NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
What is Position/ Eliminated, when Age is less than 22, and when Full Name is 'Muhammad Fairul Azreen Bin Mohd Zahid'? | CREATE TABLE table_76685 (
"Full name" text,
"Alias" text,
"Age\u00b9" real,
"From" text,
"Occupation\u00b2" text,
"Specialty" text,
"Position/ Eliminated" text
) | SELECT "Position/ Eliminated" FROM table_76685 WHERE "Age\u00b9" < '22' AND "Full name" = 'muhammad fairul azreen bin mohd zahid' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3959,
3651,
755,
41,
96,
371,
83,
40,
564,
121,
1499,
6,
96,
188,
40,
23,
9,
7,
121,
1499,
6,
96,
188,
397,
2,
76,
1206,
115,
1298,
121,
490,
6,
96,
22674,
121,
1499,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
345,
32,
7,
4749,
87,
7495,
1109,
920,
121,
21680,
953,
834,
3959,
3651,
755,
549,
17444,
427,
96,
188,
397,
2,
76,
1206,
115,
1298,
121,
3,
2,
3,
31,
2884,
31,
3430,
96,
371,
83,
40,
564,
121,
3274,
3,
... |
Who was the team that lost but had 10 points? | CREATE TABLE table_43187 (
"Team" text,
"Match" text,
"Points" text,
"Draw" text,
"Lost" text
) | SELECT "Lost" FROM table_43187 WHERE "Points" = '10' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4906,
25828,
41,
96,
18699,
121,
1499,
6,
96,
329,
14547,
121,
1499,
6,
96,
22512,
7,
121,
1499,
6,
96,
308,
10936,
121,
1499,
6,
96,
434,
3481,
121,
1499,
3,
61,
3,
32... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0... | [
3,
23143,
14196,
96,
434,
3481,
121,
21680,
953,
834,
4906,
25828,
549,
17444,
427,
96,
22512,
7,
121,
3274,
3,
31,
1714,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What was the results against the Philadelphia Eagles? | CREATE TABLE table_name_20 (
result VARCHAR,
opponent VARCHAR
) | SELECT result FROM table_name_20 WHERE opponent = "philadelphia eagles" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1755,
41,
741,
584,
4280,
28027,
6,
15264,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
772,
581,
8,
9511,
10341,
7,
58,
1,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
741,
21680,
953,
834,
4350,
834,
1755,
549,
17444,
427,
15264,
3274,
96,
18118,
15311,
11692,
9,
3,
15,
9,
3537,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the highest rank when the metal total is 1 and the nation is the United Kingdom? | CREATE TABLE table_name_99 (rank INTEGER, total VARCHAR, nation VARCHAR) | SELECT MAX(rank) FROM table_name_99 WHERE total = 1 AND nation = "united kingdom" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3264,
41,
6254,
3,
21342,
17966,
6,
792,
584,
4280,
28027,
6,
2982,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2030,
11003,
116,
8,
1946,
7... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
6254,
61,
21680,
953,
834,
4350,
834,
3264,
549,
17444,
427,
792,
3274,
209,
3430,
2982,
3274,
96,
15129,
15,
26,
14740,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many times was the score 6 7(5), 6 2, 6 3? | CREATE TABLE table_22871 (
"Outcome" text,
"Year" real,
"Championship" text,
"Surface" text,
"Partner" text,
"Opponents" text,
"Score" text
) | SELECT COUNT("Opponents") FROM table_22871 WHERE "Score" = '6–7(5), 6–2, 6–3' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
2577,
4450,
41,
96,
15767,
287,
15,
121,
1499,
6,
96,
476,
2741,
121,
490,
6,
96,
254,
1483,
12364,
2009,
121,
1499,
6,
96,
134,
450,
4861,
121,
1499,
6,
96,
13725,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
667,
102,
9977,
7,
8512,
21680,
953,
834,
357,
2577,
4450,
549,
17444,
427,
96,
134,
9022,
121,
3274,
3,
31,
948,
104,
940,
15757,
6,
431,
104,
4482,
431,
104,
519,
31,
1,
-100,
-100,
-100,
... |
what name was on the year 2012 | CREATE TABLE table_37101 (
"Rank" real,
"Name" text,
"Height* ft (m)" text,
"Year* (est.)" text,
"City" text
) | SELECT "Name" FROM table_37101 WHERE "Year* (est.)" = '2012' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4118,
19621,
41,
96,
22557,
121,
490,
6,
96,
23954,
121,
1499,
6,
96,
3845,
2632,
1935,
3,
89,
17,
41,
51,
61,
121,
1499,
6,
96,
476,
2741,
1935,
41,
222,
5,
61,
121,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
