>马路天使</td>
<td>yuan muzhi</td>
<td>xiao chen</td>
</tr>
<tr>
<th>2</th>
<td>1937</td>
<td>crossroads</td>
<td>十字街头</td>
<td>shen xiling</td>
<td>zhao</td>
</tr>
<tr>
<th>3</th>
<td>1947</td>
<td>far away love</td>
<td>遙遠的愛</td>
<td>chen liting</td>
<td>xiao yuanxi</td>
</tr>
<tr>
<th>4</th>
<td>1947</td>
<td>rhapsody of happiness</td>
<td>幸福狂想曲</td>
<td>chen liting</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>1949</td>
<td>crows and sparrows</td>
<td>烏鴉与麻雀</td>
<td>zheng junli</td>
<td>little broadcast</td>
</tr>
<tr>
<th>6</th>
<td>1949</td>
<td>women side by side</td>
<td>丽人行</td>
<td>chen liting</td>
<td>zhang yuliang</td>
</tr>
<tr>
<th>7</th>
<td>1950</td>
<td>the life of wu xun</td>
<td>武训传</td>
<td>sun yu</td>
<td>wu xun</td>
</tr>
<tr>
<th>8</th>
<td>1951</td>
<td>the married couple</td>
<td>我们夫妇之间</td>
<td>zheng junli</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>1956</td>
<td>li shizhen</td>
<td>李时珍</td>
<td>shen fu</td>
<td>li shizhen</td>
</tr>
<tr>
<th>10</th>
<td>1958</td>
<td>lin zexu</td>
<td>林则徐</td>
<td>zheng junli</td>
<td>lin zexu</td>
</tr>
<tr>
<th>11</th>
<td>1959</td>
<td>nie er</td>
<td>聂耳</td>
<td>zheng junli</td>
<td>nie er</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1949</td>
</tr>
<tr>
<th>1</th>
<td>1949</td>
</tr>
</tbody>
</table> | select year where year = 1949 <table_name> : table | | year | english title | chinese title | director | role |
|---:|-------:|:------------------------------|:----------------|:------------|:-----------------|
| 0 | 1933 | twenty-four hours in shanghai | 上海二十四小时 | shen xiling | none |
| 1 | 1937 | street angel | 马路天使 | yuan muzhi | xiao chen |
| 2 | 1937 | crossroads | 十字街头 | shen xiling | zhao |
| 3 | 1947 | far away love | 遙遠的愛 | chen liting | xiao yuanxi |
| 4 | 1947 | rhapsody of happiness | 幸福狂想曲 | chen liting | none |
| 5 | 1949 | crows and sparrows | 烏鴉与麻雀 | zheng junli | little broadcast |
| 6 | 1949 | women side by side | 丽人行 | chen liting | zhang yuliang |
| 7 | 1950 | the life of wu xun | 武训传 | sun yu | wu xun |
| 8 | 1951 | the married couple | 我们夫妇之间 | zheng junli | none |
| 9 | 1956 | li shizhen | 李时珍 | shen fu | li shizhen |
| 10 | 1958 | lin zexu | 林则徐 | zheng junli | lin zexu |
| 11 | 1959 | nie er | 聂耳 | zheng junli | nie er | | | | year |
|---:|-------:|
| 0 | 1949 |
| 1 | 1949 | | [
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select count ( party ) where district office = 'lake charles' col : district | name | party | district office | first elected row 1 : 1 | a.g. crowe | rep | slidell | 2007.0 row 2 : 2 | troy brown | dem | napoleonville | 2011.0 row 3 : 3 | j.p. morrell | dem | new orleans | 2008.0 row 4 : 4 | ed murray | dem | new orleans | 2005.0 row 5 : 5 | karen carter peterson | dem | new orleans | 2010.0 row 6 : 6 | bodi white | rep | baton rouge | 2011.0 row 7 : 7 | david heitmeier | dem | new orleans | 2007.0 row 8 : 8 | john alario | rep | westwego | 2007.0 row 9 : 9 | conrad appel | rep | metairie | 2008.0 row 10 : 10 | daniel martiny | rep | metairie | 2007.0 row 11 : 11 | jack donahue | rep | mandeville | 2007.0 row 12 : 12 | ben nevers | dem | bogalusa | 2003.0 row 13 : 13 | dale m. erdey | rep | livingston | 2007.0 row 14 : 14 | yvonne dorsey-colomb | dem | baton rouge | 2007.0 row 15 : 15 | sharon weston broome | dem | baton rouge | 2004.0 row 16 : 16 | dan claitor | rep | baton rouge | 2009.0 row 17 : 17 | rick ward, iii | rep | port allen | 2011.0 row 18 : 18 | jody amedee | rep | gonzales | 2003.0 row 19 : 19 | gary smith, jr | dem | norco | 2011.0 row 20 : 20 | norby chabert | rep | houma | 2009.0 row 21 : 21 | bret allain | rep | franklin | 2011.0 row 22 : 22 | fred h. mills, jr | rep | new iberia | 2011.0 row 23 : 23 | page cortez | rep | lafayette | 2011.0 row 24 : 24 | elbert guillory | rep | opelousas | 2009.0 row 25 : 25 | dan "blade" morrish | rep | jennings | 2007.0 row 26 : 26 | jonathan perry | rep | kaplan | 2011.0 row 27 : 27 | ronnie johns | rep | lake charles | 2011.0 row 28 : 28 | eric lafleur | dem | ville platte | 2007.0 row 29 : 29 | rick gallot | dem | ruston | 2011.0 row 30 : 30 | john r. smith | rep | leesville | 2007.0 row 31 : 31 | gerald long | rep | winnfield | 2007.0 row 32 : 32 | neil riser | rep | columbia | 2007.0 row 33 : 33 | mike walsworth | rep | west monroe | 2007.0 row 34 : 34 | francis c. thompson | dem | delhi | 2007.0 row 35 : 35 | robert kostelka | rep | monroe | 2003.0 row 36 : 36 | robert adley | rep | benton | 2003.0 row 37 : 37 | bar | | | row 38 : peacock | rep | bossier | 2011 | row 39 : 38 | sherri smith buffington | rep | keithville | 2003.0 row 40 : 39 | gregory tarver | dem | shreveport | 2011.0 | col : count ( "party" ) row 1 : 1 | select count ( party ) where district office = 'lake charles' <table_name> : table \begin{tabular}{llllll}
\toprule
& district & name & party & district office & first elected \\
\midrule
0 & 1 & a.g. crowe & rep & slidell & 2007.0 \\
1 & 2 & troy brown & dem & napoleonville & 2011.0 \\
2 & 3 & j.p. morrell & dem & new orleans & 2008.0 \\
3 & 4 & ed murray & dem & new orleans & 2005.0 \\
4 & 5 & karen carter peterson & dem & new orleans & 2010.0 \\
5 & 6 & bodi white & rep & baton rouge & 2011.0 \\
6 & 7 & david heitmeier & dem & new orleans & 2007.0 \\
7 & 8 & john alario & rep & westwego & 2007.0 \\
8 & 9 & conrad appel & rep & metairie & 2008.0 \\
9 & 10 & daniel martiny & rep & metairie & 2007.0 \\
10 & 11 & jack donahue & rep & mandeville & 2007.0 \\
11 & 12 & ben nevers & dem & bogalusa & 2003.0 \\
12 & 13 & dale m. erdey & rep & livingston & 2007.0 \\
13 & 14 & yvonne dorsey-colomb & dem & baton rouge & 2007.0 \\
14 & 15 & sharon weston broome & dem & baton rouge & 2004.0 \\
15 & 16 & dan claitor & rep & baton rouge & 2009.0 \\
16 & 17 & rick ward, iii & rep & port allen & 2011.0 \\
17 & 18 & jody amedee & rep & gonzales & 2003.0 \\
18 & 19 & gary smith, jr & dem & norco & 2011.0 \\
19 & 20 & norby chabert & rep & houma & 2009.0 \\
20 & 21 & bret allain & rep & franklin & 2011.0 \\
21 & 22 & fred h. mills, jr & rep & new iberia & 2011.0 \\
22 & 23 & page cortez & rep & lafayette & 2011.0 \\
23 & 24 & elbert guillory & rep & opelousas & 2009.0 \\
24 & 25 & dan "blade" morrish & rep & jennings & 2007.0 \\
25 & 26 & jonathan perry & rep & kaplan & 2011.0 \\
26 & 27 & ronnie johns & rep & lake charles & 2011.0 \\
27 & 28 & eric lafleur & dem & ville platte & 2007.0 \\
28 & 29 & rick gallot & dem & ruston & 2011.0 \\
29 & 30 & john r. smith & rep & leesville & 2007.0 \\
30 & 31 & gerald long & rep & winnfield & 2007.0 \\
31 & 32 & neil riser & rep & columbia & 2007.0 \\
32 & 33 & mike walsworth & rep & west monroe & 2007.0 \\
33 & 34 & francis c. thompson & dem & delhi & 2007.0 \\
34 & 35 & robert kostelka & rep & monroe & 2003.0 \\
35 & 36 & robert adley & rep & benton & 2003.0 \\
36 & 37 & bar & & & \\
37 & peacock & rep & bossier & 2011 & \\
38 & 38 & sherri smith buffington & rep & keithville & 2003.0 \\
39 & 39 & gregory tarver & dem & shreveport & 2011.0 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "party" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( party ) where district office = 'lake charles' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>district</th>
<th>name</th>
<th>party</th>
<th>district office</th>
<th>first elected</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>a.g. crowe</td>
<td>rep</td>
<td>slidell</td>
<td>2007.0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>troy brown</td>
<td>dem</td>
<td>napoleonville</td>
<td>2011.0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>j.p. morrell</td>
<td>dem</td>
<td>new orleans</td>
<td>2008.0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ed murray</td>
<td>dem</td>
<td>new orleans</td>
<td>2005.0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>karen carter peterson</td>
<td>dem</td>
<td>new orleans</td>
<td>2010.0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>bodi white</td>
<td>rep</td>
<td>baton rouge</td>
<td>2011.0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>david heitmeier</td>
<td>dem</td>
<td>new orleans</td>
<td>2007.0</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>john alario</td>
<td>rep</td>
<td>westwego</td>
<td>2007.0</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>conrad appel</td>
<td>rep</td>
<td>metairie</td>
<td>2008.0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>daniel martiny</td>
<td>rep</td>
<td>metairie</td>
<td>2007.0</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>jack donahue</td>
<td>rep</td>
<td>mandeville</td>
<td>2007.0</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>ben nevers</td>
<td>dem</td>
<td>bogalusa</td>
<td>2003.0</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>dale m. erdey</td>
<td>rep</td>
<td>livingston</td>
<td>2007.0</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>yvonne dorsey-colomb</td>
<td>dem</td>
<td>baton rouge</td>
<td>2007.0</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>sharon weston broome</td>
<td>dem</td>
<td>baton rouge</td>
<td>2004.0</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>dan claitor</td>
<td>rep</td>
<td>baton rouge</td>
<td>2009.0</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>rick ward, iii</td>
<td>rep</td>
<td>port allen</td>
<td>2011.0</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>jody amedee</td>
<td>rep</td>
<td>gonzales</td>
<td>2003.0</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>gary smith, jr</td>
<td>dem</td>
<td>norco</td>
<td>2011.0</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>norby chabert</td>
<td>rep</td>
<td>houma</td>
<td>2009.0</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>bret allain</td>
<td>rep</td>
<td>franklin</td>
<td>2011.0</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>fred h. mills, jr</td>
<td>rep</td>
<td>new iberia</td>
<td>2011.0</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>page cortez</td>
<td>rep</td>
<td>lafayette</td>
<td>2011.0</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>elbert guillory</td>
<td>rep</td>
<td>opelousas</td>
<td>2009.0</td>
</tr>
<tr>
<th>24</th>
<td>25</td>
<td>dan "blade" morrish</td>
<td>rep</td>
<td>jennings</td>
<td>2007.0</td>
</tr>
<tr>
<th>25</th>
<td>26</td>
<td>jonathan perry</td>
<td>rep</td>
<td>kaplan</td>
<td>2011.0</td>
</tr>
<tr>
<th>26</th>
<td>27</td>
<td>ronnie johns</td>
<td>rep</td>
<td>lake charles</td>
<td>2011.0</td>
</tr>
<tr>
<th>27</th>
<td>28</td>
<td>eric lafleur</td>
<td>dem</td>
<td>ville platte</td>
<td>2007.0</td>
</tr>
<tr>
<th>28</th>
<td>29</td>
<td>rick gallot</td>
<td>dem</td>
<td>ruston</td>
<td>2011.0</td>
</tr>
<tr>
<th>29</th>
<td>30</td>
<td>john r. smith</td>
<td>rep</td>
<td>leesville</td>
<td>2007.0</td>
</tr>
<tr>
<th>30</th>
<td>31</td>
<td>gerald long</td>
<td>rep</td>
<td>winnfield</td>
<td>2007.0</td>
</tr>
<tr>
<th>31</th>
<td>32</td>
<td>neil riser</td>
<td>rep</td>
<td>columbia</td>
<td>2007.0</td>
</tr>
<tr>
<th>32</th>
<td>33</td>
<td>mike walsworth</td>
<td>rep</td>
<td>west monroe</td>
<td>2007.0</td>
</tr>
<tr>
<th>33</th>
<td>34</td>
<td>francis c. thompson</td>
<td>dem</td>
<td>delhi</td>
<td>2007.0</td>
</tr>
<tr>
<th>34</th>
<td>35</td>
<td>robert kostelka</td>
<td>rep</td>
<td>monroe</td>
<td>2003.0</td>
</tr>
<tr>
<th>35</th>
<td>36</td>
<td>robert adley</td>
<td>rep</td>
<td>benton</td>
<td>2003.0</td>
</tr>
<tr>
<th>36</th>
<td>37</td>
<td>bar</td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>37</th>
<td>peacock</td>
<td>rep</td>
<td>bossier</td>
<td>2011</td>
<td></td>
</tr>
<tr>
<th>38</th>
<td>38</td>
<td>sherri smith buffington</td>
<td>rep</td>
<td>keithville</td>
<td>2003.0</td>
</tr>
<tr>
<th>39</th>
<td>39</td>
<td>gregory tarver</td>
<td>dem</td>
<td>shreveport</td>
<td>2011.0</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "party" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( party ) where district office = 'lake charles' <table_name> : table | | district | name | party | district office | first elected |
|---:|:-----------|:------------------------|:--------|:------------------|:----------------|
| 0 | 1 | a.g. crowe | rep | slidell | 2007.0 |
| 1 | 2 | troy brown | dem | napoleonville | 2011.0 |
| 2 | 3 | j.p. morrell | dem | new orleans | 2008.0 |
| 3 | 4 | ed murray | dem | new orleans | 2005.0 |
| 4 | 5 | karen carter peterson | dem | new orleans | 2010.0 |
| 5 | 6 | bodi white | rep | baton rouge | 2011.0 |
| 6 | 7 | david heitmeier | dem | new orleans | 2007.0 |
| 7 | 8 | john alario | rep | westwego | 2007.0 |
| 8 | 9 | conrad appel | rep | metairie | 2008.0 |
| 9 | 10 | daniel martiny | rep | metairie | 2007.0 |
| 10 | 11 | jack donahue | rep | mandeville | 2007.0 |
| 11 | 12 | ben nevers | dem | bogalusa | 2003.0 |
| 12 | 13 | dale m. erdey | rep | livingston | 2007.0 |
| 13 | 14 | yvonne dorsey-colomb | dem | baton rouge | 2007.0 |
| 14 | 15 | sharon weston broome | dem | baton rouge | 2004.0 |
| 15 | 16 | dan claitor | rep | baton rouge | 2009.0 |
| 16 | 17 | rick ward, iii | rep | port allen | 2011.0 |
| 17 | 18 | jody amedee | rep | gonzales | 2003.0 |
| 18 | 19 | gary smith, jr | dem | norco | 2011.0 |
| 19 | 20 | norby chabert | rep | houma | 2009.0 |
| 20 | 21 | bret allain | rep | franklin | 2011.0 |
| 21 | 22 | fred h. mills, jr | rep | new iberia | 2011.0 |
| 22 | 23 | page cortez | rep | lafayette | 2011.0 |
| 23 | 24 | elbert guillory | rep | opelousas | 2009.0 |
| 24 | 25 | dan "blade" morrish | rep | jennings | 2007.0 |
| 25 | 26 | jonathan perry | rep | kaplan | 2011.0 |
| 26 | 27 | ronnie johns | rep | lake charles | 2011.0 |
| 27 | 28 | eric lafleur | dem | ville platte | 2007.0 |
| 28 | 29 | rick gallot | dem | ruston | 2011.0 |
| 29 | 30 | john r. smith | rep | leesville | 2007.0 |
| 30 | 31 | gerald long | rep | winnfield | 2007.0 |
| 31 | 32 | neil riser | rep | columbia | 2007.0 |
| 32 | 33 | mike walsworth | rep | west monroe | 2007.0 |
| 33 | 34 | francis c. thompson | dem | delhi | 2007.0 |
| 34 | 35 | robert kostelka | rep | monroe | 2003.0 |
| 35 | 36 | robert adley | rep | benton | 2003.0 |
| 36 | 37 | bar | | | |
| 37 | peacock | rep | bossier | 2011 | |
| 38 | 38 | sherri smith buffington | rep | keithville | 2003.0 |
| 39 | 39 | gregory tarver | dem | shreveport | 2011.0 | | | | count ( "party" ) |
|---:|--------------------:|
| 0 | 1 | | [
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select record where date = 'apr 29' col : # | date | opponent | score | win | loss | save | crowd | record row 1 : 1 | apr 3 | @min | w 8-1 | morris | williams | none | 34381 | 1-0 row 2 : 2 | apr 5 | @min | w 7-3 | petry | viola | none | 8373 | 2-0 row 3 : 3 | apr 6 | @chw | w 3-2 | wilcox | dotson | hernandez | 42692 | 3-0 row 4 : 4 | apr 7 | @chw | w 4-0 | morris | bannister | none | 24616 | 4-0 row 5 : 5 | apr 8 | @chw | w 7-3 | lopez | seaver | none | 20478 | 5-0 row 6 : 6 | apr 10 | tex | w 5-1 | petry | stewart | none | 51238 | 6-0 row 7 : 7 | apr 12 | tex | w 9-4 | morris | tanana | none | 19154 | 7-0 row 8 : 8 | apr 13 | @bos | w 13-9 | bair | hurst | none | 35179 | 8-0 row 9 : 9 | apr 18 | kcr | w 4-3 (10) | hernandez | beckwith | none | 12310 | 9-0 row 10 : 10 | apr 19 | kcr | l 2-5 | saberhagen | petry | quisenberry | 12100 | 9-1 row 11 : 11 | apr 20 | chw | w 3-2 | lopez | reed | none | 33554 | 10-1 row 12 : 12 | apr 21 | chw | w 4-1 | rozema | hoyt | bair | 34395 | 11-1 row 13 : 13 | apr 22 | chw | w 9-1 | berenguer | brennan | none | 10603 | 12-1 row 14 : 14 | apr 24 | min | w 6-5 | morris | davis | none | none | 13-1 row 15 : 15 | apr 24 | min | w 4-3 | abbott | viola | lopez | 20315 | 14-1 row 16 : 16 | apr 25 | @tex | w 9-4 | wilcox | stewart | hernandez | 25883 | 15-1 row 17 : 17 | apr 26 | @tex | w 7-5 | bair | tanana | lopez | 13559 | 16-1 row 18 : 18 | apr 27 | cle | l 4-8 (19) | aponte | abbott | none | 34112 | 16-2 row 19 : 19 | apr 28 | cle | w 6-2 | morris | behenna | none | 28253 | 17-2 row 20 : 20 | apr 29 | cle | w 6-1 | petry | spillner | none | 24853 | 18-2 | col : record row 1 : 18-2 | select record where date = 'apr 29' <table_name> : table \begin{tabular}{llllllllll}
\toprule
& # & date & opponent & score & win & loss & save & crowd & record \\
\midrule
0 & 1 & apr 3 & @min & w 8-1 & morris & williams & none & 34381 & 1-0 \\
1 & 2 & apr 5 & @min & w 7-3 & petry & viola & none & 8373 & 2-0 \\
2 & 3 & apr 6 & @chw & w 3-2 & wilcox & dotson & hernandez & 42692 & 3-0 \\
3 & 4 & apr 7 & @chw & w 4-0 & morris & bannister & none & 24616 & 4-0 \\
4 & 5 & apr 8 & @chw & w 7-3 & lopez & seaver & none & 20478 & 5-0 \\
5 & 6 & apr 10 & tex & w 5-1 & petry & stewart & none & 51238 & 6-0 \\
6 & 7 & apr 12 & tex & w 9-4 & morris & tanana & none & 19154 & 7-0 \\
7 & 8 & apr 13 & @bos & w 13-9 & bair & hurst & none & 35179 & 8-0 \\
8 & 9 & apr 18 & kcr & w 4-3 (10) & hernandez & beckwith & none & 12310 & 9-0 \\
9 & 10 & apr 19 & kcr & l 2-5 & saberhagen & petry & quisenberry & 12100 & 9-1 \\
10 & 11 & apr 20 & chw & w 3-2 & lopez & reed & none & 33554 & 10-1 \\
11 & 12 & apr 21 & chw & w 4-1 & rozema & hoyt & bair & 34395 & 11-1 \\
12 & 13 & apr 22 & chw & w 9-1 & berenguer & brennan & none & 10603 & 12-1 \\
13 & 14 & apr 24 & min & w 6-5 & morris & davis & none & none & 13-1 \\
14 & 15 & apr 24 & min & w 4-3 & abbott & viola & lopez & 20315 & 14-1 \\
15 & 16 & apr 25 & @tex & w 9-4 & wilcox & stewart & hernandez & 25883 & 15-1 \\
16 & 17 & apr 26 & @tex & w 7-5 & bair & tanana & lopez & 13559 & 16-1 \\
17 & 18 & apr 27 & cle & l 4-8 (19) & aponte & abbott & none & 34112 & 16-2 \\
18 & 19 & apr 28 & cle & w 6-2 & morris & behenna & none & 28253 & 17-2 \\
19 & 20 & apr 29 & cle & w 6-1 & petry & spillner & none & 24853 & 18-2 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& record \\
\midrule
0 & 18-2 \\
\bottomrule
\end{tabular}
| select record where date = 'apr 29' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>date</th>
<th>opponent</th>
<th>score</th>
<th>win</th>
<th>loss</th>
<th>save</th>
<th>crowd</th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>apr 3</td>
<td>@min</td>
<td>w 8-1</td>
<td>morris</td>
<td>williams</td>
<td>none</td>
<td>34381</td>
<td>1-0</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>apr 5</td>
<td>@min</td>
<td>w 7-3</td>
<td>petry</td>
<td>viola</td>
<td>none</td>
<td>8373</td>
<td>2-0</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>apr 6</td>
<td>@chw</td>
<td>w 3-2</td>
<td>wilcox</td>
<td>dotson</td>
<td>hernandez</td>
<td>42692</td>
<td>3-0</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>apr 7</td>
<td>@chw</td>
<td>w 4-0</td>
<td>morris</td>
<td>bannister</td>
<td>none</td>
<td>24616</td>
<td>4-0</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>apr 8</td>
<td>@chw</td>
<td>w 7-3</td>
<td>lopez</td>
<td>seaver</td>
<td>none</td>
<td>20478</td>
<td>5-0</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>apr 10</td>
<td>tex</td>
<td>w 5-1</td>
<td>petry</td>
<td>stewart</td>
<td>none</td>
<td>51238</td>
<td>6-0</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>apr 12</td>
<td>tex</td>
<td>w 9-4</td>
<td>morris</td>
<td>tanana</td>
<td>none</td>
<td>19154</td>
<td>7-0</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>apr 13</td>
<td>@bos</td>
<td>w 13-9</td>
<td>bair</td>
<td>hurst</td>
<td>none</td>
<td>35179</td>
<td>8-0</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>apr 18</td>
<td>kcr</td>
<td>w 4-3 (10)</td>
<td>hernandez</td>
<td>beckwith</td>
<td>none</td>
<td>12310</td>
<td>9-0</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>apr 19</td>
<td>kcr</td>
<td>l 2-5</td>
<td>saberhagen</td>
<td>petry</td>
<td>quisenberry</td>
<td>12100</td>
<td>9-1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>apr 20</td>
<td>chw</td>
<td>w 3-2</td>
<td>lopez</td>
<td>reed</td>
<td>none</td>
<td>33554</td>
<td>10-1</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>apr 21</td>
<td>chw</td>
<td>w 4-1</td>
<td>rozema</td>
<td>hoyt</td>
<td>bair</td>
<td>34395</td>
<td>11-1</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>apr 22</td>
<td>chw</td>
<td>w 9-1</td>
<td>berenguer</td>
<td>brennan</td>
<td>none</td>
<td>10603</td>
<td>12-1</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>apr 24</td>
<td>min</td>
<td>w 6-5</td>
<td>morris</td>
<td>davis</td>
<td>none</td>
<td>none</td>
<td>13-1</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>apr 24</td>
<td>min</td>
<td>w 4-3</td>
<td>abbott</td>
<td>viola</td>
<td>lopez</td>
<td>20315</td>
<td>14-1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>apr 25</td>
<td>@tex</td>
<td>w 9-4</td>
<td>wilcox</td>
<td>stewart</td>
<td>hernandez</td>
<td>25883</td>
<td>15-1</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>apr 26</td>
<td>@tex</td>
<td>w 7-5</td>
<td>bair</td>
<td>tanana</td>
<td>lopez</td>
<td>13559</td>
<td>16-1</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>apr 27</td>
<td>cle</td>
<td>l 4-8 (19)</td>
<td>aponte</td>
<td>abbott</td>
<td>none</td>
<td>34112</td>
<td>16-2</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>apr 28</td>
<td>cle</td>
<td>w 6-2</td>
<td>morris</td>
<td>behenna</td>
<td>none</td>
<td>28253</td>
<td>17-2</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>apr 29</td>
<td>cle</td>
<td>w 6-1</td>
<td>petry</td>
<td>spillner</td>
<td>none</td>
<td>24853</td>
<td>18-2</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>record</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>18-2</td>
</tr>
</tbody>
</table> | select record where date = 'apr 29' <table_name> : table | | # | date | opponent | score | win | loss | save | crowd | record |
|---:|----:|:-------|:-----------|:-----------|:-----------|:----------|:------------|:--------|:---------|
| 0 | 1 | apr 3 | @min | w 8-1 | morris | williams | none | 34381 | 1-0 |
| 1 | 2 | apr 5 | @min | w 7-3 | petry | viola | none | 8373 | 2-0 |
| 2 | 3 | apr 6 | @chw | w 3-2 | wilcox | dotson | hernandez | 42692 | 3-0 |
| 3 | 4 | apr 7 | @chw | w 4-0 | morris | bannister | none | 24616 | 4-0 |
| 4 | 5 | apr 8 | @chw | w 7-3 | lopez | seaver | none | 20478 | 5-0 |
| 5 | 6 | apr 10 | tex | w 5-1 | petry | stewart | none | 51238 | 6-0 |
| 6 | 7 | apr 12 | tex | w 9-4 | morris | tanana | none | 19154 | 7-0 |
| 7 | 8 | apr 13 | @bos | w 13-9 | bair | hurst | none | 35179 | 8-0 |
| 8 | 9 | apr 18 | kcr | w 4-3 (10) | hernandez | beckwith | none | 12310 | 9-0 |
| 9 | 10 | apr 19 | kcr | l 2-5 | saberhagen | petry | quisenberry | 12100 | 9-1 |
| 10 | 11 | apr 20 | chw | w 3-2 | lopez | reed | none | 33554 | 10-1 |
| 11 | 12 | apr 21 | chw | w 4-1 | rozema | hoyt | bair | 34395 | 11-1 |
| 12 | 13 | apr 22 | chw | w 9-1 | berenguer | brennan | none | 10603 | 12-1 |
| 13 | 14 | apr 24 | min | w 6-5 | morris | davis | none | none | 13-1 |
| 14 | 15 | apr 24 | min | w 4-3 | abbott | viola | lopez | 20315 | 14-1 |
| 15 | 16 | apr 25 | @tex | w 9-4 | wilcox | stewart | hernandez | 25883 | 15-1 |
| 16 | 17 | apr 26 | @tex | w 7-5 | bair | tanana | lopez | 13559 | 16-1 |
| 17 | 18 | apr 27 | cle | l 4-8 (19) | aponte | abbott | none | 34112 | 16-2 |
| 18 | 19 | apr 28 | cle | w 6-2 | morris | behenna | none | 28253 | 17-2 |
| 19 | 20 | apr 29 | cle | w 6-1 | petry | spillner | none | 24853 | 18-2 | | | | record |
|---:|:---------|
| 0 | 18-2 | | [
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] |
select count ( * ) where airdate = '1 may 2010' col : episode | airdate | game 1 | game 2 | game 3 | viewers row 1 : 1 | 17 april 2010 | 'twin peaks' | 'a walk in the dark' | 'lock and key' | 4.52m row 2 : 2 | 24 april 2010 | 'caught in the net' | 'stick 'em up' | 'power trip' | 4.41m row 3 : 3 | 1 may 2010 | 'knotting hills' | 'it's a wrap!' | 'lock and key' | 4.31m row 4 : 4 | 8 may 2010 | 'caught in the net' | 'a walk in the dark' | 'power trip' | 4.44m row 5 : 5 | 15 may 2010 | 'twin peaks' | 'it's a wrap!' | 'lock and key' | 4.46m row 6 : 6 | 22 may 2010 | 'knotting hills' | 'stick 'em up' | 'power trip' | under 2.61m row 7 : 7 | 29 may 2010 | 'caught in the net' | 'a walk in the dark' | 'lock and key' | 4.68m row 8 : 8 | 5 june 2010 | 'knotting hills' | 'stick 'em up' | 'lock and key' | 3.44m | col : count ( "*" ) row 1 : 1 | select count ( * ) where airdate = '1 may 2010' <table_name> : table \begin{tabular}{lllllll}
\toprule
& episode & airdate & game 1 & game 2 & game 3 & viewers \\
\midrule
0 & 1 & 17 april 2010 & 'twin peaks' & 'a walk in the dark' & 'lock and key' & 4.52m \\
1 & 2 & 24 april 2010 & 'caught in the net' & 'stick 'em up' & 'power trip' & 4.41m \\
2 & 3 & 1 may 2010 & 'knotting hills' & 'it's a wrap!' & 'lock and key' & 4.31m \\
3 & 4 & 8 may 2010 & 'caught in the net' & 'a walk in the dark' & 'power trip' & 4.44m \\
4 & 5 & 15 may 2010 & 'twin peaks' & 'it's a wrap!' & 'lock and key' & 4.46m \\
5 & 6 & 22 may 2010 & 'knotting hills' & 'stick 'em up' & 'power trip' & under 2.61m \\
6 & 7 & 29 may 2010 & 'caught in the net' & 'a walk in the dark' & 'lock and key' & 4.68m \\
7 & 8 & 5 june 2010 & 'knotting hills' & 'stick 'em up' & 'lock and key' & 3.44m \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where airdate = '1 may 2010' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>episode</th>
<th>airdate</th>
<th>game 1</th>
<th>game 2</th>
<th>game 3</th>
<th>viewers</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>17 april 2010</td>
<td>'twin peaks'</td>
<td>'a walk in the dark'</td>
<td>'lock and key'</td>
<td>4.52m</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>24 april 2010</td>
<td>'caught in the net'</td>
<td>'stick 'em up'</td>
<td>'power trip'</td>
<td>4.41m</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>1 may 2010</td>
<td>'knotting hills'</td>
<td>'it's a wrap!'</td>
<td>'lock and key'</td>
<td>4.31m</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>8 may 2010</td>
<td>'caught in the net'</td>
<td>'a walk in the dark'</td>
<td>'power trip'</td>
<td>4.44m</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>15 may 2010</td>
<td>'twin peaks'</td>
<td>'it's a wrap!'</td>
<td>'lock and key'</td>
<td>4.46m</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>22 may 2010</td>
<td>'knotting hills'</td>
<td>'stick 'em up'</td>
<td>'power trip'</td>
<td>under 2.61m</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>29 may 2010</td>
<td>'caught in the net'</td>
<td>'a walk in the dark'</td>
<td>'lock and key'</td>
<td>4.68m</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>5 june 2010</td>
<td>'knotting hills'</td>
<td>'stick 'em up'</td>
<td>'lock and key'</td>
<td>3.44m</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where airdate = '1 may 2010' <table_name> : table | | episode | airdate | game 1 | game 2 | game 3 | viewers |
|---:|----------:|:--------------|:--------------------|:---------------------|:---------------|:------------|
| 0 | 1 | 17 april 2010 | 'twin peaks' | 'a walk in the dark' | 'lock and key' | 4.52m |
| 1 | 2 | 24 april 2010 | 'caught in the net' | 'stick 'em up' | 'power trip' | 4.41m |
| 2 | 3 | 1 may 2010 | 'knotting hills' | 'it's a wrap!' | 'lock and key' | 4.31m |
| 3 | 4 | 8 may 2010 | 'caught in the net' | 'a walk in the dark' | 'power trip' | 4.44m |
| 4 | 5 | 15 may 2010 | 'twin peaks' | 'it's a wrap!' | 'lock and key' | 4.46m |
| 5 | 6 | 22 may 2010 | 'knotting hills' | 'stick 'em up' | 'power trip' | under 2.61m |
| 6 | 7 | 29 may 2010 | 'caught in the net' | 'a walk in the dark' | 'lock and key' | 4.68m |
| 7 | 8 | 5 june 2010 | 'knotting hills' | 'stick 'em up' | 'lock and key' | 3.44m | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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select count ( date ) where points for > 1335 col : week | date | result | record | opponent | points for | points against | first downs | attendance row 1 : 1 | september 18 | win | 1-0 | at minnesota vikings | 16 | 10 | 16 | 47,678 row 2 : 2 | september 25 | win | 2-0 | new york giants | 41 | 21 | 25 | 64,215 row 3 : 3 | october 2 | win | 3-0 | tampa bay buccaneers | 23 | 7 | 23 | 55,316 row 4 : 4 | october 9 | win | 4-0 | at st. louis cardinals | 30 | 24 | 22 | 50,129 row 5 : 5 | october 16 | win | 5-0 | washington redskins | 34 | 16 | 23 | 62,115 row 6 : 6 | october 23 | win | 6-0 | at philadelphia eagles | 16 | 10 | 17 | 65,507 row 7 : 7 | october 30 | win | 7-0 | detroit lions | 37 | 0 | 20 | 63,160 row 8 : 8 | november 6 | win | 8-0 | at new york giants | 24 | 10 | 13 | 74,532 row 9 : 9 | november 14 | loss | 8-1 | st. louis cardinals | 17 | 24 | 16 | 64,038 row 10 : 10 | november 20 | loss | 8-2 | at pittsburgh steelers | 13 | 28 | 20 | 49,761 row 11 : 11 | november 27 | win | 9-2 | at washington redskins | 14 | 7 | 19 | 55,031 row 12 : 12 | december 4 | win | 10-2 | philadelphia eagles | 24 | 14 | 19 | 60,289 row 13 : 13 | december 12 | win | 11-2 | at san francisco 49ers | 42 | 35 | 24 | 55,851 row 14 : 14 | december 18 | win | 12-2 | denver broncos | 14 | 6 | 15 | 63,752 | col : count ( "date" ) row 1 : 13 | select count ( date ) where points for > 1335 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& week & date & result & record & opponent & points for & points against & first downs & attendance \\
\midrule
0 & 1 & september 18 & win & 1-0 & at minnesota vikings & 16 & 10 & 16 & 47,678 \\
1 & 2 & september 25 & win & 2-0 & new york giants & 41 & 21 & 25 & 64,215 \\
2 & 3 & october 2 & win & 3-0 & tampa bay buccaneers & 23 & 7 & 23 & 55,316 \\
3 & 4 & october 9 & win & 4-0 & at st. louis cardinals & 30 & 24 & 22 & 50,129 \\
4 & 5 & october 16 & win & 5-0 & washington redskins & 34 & 16 & 23 & 62,115 \\
5 & 6 & october 23 & win & 6-0 & at philadelphia eagles & 16 & 10 & 17 & 65,507 \\
6 & 7 & october 30 & win & 7-0 & detroit lions & 37 & 0 & 20 & 63,160 \\
7 & 8 & november 6 & win & 8-0 & at new york giants & 24 & 10 & 13 & 74,532 \\
8 & 9 & november 14 & loss & 8-1 & st. louis cardinals & 17 & 24 & 16 & 64,038 \\
9 & 10 & november 20 & loss & 8-2 & at pittsburgh steelers & 13 & 28 & 20 & 49,761 \\
10 & 11 & november 27 & win & 9-2 & at washington redskins & 14 & 7 & 19 & 55,031 \\
11 & 12 & december 4 & win & 10-2 & philadelphia eagles & 24 & 14 & 19 & 60,289 \\
12 & 13 & december 12 & win & 11-2 & at san francisco 49ers & 42 & 35 & 24 & 55,851 \\
13 & 14 & december 18 & win & 12-2 & denver broncos & 14 & 6 & 15 & 63,752 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "date" ) \\
\midrule
0 & 13 \\
\bottomrule
\end{tabular}
| select count ( date ) where points for > 1335 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>week</th>
<th>date</th>
<th>result</th>
<th>record</th>
<th>opponent</th>
<th>points for</th>
<th>points against</th>
<th>first downs</th>
<th>attendance</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>september 18</td>
<td>win</td>
<td>1-0</td>
<td>at minnesota vikings</td>
<td>16</td>
<td>10</td>
<td>16</td>
<td>47,678</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>september 25</td>
<td>win</td>
<td>2-0</td>
<td>new york giants</td>
<td>41</td>
<td>21</td>
<td>25</td>
<td>64,215</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>october 2</td>
<td>win</td>
<td>3-0</td>
<td>tampa bay buccaneers</td>
<td>23</td>
<td>7</td>
<td>23</td>
<td>55,316</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>october 9</td>
<td>win</td>
<td>4-0</td>
<td>at st. louis cardinals</td>
<td>30</td>
<td>24</td>
<td>22</td>
<td>50,129</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>october 16</td>
<td>win</td>
<td>5-0</td>
<td>washington redskins</td>
<td>34</td>
<td>16</td>
<td>23</td>
<td>62,115</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>october 23</td>
<td>win</td>
<td>6-0</td>
<td>at philadelphia eagles</td>
<td>16</td>
<td>10</td>
<td>17</td>
<td>65,507</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>october 30</td>
<td>win</td>
<td>7-0</td>
<td>detroit lions</td>
<td>37</td>
<td>0</td>
<td>20</td>
<td>63,160</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>november 6</td>
<td>win</td>
<td>8-0</td>
<td>at new york giants</td>
<td>24</td>
<td>10</td>
<td>13</td>
<td>74,532</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>november 14</td>
<td>loss</td>
<td>8-1</td>
<td>st. louis cardinals</td>
<td>17</td>
<td>24</td>
<td>16</td>
<td>64,038</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>november 20</td>
<td>loss</td>
<td>8-2</td>
<td>at pittsburgh steelers</td>
<td>13</td>
<td>28</td>
<td>20</td>
<td>49,761</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>november 27</td>
<td>win</td>
<td>9-2</td>
<td>at washington redskins</td>
<td>14</td>
<td>7</td>
<td>19</td>
<td>55,031</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>december 4</td>
<td>win</td>
<td>10-2</td>
<td>philadelphia eagles</td>
<td>24</td>
<td>14</td>
<td>19</td>
<td>60,289</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>december 12</td>
<td>win</td>
<td>11-2</td>
<td>at san francisco 49ers</td>
<td>42</td>
<td>35</td>
<td>24</td>
<td>55,851</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>december 18</td>
<td>win</td>
<td>12-2</td>
<td>denver broncos</td>
<td>14</td>
<td>6</td>
<td>15</td>
<td>63,752</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "date" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>13</td>
</tr>
</tbody>
</table> | select count ( date ) where points for > 1335 <table_name> : table | | week | date | result | record | opponent | points for | points against | first downs | attendance |
|---:|-------:|:-------------|:---------|:---------|:-----------------------|-------------:|-----------------:|--------------:|:-------------|
| 0 | 1 | september 18 | win | 1-0 | at minnesota vikings | 16 | 10 | 16 | 47,678 |
| 1 | 2 | september 25 | win | 2-0 | new york giants | 41 | 21 | 25 | 64,215 |
| 2 | 3 | october 2 | win | 3-0 | tampa bay buccaneers | 23 | 7 | 23 | 55,316 |
| 3 | 4 | october 9 | win | 4-0 | at st. louis cardinals | 30 | 24 | 22 | 50,129 |
| 4 | 5 | october 16 | win | 5-0 | washington redskins | 34 | 16 | 23 | 62,115 |
| 5 | 6 | october 23 | win | 6-0 | at philadelphia eagles | 16 | 10 | 17 | 65,507 |
| 6 | 7 | october 30 | win | 7-0 | detroit lions | 37 | 0 | 20 | 63,160 |
| 7 | 8 | november 6 | win | 8-0 | at new york giants | 24 | 10 | 13 | 74,532 |
| 8 | 9 | november 14 | loss | 8-1 | st. louis cardinals | 17 | 24 | 16 | 64,038 |
| 9 | 10 | november 20 | loss | 8-2 | at pittsburgh steelers | 13 | 28 | 20 | 49,761 |
| 10 | 11 | november 27 | win | 9-2 | at washington redskins | 14 | 7 | 19 | 55,031 |
| 11 | 12 | december 4 | win | 10-2 | philadelphia eagles | 24 | 14 | 19 | 60,289 |
| 12 | 13 | december 12 | win | 11-2 | at san francisco 49ers | 42 | 35 | 24 | 55,851 |
| 13 | 14 | december 18 | win | 12-2 | denver broncos | 14 | 6 | 15 | 63,752 | | | | count ( "date" ) |
|---:|-------------------:|
| 0 | 13 | | [
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select count ( pos ) where points = 'none' col : pos | rider | manufacturer | laps | time/retired | grid | points row 1 : 1 | manuel poggiali | gilera | 25 | 41:18.211 | 1 | 25 row 2 : 2 | dani pedrosa | honda | 25 | 0.019 | 4 | 20 row 3 : 3 | steve jenkner | aprilia | 25 | 9.888 | 3 | 16 row 4 : 4 | lucio cecchinello | aprilia | 25 | 15.397 | 5 | 13 row 5 : 5 | simone sanna | aprilia | 25 | 15.452 | 8 | 11 row 6 : 6 | joan olive | honda | 25 | 15.486 | 20 | 10 row 7 : 7 | stefano bianco | aprilia | 25 | 15.549 | 11 | 9 row 8 : 8 | pablo nieto | aprilia | 25 | 16.218 | 2 | 8 row 9 : 9 | mika kallio | honda | 25 | 22.762 | 10 | 7 row 10 : 10 | mirko giansanti | honda | 25 | 22.839 | 16 | 6 row 11 : 11 | arnaud vincent | aprilia | 25 | 23.067 | 23 | 5 row 12 : 12 | andrea ballerini | honda | 25 | 23.134 | 18 | 4 row 13 : 13 | stefano perugini | italjet | 25 | 43.345 | 17 | 3 row 14 : 14 | jorge lorenzo | derbi | 25 | 43.973 | 7 | 2 row 15 : 15 | masao azuma | honda | 25 | 47.189 | 13 | 1 row 16 : 16 | jakub smrz | honda | 25 | 47.333 | 24 | none row 17 : 17 | gianluigi scalvini | aprilia | 25 | 52 | 22 | none row 18 : 18 | hector barbera | aprilia | 25 | +1:11.358 | 27 | none row 19 : 19 | mattia angeloni | gilera | 25 | +1:11.488 | 29 | none row 20 : 20 | alex baldolini | aprilia | 25 | +1:21.603 | 32 | none row 21 : 21 | jaroslav hules | aprilia | 25 | +1:21.681 | 15 | none row 22 : 22 | julian simon | honda | 25 | +1:31.723 | 26 | none row 23 : 23 | imre toth | honda | 25 | +1:31.794 | 31 | none row 24 : 24 | leon camier | italjet | 24 | +1 lap | 33 | none row 25 : ret | chaz davies | aprilia | 18 | retirement | 21 | none row 26 : ret | michel fabrizio | gilera | 14 | accident | 19 | none row 27 : ret | youichi ui | derbi | 13 | accident | 6 | none row 28 : ret | alex de angelis | aprilia | 13 | accident | 12 | none row 29 : ret | angel rodriguez | aprilia | 4 | retirement | 25 | none row 30 : ret | gino borsoi | aprilia | 0 | accident | 9 | none row 31 : ret | andrea dovizioso | honda | 0 | accident | 14 | none row 32 : ret | alessandro brannetti | honda | 0 | accident | 30 | none row 33 : ret | alvaro bautista | aprilia | 0 | accident | 28 | none row 34 : dnq | javier machado | honda | none | none | none | none | col : count ( "pos" ) row 1 : 19 | select count ( pos ) where points = 'none' <table_name> : table \begin{tabular}{llllllll}