23954,
121,
21680,
953,
834,
4118,
19621,
549,
17444,
427,
96,
476,
2741,
1935,
41,
222,
5,
61,
121,
3274,
3,
31,
12172,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What was the record lowest temperature with a precipitation of 1.71 in.? | CREATE TABLE table_26558_1 (
record_low VARCHAR,
precip VARCHAR
) | SELECT record_low FROM table_26558_1 WHERE precip = "1.71 in." | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
4122,
3449,
834,
536,
41,
1368,
834,
3216,
584,
4280,
28027,
6,
554,
3389,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1368,
7402,
2912,
28,
3,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1368,
834,
3216,
21680,
953,
834,
357,
4122,
3449,
834,
536,
549,
17444,
427,
554,
3389,
3274,
96,
18596,
536,
16,
535,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the highest number of bills cosponsored associated with under 24 bills sponsored and under 16 amendments sponsored? | CREATE TABLE table_64203 (
"Years covered" text,
"All bills sponsored" real,
"All amendments sponsored" real,
"All bills cosponsored" real,
"All amendments cosponsored" real,
"Bills originally cosponsored" real,
"Amendments originally cosponsored" real
) | SELECT MAX("All bills cosponsored") FROM table_64203 WHERE "All bills sponsored" < '24' AND "All amendments sponsored" < '16' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
23330,
41,
96,
476,
2741,
7,
2303,
121,
1499,
6,
96,
6838,
7200,
11851,
121,
490,
6,
96,
6838,
12123,
7,
11851,
121,
490,
6,
96,
6838,
7200,
576,
27959,
121,
490,
6... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
6838,
7200,
576,
27959,
8512,
21680,
953,
834,
4389,
23330,
549,
17444,
427,
96,
6838,
7200,
11851,
121,
3,
2,
3,
31,
2266,
31,
3430,
96,
6838,
12123,
7,
11851,
121,
3,
2,
3,
31,
2938,
31,
1,
... |
Which Pick # is the highest one that has an Overall larger than 21, and a College of north carolina, and a Round smaller than 3? | CREATE TABLE table_name_14 (pick__number INTEGER, round VARCHAR, overall VARCHAR, college VARCHAR) | SELECT MAX(pick__number) FROM table_name_14 WHERE overall > 21 AND college = "north carolina" AND round < 3 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2534,
41,
17967,
834,
834,
5525,
1152,
3,
21342,
17966,
6,
1751,
584,
4280,
28027,
6,
1879,
584,
4280,
28027,
6,
1900,
584,
4280,
28027,
61,
3,
32102,
32103,
32101... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
17967,
834,
834,
5525,
1152,
61,
21680,
953,
834,
4350,
834,
2534,
549,
17444,
427,
1879,
2490,
1401,
3430,
1900,
3274,
96,
29,
127,
189,
443,
12057,
9,
121,
3430,
1751,
3,
2,
220,
1,
-100,
-100,
-10... |
when was the marriage when became dauphine is 31 august 1412? | CREATE TABLE table_77358 (
"Name" text,
"Birth" text,
"Marriage" text,
"Became Dauphine" text,
"Ceased to be Dauphine" text,
"Death" text,
"Husband" text
) | SELECT "Marriage" FROM table_77358 WHERE "Became Dauphine" = '31 august 1412' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4013,
519,
3449,
41,
96,
23954,
121,
1499,
6,
96,
279,
23,
52,
189,
121,
1499,
6,
96,
329,
10269,
545,
121,
1499,
6,
96,
2703,
6527,
15,
878,
413,
2907,
15,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
329,
10269,
545,
121,
21680,
953,
834,
4013,
519,
3449,
549,
17444,
427,
96,
2703,
6527,
15,
878,
413,
2907,
15,
121,
3274,
3,
31,
3341,
14663,
968,
2122,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many people were in attendance on may 17? | CREATE TABLE table_69947 (
"Date" text,
"Opponent" text,
"Score" text,
"Loss" text,
"Attendance" real,
"Record" text
) | SELECT MIN("Attendance") FROM table_69947 WHERE "Date" = 'may 17' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
948,
3264,
4177,
41,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
434,
32,
7,
7,
121,
1499,
6,
96,
188,
17,
324,
26,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
188,
17,
324,
26,
663,
8512,
21680,
953,
834,
948,
3264,
4177,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
13726,
1003,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
When ellesmere port & neston is the team what are the points 1? | CREATE TABLE table_21880 (