\toprule
& pos & rider & manufacturer & laps & time/retired & grid & points \\
\midrule
0 & 1 & manuel poggiali & gilera & 25 & 41:18.211 & 1 & 25 \\
1 & 2 & dani pedrosa & honda & 25 & 0.019 & 4 & 20 \\
2 & 3 & steve jenkner & aprilia & 25 & 9.888 & 3 & 16 \\
3 & 4 & lucio cecchinello & aprilia & 25 & 15.397 & 5 & 13 \\
4 & 5 & simone sanna & aprilia & 25 & 15.452 & 8 & 11 \\
5 & 6 & joan olive & honda & 25 & 15.486 & 20 & 10 \\
6 & 7 & stefano bianco & aprilia & 25 & 15.549 & 11 & 9 \\
7 & 8 & pablo nieto & aprilia & 25 & 16.218 & 2 & 8 \\
8 & 9 & mika kallio & honda & 25 & 22.762 & 10 & 7 \\
9 & 10 & mirko giansanti & honda & 25 & 22.839 & 16 & 6 \\
10 & 11 & arnaud vincent & aprilia & 25 & 23.067 & 23 & 5 \\
11 & 12 & andrea ballerini & honda & 25 & 23.134 & 18 & 4 \\
12 & 13 & stefano perugini & italjet & 25 & 43.345 & 17 & 3 \\
13 & 14 & jorge lorenzo & derbi & 25 & 43.973 & 7 & 2 \\
14 & 15 & masao azuma & honda & 25 & 47.189 & 13 & 1 \\
15 & 16 & jakub smrz & honda & 25 & 47.333 & 24 & none \\
16 & 17 & gianluigi scalvini & aprilia & 25 & 52 & 22 & none \\
17 & 18 & hector barbera & aprilia & 25 & +1:11.358 & 27 & none \\
18 & 19 & mattia angeloni & gilera & 25 & +1:11.488 & 29 & none \\
19 & 20 & alex baldolini & aprilia & 25 & +1:21.603 & 32 & none \\
20 & 21 & jaroslav hules & aprilia & 25 & +1:21.681 & 15 & none \\
21 & 22 & julian simon & honda & 25 & +1:31.723 & 26 & none \\
22 & 23 & imre toth & honda & 25 & +1:31.794 & 31 & none \\
23 & 24 & leon camier & italjet & 24 & +1 lap & 33 & none \\
24 & ret & chaz davies & aprilia & 18 & retirement & 21 & none \\
25 & ret & michel fabrizio & gilera & 14 & accident & 19 & none \\
26 & ret & youichi ui & derbi & 13 & accident & 6 & none \\
27 & ret & alex de angelis & aprilia & 13 & accident & 12 & none \\
28 & ret & angel rodriguez & aprilia & 4 & retirement & 25 & none \\
29 & ret & gino borsoi & aprilia & 0 & accident & 9 & none \\
30 & ret & andrea dovizioso & honda & 0 & accident & 14 & none \\
31 & ret & alessandro brannetti & honda & 0 & accident & 30 & none \\
32 & ret & alvaro bautista & aprilia & 0 & accident & 28 & none \\
33 & dnq & javier machado & honda & none & none & none & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "pos" ) \\
\midrule
0 & 19 \\
\bottomrule
\end{tabular}
| select count ( pos ) where points = 'none' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>rider</th>
<th>manufacturer</th>
<th>laps</th>
<th>time/retired</th>
<th>grid</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>manuel poggiali</td>
<td>gilera</td>
<td>25</td>
<td>41:18.211</td>
<td>1</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>dani pedrosa</td>
<td>honda</td>
<td>25</td>
<td>0.019</td>
<td>4</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>steve jenkner</td>
<td>aprilia</td>
<td>25</td>
<td>9.888</td>
<td>3</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>lucio cecchinello</td>
<td>aprilia</td>
<td>25</td>
<td>15.397</td>
<td>5</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>simone sanna</td>
<td>aprilia</td>
<td>25</td>
<td>15.452</td>
<td>8</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>joan olive</td>
<td>honda</td>
<td>25</td>
<td>15.486</td>
<td>20</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>stefano bianco</td>
<td>aprilia</td>
<td>25</td>
<td>15.549</td>
<td>11</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>pablo nieto</td>
<td>aprilia</td>
<td>25</td>
<td>16.218</td>
<td>2</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>mika kallio</td>
<td>honda</td>
<td>25</td>
<td>22.762</td>
<td>10</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>mirko giansanti</td>
<td>honda</td>
<td>25</td>
<td>22.839</td>
<td>16</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>arnaud vincent</td>
<td>aprilia</td>
<td>25</td>
<td>23.067</td>
<td>23</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>andrea ballerini</td>
<td>honda</td>
<td>25</td>
<td>23.134</td>
<td>18</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>stefano perugini</td>
<td>italjet</td>
<td>25</td>
<td>43.345</td>
<td>17</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>jorge lorenzo</td>
<td>derbi</td>
<td>25</td>
<td>43.973</td>
<td>7</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>masao azuma</td>
<td>honda</td>
<td>25</td>
<td>47.189</td>
<td>13</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>jakub smrz</td>
<td>honda</td>
<td>25</td>
<td>47.333</td>
<td>24</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>gianluigi scalvini</td>
<td>aprilia</td>
<td>25</td>
<td>52</td>
<td>22</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>hector barbera</td>
<td>aprilia</td>
<td>25</td>
<td>+1:11.358</td>
<td>27</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>mattia angeloni</td>
<td>gilera</td>
<td>25</td>
<td>+1:11.488</td>
<td>29</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>alex baldolini</td>
<td>aprilia</td>
<td>25</td>
<td>+1:21.603</td>
<td>32</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>jaroslav hules</td>
<td>aprilia</td>
<td>25</td>
<td>+1:21.681</td>
<td>15</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>julian simon</td>
<td>honda</td>
<td>25</td>
<td>+1:31.723</td>
<td>26</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>23</td>
<td>imre toth</td>
<td>honda</td>
<td>25</td>
<td>+1:31.794</td>
<td>31</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>24</td>
<td>leon camier</td>
<td>italjet</td>
<td>24</td>
<td>+1 lap</td>
<td>33</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>chaz davies</td>
<td>aprilia</td>
<td>18</td>
<td>retirement</td>
<td>21</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>michel fabrizio</td>
<td>gilera</td>
<td>14</td>
<td>accident</td>
<td>19</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>youichi ui</td>
<td>derbi</td>
<td>13</td>
<td>accident</td>
<td>6</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>alex de angelis</td>
<td>aprilia</td>
<td>13</td>
<td>accident</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>ret</td>
<td>angel rodriguez</td>
<td>aprilia</td>
<td>4</td>
<td>retirement</td>
<td>25</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>ret</td>
<td>gino borsoi</td>
<td>aprilia</td>
<td>0</td>
<td>accident</td>
<td>9</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>ret</td>
<td>andrea dovizioso</td>
<td>honda</td>
<td>0</td>
<td>accident</td>
<td>14</td>
<td>none</td>
</tr>
<tr>
<th>31</th>
<td>ret</td>
<td>alessandro brannetti</td>
<td>honda</td>
<td>0</td>
<td>accident</td>
<td>30</td>
<td>none</td>
</tr>
<tr>
<th>32</th>
<td>ret</td>
<td>alvaro bautista</td>
<td>aprilia</td>
<td>0</td>
<td>accident</td>
<td>28</td>
<td>none</td>
</tr>
<tr>
<th>33</th>
<td>dnq</td>
<td>javier machado</td>
<td>honda</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "pos" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>19</td>
</tr>
</tbody>
</table> | select count ( pos ) where points = 'none' <table_name> : table | | pos | rider | manufacturer | laps | time/retired | grid | points |
|---:|:------|:---------------------|:---------------|:-------|:---------------|:-------|:---------|
| 0 | 1 | manuel poggiali | gilera | 25 | 41:18.211 | 1 | 25 |
| 1 | 2 | dani pedrosa | honda | 25 | 0.019 | 4 | 20 |
| 2 | 3 | steve jenkner | aprilia | 25 | 9.888 | 3 | 16 |
| 3 | 4 | lucio cecchinello | aprilia | 25 | 15.397 | 5 | 13 |
| 4 | 5 | simone sanna | aprilia | 25 | 15.452 | 8 | 11 |
| 5 | 6 | joan olive | honda | 25 | 15.486 | 20 | 10 |
| 6 | 7 | stefano bianco | aprilia | 25 | 15.549 | 11 | 9 |
| 7 | 8 | pablo nieto | aprilia | 25 | 16.218 | 2 | 8 |
| 8 | 9 | mika kallio | honda | 25 | 22.762 | 10 | 7 |
| 9 | 10 | mirko giansanti | honda | 25 | 22.839 | 16 | 6 |
| 10 | 11 | arnaud vincent | aprilia | 25 | 23.067 | 23 | 5 |
| 11 | 12 | andrea ballerini | honda | 25 | 23.134 | 18 | 4 |
| 12 | 13 | stefano perugini | italjet | 25 | 43.345 | 17 | 3 |
| 13 | 14 | jorge lorenzo | derbi | 25 | 43.973 | 7 | 2 |
| 14 | 15 | masao azuma | honda | 25 | 47.189 | 13 | 1 |
| 15 | 16 | jakub smrz | honda | 25 | 47.333 | 24 | none |
| 16 | 17 | gianluigi scalvini | aprilia | 25 | 52 | 22 | none |
| 17 | 18 | hector barbera | aprilia | 25 | +1:11.358 | 27 | none |
| 18 | 19 | mattia angeloni | gilera | 25 | +1:11.488 | 29 | none |
| 19 | 20 | alex baldolini | aprilia | 25 | +1:21.603 | 32 | none |
| 20 | 21 | jaroslav hules | aprilia | 25 | +1:21.681 | 15 | none |
| 21 | 22 | julian simon | honda | 25 | +1:31.723 | 26 | none |
| 22 | 23 | imre toth | honda | 25 | +1:31.794 | 31 | none |
| 23 | 24 | leon camier | italjet | 24 | +1 lap | 33 | none |
| 24 | ret | chaz davies | aprilia | 18 | retirement | 21 | none |
| 25 | ret | michel fabrizio | gilera | 14 | accident | 19 | none |
| 26 | ret | youichi ui | derbi | 13 | accident | 6 | none |
| 27 | ret | alex de angelis | aprilia | 13 | accident | 12 | none |
| 28 | ret | angel rodriguez | aprilia | 4 | retirement | 25 | none |
| 29 | ret | gino borsoi | aprilia | 0 | accident | 9 | none |
| 30 | ret | andrea dovizioso | honda | 0 | accident | 14 | none |
| 31 | ret | alessandro brannetti | honda | 0 | accident | 30 | none |
| 32 | ret | alvaro bautista | aprilia | 0 | accident | 28 | none |
| 33 | dnq | javier machado | honda | none | none | none | none | | | | count ( "pos" ) |
|---:|------------------:|
| 0 | 19 | | [
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] |
select discipline where discipline = 'hurdles' order by michelle limit 119 col : discipline | amanda | bernie | javine h | julia | michelle row 1 : whitewater kayak | 0 | 2 | 4 | 3 | 6 row 2 : hurdles | 3 | 1 | 6 | 5 | 3 row 3 : cycling | 4 | 2 | 4 | 6 | 0 row 4 : gym floor | 0 | 3 | 6 | 5 | 2 row 5 : swimming | 4 | 3 | 6 | 5 | 0 row 6 : curling | 0 | 2 | 4 | 3 | 5 row 7 : archery | 4 | 0 | 5 | 2 | 3 row 8 : hammer | 2 | 3 | 5 | 4 | 2 row 9 : 100m sprint | 2 | 0 | 5 | 3 | 4 row 10 : total | 19 | 16 | 45 | 36 | 25 | col : discipline row 1 : hurdles | select discipline where discipline = 'hurdles' order by michelle limit 119 <table_name> : table \begin{tabular}{lllllll}
\toprule
& discipline & amanda & bernie & javine h & julia & michelle \\
\midrule
0 & whitewater kayak & 0 & 2 & 4 & 3 & 6 \\
1 & hurdles & 3 & 1 & 6 & 5 & 3 \\
2 & cycling & 4 & 2 & 4 & 6 & 0 \\
3 & gym floor & 0 & 3 & 6 & 5 & 2 \\
4 & swimming & 4 & 3 & 6 & 5 & 0 \\
5 & curling & 0 & 2 & 4 & 3 & 5 \\
6 & archery & 4 & 0 & 5 & 2 & 3 \\
7 & hammer & 2 & 3 & 5 & 4 & 2 \\
8 & 100m sprint & 2 & 0 & 5 & 3 & 4 \\
9 & total & 19 & 16 & 45 & 36 & 25 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& discipline \\
\midrule
0 & hurdles \\
\bottomrule
\end{tabular}
| select discipline where discipline = 'hurdles' order by michelle limit 119 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>discipline</th>
<th>amanda</th>
<th>bernie</th>
<th>javine h</th>
<th>julia</th>
<th>michelle</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>whitewater kayak</td>
<td>0</td>
<td>2</td>
<td>4</td>
<td>3</td>
<td>6</td>
</tr>
<tr>
<th>1</th>
<td>hurdles</td>
<td>3</td>
<td>1</td>
<td>6</td>
<td>5</td>
<td>3</td>
</tr>
<tr>
<th>2</th>
<td>cycling</td>
<td>4</td>
<td>2</td>
<td>4</td>
<td>6</td>
<td>0</td>
</tr>
<tr>
<th>3</th>
<td>gym floor</td>
<td>0</td>
<td>3</td>
<td>6</td>
<td>5</td>
<td>2</td>
</tr>
<tr>
<th>4</th>
<td>swimming</td>
<td>4</td>
<td>3</td>
<td>6</td>
<td>5</td>
<td>0</td>
</tr>
<tr>
<th>5</th>
<td>curling</td>
<td>0</td>
<td>2</td>
<td>4</td>
<td>3</td>
<td>5</td>
</tr>
<tr>
<th>6</th>
<td>archery</td>
<td>4</td>
<td>0</td>
<td>5</td>
<td>2</td>
<td>3</td>
</tr>
<tr>
<th>7</th>
<td>hammer</td>
<td>2</td>
<td>3</td>
<td>5</td>
<td>4</td>
<td>2</td>
</tr>
<tr>
<th>8</th>
<td>100m sprint</td>
<td>2</td>
<td>0</td>
<td>5</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<th>9</th>
<td>total</td>
<td>19</td>
<td>16</td>
<td>45</td>
<td>36</td>
<td>25</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>discipline</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>hurdles</td>
</tr>
</tbody>
</table> | select discipline where discipline = 'hurdles' order by michelle limit 119 <table_name> : table | | discipline | amanda | bernie | javine h | julia | michelle |
|---:|:-----------------|---------:|---------:|-----------:|--------:|-----------:|
| 0 | whitewater kayak | 0 | 2 | 4 | 3 | 6 |
| 1 | hurdles | 3 | 1 | 6 | 5 | 3 |
| 2 | cycling | 4 | 2 | 4 | 6 | 0 |
| 3 | gym floor | 0 | 3 | 6 | 5 | 2 |
| 4 | swimming | 4 | 3 | 6 | 5 | 0 |
| 5 | curling | 0 | 2 | 4 | 3 | 5 |
| 6 | archery | 4 | 0 | 5 | 2 | 3 |
| 7 | hammer | 2 | 3 | 5 | 4 | 2 |
| 8 | 100m sprint | 2 | 0 | 5 | 3 | 4 |
| 9 | total | 19 | 16 | 45 | 36 | 25 | | | | discipline |
|---:|:-------------|
| 0 | hurdles | | [
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select count ( section ) where section = 'uppland/gotland host' col : season | level | division | section | position | movements row 1 : 1999 | tier 5 | division 4 | gotland | 6th | varserier (spring series) row 2 : none | tier 5 | division 4 | gotland | 5th | hostserier (autumn series) row 3 : 2000 | tier 5 | division 4 | gotland | 2nd | varserier (spring series) row 4 : none | tier 5 | division 4 | uppland/gotland host | 10th | hostserier (autumn series) row 5 : 2001 | tier 5 | division 4 | gotland | 4th | varserier (spring series) row 6 : none | tier 5 | division 4 | gotland | 4th | slutspel a (playoff a) row 7 : 2002 | tier 5 | division 4 | gotland | 3rd | promotion playoffs row 8 : 2003 | tier 5 | division 4 | gotland | 6th | none row 9 : 2004 | tier 5 | division 4 | gotland | 4th | none row 10 : 2005 | tier 5 | division 4 | gotland | 1st | none row 11 : 2006 | tier 5 | division 3 | ostra svealand | 12th | relegated row 12 : 2007 | tier 6 | division 4 | gotland | 2nd | none row 13 : 2008 | tier 6 | division 4 | gotland | 3rd | none row 14 : 2009 | tier 6 | division 4 | gotland | 7th | none row 15 : 2010 | tier 6 | division 4 | gotland | 2nd | none row 16 : 2011 | tier 6 | division 4 | gotland | 4th | none | col : count ( "section" ) row 1 : 1 | select count ( section ) where section = 'uppland/gotland host' <table_name> : table \begin{tabular}{lllllll}
\toprule
& season & level & division & section & position & movements \\
\midrule
0 & 1999 & tier 5 & division 4 & gotland & 6th & varserier (spring series) \\
1 & none & tier 5 & division 4 & gotland & 5th & hostserier (autumn series) \\
2 & 2000 & tier 5 & division 4 & gotland & 2nd & varserier (spring series) \\
3 & none & tier 5 & division 4 & uppland/gotland host & 10th & hostserier (autumn series) \\
4 & 2001 & tier 5 & division 4 & gotland & 4th & varserier (spring series) \\
5 & none & tier 5 & division 4 & gotland & 4th & slutspel a (playoff a) \\
6 & 2002 & tier 5 & division 4 & gotland & 3rd & promotion playoffs \\
7 & 2003 & tier 5 & division 4 & gotland & 6th & none \\
8 & 2004 & tier 5 & division 4 & gotland & 4th & none \\
9 & 2005 & tier 5 & division 4 & gotland & 1st & none \\
10 & 2006 & tier 5 & division 3 & ostra svealand & 12th & relegated \\
11 & 2007 & tier 6 & division 4 & gotland & 2nd & none \\
12 & 2008 & tier 6 & division 4 & gotland & 3rd & none \\
13 & 2009 & tier 6 & division 4 & gotland & 7th & none \\
14 & 2010 & tier 6 & division 4 & gotland & 2nd & none \\
15 & 2011 & tier 6 & division 4 & gotland & 4th & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "section" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( section ) where section = 'uppland/gotland host' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>season</th>
<th>level</th>
<th>division</th>
<th>section</th>
<th>position</th>
<th>movements</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1999</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>6th</td>
<td>varserier (spring series)</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>5th</td>
<td>hostserier (autumn series)</td>
</tr>
<tr>
<th>2</th>
<td>2000</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>2nd</td>
<td>varserier (spring series)</td>
</tr>
<tr>
<th>3</th>
<td>none</td>
<td>tier 5</td>
<td>division 4</td>
<td>uppland/gotland host</td>
<td>10th</td>
<td>hostserier (autumn series)</td>
</tr>
<tr>
<th>4</th>
<td>2001</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>4th</td>
<td>varserier (spring series)</td>
</tr>
<tr>
<th>5</th>
<td>none</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>4th</td>
<td>slutspel a (playoff a)</td>
</tr>
<tr>
<th>6</th>
<td>2002</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>3rd</td>
<td>promotion playoffs</td>
</tr>
<tr>
<th>7</th>
<td>2003</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>6th</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>2004</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>4th</td>
<td>none</td>
</tr>
<tr>
<th>9</th>
<td>2005</td>
<td>tier 5</td>
<td>division 4</td>
<td>gotland</td>
<td>1st</td>
<td>none</td>
</tr>
<tr>
<th>10</th>
<td>2006</td>
<td>tier 5</td>
<td>division 3</td>
<td>ostra svealand</td>
<td>12th</td>
<td>relegated</td>
</tr>
<tr>
<th>11</th>
<td>2007</td>
<td>tier 6</td>
<td>division 4</td>
<td>gotland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>12</th>
<td>2008</td>
<td>tier 6</td>
<td>division 4</td>
<td>gotland</td>
<td>3rd</td>
<td>none</td>
</tr>
<tr>
<th>13</th>
<td>2009</td>
<td>tier 6</td>
<td>division 4</td>
<td>gotland</td>
<td>7th</td>
<td>none</td>
</tr>
<tr>
<th>14</th>
<td>2010</td>
<td>tier 6</td>
<td>division 4</td>
<td>gotland</td>
<td>2nd</td>
<td>none</td>
</tr>
<tr>
<th>15</th>
<td>2011</td>
<td>tier 6</td>
<td>division 4</td>
<td>gotland</td>
<td>4th</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "section" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( section ) where section = 'uppland/gotland host' <table_name> : table | | season | level | division | section | position | movements |
|---:|:---------|:--------|:-----------|:---------------------|:-----------|:---------------------------|
| 0 | 1999 | tier 5 | division 4 | gotland | 6th | varserier (spring series) |
| 1 | none | tier 5 | division 4 | gotland | 5th | hostserier (autumn series) |
| 2 | 2000 | tier 5 | division 4 | gotland | 2nd | varserier (spring series) |
| 3 | none | tier 5 | division 4 | uppland/gotland host | 10th | hostserier (autumn series) |
| 4 | 2001 | tier 5 | division 4 | gotland | 4th | varserier (spring series) |
| 5 | none | tier 5 | division 4 | gotland | 4th | slutspel a (playoff a) |
| 6 | 2002 | tier 5 | division 4 | gotland | 3rd | promotion playoffs |
| 7 | 2003 | tier 5 | division 4 | gotland | 6th | none |
| 8 | 2004 | tier 5 | division 4 | gotland | 4th | none |
| 9 | 2005 | tier 5 | division 4 | gotland | 1st | none |
| 10 | 2006 | tier 5 | division 3 | ostra svealand | 12th | relegated |
| 11 | 2007 | tier 6 | division 4 | gotland | 2nd | none |
| 12 | 2008 | tier 6 | division 4 | gotland | 3rd | none |
| 13 | 2009 | tier 6 | division 4 | gotland | 7th | none |
| 14 | 2010 | tier 6 | division 4 | gotland | 2nd | none |
| 15 | 2011 | tier 6 | division 4 | gotland | 4th | none | | | | count ( "section" ) |
|---:|----------------------:|
| 0 | 1 | | [
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[
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select count ( distinct position ) where years in nba > 0 col : date | team | name | position | years in nba | notes row 1 : 2009-04-23 00:00:00 | houston rockets | dikembe mutombo | c | 18 | suffered a season-ending injury row 2 : 2009-05-21 00:00:00 | free agent | sam cassell | g | 15 | became an assistant coach of the wizards row 3 : 2009-09-03 00:00:00 | free agent | bruce bowen | f | 12 | none row 4 : 2009-10-22 00:00:00 | free agent | mark madsen | f | 9 | became an assistant coach of the utah flash (d-league) row 5 : 2009-10-23 00:00:00 | free agent | bobby jackson | g | 12 | none row 6 : 2009-10-23 00:00:00 | free agent | tyronn lue | g | 11 | became the director of basketball development of the celtics row 7 : 2009-11-05 00:00:00 | free agent | darrick martin | g | 14 | named assistant director of player development of timberwolves | col : count ( "distinct position" ) row 1 : 7 | select count ( distinct position ) where years in nba > 0 <table_name> : table \begin{tabular}{lllllll}
\toprule
& date & team & name & position & years in nba & notes \\
\midrule
0 & 2009-04-23 00:00:00 & houston rockets & dikembe mutombo & c & 18 & suffered a season-ending injury \\
1 & 2009-05-21 00:00:00 & free agent & sam cassell & g & 15 & became an assistant coach of the wizards \\
2 & 2009-09-03 00:00:00 & free agent & bruce bowen & f & 12 & none \\
3 & 2009-10-22 00:00:00 & free agent & mark madsen & f & 9 & became an assistant coach of the utah flash (d-league) \\
4 & 2009-10-23 00:00:00 & free agent & bobby jackson & g & 12 & none \\
5 & 2009-10-23 00:00:00 & free agent & tyronn lue & g & 11 & became the director of basketball development of the celtics \\
6 & 2009-11-05 00:00:00 & free agent & darrick martin & g & 14 & named assistant director of player development of timberwolves \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "distinct position" ) \\
\midrule
0 & 7 \\
\bottomrule
\end{tabular}
| select count ( distinct position ) where years in nba > 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>team</th>
<th>name</th>
<th>position</th>
<th>years in nba</th>
<th>notes</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2009-04-23 00:00:00</td>
<td>houston rockets</td>
<td>dikembe mutombo</td>
<td>c</td>
<td>18</td>
<td>suffered a season-ending injury</td>
</tr>
<tr>
<th>1</th>
<td>2009-05-21 00:00:00</td>
<td>free agent</td>
<td>sam cassell</td>
<td>g</td>
<td>15</td>
<td>became an assistant coach of the wizards</td>
</tr>
<tr>
<th>2</th>
<td>2009-09-03 00:00:00</td>
<td>free agent</td>
<td>bruce bowen</td>
<td>f</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>3</th>
<td>2009-10-22 00:00:00</td>
<td>free agent</td>
<td>mark madsen</td>
<td>f</td>
<td>9</td>
<td>became an assistant coach of the utah flash (d-league)</td>
</tr>
<tr>
<th>4</th>
<td>2009-10-23 00:00:00</td>
<td>free agent</td>
<td>bobby jackson</td>
<td>g</td>
<td>12</td>
<td>none</td>
</tr>
<tr>
<th>5</th>
<td>2009-10-23 00:00:00</td>
<td>free agent</td>
<td>tyronn lue</td>
<td>g</td>
<td>11</td>
<td>became the director of basketball development of the celtics</td>
</tr>
<tr>
<th>6</th>
<td>2009-11-05 00:00:00</td>
<td>free agent</td>
<td>darrick martin</td>
<td>g</td>
<td>14</td>
<td>named assistant director of player development of timberwolves</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "distinct position" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>7</td>
</tr>
</tbody>
</table> | select count ( distinct position ) where years in nba > 0 <table_name> : table | | date | team | name | position | years in nba | notes |
|---:|:--------------------|:----------------|:----------------|:-----------|---------------:|:---------------------------------------------------------------|
| 0 | 2009-04-23 00:00:00 | houston rockets | dikembe mutombo | c | 18 | suffered a season-ending injury |
| 1 | 2009-05-21 00:00:00 | free agent | sam cassell | g | 15 | became an assistant coach of the wizards |
| 2 | 2009-09-03 00:00:00 | free agent | bruce bowen | f | 12 | none |
| 3 | 2009-10-22 00:00:00 | free agent | mark madsen | f | 9 | became an assistant coach of the utah flash (d-league) |
| 4 | 2009-10-23 00:00:00 | free agent | bobby jackson | g | 12 | none |
| 5 | 2009-10-23 00:00:00 | free agent | tyronn lue | g | 11 | became the director of basketball development of the celtics |
| 6 | 2009-11-05 00:00:00 | free agent | darrick martin | g | 14 | named assistant director of player development of timberwolves | | | | count ( "distinct position" ) |
|---:|--------------------------------:|
| 0 | 7 | | [
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select year - year where women's team = 'united states' col : year | location | men's individual | women's individual | men's team | women's team | mixed team | ref row 1 : 1996 | vaulx-en-velin | franck dauphin (fra) | anna campagnoli (ita) | none | none | none | row 2 : 1998 | taoyuan | john blaschke (usa) | shih ya-ping (tpe) | united states | chinese taipei | none | row 3 : 2000 | madrid | tsai sung-pin (tpe) | jamie van natta (usa) | united states | united states | none | row 4 : 2002 | chonburi | adam wheatcroft (usa) | mary zorn (usa) | united states | united states | none | row 5 : 2004 | madrid | choi yong-hee (kor) | mary zorn (usa) | south korea | united states | none | row 6 : 2006 | vinicne | braden gellenthien (usa) | amandine bouillot (fra) | united states | france | united states | row 7 : 2008 | tainan | jedd greschock (usa) | erika anschutz (usa) | mexico | south korea | united states | row 8 : 2010 | shenzhen | adam gallant (usa) | vida halimian (iri) | united states | united states | united states | row 9 : 2012 | cordoba | daniel suter (usa) | kristina berger (ger) | italy | united states | united states | row 10 : 2014 | legnica | none | none | none | none | none | | col : "year - year" row 1 : year - year row 2 : year - year row 3 : year - year row 4 : year - year row 5 : year - year | select year - year where women's team = 'united states' <table_name> : table \begin{tabular}{lllllllll}
\toprule
& year & location & men's individual & women's individual & men's team & women's team & mixed team & ref \\
\midrule
0 & 1996 & vaulx-en-velin & franck dauphin (fra) & anna campagnoli (ita) & none & none & none & \\
1 & 1998 & taoyuan & john blaschke (usa) & shih ya-ping (tpe) & united states & chinese taipei & none & \\
2 & 2000 & madrid & tsai sung-pin (tpe) & jamie van natta (usa) & united states & united states & none & \\
3 & 2002 & chonburi & adam wheatcroft (usa) & mary zorn (usa) & united states & united states & none & \\
4 & 2004 & madrid & choi yong-hee (kor) & mary zorn (usa) & south korea & united states & none & \\
5 & 2006 & vinicne & braden gellenthien (usa) & amandine bouillot (fra) & united states & france & united states & \\
6 & 2008 & tainan & jedd greschock (usa) & erika anschutz (usa) & mexico & south korea & united states & \\
7 & 2010 & shenzhen & adam gallant (usa) & vida halimian (iri) & united states & united states & united states & \\
8 & 2012 & cordoba & daniel suter (usa) & kristina berger (ger) & italy & united states & united states & \\
9 & 2014 & legnica & none & none & none & none & none | & NaN \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& "year - year" \\
\midrule
0 & year - year \\
1 & year - year \\
2 & year - year \\
3 & year - year \\
4 & year - year \\
\bottomrule
\end{tabular}
| select year - year where women's team = 'united states' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>location</th>
<th>men's individual</th>
<th>women's individual</th>
<th>men's team</th>
<th>women's team</th>
<th>mixed team</th>
<th>ref</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1996</td>
<td>vaulx-en-velin</td>
<td>franck dauphin (fra)</td>
<td>anna campagnoli (ita)</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>1</th>
<td>1998</td>
<td>taoyuan</td>
<td>john blaschke (usa)</td>
<td>shih ya-ping (tpe)</td>
<td>united states</td>
<td>chinese taipei</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>2</th>
<td>2000</td>
<td>madrid</td>
<td>tsai sung-pin (tpe)</td>
<td>jamie van natta (usa)</td>
<td>united states</td>
<td>united states</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>3</th>
<td>2002</td>
<td>chonburi</td>
<td>adam wheatcroft (usa)</td>
<td>mary zorn (usa)</td>
<td>united states</td>
<td>united states</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>2004</td>
<td>madrid</td>
<td>choi yong-hee (kor)</td>
<td>mary zorn (usa)</td>
<td>south korea</td>
<td>united states</td>
<td>none</td>
<td></td>
</tr>
<tr>
<th>5</th>
<td>2006</td>
<td>vinicne</td>
<td>braden gellenthien (usa)</td>
<td>amandine bouillot (fra)</td>
<td>united states</td>
<td>france</td>
<td>united states</td>
<td></td>
</tr>
<tr>
<th>6</th>
<td>2008</td>
<td>tainan</td>
<td>jedd greschock (usa)</td>
<td>erika anschutz (usa)</td>
<td>mexico</td>
<td>south korea</td>
<td>united states</td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>2010</td>
<td>shenzhen</td>
<td>adam gallant (usa)</td>
<td>vida halimian (iri)</td>
<td>united states</td>
<td>united states</td>
<td>united states</td>
<td></td>
</tr>
<tr>
<th>8</th>
<td>2012</td>
<td>cordoba</td>
<td>daniel suter (usa)</td>
<td>kristina berger (ger)</td>
<td>italy</td>
<td>united states</td>
<td>united states</td>
<td></td>
</tr>
<tr>
<th>9</th>
<td>2014</td>
<td>legnica</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none</td>
<td>none |</td>
<td>None</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>"year - year"</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>year - year</td>
</tr>
<tr>
<th>1</th>
<td>year - year</td>
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<tr>
<th>2</th>
<td>year - year</td>
</tr>
<tr>
<th>3</th>
<td>year - year</td>
</tr>
<tr>
<th>4</th>
<td>year - year</td>
</tr>
</tbody>
</table> | select year - year where women's team = 'united states' <table_name> : table | | year | location | men's individual | women's individual | men's team | women's team | mixed team | ref |
|---:|-------:|:---------------|:-------------------------|:------------------------|:--------------|:---------------|:--------------|:------|
| 0 | 1996 | vaulx-en-velin | franck dauphin (fra) | anna campagnoli (ita) | none | none | none | |
| 1 | 1998 | taoyuan | john blaschke (usa) | shih ya-ping (tpe) | united states | chinese taipei | none | |
| 2 | 2000 | madrid | tsai sung-pin (tpe) | jamie van natta (usa) | united states | united states | none | |
| 3 | 2002 | chonburi | adam wheatcroft (usa) | mary zorn (usa) | united states | united states | none | |
| 4 | 2004 | madrid | choi yong-hee (kor) | mary zorn (usa) | south korea | united states | none | |
| 5 | 2006 | vinicne | braden gellenthien (usa) | amandine bouillot (fra) | united states | france | united states | |
| 6 | 2008 | tainan | jedd greschock (usa) | erika anschutz (usa) | mexico | south korea | united states | |
| 7 | 2010 | shenzhen | adam gallant (usa) | vida halimian (iri) | united states | united states | united states | |
| 8 | 2012 | cordoba | daniel suter (usa) | kristina berger (ger) | italy | united states | united states | |
| 9 | 2014 | legnica | none | none | none | none | none | | | | | | "year - year" |
|---:|:----------------|
| 0 | year - year |
| 1 | year - year |
| 2 | year - year |
| 3 | year - year |
| 4 | year - year | | [
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select production code where # = 2 col : no | # | title | directed by | written by | original air date | production code row 1 : 1 | 1 | "class of beverly hills" | tim hunter | darren star | october 4, 1990 | none row 2 : 2 | 2 | "the green room" | michael uno | david stenn | october 11, 1990 | 2190001 row 3 : 3 | 3 | "every dream has its price (tag)" | catlin adams | amy spies | october 18, 1990 | 2190002 row 4 : 4 | 4 | "the first time" | bethany rooney | darren star | october 25, 1990 | 2190003 row 5 : 5 | 5 | "one on one" | artie mandelberg | charles rosin | november 1, 1990 | 2190004 row 6 : 6 | 6 | "higher education" | artie mandelberg | jordan budde | november 15, 1990 | 2190005 row 7 : 7 | 7 | "perfect mom" | bethany rooney | darren star | november 22, 1990 | 2190006 row 8 : 8 | 8 | "the 17-year itch" | jefferson kibbee | amy spies | november 29, 1990 | 2190007 row 9 : 9 | 9 | "the gentle art of listening" | dan attias | charles rosin | december 6, 1990 | 2190008 row 10 : 10 | 10 | "isn't it romantic?" | nancy malone | charles rosin | january 3, 1991 | 2190009 row 11 : 11 | 11 | "b.y.o.b." | miles watkins | jordan budde | january 10, 1991 | 2190010 row 12 : 12 | 12 | "one man and a baby" | burt brinckerhoff | amy spies | january 24, 1991 | 2190011 row 13 : 13 | 13 | "slumber party" | charles braverman | darren star | january 31, 1991 | 2190012 row 14 : 14 | 14 | "east side story" | dan attias | charles rosin | february 14, 1991 | 2190013 row 15 : 15 | 15 | "a fling in palm springs" | jefferson kibbee | jordan budde | february 21, 1991 | 2190014 row 16 : 16 | 16 | "fame is where you find it" | paul schneider | charles rosin & karen rosin | february 28, 1991 | 2190015 row 17 : 17 | 17 | "stand (up) and deliver" | burt brinckerhoff | amy spies | march 7, 1991 | 2190016 row 18 : 18 | 18 | "it's only a test" | charles braverman | darren star | march 28, 1991 | 2190017 row 19 : 19 | 19 | "april is the cruelest month" | dan attias | steve wasserman & jessica klein | april 11, 1991 | 2190018 row 20 : 20 | 20 | "spring training" | burt brinckerhoff | charles rosin | april 25, 1991 | 2190019 row 21 : 21 | 21 | "spring dance" | darren star | darren star | may 2, 1991 | 2190020 row 22 : 22 | 22 | "home again" | charles braverman | amy spies | may 9, 1991 | 2190021 | col : production code row 1 : 2190001 | select production code where # = 2 <table_name> : table \begin{tabular}{llllllll}
\toprule
& no & # & title & directed by & written by & original air date & production code \\
\midrule
0 & 1 & 1 & "class of beverly hills" & tim hunter & darren star & october 4, 1990 & none \\
1 & 2 & 2 & "the green room" & michael uno & david stenn & october 11, 1990 & 2190001 \\
2 & 3 & 3 & "every dream has its price (tag)" & catlin adams & amy spies & october 18, 1990 & 2190002 \\
3 & 4 & 4 & "the first time" & bethany rooney & darren star & october 25, 1990 & 2190003 \\
4 & 5 & 5 & "one on one" & artie mandelberg & charles rosin & november 1, 1990 & 2190004 \\
5 & 6 & 6 & "higher education" & artie mandelberg & jordan budde & november 15, 1990 & 2190005 \\
6 & 7 & 7 & "perfect mom" & bethany rooney & darren star & november 22, 1990 & 2190006 \\
7 & 8 & 8 & "the 17-year itch" & jefferson kibbee & amy spies & november 29, 1990 & 2190007 \\
8 & 9 & 9 & "the gentle art of listening" & dan attias & charles rosin & december 6, 1990 & 2190008 \\
9 & 10 & 10 & "isn't it romantic?" & nancy malone & charles rosin & january 3, 1991 & 2190009 \\
10 & 11 & 11 & "b.y.o.b." & miles watkins & jordan budde & january 10, 1991 & 2190010 \\
11 & 12 & 12 & "one man and a baby" & burt brinckerhoff & amy spies & january 24, 1991 & 2190011 \\
12 & 13 & 13 & "slumber party" & charles braverman & darren star & january 31, 1991 & 2190012 \\
13 & 14 & 14 & "east side story" & dan attias & charles rosin & february 14, 1991 & 2190013 \\
14 & 15 & 15 & "a fling in palm springs" & jefferson kibbee & jordan budde & february 21, 1991 & 2190014 \\
15 & 16 & 16 & "fame is where you find it" & paul schneider & charles rosin & karen rosin & february 28, 1991 & 2190015 \\
16 & 17 & 17 & "stand (up) and deliver" & burt brinckerhoff & amy spies & march 7, 1991 & 2190016 \\
17 & 18 & 18 & "it's only a test" & charles braverman & darren star & march 28, 1991 & 2190017 \\