"Position" real,
"Team" text,
"Played" real,
"Won" real,
"Drawn" real,
"Lost" real,
"Goals For" real,
"Goals Against" real,
"Goal Difference" text,
"Points 1" text
) | SELECT "Points 1" FROM table_21880 WHERE "Team" = 'Ellesmere Port & Neston' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
2606,
2079,
41,
96,
345,
32,
7,
4749,
121,
490,
6,
96,
18699,
121,
1499,
6,
96,
15800,
15,
26,
121,
490,
6,
96,
518,
106,
121,
490,
6,
96,
308,
10936,
29,
121,
4... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
22512,
7,
209,
121,
21680,
953,
834,
357,
2606,
2079,
549,
17444,
427,
96,
18699,
121,
3274,
3,
31,
10991,
965,
935,
15,
3625,
3,
184,
21351,
106,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Name the champion for london hunt and country club ( london , on ) | CREATE TABLE table_1628792_1 (champion VARCHAR, tournament_location VARCHAR) | SELECT champion FROM table_1628792_1 WHERE tournament_location = "London Hunt and country Club ( London , ON )" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
2577,
4440,
357,
834,
536,
41,
17788,
12364,
584,
4280,
28027,
6,
5892,
834,
14836,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
6336,
21,
3,
40,
106,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
6336,
21680,
953,
834,
2938,
2577,
4440,
357,
834,
536,
549,
17444,
427,
5892,
834,
14836,
3274,
96,
29712,
9550,
11,
684,
1949,
41,
1524,
3,
6,
9191,
3,
61,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many values for attendance on the date of September 5? | CREATE TABLE table_23916462_3 (
attendance VARCHAR,
date VARCHAR
) | SELECT COUNT(attendance) FROM table_23916462_3 WHERE date = "September 5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3288,
26987,
4056,
834,
519,
41,
11364,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
2620,
21,
11364,
30,
8,
833,
13,
16... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
15116,
663,
61,
21680,
953,
834,
357,
3288,
26987,
4056,
834,
519,
549,
17444,
427,
833,
3274,
96,
27652,
3,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is every description if NO votes is 233759? | CREATE TABLE table_256286_43 (description VARCHAR, no_votes VARCHAR) | SELECT description FROM table_256286_43 WHERE no_votes = 233759 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1828,
4056,
3840,
834,
4906,
41,
221,
11830,
584,
4280,
28027,
6,
150,
834,
1621,
1422,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
334,
4210,
3,
99,
5693,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4210,
21680,
953,
834,
1828,
4056,
3840,
834,
4906,
549,
17444,
427,
150,
834,
1621,
1422,
3274,
1902,
4118,
3390,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
provide the number of patients whose days of hospital stay is greater than 15 and drug name is niacin? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.days_stay > "15" AND prescriptions.drug = "Niacin" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
18730,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
7744,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7744,
7,
5,
8399,
51,
834,
23,
26,
549... |
What 2nd Party has an Election of 1834? | CREATE TABLE table_name_11 (
election VARCHAR
) | SELECT 2 AS nd_party FROM table_name_11 WHERE election = "1834" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2596,
41,
4356,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
204,
727,
3450,
65,
46,
19488,
13,
507,
3710,
58,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
204,
6157,
3,
727,
834,
8071,
21680,
953,
834,
4350,
834,
2596,
549,
17444,
427,
4356,
3274,
96,
24361,
20364,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Virtual channel of 16.5 has what call sign? | CREATE TABLE table_name_23 (
call_sign VARCHAR,
virtual_channel VARCHAR
) | SELECT call_sign FROM table_name_23 WHERE virtual_channel = "16.5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2773,
41,
580,
834,
6732,
584,
4280,
28027,
6,
4291,
834,
19778,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
11143,
4245,
13,
209,
17255,
65,
125,
580,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
580,
834,
6732,
21680,
953,
834,
4350,
834,
2773,
549,
17444,
427,
4291,
834,
19778,
3274,
96,
2938,
5,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Who was the partner for the match with a score in the final of 4 6, 6 7? | CREATE TABLE table_50609 (
"Outcome" text,
"Date" real,
"Tournament" text,
"Surface" text,
"Partner" text,
"Opponents in the final" text,
"Score in the final" text
) | SELECT "Partner" FROM table_50609 WHERE "Score in the final" = '4–6, 6–7' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1752,
948,
4198,
41,
96,
15767,
287,
15,
121,
1499,
6,
96,
308,
342,
121,
490,
6,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
134,
450,
4861,
121,
1499,
6,
96,
13725,
6... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
13725,
687,
121,
21680,
953,
834,
1752,
948,
4198,
549,
17444,
427,
96,
134,
9022,
16,
8,
804,
121,
3274,
3,
31,
591,
104,
11071,
431,
104,
940,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is every original air date for series# of 26? | CREATE TABLE table_26866205_1 (original_airdate VARCHAR, series__number VARCHAR) | SELECT original_airdate FROM table_26866205_1 WHERE series__number = 26 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
26750,
23201,
834,
536,
41,
21878,
834,
2256,
5522,
584,
4280,
28027,
6,
939,
834,
834,
5525,
1152,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
334,
9... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
926,
834,
2256,
5522,
21680,
953,
834,
2688,
26750,
23201,
834,
536,
549,
17444,
427,
939,
834,
834,
5525,
1152,
3274,
2208,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the ISIN associated with the maturity date of 3/11/2011? | CREATE TABLE table_21692771_1 (
isin VARCHAR,
maturity VARCHAR
) | SELECT isin FROM table_21692771_1 WHERE maturity = "3/11/2011" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2658,
3951,
2555,
4450,
834,
536,
41,
19,
77,
584,
4280,
28027,
6,
22004,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
6827,
3162,
1968,
28,
8,
22004... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
19,
77,
21680,
953,
834,
2658,
3951,
2555,
4450,
834,
536,
549,
17444,
427,
22004,
3274,
96,
519,
20223,
87,
13907,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
For all employees who have the letters D or S in their first name, show me about the distribution of hire_date and the amount of hire_date bin hire_date by weekday in a bar chart. | CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
) | SELECT HIRE_DATE, COUNT(HIRE_DATE) FROM employees WHERE FIRST_NAME LIKE '%D%' OR FIRST_NAME LIKE '%S%' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2476,
41,
446,
10539,
834,
4309,
3,
4331,
4059,
599,
16968,
6,
446,
10539,
834,
382,
3177,
3765,
3,
4331,
4059,
599,
2469,
201,
3,
17684,
834,
134,
4090,
24721,
7908,
1982,
599,
11071,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
454,
14132,
834,
308,
6048,
6,
2847,
17161,
599,
566,
14132,
834,
308,
6048,
61,
21680,
1652,
549,
17444,
427,
30085,
834,
567,
17683,
8729,
9914,
3,
31,
1454,
308,
1454,
31,
4674,
30085,
834,
567,
17683,
8729,
9914,
... |
For directors who had more than one movie, bin the dates of release into Year interval and them compute the total number of movies in each year bucket Show me the result using a line chart, I want to rank year from low to high order. | CREATE TABLE Reviewer (
rID int,
name text
)
CREATE TABLE Movie (
mID int,
title text,
year int,
director text
)
CREATE TABLE Rating (
rID int,
mID int,
stars int,
ratingDate date
) | SELECT year, COUNT(year) FROM Movie AS T1 JOIN Movie AS T2 ON T1.director = T2.director WHERE T1.title <> T2.title ORDER BY year | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4543,
49,
41,
3,
52,
4309,
16,
17,
6,
564,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
10743,
41,
3,
51,
4309,
16,
17,
6,
2233,
1499,
6,
215,
16,
17,
6,
2... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
215,
6,
2847,
17161,
599,
1201,
61,
21680,
10743,
6157,
332,
536,
3,
15355,
3162,
10743,
6157,
332,
357,
9191,
332,
5411,
25982,
3274,
332,