18 & 19 & 19 & "april is the cruelest month" & dan attias & steve wasserman & jessica klein & april 11, 1991 & 2190018 \\
19 & 20 & 20 & "spring training" & burt brinckerhoff & charles rosin & april 25, 1991 & 2190019 \\
20 & 21 & 21 & "spring dance" & darren star & darren star & may 2, 1991 & 2190020 \\
21 & 22 & 22 & "home again" & charles braverman & amy spies & may 9, 1991 & 2190021 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& production code \\
\midrule
0 & 2190001 \\
\bottomrule
\end{tabular}
| select production code where # = 2 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>no</th>
<th>#</th>
<th>title</th>
<th>directed by</th>
<th>written by</th>
<th>original air date</th>
<th>production code</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>1</td>
<td>"class of beverly hills"</td>
<td>tim hunter</td>
<td>darren star</td>
<td>october 4, 1990</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>2</td>
<td>"the green room"</td>
<td>michael uno</td>
<td>david stenn</td>
<td>october 11, 1990</td>
<td>2190001</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>3</td>
<td>"every dream has its price (tag)"</td>
<td>catlin adams</td>
<td>amy spies</td>
<td>october 18, 1990</td>
<td>2190002</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>4</td>
<td>"the first time"</td>
<td>bethany rooney</td>
<td>darren star</td>
<td>october 25, 1990</td>
<td>2190003</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>5</td>
<td>"one on one"</td>
<td>artie mandelberg</td>
<td>charles rosin</td>
<td>november 1, 1990</td>
<td>2190004</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>6</td>
<td>"higher education"</td>
<td>artie mandelberg</td>
<td>jordan budde</td>
<td>november 15, 1990</td>
<td>2190005</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>7</td>
<td>"perfect mom"</td>
<td>bethany rooney</td>
<td>darren star</td>
<td>november 22, 1990</td>
<td>2190006</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>8</td>
<td>"the 17-year itch"</td>
<td>jefferson kibbee</td>
<td>amy spies</td>
<td>november 29, 1990</td>
<td>2190007</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>9</td>
<td>"the gentle art of listening"</td>
<td>dan attias</td>
<td>charles rosin</td>
<td>december 6, 1990</td>
<td>2190008</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>10</td>
<td>"isn't it romantic?"</td>
<td>nancy malone</td>
<td>charles rosin</td>
<td>january 3, 1991</td>
<td>2190009</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>11</td>
<td>"b.y.o.b."</td>
<td>miles watkins</td>
<td>jordan budde</td>
<td>january 10, 1991</td>
<td>2190010</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>12</td>
<td>"one man and a baby"</td>
<td>burt brinckerhoff</td>
<td>amy spies</td>
<td>january 24, 1991</td>
<td>2190011</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>13</td>
<td>"slumber party"</td>
<td>charles braverman</td>
<td>darren star</td>
<td>january 31, 1991</td>
<td>2190012</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>14</td>
<td>"east side story"</td>
<td>dan attias</td>
<td>charles rosin</td>
<td>february 14, 1991</td>
<td>2190013</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>15</td>
<td>"a fling in palm springs"</td>
<td>jefferson kibbee</td>
<td>jordan budde</td>
<td>february 21, 1991</td>
<td>2190014</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>16</td>
<td>"fame is where you find it"</td>
<td>paul schneider</td>
<td>charles rosin & karen rosin</td>
<td>february 28, 1991</td>
<td>2190015</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>17</td>
<td>"stand (up) and deliver"</td>
<td>burt brinckerhoff</td>
<td>amy spies</td>
<td>march 7, 1991</td>
<td>2190016</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>18</td>
<td>"it's only a test"</td>
<td>charles braverman</td>
<td>darren star</td>
<td>march 28, 1991</td>
<td>2190017</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>19</td>
<td>"april is the cruelest month"</td>
<td>dan attias</td>
<td>steve wasserman & jessica klein</td>
<td>april 11, 1991</td>
<td>2190018</td>
</tr>
<tr>
<th>19</th>
<td>20</td>
<td>20</td>
<td>"spring training"</td>
<td>burt brinckerhoff</td>
<td>charles rosin</td>
<td>april 25, 1991</td>
<td>2190019</td>
</tr>
<tr>
<th>20</th>
<td>21</td>
<td>21</td>
<td>"spring dance"</td>
<td>darren star</td>
<td>darren star</td>
<td>may 2, 1991</td>
<td>2190020</td>
</tr>
<tr>
<th>21</th>
<td>22</td>
<td>22</td>
<td>"home again"</td>
<td>charles braverman</td>
<td>amy spies</td>
<td>may 9, 1991</td>
<td>2190021</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>production code</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>2190001</td>
</tr>
</tbody>
</table> | select production code where # = 2 <table_name> : table | | no | # | title | directed by | written by | original air date | production code |
|---:|-----:|----:|:----------------------------------|:------------------|:--------------------------------|:--------------------|:------------------|
| 0 | 1 | 1 | "class of beverly hills" | tim hunter | darren star | october 4, 1990 | none |
| 1 | 2 | 2 | "the green room" | michael uno | david stenn | october 11, 1990 | 2190001 |
| 2 | 3 | 3 | "every dream has its price (tag)" | catlin adams | amy spies | october 18, 1990 | 2190002 |
| 3 | 4 | 4 | "the first time" | bethany rooney | darren star | october 25, 1990 | 2190003 |
| 4 | 5 | 5 | "one on one" | artie mandelberg | charles rosin | november 1, 1990 | 2190004 |
| 5 | 6 | 6 | "higher education" | artie mandelberg | jordan budde | november 15, 1990 | 2190005 |
| 6 | 7 | 7 | "perfect mom" | bethany rooney | darren star | november 22, 1990 | 2190006 |
| 7 | 8 | 8 | "the 17-year itch" | jefferson kibbee | amy spies | november 29, 1990 | 2190007 |
| 8 | 9 | 9 | "the gentle art of listening" | dan attias | charles rosin | december 6, 1990 | 2190008 |
| 9 | 10 | 10 | "isn't it romantic?" | nancy malone | charles rosin | january 3, 1991 | 2190009 |
| 10 | 11 | 11 | "b.y.o.b." | miles watkins | jordan budde | january 10, 1991 | 2190010 |
| 11 | 12 | 12 | "one man and a baby" | burt brinckerhoff | amy spies | january 24, 1991 | 2190011 |
| 12 | 13 | 13 | "slumber party" | charles braverman | darren star | january 31, 1991 | 2190012 |
| 13 | 14 | 14 | "east side story" | dan attias | charles rosin | february 14, 1991 | 2190013 |
| 14 | 15 | 15 | "a fling in palm springs" | jefferson kibbee | jordan budde | february 21, 1991 | 2190014 |
| 15 | 16 | 16 | "fame is where you find it" | paul schneider | charles rosin & karen rosin | february 28, 1991 | 2190015 |
| 16 | 17 | 17 | "stand (up) and deliver" | burt brinckerhoff | amy spies | march 7, 1991 | 2190016 |
| 17 | 18 | 18 | "it's only a test" | charles braverman | darren star | march 28, 1991 | 2190017 |
| 18 | 19 | 19 | "april is the cruelest month" | dan attias | steve wasserman & jessica klein | april 11, 1991 | 2190018 |
| 19 | 20 | 20 | "spring training" | burt brinckerhoff | charles rosin | april 25, 1991 | 2190019 |
| 20 | 21 | 21 | "spring dance" | darren star | darren star | may 2, 1991 | 2190020 |
| 21 | 22 | 22 | "home again" | charles braverman | amy spies | may 9, 1991 | 2190021 | | | | production code |
|---:|------------------:|
| 0 | 2190001 | | [
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select name where name = 'knut nordahl' col : name | pos. | caps | goals | club row 1 : olle ahlund | mf | 1 | 0 | degerfors if row 2 : sune "mona-lisa" andersson | mf | 5 | 0 | aik solna row 3 : henry "garvis" carlsson | fw | 2 | 0 | aik solna row 4 : rune "killing" emanuelsson | mf | 2 | 0 | ifk goteborg row 5 : thure grahn | df | 1 | 0 | is halmia halmstad row 6 : gunnar "il professore" gren | fw | 5 | 5 | ifk goteborg row 7 : sven "jack" jacobsson | mf | 1 | 0 | gais goteborg row 8 : egon "hemliga" jonsson | fw | 1 | 0 | malmo ff row 9 : borje leander | mf | 1 | 0 | aik solna row 10 : nils "lidas"/"greven" liedholm | fw | 6 | 5 | ifk norrkoping row 11 : torsten "lindy" lindberg | gk | 5 | 0 | ifk norrkoping row 12 : lennart lindskog | fw | 1 | 0 | degerfors if row 13 : malte "svarta blixten" martensson | fw | 2 | 0 | halsingborgs if row 14 : erik nilsson | df | 4 | 0 | malmo ff row 15 : harry nilsson | df | 2 | 0 | aik solna row 16 : ove nilsson | gk | 1 | 0 | djurgardens if stockholm row 17 : stellan nilsson | fw | 4 | 0 | malmo ff row 18 : bertil nordahl | mf | 4 | 0 | degerfors if row 19 : gunnar nordahl | fw | 6 | 8 | ifk norrkoping row 20 : knut nordahl | df | 5 | 0 | ifk norrkoping row 21 : stig nystrom | fw | 1 | 1 | djurgardens if stockholm row 22 : kjell rosen | mf/fw | 4 | 0 | malmo ff row 23 : birger "bian" rosengren | mf | 1 | 0 | ifk norrkoping row 24 : rolf svensson | fw | 1 | 0 | halsingborgs if row 25 : borje tapper | fw | 1 | 1 | malmo ff | col : name row 1 : knut nordahl | select name where name = 'knut nordahl' <table_name> : table \begin{tabular}{llllll}
\toprule
& name & pos. & caps & goals & club \\
\midrule
0 & olle ahlund & mf & 1 & 0 & degerfors if \\
1 & sune "mona-lisa" andersson & mf & 5 & 0 & aik solna \\
2 & henry "garvis" carlsson & fw & 2 & 0 & aik solna \\
3 & rune "killing" emanuelsson & mf & 2 & 0 & ifk goteborg \\
4 & thure grahn & df & 1 & 0 & is halmia halmstad \\
5 & gunnar "il professore" gren & fw & 5 & 5 & ifk goteborg \\
6 & sven "jack" jacobsson & mf & 1 & 0 & gais goteborg \\
7 & egon "hemliga" jonsson & fw & 1 & 0 & malmo ff \\
8 & borje leander & mf & 1 & 0 & aik solna \\
9 & nils "lidas"/"greven" liedholm & fw & 6 & 5 & ifk norrkoping \\
10 & torsten "lindy" lindberg & gk & 5 & 0 & ifk norrkoping \\
11 & lennart lindskog & fw & 1 & 0 & degerfors if \\
12 & malte "svarta blixten" martensson & fw & 2 & 0 & halsingborgs if \\
13 & erik nilsson & df & 4 & 0 & malmo ff \\
14 & harry nilsson & df & 2 & 0 & aik solna \\
15 & ove nilsson & gk & 1 & 0 & djurgardens if stockholm \\
16 & stellan nilsson & fw & 4 & 0 & malmo ff \\
17 & bertil nordahl & mf & 4 & 0 & degerfors if \\
18 & gunnar nordahl & fw & 6 & 8 & ifk norrkoping \\
19 & knut nordahl & df & 5 & 0 & ifk norrkoping \\
20 & stig nystrom & fw & 1 & 1 & djurgardens if stockholm \\
21 & kjell rosen & mf/fw & 4 & 0 & malmo ff \\
22 & birger "bian" rosengren & mf & 1 & 0 & ifk norrkoping \\
23 & rolf svensson & fw & 1 & 0 & halsingborgs if \\
24 & borje tapper & fw & 1 & 1 & malmo ff \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& name \\
\midrule
0 & knut nordahl \\
\bottomrule
\end{tabular}
| select name where name = 'knut nordahl' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
<th>pos.</th>
<th>caps</th>
<th>goals</th>
<th>club</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>olle ahlund</td>
<td>mf</td>
<td>1</td>
<td>0</td>
<td>degerfors if</td>
</tr>
<tr>
<th>1</th>
<td>sune "mona-lisa" andersson</td>
<td>mf</td>
<td>5</td>
<td>0</td>
<td>aik solna</td>
</tr>
<tr>
<th>2</th>
<td>henry "garvis" carlsson</td>
<td>fw</td>
<td>2</td>
<td>0</td>
<td>aik solna</td>
</tr>
<tr>
<th>3</th>
<td>rune "killing" emanuelsson</td>
<td>mf</td>
<td>2</td>
<td>0</td>
<td>ifk goteborg</td>
</tr>
<tr>
<th>4</th>
<td>thure grahn</td>
<td>df</td>
<td>1</td>
<td>0</td>
<td>is halmia halmstad</td>
</tr>
<tr>
<th>5</th>
<td>gunnar "il professore" gren</td>
<td>fw</td>
<td>5</td>
<td>5</td>
<td>ifk goteborg</td>
</tr>
<tr>
<th>6</th>
<td>sven "jack" jacobsson</td>
<td>mf</td>
<td>1</td>
<td>0</td>
<td>gais goteborg</td>
</tr>
<tr>
<th>7</th>
<td>egon "hemliga" jonsson</td>
<td>fw</td>
<td>1</td>
<td>0</td>
<td>malmo ff</td>
</tr>
<tr>
<th>8</th>
<td>borje leander</td>
<td>mf</td>
<td>1</td>
<td>0</td>
<td>aik solna</td>
</tr>
<tr>
<th>9</th>
<td>nils "lidas"/"greven" liedholm</td>
<td>fw</td>
<td>6</td>
<td>5</td>
<td>ifk norrkoping</td>
</tr>
<tr>
<th>10</th>
<td>torsten "lindy" lindberg</td>
<td>gk</td>
<td>5</td>
<td>0</td>
<td>ifk norrkoping</td>
</tr>
<tr>
<th>11</th>
<td>lennart lindskog</td>
<td>fw</td>
<td>1</td>
<td>0</td>
<td>degerfors if</td>
</tr>
<tr>
<th>12</th>
<td>malte "svarta blixten" martensson</td>
<td>fw</td>
<td>2</td>
<td>0</td>
<td>halsingborgs if</td>
</tr>
<tr>
<th>13</th>
<td>erik nilsson</td>
<td>df</td>
<td>4</td>
<td>0</td>
<td>malmo ff</td>
</tr>
<tr>
<th>14</th>
<td>harry nilsson</td>
<td>df</td>
<td>2</td>
<td>0</td>
<td>aik solna</td>
</tr>
<tr>
<th>15</th>
<td>ove nilsson</td>
<td>gk</td>
<td>1</td>
<td>0</td>
<td>djurgardens if stockholm</td>
</tr>
<tr>
<th>16</th>
<td>stellan nilsson</td>
<td>fw</td>
<td>4</td>
<td>0</td>
<td>malmo ff</td>
</tr>
<tr>
<th>17</th>
<td>bertil nordahl</td>
<td>mf</td>
<td>4</td>
<td>0</td>
<td>degerfors if</td>
</tr>
<tr>
<th>18</th>
<td>gunnar nordahl</td>
<td>fw</td>
<td>6</td>
<td>8</td>
<td>ifk norrkoping</td>
</tr>
<tr>
<th>19</th>
<td>knut nordahl</td>
<td>df</td>
<td>5</td>
<td>0</td>
<td>ifk norrkoping</td>
</tr>
<tr>
<th>20</th>
<td>stig nystrom</td>
<td>fw</td>
<td>1</td>
<td>1</td>
<td>djurgardens if stockholm</td>
</tr>
<tr>
<th>21</th>
<td>kjell rosen</td>
<td>mf/fw</td>
<td>4</td>
<td>0</td>
<td>malmo ff</td>
</tr>
<tr>
<th>22</th>
<td>birger "bian" rosengren</td>
<td>mf</td>
<td>1</td>
<td>0</td>
<td>ifk norrkoping</td>
</tr>
<tr>
<th>23</th>
<td>rolf svensson</td>
<td>fw</td>
<td>1</td>
<td>0</td>
<td>halsingborgs if</td>
</tr>
<tr>
<th>24</th>
<td>borje tapper</td>
<td>fw</td>
<td>1</td>
<td>1</td>
<td>malmo ff</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>name</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>knut nordahl</td>
</tr>
</tbody>
</table> | select name where name = 'knut nordahl' <table_name> : table | | name | pos. | caps | goals | club |
|---:|:----------------------------------|:-------|-------:|--------:|:-------------------------|
| 0 | olle ahlund | mf | 1 | 0 | degerfors if |
| 1 | sune "mona-lisa" andersson | mf | 5 | 0 | aik solna |
| 2 | henry "garvis" carlsson | fw | 2 | 0 | aik solna |
| 3 | rune "killing" emanuelsson | mf | 2 | 0 | ifk goteborg |
| 4 | thure grahn | df | 1 | 0 | is halmia halmstad |
| 5 | gunnar "il professore" gren | fw | 5 | 5 | ifk goteborg |
| 6 | sven "jack" jacobsson | mf | 1 | 0 | gais goteborg |
| 7 | egon "hemliga" jonsson | fw | 1 | 0 | malmo ff |
| 8 | borje leander | mf | 1 | 0 | aik solna |
| 9 | nils "lidas"/"greven" liedholm | fw | 6 | 5 | ifk norrkoping |
| 10 | torsten "lindy" lindberg | gk | 5 | 0 | ifk norrkoping |
| 11 | lennart lindskog | fw | 1 | 0 | degerfors if |
| 12 | malte "svarta blixten" martensson | fw | 2 | 0 | halsingborgs if |
| 13 | erik nilsson | df | 4 | 0 | malmo ff |
| 14 | harry nilsson | df | 2 | 0 | aik solna |
| 15 | ove nilsson | gk | 1 | 0 | djurgardens if stockholm |
| 16 | stellan nilsson | fw | 4 | 0 | malmo ff |
| 17 | bertil nordahl | mf | 4 | 0 | degerfors if |
| 18 | gunnar nordahl | fw | 6 | 8 | ifk norrkoping |
| 19 | knut nordahl | df | 5 | 0 | ifk norrkoping |
| 20 | stig nystrom | fw | 1 | 1 | djurgardens if stockholm |
| 21 | kjell rosen | mf/fw | 4 | 0 | malmo ff |
| 22 | birger "bian" rosengren | mf | 1 | 0 | ifk norrkoping |
| 23 | rolf svensson | fw | 1 | 0 | halsingborgs if |
| 24 | borje tapper | fw | 1 | 1 | malmo ff | | | | name |
|---:|:-------------|
| 0 | knut nordahl | | [
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select driver where driver = 'jason leffler' col : pos. | car # | driver | make | team row 1 : 1 | 38 | jason leffler | toyota | braun racing row 2 : 2 | 16 | greg biffle | ford | roush fenway racing row 3 : 3 | 99 | david reutimann | toyota | michael waltrip racing row 4 : 4 | 60 | carl edwards | ford | roush fenway racing row 5 : 5 | 77 | ron hornaday | chevrolet | kevin harvick incorporated row 6 : 6 | 20 | aric almirola | chevrolet | joe gibbs racing row 7 : 7 | 29 | scott wimmer | chevrolet | richard childress racing row 8 : 8 | 42 | kevin hamlin | dodge | chip ganassi racing row 9 : 9 | 10 | mike bliss | toyota | braun racing row 10 : 10 | 88 | brad keselowski | chevrolet | jr motorsports | col : driver row 1 : jason leffler | select driver where driver = 'jason leffler' <table_name> : table \begin{tabular}{llllll}
\toprule
& pos. & car # & driver & make & team \\
\midrule
0 & 1 & 38 & jason leffler & toyota & braun racing \\
1 & 2 & 16 & greg biffle & ford & roush fenway racing \\
2 & 3 & 99 & david reutimann & toyota & michael waltrip racing \\
3 & 4 & 60 & carl edwards & ford & roush fenway racing \\
4 & 5 & 77 & ron hornaday & chevrolet & kevin harvick incorporated \\
5 & 6 & 20 & aric almirola & chevrolet & joe gibbs racing \\
6 & 7 & 29 & scott wimmer & chevrolet & richard childress racing \\
7 & 8 & 42 & kevin hamlin & dodge & chip ganassi racing \\
8 & 9 & 10 & mike bliss & toyota & braun racing \\
9 & 10 & 88 & brad keselowski & chevrolet & jr motorsports \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& driver \\
\midrule
0 & jason leffler \\
\bottomrule
\end{tabular}
| select driver where driver = 'jason leffler' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos.</th>
<th>car #</th>
<th>driver</th>
<th>make</th>
<th>team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>38</td>
<td>jason leffler</td>
<td>toyota</td>
<td>braun racing</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>16</td>
<td>greg biffle</td>
<td>ford</td>
<td>roush fenway racing</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>99</td>
<td>david reutimann</td>
<td>toyota</td>
<td>michael waltrip racing</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>60</td>
<td>carl edwards</td>
<td>ford</td>
<td>roush fenway racing</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>77</td>
<td>ron hornaday</td>
<td>chevrolet</td>
<td>kevin harvick incorporated</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>20</td>
<td>aric almirola</td>
<td>chevrolet</td>
<td>joe gibbs racing</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>29</td>
<td>scott wimmer</td>
<td>chevrolet</td>
<td>richard childress racing</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>42</td>
<td>kevin hamlin</td>
<td>dodge</td>