4416,
25982,
549,
17444,
427,
332,
5411,
21869,
3,
2,
3155,
332,
4416,
21869,... |
what is the attendance when the home team is chester city? | CREATE TABLE table_name_51 (
attendance VARCHAR,
home_team VARCHAR
) | SELECT attendance FROM table_name_51 WHERE home_team = "chester city" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5553,
41,
11364,
584,
4280,
28027,
6,
234,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
125,
19,
8,
11364,
116,
8,
234,
372,
19,
3,
13263,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
11364,
21680,
953,
834,
4350,
834,
5553,
549,
17444,
427,
234,
834,
11650,
3274,
96,
13263,
690,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the shield animal of knight phil? | CREATE TABLE table_60417 (
"Knight" text,
"Weapon/item" text,
"External weapon" text,
"Shield animal" text,
"Cart" text
) | SELECT "Shield animal" FROM table_60417 WHERE "Knight" = 'phil' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3328,
591,
2517,
41,
96,
439,
7602,
121,
1499,
6,
96,
1326,
9,
5041,
87,
23,
3524,
121,
1499,
6,
96,
5420,
2947,
138,
10931,
121,
1499,
6,
96,
134,
16219,
26,
2586,
121,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
134,
16219,
26,
2586,
121,
21680,
953,
834,
3328,
591,
2517,
549,
17444,
427,
96,
439,
7602,
121,
3274,
3,
31,
18118,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the Tennessee that Georgia of kevin butler is in? | CREATE TABLE table_name_27 (
tennessee VARCHAR,
georgia VARCHAR
) | SELECT tennessee FROM table_name_27 WHERE georgia = "kevin butler" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2555,
41,
3,
324,
655,
15,
15,
584,
4280,
28027,
6,
873,
1677,
23,
9,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
12976,
24,
5664,
13,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
324,
655,
15,
15,
21680,
953,
834,
4350,
834,
2555,
549,
17444,
427,
873,
1677,
23,
9,
3274,
96,
1050,
2494,
68,
1171,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
find the average age of female patients with death status 1. | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
) | SELECT AVG(demographic.age) FROM demographic WHERE demographic.gender = "F" AND demographic.expire_flag = "1" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
71,
17217,
599,
1778,
16587,
5,
545,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
122,
3868,
3274,
96,
371,
121,
3430,
14798,
5,
994,
2388,
15,
834,
89,
5430,
3274,
96,
536,
121,
1,
-100,
-100,
-100,
-100,
-100,
-... |
What is the premiere rating associated with an average of 35 ranked above 1? | CREATE TABLE table_name_7 (premiere INTEGER, average VARCHAR, rank VARCHAR) | SELECT MIN(premiere) FROM table_name_7 WHERE average = 35 AND rank > 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
940,
41,
2026,
2720,
60,
3,
21342,
17966,
6,
1348,
584,
4280,
28027,
6,
11003,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
13539,
5773,
1968,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
2026,
2720,
60,
61,
21680,
953,
834,
4350,
834,
940,
549,
17444,
427,
1348,
3274,
3097,
3430,
11003,
2490,
209,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Game of game 5 had what result? | CREATE TABLE table_75400 (
"Game" text,
"Date" text,
"Home Team" text,
"Result" text,
"Road Team" text
) | SELECT "Result" FROM table_75400 WHERE "Game" = 'game 5' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3072,
5548,
41,
96,
23055,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
19040,
2271,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
448,
32,
9,
26,
2271,
121,
1499,
3,
61,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
96,
20119,
121,
21680,
953,
834,
3072,
5548,
549,
17444,
427,
96,
23055,
121,
3274,
3,
31,
7261,
305,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the average salary for each job title? | CREATE TABLE locations (
location_id number,
street_address text,
postal_code text,
city text,
state_province text,
country_id text
)
CREATE TABLE employees (
employee_id number,
first_name text,
last_name text,
email text,
phone_number text,
hire_date time,
job_id text,