<td>chip ganassi racing</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>10</td>
<td>mike bliss</td>
<td>toyota</td>
<td>braun racing</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>88</td>
<td>brad keselowski</td>
<td>chevrolet</td>
<td>jr motorsports</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>driver</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>jason leffler</td>
</tr>
</tbody>
</table> | select driver where driver = 'jason leffler' <table_name> : table | | pos. | car # | driver | make | team |
|---:|-------:|--------:|:----------------|:----------|:---------------------------|
| 0 | 1 | 38 | jason leffler | toyota | braun racing |
| 1 | 2 | 16 | greg biffle | ford | roush fenway racing |
| 2 | 3 | 99 | david reutimann | toyota | michael waltrip racing |
| 3 | 4 | 60 | carl edwards | ford | roush fenway racing |
| 4 | 5 | 77 | ron hornaday | chevrolet | kevin harvick incorporated |
| 5 | 6 | 20 | aric almirola | chevrolet | joe gibbs racing |
| 6 | 7 | 29 | scott wimmer | chevrolet | richard childress racing |
| 7 | 8 | 42 | kevin hamlin | dodge | chip ganassi racing |
| 8 | 9 | 10 | mike bliss | toyota | braun racing |
| 9 | 10 | 88 | brad keselowski | chevrolet | jr motorsports | | | | driver |
|---:|:--------------|
| 0 | jason leffler | | [
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select venue where result = '1-2' col : date | opponent | venue | result | scorers row 1 : 1979-03-31 00:00:00 | portland timbers | h | 3-4 | gersdorff, child, cohen row 2 : 1979-04-14 00:00:00 | edmonton drillers | h | 0-1 | none row 3 : 1979-04-21 00:00:00 | san diego sockers | a | 3-3 | child (2), ryan row 4 : 1979-04-28 00:00:00 | los angeles aztecs | h | 1-2 | child row 5 : 1979-05-05 00:00:00 | vancouver whitecaps | h | 1-2 | gersdorff row 6 : 1979-05-09 00:00:00 | detroit express | a | 0-3 | none row 7 : 1979-05-12 00:00:00 | seattle sounders | a | 1-2 | gersdorff row 8 : 1979-05-19 00:00:00 | seattle sounders | h | 0-1 | none row 9 : 1979-05-26 00:00:00 | edmonton drillers | a | 2-1 | child, lawson row 10 : 1979-06-02 00:00:00 | memphis rogues | h | 2-1 | etterich, flindt row 11 : 1979-06-06 00:00:00 | minnesota kicks | a | 1-4 | gersdorff row 12 : 1979-06-09 00:00:00 | toronto blizzard | h | 2-3 | child, gersdorff row 13 : 1979-06-13 00:00:00 | tampa bay rowdies | a | 2-2 | child, versen row 14 : 1979-06-16 00:00:00 | fort lauderdale strikers | a | 1-3 | armstrong row 15 : 1979-06-20 00:00:00 | portland timbers | a | 2-1 | etterich, ryan row 16 : 1979-06-23 00:00:00 | chicago sting | h | 4-2 | etterich, bick, webers, gersdorff row 17 : 1979-06-27 00:00:00 | new england tea men | h | 0-1 | none row 18 : 1979-06-30 00:00:00 | philadelphia fury | a | 1-2 | wood row 19 : 1979-07-04 00:00:00 | houston hurricane | a | 0-4 | none row 20 : 1979-07-07 00:00:00 | fort lauderdale strikers | h | 1-2 | flindt row 21 : 1979-07-11 00:00:00 | philadelphia fury | h | 4-4 | armstrong, etterich, gersdorff, wood row 22 : 1979-07-14 00:00:00 | los angeles aztecs | a | 0-0 | none row 23 : 1979-07-18 00:00:00 | houston hurricane | h | 1-2 | gersdorff row 24 : 1979-07-21 00:00:00 | tulsa roughnecks | h | 3-2 | armstrong (2), wood row 25 : 1979-07-25 00:00:00 | chicago sting | a | 3-2 | gersdorff (2), child row 26 : 1979-07-29 00:00:00 | new york cosmos | a | 0-5 | none row 27 : 1979-08-01 00:00:00 | california surf | h | 0-2 | none row 28 : 1979-08-04 00:00:00 | california surf | a | 1-4 | wood row 29 : 1979-08-08 00:00:00 | vancouver whitecaps | a | 0-1 | none row 30 : 1979-08-11 00:00:00 | san diego sockers | h | 0-6 | none | col : venue row 1 : h row 2 : h row 3 : a row 4 : a row 5 : h row 6 : h | select venue where result = '1-2' <table_name> : table \begin{tabular}{llllll}
\toprule
& date & opponent & venue & result & scorers \\
\midrule
0 & 1979-03-31 00:00:00 & portland timbers & h & 3-4 & gersdorff, child, cohen \\
1 & 1979-04-14 00:00:00 & edmonton drillers & h & 0-1 & none \\
2 & 1979-04-21 00:00:00 & san diego sockers & a & 3-3 & child (2), ryan \\
3 & 1979-04-28 00:00:00 & los angeles aztecs & h & 1-2 & child \\
4 & 1979-05-05 00:00:00 & vancouver whitecaps & h & 1-2 & gersdorff \\
5 & 1979-05-09 00:00:00 & detroit express & a & 0-3 & none \\
6 & 1979-05-12 00:00:00 & seattle sounders & a & 1-2 & gersdorff \\
7 & 1979-05-19 00:00:00 & seattle sounders & h & 0-1 & none \\
8 & 1979-05-26 00:00:00 & edmonton drillers & a & 2-1 & child, lawson \\
9 & 1979-06-02 00:00:00 & memphis rogues & h & 2-1 & etterich, flindt \\
10 & 1979-06-06 00:00:00 & minnesota kicks & a & 1-4 & gersdorff \\
11 & 1979-06-09 00:00:00 & toronto blizzard & h & 2-3 & child, gersdorff \\
12 & 1979-06-13 00:00:00 & tampa bay rowdies & a & 2-2 & child, versen \\
13 & 1979-06-16 00:00:00 & fort lauderdale strikers & a & 1-3 & armstrong \\
14 & 1979-06-20 00:00:00 & portland timbers & a & 2-1 & etterich, ryan \\
15 & 1979-06-23 00:00:00 & chicago sting & h & 4-2 & etterich, bick, webers, gersdorff \\
16 & 1979-06-27 00:00:00 & new england tea men & h & 0-1 & none \\
17 & 1979-06-30 00:00:00 & philadelphia fury & a & 1-2 & wood \\
18 & 1979-07-04 00:00:00 & houston hurricane & a & 0-4 & none \\
19 & 1979-07-07 00:00:00 & fort lauderdale strikers & h & 1-2 & flindt \\
20 & 1979-07-11 00:00:00 & philadelphia fury & h & 4-4 & armstrong, etterich, gersdorff, wood \\
21 & 1979-07-14 00:00:00 & los angeles aztecs & a & 0-0 & none \\
22 & 1979-07-18 00:00:00 & houston hurricane & h & 1-2 & gersdorff \\
23 & 1979-07-21 00:00:00 & tulsa roughnecks & h & 3-2 & armstrong (2), wood \\
24 & 1979-07-25 00:00:00 & chicago sting & a & 3-2 & gersdorff (2), child \\
25 & 1979-07-29 00:00:00 & new york cosmos & a & 0-5 & none \\
26 & 1979-08-01 00:00:00 & california surf & h & 0-2 & none \\
27 & 1979-08-04 00:00:00 & california surf & a & 1-4 & wood \\
28 & 1979-08-08 00:00:00 & vancouver whitecaps & a & 0-1 & none \\
29 & 1979-08-11 00:00:00 & san diego sockers & h & 0-6 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& venue \\
\midrule
0 & h \\
1 & h \\
2 & a \\
3 & a \\
4 & h \\
5 & h \\
\bottomrule
\end{tabular}
| select venue where result = '1-2' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>date</th>
<th>opponent</th>
<th>venue</th>
<th>result</th>
<th>scorers</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1979-03-31 00:00:00</td>
<td>portland timbers</td>
<td>h</td>
<td>3-4</td>
<td>gersdorff, child, cohen</td>
</tr>
<tr>
<th>1</th>
<td>1979-04-14 00:00:00</td>
<td>edmonton drillers</td>
<td>h</td>
<td>0-1</td>
<td>none</td>
</tr>
<tr>
<th>2</th>
<td>1979-04-21 00:00:00</td>
<td>san diego sockers</td>
<td>a</td>
<td>3-3</td>
<td>child (2), ryan</td>
</tr>
<tr>
<th>3</th>
<td>1979-04-28 00:00:00</td>
<td>los angeles aztecs</td>
<td>h</td>
<td>1-2</td>
<td>child</td>
</tr>
<tr>
<th>4</th>
<td>1979-05-05 00:00:00</td>
<td>vancouver whitecaps</td>
<td>h</td>
<td>1-2</td>
<td>gersdorff</td>
</tr>
<tr>
<th>5</th>
<td>1979-05-09 00:00:00</td>
<td>detroit express</td>
<td>a</td>
<td>0-3</td>
<td>none</td>
</tr>
<tr>
<th>6</th>
<td>1979-05-12 00:00:00</td>
<td>seattle sounders</td>
<td>a</td>
<td>1-2</td>
<td>gersdorff</td>
</tr>
<tr>
<th>7</th>
<td>1979-05-19 00:00:00</td>
<td>seattle sounders</td>
<td>h</td>
<td>0-1</td>
<td>none</td>
</tr>
<tr>
<th>8</th>
<td>1979-05-26 00:00:00</td>
<td>edmonton drillers</td>
<td>a</td>
<td>2-1</td>
<td>child, lawson</td>
</tr>
<tr>
<th>9</th>
<td>1979-06-02 00:00:00</td>
<td>memphis rogues</td>
<td>h</td>
<td>2-1</td>
<td>etterich, flindt</td>
</tr>
<tr>
<th>10</th>
<td>1979-06-06 00:00:00</td>
<td>minnesota kicks</td>
<td>a</td>
<td>1-4</td>
<td>gersdorff</td>
</tr>
<tr>
<th>11</th>
<td>1979-06-09 00:00:00</td>
<td>toronto blizzard</td>
<td>h</td>
<td>2-3</td>
<td>child, gersdorff</td>
</tr>
<tr>
<th>12</th>
<td>1979-06-13 00:00:00</td>
<td>tampa bay rowdies</td>
<td>a</td>
<td>2-2</td>
<td>child, versen</td>
</tr>
<tr>
<th>13</th>
<td>1979-06-16 00:00:00</td>
<td>fort lauderdale strikers</td>
<td>a</td>
<td>1-3</td>
<td>armstrong</td>
</tr>
<tr>
<th>14</th>
<td>1979-06-20 00:00:00</td>
<td>portland timbers</td>
<td>a</td>
<td>2-1</td>
<td>etterich, ryan</td>
</tr>
<tr>
<th>15</th>
<td>1979-06-23 00:00:00</td>
<td>chicago sting</td>
<td>h</td>
<td>4-2</td>
<td>etterich, bick, webers, gersdorff</td>
</tr>
<tr>
<th>16</th>
<td>1979-06-27 00:00:00</td>
<td>new england tea men</td>
<td>h</td>
<td>0-1</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>1979-06-30 00:00:00</td>
<td>philadelphia fury</td>
<td>a</td>
<td>1-2</td>
<td>wood</td>
</tr>
<tr>
<th>18</th>
<td>1979-07-04 00:00:00</td>
<td>houston hurricane</td>
<td>a</td>
<td>0-4</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>1979-07-07 00:00:00</td>
<td>fort lauderdale strikers</td>
<td>h</td>
<td>1-2</td>
<td>flindt</td>
</tr>
<tr>
<th>20</th>
<td>1979-07-11 00:00:00</td>
<td>philadelphia fury</td>
<td>h</td>
<td>4-4</td>
<td>armstrong, etterich, gersdorff, wood</td>
</tr>
<tr>
<th>21</th>
<td>1979-07-14 00:00:00</td>
<td>los angeles aztecs</td>
<td>a</td>
<td>0-0</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>1979-07-18 00:00:00</td>
<td>houston hurricane</td>
<td>h</td>
<td>1-2</td>
<td>gersdorff</td>
</tr>
<tr>
<th>23</th>
<td>1979-07-21 00:00:00</td>
<td>tulsa roughnecks</td>
<td>h</td>
<td>3-2</td>
<td>armstrong (2), wood</td>
</tr>
<tr>
<th>24</th>
<td>1979-07-25 00:00:00</td>
<td>chicago sting</td>
<td>a</td>
<td>3-2</td>
<td>gersdorff (2), child</td>
</tr>
<tr>
<th>25</th>
<td>1979-07-29 00:00:00</td>
<td>new york cosmos</td>
<td>a</td>
<td>0-5</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>1979-08-01 00:00:00</td>
<td>california surf</td>
<td>h</td>
<td>0-2</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>1979-08-04 00:00:00</td>
<td>california surf</td>
<td>a</td>
<td>1-4</td>
<td>wood</td>
</tr>
<tr>
<th>28</th>
<td>1979-08-08 00:00:00</td>
<td>vancouver whitecaps</td>
<td>a</td>
<td>0-1</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>1979-08-11 00:00:00</td>
<td>san diego sockers</td>
<td>h</td>
<td>0-6</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>venue</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>h</td>
</tr>
<tr>
<th>1</th>
<td>h</td>
</tr>
<tr>
<th>2</th>
<td>a</td>
</tr>
<tr>
<th>3</th>
<td>a</td>
</tr>
<tr>
<th>4</th>
<td>h</td>
</tr>
<tr>
<th>5</th>
<td>h</td>
</tr>
</tbody>
</table> | select venue where result = '1-2' <table_name> : table | | date | opponent | venue | result | scorers |
|---:|:--------------------|:-------------------------|:--------|:---------|:-------------------------------------|
| 0 | 1979-03-31 00:00:00 | portland timbers | h | 3-4 | gersdorff, child, cohen |
| 1 | 1979-04-14 00:00:00 | edmonton drillers | h | 0-1 | none |
| 2 | 1979-04-21 00:00:00 | san diego sockers | a | 3-3 | child (2), ryan |
| 3 | 1979-04-28 00:00:00 | los angeles aztecs | h | 1-2 | child |
| 4 | 1979-05-05 00:00:00 | vancouver whitecaps | h | 1-2 | gersdorff |
| 5 | 1979-05-09 00:00:00 | detroit express | a | 0-3 | none |
| 6 | 1979-05-12 00:00:00 | seattle sounders | a | 1-2 | gersdorff |
| 7 | 1979-05-19 00:00:00 | seattle sounders | h | 0-1 | none |
| 8 | 1979-05-26 00:00:00 | edmonton drillers | a | 2-1 | child, lawson |
| 9 | 1979-06-02 00:00:00 | memphis rogues | h | 2-1 | etterich, flindt |
| 10 | 1979-06-06 00:00:00 | minnesota kicks | a | 1-4 | gersdorff |
| 11 | 1979-06-09 00:00:00 | toronto blizzard | h | 2-3 | child, gersdorff |
| 12 | 1979-06-13 00:00:00 | tampa bay rowdies | a | 2-2 | child, versen |
| 13 | 1979-06-16 00:00:00 | fort lauderdale strikers | a | 1-3 | armstrong |
| 14 | 1979-06-20 00:00:00 | portland timbers | a | 2-1 | etterich, ryan |
| 15 | 1979-06-23 00:00:00 | chicago sting | h | 4-2 | etterich, bick, webers, gersdorff |
| 16 | 1979-06-27 00:00:00 | new england tea men | h | 0-1 | none |
| 17 | 1979-06-30 00:00:00 | philadelphia fury | a | 1-2 | wood |
| 18 | 1979-07-04 00:00:00 | houston hurricane | a | 0-4 | none |
| 19 | 1979-07-07 00:00:00 | fort lauderdale strikers | h | 1-2 | flindt |
| 20 | 1979-07-11 00:00:00 | philadelphia fury | h | 4-4 | armstrong, etterich, gersdorff, wood |
| 21 | 1979-07-14 00:00:00 | los angeles aztecs | a | 0-0 | none |
| 22 | 1979-07-18 00:00:00 | houston hurricane | h | 1-2 | gersdorff |
| 23 | 1979-07-21 00:00:00 | tulsa roughnecks | h | 3-2 | armstrong (2), wood |
| 24 | 1979-07-25 00:00:00 | chicago sting | a | 3-2 | gersdorff (2), child |
| 25 | 1979-07-29 00:00:00 | new york cosmos | a | 0-5 | none |
| 26 | 1979-08-01 00:00:00 | california surf | h | 0-2 | none |
| 27 | 1979-08-04 00:00:00 | california surf | a | 1-4 | wood |
| 28 | 1979-08-08 00:00:00 | vancouver whitecaps | a | 0-1 | none |
| 29 | 1979-08-11 00:00:00 | san diego sockers | h | 0-6 | none | | | | venue |
|---:|:--------|
| 0 | h |
| 1 | h |
| 2 | a |
| 3 | a |
| 4 | h |
| 5 | h | | [
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select count ( party leader(s) ) where party = 'japanese communist party (jcp) nihon kyosan-to 日本共産党' col : party | diet representation representatives | diet representation councillors | party leader(s) | comments row 1 : your party (yp) minna no to みんなの党 ("everybody's party") | 18.0 | 18.0 | yoshimi watanabe reps | conservative liberalism, neoliberalism, economic liberalism, libertarianism, anti-nuclear row 2 : japanese communist party (jcp) nihon kyosan-to 日本共産党 | 8.0 | 11.0 | kazuo shii reps | the japanese communist party is japan's oldest party. it was formed in 1922 as an underground organization in the empire of japan, but was legalized after world war ii during the occupation. it used to be a communist party, but the party has recently shifted to a socialist party row 3 : people's life party (plp) seikatsu no to 生活の党 | 7.0 | 2.0 | ichiro ozawa reps | life party was founded by ichiro ozawa and 14 other diet members who were in the tomor row 4 : party of japan after a leadership dispute between ozawa and yukiko kada | | | | row 5 : social democratic party (sdp) shakai minshu-to 社会民主党 | 2.0 | 3.0 | mizuho fukushima coun | sdp is a social democratic party. it is a successor of japan socialist party, which had been japan's largest opposition party in the 1955 system row 6 : green wind midori no kaze みとりの風 | 2.0 | 0.0 | kuniko tanioka coun | a house of councillors parliamentary group founded in july 2012, temporarily registered as a party from november to december 2012, opposed to joining tpp, vat increase, nuclear power. may merge with tomor row 7 : party of japan in the near future | | | | row 8 : new party daichi - true democrats shinto daichi - shinminshu 新党大地・真民主 | 1.0 | 0.0 | muneo suzuki | founded in december 2011 by new party daichi and ex-democrats, hokkaido regionalism, opposed to joining tpp row 9 : new renaissance party (nrp) shinto kaikaku 新党改革 ("new reform party") | 0.0 | 1.0 | yoichi masuzoe coun | conservatism, neoliberalism row 10 : okinawa socialist masses party (osmp) okinawa shakai taishuto 沖縄社会大衆党 | 0.0 | 1.0 | keiko itokazu coun | social democracy, okinawa regionalism | col : count ( "party leader(s" ) row 1 : 1 | select count ( party leader(s) ) where party = 'japanese communist party (jcp) nihon kyosan-to 日本共産党' <table_name> : table \begin{tabular}{llllll}
\toprule
& party & diet representation representatives & diet representation councillors & party leader(s) & comments \\
\midrule
0 & your party (yp) minna no to みんなの党 ("everybody's party") & 18.0 & 18.0 & yoshimi watanabe reps & conservative liberalism, neoliberalism, economic liberalism, libertarianism, anti-nuclear \\
1 & japanese communist party (jcp) nihon kyosan-to 日本共産党 & 8.0 & 11.0 & kazuo shii reps & the japanese communist party is japan's oldest party. it was formed in 1922 as an underground organization in the empire of japan, but was legalized after world war ii during the occupation. it used to be a communist party, but the party has recently shifted to a socialist party \\
2 & people's life party (plp) seikatsu no to 生活の党 & 7.0 & 2.0 & ichiro ozawa reps & life party was founded by ichiro ozawa and 14 other diet members who were in the tomor \\
3 & party of japan after a leadership dispute between ozawa and yukiko kada & & & & \\
4 & social democratic party (sdp) shakai minshu-to 社会民主党 & 2.0 & 3.0 & mizuho fukushima coun & sdp is a social democratic party. it is a successor of japan socialist party, which had been japan's largest opposition party in the 1955 system \\
5 & green wind midori no kaze みとりの風 & 2.0 & 0.0 & kuniko tanioka coun & a house of councillors parliamentary group founded in july 2012, temporarily registered as a party from november to december 2012, opposed to joining tpp, vat increase, nuclear power. may merge with tomor \\
6 & party of japan in the near future & & & & \\
7 & new party daichi - true democrats shinto daichi - shinminshu 新党大地・真民主 & 1.0 & 0.0 & muneo suzuki & founded in december 2011 by new party daichi and ex-democrats, hokkaido regionalism, opposed to joining tpp \\
8 & new renaissance party (nrp) shinto kaikaku 新党改革 ("new reform party") & 0.0 & 1.0 & yoichi masuzoe coun & conservatism, neoliberalism \\
9 & okinawa socialist masses party (osmp) okinawa shakai taishuto 沖縄社会大衆党 & 0.0 & 1.0 & keiko itokazu coun & social democracy, okinawa regionalism \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "party leader(s" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( party leader(s) ) where party = 'japanese communist party (jcp) nihon kyosan-to 日本共産党' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>party</th>
<th>diet representation representatives</th>
<th>diet representation councillors</th>
<th>party leader(s)</th>
<th>comments</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>your party (yp) minna no to みんなの党 ("everybody's party")</td>
<td>18.0</td>
<td>18.0</td>
<td>yoshimi watanabe reps</td>
<td>conservative liberalism, neoliberalism, economic liberalism, libertarianism, anti-nuclear</td>
</tr>
<tr>
<th>1</th>
<td>japanese communist party (jcp) nihon kyosan-to 日本共産党</td>
<td>8.0</td>
<td>11.0</td>
<td>kazuo shii reps</td>
<td>the japanese communist party is japan's oldest party. it was formed in 1922 as an underground organization in the empire of japan, but was legalized after world war ii during the occupation. it used to be a communist party, but the party has recently shifted to a socialist party</td>
</tr>
<tr>
<th>2</th>
<td>people's life party (plp) seikatsu no to 生活の党</td>
<td>7.0</td>
<td>2.0</td>
<td>ichiro ozawa reps</td>
<td>life party was founded by ichiro ozawa and 14 other diet members who were in the tomor</td>
</tr>
<tr>
<th>3</th>
<td>party of japan after a leadership dispute between ozawa and yukiko kada</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>4</th>
<td>social democratic party (sdp) shakai minshu-to 社会民主党</td>
<td>2.0</td>
<td>3.0</td>
<td>mizuho fukushima coun</td>
<td>sdp is a social democratic party. it is a successor of japan socialist party, which had been japan's largest opposition party in the 1955 system</td>
</tr>
<tr>
<th>5</th>
<td>green wind midori no kaze みとりの風</td>
<td>2.0</td>
<td>0.0</td>
<td>kuniko tanioka coun</td>
<td>a house of councillors parliamentary group founded in july 2012, temporarily registered as a party from november to december 2012, opposed to joining tpp, vat increase, nuclear power. may merge with tomor</td>
</tr>
<tr>
<th>6</th>
<td>party of japan in the near future</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr>
<th>7</th>
<td>new party daichi - true democrats shinto daichi - shinminshu 新党大地・真民主</td>
<td>1.0</td>
<td>0.0</td>
<td>muneo suzuki</td>
<td>founded in december 2011 by new party daichi and ex-democrats, hokkaido regionalism, opposed to joining tpp</td>
</tr>
<tr>
<th>8</th>
<td>new renaissance party (nrp) shinto kaikaku 新党改革 ("new reform party")</td>
<td>0.0</td>
<td>1.0</td>
<td>yoichi masuzoe coun</td>
<td>conservatism, neoliberalism</td>
</tr>
<tr>
<th>9</th>
<td>okinawa socialist masses party (osmp) okinawa shakai taishuto 沖縄社会大衆党</td>
<td>0.0</td>
<td>1.0</td>
<td>keiko itokazu coun</td>
<td>social democracy, okinawa regionalism</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "party leader(s" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( party leader(s) ) where party = 'japanese communist party (jcp) nihon kyosan-to 日本共産党' <table_name> : table | | party | diet representation representatives | diet representation councillors | party leader(s) | comments |
|---:|:------------------------------------------------------------------------------|:--------------------------------------|:----------------------------------|:----------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| 0 | your party (yp) minna no to みんなの党 ("everybody's party") | 18.0 | 18.0 | yoshimi watanabe reps | conservative liberalism, neoliberalism, economic liberalism, libertarianism, anti-nuclear |
| 1 | japanese communist party (jcp) nihon kyosan-to 日本共産党 | 8.0 | 11.0 | kazuo shii reps | the japanese communist party is japan's oldest party. it was formed in 1922 as an underground organization in the empire of japan, but was legalized after world war ii during the occupation. it used to be a communist party, but the party has recently shifted to a socialist party |
| 2 | people's life party (plp) seikatsu no to 生活の党 | 7.0 | 2.0 | ichiro ozawa reps | life party was founded by ichiro ozawa and 14 other diet members who were in the tomor |
| 3 | party of japan after a leadership dispute between ozawa and yukiko kada | | | | |
| 4 | social democratic party (sdp) shakai minshu-to 社会民主党 | 2.0 | 3.0 | mizuho fukushima coun | sdp is a social democratic party. it is a successor of japan socialist party, which had been japan's largest opposition party in the 1955 system |
| 5 | green wind midori no kaze みとりの風 | 2.0 | 0.0 | kuniko tanioka coun | a house of councillors parliamentary group founded in july 2012, temporarily registered as a party from november to december 2012, opposed to joining tpp, vat increase, nuclear power. may merge with tomor |
| 6 | party of japan in the near future | | | | |
| 7 | new party daichi - true democrats shinto daichi - shinminshu 新党大地・真民主 | 1.0 | 0.0 | muneo suzuki | founded in december 2011 by new party daichi and ex-democrats, hokkaido regionalism, opposed to joining tpp |
| 8 | new renaissance party (nrp) shinto kaikaku 新党改革 ("new reform party") | 0.0 | 1.0 | yoichi masuzoe coun | conservatism, neoliberalism |
| 9 | okinawa socialist masses party (osmp) okinawa shakai taishuto 沖縄社会大衆党 | 0.0 | 1.0 | keiko itokazu coun | social democracy, okinawa regionalism | | | | count ( "party leader(s" ) |
|---:|-----------------------------:|
| 0 | 1 | | [
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select count ( office ) where # < 1703 col : # | office | current officer row 1 : none | may succeed to governorship | none row 2 : none | governor of new mexico | susana martinez row 3 : 1 | lieutenant governor of new mexico | john sanchez row 4 : 2 | secretary of state of new mexico | dianna duran row 5 : 3 | president pro tempore of the senate | mary kay papen row 6 : 4 | speaker of the house of representatives | w. ken martinez row 7 : none | may serve as emergency interim successor | none row 8 : 4 | attorney general of new mexico | gary king row 9 : 5 | state auditor | hector balderas row 10 : 6 | state treasurer | james b. lewis row 11 : 7 | commissioner of public lands | ray powell row 12 : 8 | ,public regulation commission,, chair, | patrick lyons row 13 : 9 | public regulation commissioner | karen montoya row 14 : 10 | public regulation commissioner | valerie espinoza row 15 : 11 | public regulation commissioner | theresa becenti-aguilar row 16 : 12 | public regulation commissioner | ben hall | col : count ( "office" ) row 1 : 4 | select count ( office ) where # < 1703 <table_name> : table \begin{tabular}{llll}
\toprule
& # & office & current officer \\
\midrule
0 & none & may succeed to governorship & none \\
1 & none & governor of new mexico & susana martinez \\
2 & 1 & lieutenant governor of new mexico & john sanchez \\
3 & 2 & secretary of state of new mexico & dianna duran \\
4 & 3 & president pro tempore of the senate & mary kay papen \\
5 & 4 & speaker of the house of representatives & w. ken martinez \\
6 & none & may serve as emergency interim successor & none \\
7 & 4 & attorney general of new mexico & gary king \\
8 & 5 & state auditor & hector balderas \\
9 & 6 & state treasurer & james b. lewis \\
10 & 7 & commissioner of public lands & ray powell \\
11 & 8 & ,public regulation commission,, chair, & patrick lyons \\
12 & 9 & public regulation commissioner & karen montoya \\
13 & 10 & public regulation commissioner & valerie espinoza \\
14 & 11 & public regulation commissioner & theresa becenti-aguilar \\
15 & 12 & public regulation commissioner & ben hall \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "office" ) \\
\midrule
0 & 4 \\
\bottomrule
\end{tabular}
| select count ( office ) where # < 1703 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>#</th>
<th>office</th>
<th>current officer</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>none</td>
<td>may succeed to governorship</td>
<td>none</td>
</tr>
<tr>
<th>1</th>
<td>none</td>
<td>governor of new mexico</td>
<td>susana martinez</td>
</tr>
<tr>
<th>2</th>
<td>1</td>
<td>lieutenant governor of new mexico</td>
<td>john sanchez</td>
</tr>
<tr>
<th>3</th>
<td>2</td>
<td>secretary of state of new mexico</td>
<td>dianna duran</td>
</tr>
<tr>
<th>4</th>
<td>3</td>
<td>president pro tempore of the senate</td>
<td>mary kay papen</td>
</tr>
<tr>
<th>5</th>
<td>4</td>
<td>speaker of the house of representatives</td>
<td>w. ken martinez</td>
</tr>
<tr>
<th>6</th>
<td>none</td>
<td>may serve as emergency interim successor</td>
<td>none</td>
</tr>
<tr>
<th>7</th>
<td>4</td>
<td>attorney general of new mexico</td>
<td>gary king</td>
</tr>
<tr>
<th>8</th>
<td>5</td>
<td>state auditor</td>
<td>hector balderas</td>
</tr>
<tr>
<th>9</th>
<td>6</td>
<td>state treasurer</td>
<td>james b. lewis</td>
</tr>
<tr>
<th>10</th>
<td>7</td>
<td>commissioner of public lands</td>
<td>ray powell</td>
</tr>
<tr>
<th>11</th>
<td>8</td>
<td>,public regulation commission,, chair,</td>
<td>patrick lyons</td>
</tr>
<tr>
<th>12</th>
<td>9</td>
<td>public regulation commissioner</td>
<td>karen montoya</td>
</tr>
<tr>
<th>13</th>
<td>10</td>
<td>public regulation commissioner</td>
<td>valerie espinoza</td>
</tr>
<tr>
<th>14</th>
<td>11</td>
<td>public regulation commissioner</td>
<td>theresa becenti-aguilar</td>
</tr>
<tr>
<th>15</th>
<td>12</td>
<td>public regulation commissioner</td>
<td>ben hall</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "office" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>4</td>
</tr>
</tbody>
</table> | select count ( office ) where # < 1703 <table_name> : table | | # | office | current officer |
|---:|:-----|:-----------------------------------------|:------------------------|
| 0 | none | may succeed to governorship | none |
| 1 | none | governor of new mexico | susana martinez |
| 2 | 1 | lieutenant governor of new mexico | john sanchez |
| 3 | 2 | secretary of state of new mexico | dianna duran |
| 4 | 3 | president pro tempore of the senate | mary kay papen |
| 5 | 4 | speaker of the house of representatives | w. ken martinez |
| 6 | none | may serve as emergency interim successor | none |
| 7 | 4 | attorney general of new mexico | gary king |
| 8 | 5 | state auditor | hector balderas |
| 9 | 6 | state treasurer | james b. lewis |
| 10 | 7 | commissioner of public lands | ray powell |
| 11 | 8 | ,public regulation commission,, chair, | patrick lyons |
| 12 | 9 | public regulation commissioner | karen montoya |
| 13 | 10 | public regulation commissioner | valerie espinoza |
| 14 | 11 | public regulation commissioner | theresa becenti-aguilar |
| 15 | 12 | public regulation commissioner | ben hall | | | | count ( "office" ) |
|---:|---------------------:|
| 0 | 4 | | [
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select min ( total ) where total > 1 col : rank | nation | gold | silver | bronze | total row 1 : 1 | china (chn) | 14 | 10 | 12 | 36 row 2 : 2 | thailand (tha) | 13 | 9 | 6 | 28 row 3 : 3 | south korea (kor) | 6 | 7 | 10 | 23 row 4 : 4 | indonesia (ina) | 6 | 6 | 4 | 16 row 5 : 5 | chinese taipei (tpe) | 3 | 6 | 6 | 15 row 6 : 6 | india (ind) | 2 | 0 | 1 | 3 row 7 : 7 | iran (iri) | 2 | 0 | 0 | 2 row 8 : 8 | japan (jpn) | 1 | 3 | 2 | 6 row 9 : 9 | afghanistan (afg) | 1 | 0 | 0 | 1 row 10 : 9 | qatar (qat) | 1 | 0 | 0 | 1 row 11 : 11 | philippines (phi) | 0 | 2 | 2 | 4 row 12 : 12 | vietnam (vie) | 0 | 2 | 1 | 3 row 13 : 13 | kazakhstan (kaz) | 0 | 1 | 1 | 2 row 14 : 13 | pakistan (pak) | 0 | 1 | 1 | 2 row 15 : 15 | bahrain (brn) | 0 | 1 | 0 | 1 row 16 : 15 | turkmenistan (tkm) | 0 | 1 | 0 | 1 row 17 : 17 | sri lanka (sri) | 0 | 0 | 2 | 2 row 18 : 18 | bangladesh (ban) | 0 | 0 | 1 | 1 row 19 : 18 | brunei (bru) | 0 | 0 | 1 | 1 row 20 : 18 | laos (lao) | 0 | 0 | 1 | 1 row 21 : 18 | mongolia (mgl) | 0 | 0 | 1 | 1 row 22 : 18 | palestine (ple) | 0 | 0 | 1 | 1 row 23 : 18 | singapore (sin) | 0 | 0 | 1 | 1 row 24 : total | total | 49 | 49 | 54 | 152 | col : min ( "total" ) row 1 : 15 | select min ( total ) where total > 1 <table_name> : table \begin{tabular}{lllllll}
\toprule
& rank & nation & gold & silver & bronze & total \\
\midrule
0 & 1 & china (chn) & 14 & 10 & 12 & 36 \\
1 & 2 & thailand (tha) & 13 & 9 & 6 & 28 \\
2 & 3 & south korea (kor) & 6 & 7 & 10 & 23 \\
3 & 4 & indonesia (ina) & 6 & 6 & 4 & 16 \\
4 & 5 & chinese taipei (tpe) & 3 & 6 & 6 & 15 \\
5 & 6 & india (ind) & 2 & 0 & 1 & 3 \\
6 & 7 & iran (iri) & 2 & 0 & 0 & 2 \\
7 & 8 & japan (jpn) & 1 & 3 & 2 & 6 \\
8 & 9 & afghanistan (afg) & 1 & 0 & 0 & 1 \\
9 & 9 & qatar (qat) & 1 & 0 & 0 & 1 \\
10 & 11 & philippines (phi) & 0 & 2 & 2 & 4 \\
11 & 12 & vietnam (vie) & 0 & 2 & 1 & 3 \\
12 & 13 & kazakhstan (kaz) & 0 & 1 & 1 & 2 \\
13 & 13 & pakistan (pak) & 0 & 1 & 1 & 2 \\
14 & 15 & bahrain (brn) & 0 & 1 & 0 & 1 \\
15 & 15 & turkmenistan (tkm) & 0 & 1 & 0 & 1 \\
16 & 17 & sri lanka (sri) & 0 & 0 & 2 & 2 \\
17 & 18 & bangladesh (ban) & 0 & 0 & 1 & 1 \\
18 & 18 & brunei (bru) & 0 & 0 & 1 & 1 \\
19 & 18 & laos (lao) & 0 & 0 & 1 & 1 \\
20 & 18 & mongolia (mgl) & 0 & 0 & 1 & 1 \\
21 & 18 & palestine (ple) & 0 & 0 & 1 & 1 \\
22 & 18 & singapore (sin) & 0 & 0 & 1 & 1 \\
23 & total & total & 49 & 49 & 54 & 152 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& min ( "total" ) \\
\midrule
0 & 15 \\
\bottomrule
\end{tabular}
| select min ( total ) where total > 1 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>rank</th>
<th>nation</th>
<th>gold</th>
<th>silver</th>
<th>bronze</th>
<th>total</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>china (chn)</td>
<td>14</td>
<td>10</td>
<td>12</td>
<td>36</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>thailand (tha)</td>
<td>13</td>
<td>9</td>
<td>6</td>
<td>28</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>south korea (kor)</td>
<td>6</td>
<td>7</td>
<td>10</td>
<td>23</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>indonesia (ina)</td>
<td>6</td>
<td>6</td>
<td>4</td>
<td>16</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>chinese taipei (tpe)</td>
<td>3</td>
<td>6</td>
<td>6</td>
<td>15</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>india (ind)</td>
<td>2</td>
<td>0</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>iran (iri)</td>
<td>2</td>
<td>0</td>
<td>0</td>
<td>2</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>japan (jpn)</td>
<td>1</td>
<td>3</td>
<td>2</td>
<td>6</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>afghanistan (afg)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>9</th>
<td>9</td>
<td>qatar (qat)</td>
<td>1</td>
<td>0</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>philippines (phi)</td>
<td>0</td>
<td>2</td>
<td>2</td>
<td>4</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>vietnam (vie)</td>
<td>0</td>
<td>2</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>kazakhstan (kaz)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>13</th>
<td>13</td>
<td>pakistan (pak)</td>
<td>0</td>
<td>1</td>
<td>1</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>bahrain (brn)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>15</td>
<td>turkmenistan (tkm)</td>
<td>0</td>
<td>1</td>
<td>0</td>
<td>1</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>sri lanka (sri)</td>
<td>0</td>
<td>0</td>
<td>2</td>
<td>2</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>bangladesh (ban)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>18</th>
<td>18</td>
<td>brunei (bru)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>19</th>
<td>18</td>
<td>laos (lao)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>20</th>
<td>18</td>
<td>mongolia (mgl)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>21</th>
<td>18</td>
<td>palestine (ple)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>22</th>
<td>18</td>
<td>singapore (sin)</td>
<td>0</td>
<td>0</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<th>23</th>
<td>total</td>
<td>total</td>
<td>49</td>
<td>49</td>
<td>54</td>
<td>152</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>min ( "total" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>15</td>
</tr>
</tbody>
</table> | select min ( total ) where total > 1 <table_name> : table | | rank | nation | gold | silver | bronze | total |
|---:|:-------|:---------------------|-------:|---------:|---------:|--------:|
| 0 | 1 | china (chn) | 14 | 10 | 12 | 36 |
| 1 | 2 | thailand (tha) | 13 | 9 | 6 | 28 |
| 2 | 3 | south korea (kor) | 6 | 7 | 10 | 23 |
| 3 | 4 | indonesia (ina) | 6 | 6 | 4 | 16 |
| 4 | 5 | chinese taipei (tpe) | 3 | 6 | 6 | 15 |
| 5 | 6 | india (ind) | 2 | 0 | 1 | 3 |
| 6 | 7 | iran (iri) | 2 | 0 | 0 | 2 |
| 7 | 8 | japan (jpn) | 1 | 3 | 2 | 6 |
| 8 | 9 | afghanistan (afg) | 1 | 0 | 0 | 1 |
| 9 | 9 | qatar (qat) | 1 | 0 | 0 | 1 |
| 10 | 11 | philippines (phi) | 0 | 2 | 2 | 4 |
| 11 | 12 | vietnam (vie) | 0 | 2 | 1 | 3 |
| 12 | 13 | kazakhstan (kaz) | 0 | 1 | 1 | 2 |
| 13 | 13 | pakistan (pak) | 0 | 1 | 1 | 2 |
| 14 | 15 | bahrain (brn) | 0 | 1 | 0 | 1 |
| 15 | 15 | turkmenistan (tkm) | 0 | 1 | 0 | 1 |
| 16 | 17 | sri lanka (sri) | 0 | 0 | 2 | 2 |
| 17 | 18 | bangladesh (ban) | 0 | 0 | 1 | 1 |
| 18 | 18 | brunei (bru) | 0 | 0 | 1 | 1 |
| 19 | 18 | laos (lao) | 0 | 0 | 1 | 1 |
| 20 | 18 | mongolia (mgl) | 0 | 0 | 1 | 1 |
| 21 | 18 | palestine (ple) | 0 | 0 | 1 | 1 |
| 22 | 18 | singapore (sin) | 0 | 0 | 1 | 1 |
| 23 | total | total | 49 | 49 | 54 | 152 | | | | min ( "total" ) |
|---:|------------------:|
| 0 | 15 | | [
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select team where team = 'corinthians' col : position | team | points | played | won | drawn | lost | for | against | difference row 1 : 1 | paulistano | 30 | 18 | 14 | 2 | 2 | 62 | 19 | 43 row 2 : 2 | palestra italia-sp | 29 | 18 | 14 | 1 | 3 | 59 | 21 | 38 row 3 : 3 | corinthians | 26 | 18 | 12 | 2 | 4 | 51 | 16 | 35 row 4 : 4 | ypiranga-sp | 25 | 18 | 11 | 3 | 4 | 56 | 34 | 22 row 5 : 5 | aa sao bento | 16 | 18 | 7 | 2 | 9 | 38 | 44 | -6 row 6 : 6 | santos | 13 | 18 | 6 | 1 | 11 | 36 | 43 | -7 row 7 : 7 | sc internacional de sao paulo | 11 | 15 | 3 | 5 | 7 | 26 | 44 | -18 row 8 : 8 | minas gerais | 10 | 15 | 4 | 2 | 9 | 18 | 49 | -31 row 9 : 9 | aa das palmeiras | 6 | 15 | 3 | 0 | 12 | 27 | 57 | -30 row 10 : 10 | mackenzie | 2 | 15 | 1 | 0 | 14 | 11 | 57 | -46 | col : team row 1 : corinthians | select team where team = 'corinthians' <table_name> : table \begin{tabular}{lllllllllll}
\toprule
& position & team & points & played & won & drawn & lost & for & against & difference \\
\midrule
0 & 1 & paulistano & 30 & 18 & 14 & 2 & 2 & 62 & 19 & 43 \\
1 & 2 & palestra italia-sp & 29 & 18 & 14 & 1 & 3 & 59 & 21 & 38 \\
2 & 3 & corinthians & 26 & 18 & 12 & 2 & 4 & 51 & 16 & 35 \\
3 & 4 & ypiranga-sp & 25 & 18 & 11 & 3 & 4 & 56 & 34 & 22 \\
4 & 5 & aa sao bento & 16 & 18 & 7 & 2 & 9 & 38 & 44 & -6 \\
5 & 6 & santos & 13 & 18 & 6 & 1 & 11 & 36 & 43 & -7 \\
6 & 7 & sc internacional de sao paulo & 11 & 15 & 3 & 5 & 7 & 26 & 44 & -18 \\
7 & 8 & minas gerais & 10 & 15 & 4 & 2 & 9 & 18 & 49 & -31 \\
8 & 9 & aa das palmeiras & 6 & 15 & 3 & 0 & 12 & 27 & 57 & -30 \\
9 & 10 & mackenzie & 2 & 15 & 1 & 0 & 14 & 11 & 57 & -46 \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& team \\
\midrule
0 & corinthians \\
\bottomrule
\end{tabular}
| select team where team = 'corinthians' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>position</th>
<th>team</th>
<th>points</th>
<th>played</th>
<th>won</th>
<th>drawn</th>
<th>lost</th>
<th>for</th>
<th>against</th>
<th>difference</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>paulistano</td>
<td>30</td>
<td>18</td>
<td>14</td>
<td>2</td>
<td>2</td>
<td>62</td>
<td>19</td>
<td>43</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>palestra italia-sp</td>
<td>29</td>
<td>18</td>
<td>14</td>
<td>1</td>
<td>3</td>
<td>59</td>
<td>21</td>
<td>38</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>corinthians</td>
<td>26</td>
<td>18</td>
<td>12</td>
<td>2</td>
<td>4</td>
<td>51</td>
<td>16</td>
<td>35</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>ypiranga-sp</td>
<td>25</td>
<td>18</td>
<td>11</td>
<td>3</td>
<td>4</td>
<td>56</td>
<td>34</td>
<td>22</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>aa sao bento</td>
<td>16</td>
<td>18</td>
<td>7</td>
<td>2</td>
<td>9</td>
<td>38</td>
<td>44</td>
<td>-6</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>santos</td>
<td>13</td>
<td>18</td>
<td>6</td>
<td>1</td>
<td>11</td>
<td>36</td>
<td>43</td>
<td>-7</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>sc internacional de sao paulo</td>
<td>11</td>
<td>15</td>
<td>3</td>
<td>5</td>
<td>7</td>
<td>26</td>
<td>44</td>
<td>-18</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>minas gerais</td>
<td>10</td>
<td>15</td>
<td>4</td>
<td>2</td>
<td>9</td>
<td>18</td>
<td>49</td>
<td>-31</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>aa das palmeiras</td>
<td>6</td>
<td>15</td>
<td>3</td>
<td>0</td>
<td>12</td>
<td>27</td>
<td>57</td>
<td>-30</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>mackenzie</td>
<td>2</td>
<td>15</td>
<td>1</td>
<td>0</td>
<td>14</td>
<td>11</td>
<td>57</td>
<td>-46</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>team</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>corinthians</td>
</tr>
</tbody>
</table> | select team where team = 'corinthians' <table_name> : table | | position | team | points | played | won | drawn | lost | for | against | difference |
|---:|-----------:|:------------------------------|---------:|---------:|------:|--------:|-------:|------:|----------:|-------------:|
| 0 | 1 | paulistano | 30 | 18 | 14 | 2 | 2 | 62 | 19 | 43 |
| 1 | 2 | palestra italia-sp | 29 | 18 | 14 | 1 | 3 | 59 | 21 | 38 |
| 2 | 3 | corinthians | 26 | 18 | 12 | 2 | 4 | 51 | 16 | 35 |
| 3 | 4 | ypiranga-sp | 25 | 18 | 11 | 3 | 4 | 56 | 34 | 22 |
| 4 | 5 | aa sao bento | 16 | 18 | 7 | 2 | 9 | 38 | 44 | -6 |
| 5 | 6 | santos | 13 | 18 | 6 | 1 | 11 | 36 | 43 | -7 |
| 6 | 7 | sc internacional de sao paulo | 11 | 15 | 3 | 5 | 7 | 26 | 44 | -18 |
| 7 | 8 | minas gerais | 10 | 15 | 4 | 2 | 9 | 18 | 49 | -31 |
| 8 | 9 | aa das palmeiras | 6 | 15 | 3 | 0 | 12 | 27 | 57 | -30 |
| 9 | 10 | mackenzie | 2 | 15 | 1 | 0 | 14 | 11 | 57 | -46 | | | | team |
|---:|:------------|
| 0 | corinthians | | [
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] |
select count ( retired ) where finish = 0 col : year | car | start | qual | rank | finish | laps | led | retired row 1 : 1956 | 14 | 23 | 142.535 | 16 | 7 | 200 | 0 | running row 2 : 1957 | 7 | 16 | 141.016 | 19 | 9 | 200 | 0 | running row 3 : 1958 | 14 | 4 | 144.881 | 4 | 26 | 1 | 0 | crash t3 row 4 : 1959 | 74 | 7 | 144.023 | 8 | 12 | 200 | 0 | running row 5 : 1960 | 44 | 25 | 143.363 | 23 | 8 | 200 | 0 | running row 6 : 1962 | 96 | 19 | 146.157 | 32 | 33 | 12 | 0 | engine row 7 : 1963 | 86 | 24 | 148.289 | 26 | 26 | 74 | 0 | valve row 8 : 1964 | 54 | 23 | 153.381 | 10 | 19 | 88 | 0 | piston row 9 : 1965 | 54 | 10 | 156.427 | 11 | 24 | 58 | 0 | piston row 10 : 1967 | 46 | 28 | 162.58 | 32 | 11 | 189 | 0 | flagged row 11 : 1968 | 16 | 24 | 163.495 | 24 | 11 | 196 | 0 | flagged row 12 : totals | totals | totals | totals | totals | totals | 1418 | 0 | none | col : count ( "retired" ) row 1 : 0 | select count ( retired ) where finish = 0 <table_name> : table \begin{tabular}{llllllllll}
\toprule
& year & car & start & qual & rank & finish & laps & led & retired \\
\midrule
0 & 1956 & 14 & 23 & 142.535 & 16 & 7 & 200 & 0 & running \\
1 & 1957 & 7 & 16 & 141.016 & 19 & 9 & 200 & 0 & running \\
2 & 1958 & 14 & 4 & 144.881 & 4 & 26 & 1 & 0 & crash t3 \\
3 & 1959 & 74 & 7 & 144.023 & 8 & 12 & 200 & 0 & running \\
4 & 1960 & 44 & 25 & 143.363 & 23 & 8 & 200 & 0 & running \\
5 & 1962 & 96 & 19 & 146.157 & 32 & 33 & 12 & 0 & engine \\
6 & 1963 & 86 & 24 & 148.289 & 26 & 26 & 74 & 0 & valve \\
7 & 1964 & 54 & 23 & 153.381 & 10 & 19 & 88 & 0 & piston \\
8 & 1965 & 54 & 10 & 156.427 & 11 & 24 & 58 & 0 & piston \\
9 & 1967 & 46 & 28 & 162.58 & 32 & 11 & 189 & 0 & flagged \\
10 & 1968 & 16 & 24 & 163.495 & 24 & 11 & 196 & 0 & flagged \\
11 & totals & totals & totals & totals & totals & totals & 1418 & 0 & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "retired" ) \\
\midrule
0 & 0 \\
\bottomrule
\end{tabular}
| select count ( retired ) where finish = 0 <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>year</th>
<th>car</th>
<th>start</th>
<th>qual</th>
<th>rank</th>
<th>finish</th>
<th>laps</th>
<th>led</th>
<th>retired</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1956</td>
<td>14</td>
<td>23</td>
<td>142.535</td>
<td>16</td>
<td>7</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>1</th>
<td>1957</td>
<td>7</td>
<td>16</td>
<td>141.016</td>
<td>19</td>
<td>9</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>2</th>
<td>1958</td>
<td>14</td>
<td>4</td>
<td>144.881</td>
<td>4</td>
<td>26</td>
<td>1</td>
<td>0</td>
<td>crash t3</td>
</tr>
<tr>
<th>3</th>
<td>1959</td>
<td>74</td>
<td>7</td>
<td>144.023</td>
<td>8</td>
<td>12</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>4</th>
<td>1960</td>
<td>44</td>
<td>25</td>
<td>143.363</td>
<td>23</td>
<td>8</td>
<td>200</td>
<td>0</td>
<td>running</td>
</tr>
<tr>
<th>5</th>
<td>1962</td>
<td>96</td>
<td>19</td>
<td>146.157</td>
<td>32</td>
<td>33</td>
<td>12</td>
<td>0</td>
<td>engine</td>
</tr>
<tr>
<th>6</th>
<td>1963</td>
<td>86</td>
<td>24</td>
<td>148.289</td>
<td>26</td>
<td>26</td>
<td>74</td>
<td>0</td>
<td>valve</td>
</tr>
<tr>
<th>7</th>
<td>1964</td>
<td>54</td>
<td>23</td>
<td>153.381</td>
<td>10</td>
<td>19</td>
<td>88</td>
<td>0</td>
<td>piston</td>
</tr>
<tr>
<th>8</th>
<td>1965</td>
<td>54</td>
<td>10</td>
<td>156.427</td>
<td>11</td>
<td>24</td>
<td>58</td>
<td>0</td>
<td>piston</td>
</tr>
<tr>
<th>9</th>
<td>1967</td>
<td>46</td>
<td>28</td>
<td>162.58</td>
<td>32</td>
<td>11</td>
<td>189</td>
<td>0</td>
<td>flagged</td>
</tr>
<tr>
<th>10</th>
<td>1968</td>
<td>16</td>
<td>24</td>
<td>163.495</td>
<td>24</td>
<td>11</td>
<td>196</td>
<td>0</td>
<td>flagged</td>
</tr>
<tr>
<th>11</th>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>totals</td>
<td>1418</td>
<td>0</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "retired" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>0</td>
</tr>
</tbody>
</table> | select count ( retired ) where finish = 0 <table_name> : table | | year | car | start | qual | rank | finish | laps | led | retired |
|---:|:-------|:-------|:--------|:--------|:-------|:---------|-------:|------:|:----------|
| 0 | 1956 | 14 | 23 | 142.535 | 16 | 7 | 200 | 0 | running |
| 1 | 1957 | 7 | 16 | 141.016 | 19 | 9 | 200 | 0 | running |
| 2 | 1958 | 14 | 4 | 144.881 | 4 | 26 | 1 | 0 | crash t3 |
| 3 | 1959 | 74 | 7 | 144.023 | 8 | 12 | 200 | 0 | running |
| 4 | 1960 | 44 | 25 | 143.363 | 23 | 8 | 200 | 0 | running |
| 5 | 1962 | 96 | 19 | 146.157 | 32 | 33 | 12 | 0 | engine |
| 6 | 1963 | 86 | 24 | 148.289 | 26 | 26 | 74 | 0 | valve |
| 7 | 1964 | 54 | 23 | 153.381 | 10 | 19 | 88 | 0 | piston |
| 8 | 1965 | 54 | 10 | 156.427 | 11 | 24 | 58 | 0 | piston |
| 9 | 1967 | 46 | 28 | 162.58 | 32 | 11 | 189 | 0 | flagged |
| 10 | 1968 | 16 | 24 | 163.495 | 24 | 11 | 196 | 0 | flagged |
| 11 | totals | totals | totals | totals | totals | totals | 1418 | 0 | none | | | | count ( "retired" ) |
|---:|----------------------:|
| 0 | 0 | | [
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] |
select count ( * ) where rider = 'jarno janssen' col : pos | rider | manufacturer | time/retired | points row 1 : 1 | tohru ukawa | honda | 49:50.449 | 25 row 2 : 2 | franco battaini | aprilia | 5.125 | 20 row 3 : 3 | loris capirossi | honda | 10.224 | 16 row 4 : 4 | shinya nakano | yamaha | 14.848 | 13 row 5 : 5 | stefano perugini | honda | 34.042 | 11 row 6 : 6 | sebastian porto | yamaha | 37.495 | 10 row 7 : 7 | jason vincent | honda | 44.911 | 9 row 8 : 8 | valentino rossi | aprilia | +1:01.110 | 8 row 9 : 9 | anthony west | tsr-honda | +1:10.352 | 7 row 10 : 10 | alex hofmann | tsr-honda | +1:18.683 | 6 row 11 : 11 | luca boscoscuro | tsr-honda | +1:20.847 | 5 row 12 : 12 | lucas oliver bulto | yamaha | +1:23.052 | 4 row 13 : 13 | roberto rolfo | aprilia | +1:24.329 | 3 row 14 : 14 | masaki tokudome | tsr-honda | +1:26.837 | 2 row 15 : 15 | fonsi nieto | yamaha | +1:45.669 | 1 row 16 : 16 | david garcia | yamaha | +1:48.926 | none row 17 : 17 | scott smart | aprilia | +1:49.730 | none row 18 : 18 | alex debon | honda | +1 lap | none row 19 : 19 | jarno janssen | tsr-honda | +1 lap | none row 20 : ret | alvaro molina | honda | retirement | none row 21 : ret | julien allemand | tsr-honda | retirement | none row 22 : ret | ismael bonilla | honda | retirement | none row 23 : ret | daniel ribalta | aprilia | retirement | none row 24 : ret | maurice bolwerk | honda | retirement | none row 25 : ret | tomomi manako | yamaha | retirement | none row 26 : ret | johann stigefelt | yamaha | retirement | none row 27 : ret | olivier jacque | yamaha | retirement | none row 28 : ret | jeremy mcwilliams | aprilia | retirement | none row 29 : ret | david ortega | tsr-honda | retirement | none row 30 : ret | alfredo rios | aprilia | retirement | none row 31 : ret | ralf waldmann | aprilia | retirement | none | col : count ( "*" ) row 1 : 1 | select count ( * ) where rider = 'jarno janssen' <table_name> : table \begin{tabular}{llllll}
\toprule
& pos & rider & manufacturer & time/retired & points \\
\midrule
0 & 1 & tohru ukawa & honda & 49:50.449 & 25 \\
1 & 2 & franco battaini & aprilia & 5.125 & 20 \\
2 & 3 & loris capirossi & honda & 10.224 & 16 \\
3 & 4 & shinya nakano & yamaha & 14.848 & 13 \\
4 & 5 & stefano perugini & honda & 34.042 & 11 \\
5 & 6 & sebastian porto & yamaha & 37.495 & 10 \\
6 & 7 & jason vincent & honda & 44.911 & 9 \\
7 & 8 & valentino rossi & aprilia & +1:01.110 & 8 \\
8 & 9 & anthony west & tsr-honda & +1:10.352 & 7 \\
9 & 10 & alex hofmann & tsr-honda & +1:18.683 & 6 \\
10 & 11 & luca boscoscuro & tsr-honda & +1:20.847 & 5 \\
11 & 12 & lucas oliver bulto & yamaha & +1:23.052 & 4 \\
12 & 13 & roberto rolfo & aprilia & +1:24.329 & 3 \\
13 & 14 & masaki tokudome & tsr-honda & +1:26.837 & 2 \\
14 & 15 & fonsi nieto & yamaha & +1:45.669 & 1 \\
15 & 16 & david garcia & yamaha & +1:48.926 & none \\
16 & 17 & scott smart & aprilia & +1:49.730 & none \\
17 & 18 & alex debon & honda & +1 lap & none \\
18 & 19 & jarno janssen & tsr-honda & +1 lap & none \\
19 & ret & alvaro molina & honda & retirement & none \\
20 & ret & julien allemand & tsr-honda & retirement & none \\
21 & ret & ismael bonilla & honda & retirement & none \\
22 & ret & daniel ribalta & aprilia & retirement & none \\
23 & ret & maurice bolwerk & honda & retirement & none \\
24 & ret & tomomi manako & yamaha & retirement & none \\
25 & ret & johann stigefelt & yamaha & retirement & none \\
26 & ret & olivier jacque & yamaha & retirement & none \\
27 & ret & jeremy mcwilliams & aprilia & retirement & none \\
28 & ret & david ortega & tsr-honda & retirement & none \\
29 & ret & alfredo rios & aprilia & retirement & none \\
30 & ret & ralf waldmann & aprilia & retirement & none \\
\bottomrule
\end{tabular}
| \begin{tabular}{ll}
\toprule
& count ( "*" ) \\
\midrule
0 & 1 \\
\bottomrule
\end{tabular}
| select count ( * ) where rider = 'jarno janssen' <table_name> : table <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>pos</th>
<th>rider</th>
<th>manufacturer</th>
<th>time/retired</th>
<th>points</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
<td>tohru ukawa</td>
<td>honda</td>
<td>49:50.449</td>
<td>25</td>
</tr>
<tr>
<th>1</th>
<td>2</td>
<td>franco battaini</td>
<td>aprilia</td>
<td>5.125</td>
<td>20</td>
</tr>
<tr>
<th>2</th>
<td>3</td>
<td>loris capirossi</td>
<td>honda</td>
<td>10.224</td>
<td>16</td>
</tr>
<tr>
<th>3</th>
<td>4</td>
<td>shinya nakano</td>
<td>yamaha</td>
<td>14.848</td>
<td>13</td>
</tr>
<tr>
<th>4</th>
<td>5</td>
<td>stefano perugini</td>
<td>honda</td>
<td>34.042</td>
<td>11</td>
</tr>
<tr>
<th>5</th>
<td>6</td>
<td>sebastian porto</td>
<td>yamaha</td>
<td>37.495</td>
<td>10</td>
</tr>
<tr>
<th>6</th>
<td>7</td>
<td>jason vincent</td>
<td>honda</td>
<td>44.911</td>
<td>9</td>
</tr>
<tr>
<th>7</th>
<td>8</td>
<td>valentino rossi</td>
<td>aprilia</td>
<td>+1:01.110</td>
<td>8</td>
</tr>
<tr>
<th>8</th>
<td>9</td>
<td>anthony west</td>
<td>tsr-honda</td>
<td>+1:10.352</td>
<td>7</td>
</tr>
<tr>
<th>9</th>
<td>10</td>
<td>alex hofmann</td>
<td>tsr-honda</td>
<td>+1:18.683</td>
<td>6</td>
</tr>
<tr>
<th>10</th>
<td>11</td>
<td>luca boscoscuro</td>
<td>tsr-honda</td>
<td>+1:20.847</td>
<td>5</td>
</tr>
<tr>
<th>11</th>
<td>12</td>
<td>lucas oliver bulto</td>
<td>yamaha</td>
<td>+1:23.052</td>
<td>4</td>
</tr>
<tr>
<th>12</th>
<td>13</td>
<td>roberto rolfo</td>
<td>aprilia</td>
<td>+1:24.329</td>
<td>3</td>
</tr>
<tr>
<th>13</th>
<td>14</td>
<td>masaki tokudome</td>
<td>tsr-honda</td>
<td>+1:26.837</td>
<td>2</td>
</tr>
<tr>
<th>14</th>
<td>15</td>
<td>fonsi nieto</td>
<td>yamaha</td>
<td>+1:45.669</td>
<td>1</td>
</tr>
<tr>
<th>15</th>
<td>16</td>
<td>david garcia</td>
<td>yamaha</td>
<td>+1:48.926</td>
<td>none</td>
</tr>
<tr>
<th>16</th>
<td>17</td>
<td>scott smart</td>
<td>aprilia</td>
<td>+1:49.730</td>
<td>none</td>
</tr>
<tr>
<th>17</th>
<td>18</td>
<td>alex debon</td>
<td>honda</td>
<td>+1 lap</td>
<td>none</td>
</tr>
<tr>
<th>18</th>
<td>19</td>
<td>jarno janssen</td>
<td>tsr-honda</td>
<td>+1 lap</td>
<td>none</td>
</tr>
<tr>
<th>19</th>
<td>ret</td>
<td>alvaro molina</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>20</th>
<td>ret</td>
<td>julien allemand</td>
<td>tsr-honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>21</th>
<td>ret</td>
<td>ismael bonilla</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>22</th>
<td>ret</td>
<td>daniel ribalta</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>23</th>
<td>ret</td>
<td>maurice bolwerk</td>
<td>honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>24</th>
<td>ret</td>
<td>tomomi manako</td>
<td>yamaha</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>25</th>
<td>ret</td>
<td>johann stigefelt</td>
<td>yamaha</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>26</th>
<td>ret</td>
<td>olivier jacque</td>
<td>yamaha</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>27</th>
<td>ret</td>
<td>jeremy mcwilliams</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>28</th>
<td>ret</td>
<td>david ortega</td>
<td>tsr-honda</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>29</th>
<td>ret</td>
<td>alfredo rios</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
<tr>
<th>30</th>
<td>ret</td>
<td>ralf waldmann</td>
<td>aprilia</td>
<td>retirement</td>
<td>none</td>
</tr>
</tbody>
</table> | <table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>count ( "*" )</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td>1</td>
</tr>
</tbody>
</table> | select count ( * ) where rider = 'jarno janssen' <table_name> : table | | pos | rider | manufacturer | time/retired | points |
|---:|:------|:-------------------|:---------------|:---------------|:---------|
| 0 | 1 | tohru ukawa | honda | 49:50.449 | 25 |
| 1 | 2 | franco battaini | aprilia | 5.125 | 20 |
| 2 | 3 | loris capirossi | honda | 10.224 | 16 |
| 3 | 4 | shinya nakano | yamaha | 14.848 | 13 |
| 4 | 5 | stefano perugini | honda | 34.042 | 11 |
| 5 | 6 | sebastian porto | yamaha | 37.495 | 10 |
| 6 | 7 | jason vincent | honda | 44.911 | 9 |
| 7 | 8 | valentino rossi | aprilia | +1:01.110 | 8 |
| 8 | 9 | anthony west | tsr-honda | +1:10.352 | 7 |
| 9 | 10 | alex hofmann | tsr-honda | +1:18.683 | 6 |
| 10 | 11 | luca boscoscuro | tsr-honda | +1:20.847 | 5 |
| 11 | 12 | lucas oliver bulto | yamaha | +1:23.052 | 4 |
| 12 | 13 | roberto rolfo | aprilia | +1:24.329 | 3 |
| 13 | 14 | masaki tokudome | tsr-honda | +1:26.837 | 2 |
| 14 | 15 | fonsi nieto | yamaha | +1:45.669 | 1 |
| 15 | 16 | david garcia | yamaha | +1:48.926 | none |
| 16 | 17 | scott smart | aprilia | +1:49.730 | none |
| 17 | 18 | alex debon | honda | +1 lap | none |
| 18 | 19 | jarno janssen | tsr-honda | +1 lap | none |
| 19 | ret | alvaro molina | honda | retirement | none |
| 20 | ret | julien allemand | tsr-honda | retirement | none |
| 21 | ret | ismael bonilla | honda | retirement | none |
| 22 | ret | daniel ribalta | aprilia | retirement | none |
| 23 | ret | maurice bolwerk | honda | retirement | none |
| 24 | ret | tomomi manako | yamaha | retirement | none |
| 25 | ret | johann stigefelt | yamaha | retirement | none |
| 26 | ret | olivier jacque | yamaha | retirement | none |
| 27 | ret | jeremy mcwilliams | aprilia | retirement | none |
| 28 | ret | david ortega | tsr-honda | retirement | none |
| 29 | ret | alfredo rios | aprilia | retirement | none |
| 30 | ret | ralf waldmann | aprilia | retirement | none | | | | count ( "*" ) |
|---:|----------------:|
| 0 | 1 | | [
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