salary number,
commission_pct number,
manager_id number,
department_id number
)
CREATE TABLE departments (
department_id number,
department_name text,
manager_id number,
location_id number
)
CREATE TABLE countries (
country_id text,
country_name text,
region_id number
)
CREATE TABLE regions (
region_id number,
region_name text
)
CREATE TABLE jobs (
job_id text,
job_title text,
min_salary number,
max_salary number
)
CREATE TABLE job_history (
employee_id number,
start_date time,
end_date time,
job_id text,
department_id number
) | SELECT job_title, AVG(salary) FROM employees AS T1 JOIN jobs AS T2 ON T1.job_id = T2.job_id GROUP BY T2.job_title | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3248,
41,
1128,
834,
23,
26,
381,
6,
2815,
834,
9,
26,
12039,
1499,
6,
19085,
834,
4978,
1499,
6,
690,
1499,
6,
538,
834,
1409,
2494,
565,
1499,
6,
684,
834,
23,
26,
1499,
3,
61,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
613,
834,
21869,
6,
71,
17217,
599,
7,
138,
1208,
61,
21680,
1652,
6157,
332,
536,
3,
15355,
3162,
2476,
6157,
332,
357,
9191,
332,
5411,
16899,
834,
23,
26,
3274,
332,
4416,
16899,
834,
23,
26,
350,
4630,
6880,
2... |
how many total events will occur in all ? | CREATE TABLE table_204_206 (
id number,
"saros" number,
"member" number,
"date" text,
"time\n(greatest)\nutc" text,
"type" text,
"location\nlat,long" text,
"gamma" number,
"mag." number,
"width\n(km)" number,
"duration\n(min:sec)" text,
"ref" number
) | SELECT COUNT(*) FROM table_204_206 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
24643,
41,
3,
23,
26,
381,
6,
96,
7,
9,
1859,
121,
381,
6,
96,
12066,
121,
381,
6,
96,
5522,
121,
1499,
6,
96,
715,
2,
29,
599,
20288,
222,
61,
2,
4796,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
1935,
61,
21680,
953,
834,
26363,
834,
24643,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the total number of Year(s), when Tournament is "World Championships"? | CREATE TABLE table_name_50 (year VARCHAR, tournament VARCHAR) | SELECT COUNT(year) FROM table_name_50 WHERE tournament = "world championships" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1752,
41,
1201,
584,
4280,
28027,
6,
5892,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
792,
381,
13,
2929,
599,
7,
201,
116,
20502,
19,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
1201,
61,
21680,
953,
834,
4350,
834,
1752,
549,
17444,
427,
5892,
3274,
96,
7276,
10183,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
which artist only has its single entered on 2 january 1994 ? | CREATE TABLE table_204_220 (
id number,
"entered" text,
"weeks in\ntop 10" number,
"single" text,
"artist" text,
"peak" number,
"peak\nreached" text,
"weeks\nat peak" number
) | SELECT "artist" FROM table_204_220 WHERE "entered" = '2 january 1994' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
357,
1755,
41,
3,
23,
26,
381,
6,
96,
35,
11196,
121,
1499,
6,
96,
8041,
7,
16,
2,
29,
2916,
335,
121,
381,
6,
96,
7,
53,
109,
121,
1499,
6,
96,
1408,
3... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
1408,
343,
121,
21680,
953,
834,
26363,
834,
357,
1755,
549,
17444,
427,
96,
35,
11196,
121,
3274,
3,
31,
357,
3,
7066,
76,
1208,
7520,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
A bar chart about how films are produced by each studio? | CREATE TABLE market (
Market_ID int,
Country text,
Number_cities int
)
CREATE TABLE film_market_estimation (
Estimation_ID int,
Low_Estimate real,
High_Estimate real,
Film_ID int,
Type text,
Market_ID int,
Year int
)
CREATE TABLE film (
Film_ID int,
Title text,
Studio text,
Director text,
Gross_in_dollar int
) | SELECT Studio, COUNT(*) FROM film GROUP BY Studio | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
512,
41,
3611,
834,
4309,
16,
17,
6,
6993,
1499,
6,
7720,
834,
75,
2197,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
814,
834,
8809,
834,
3340,
51,
257,
41,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
5929,
6,
2847,
17161,
599,
1935,
61,
21680,
814,
350,
4630,
6880,
272,
476,
5929,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the pick# from South Dakota college? | CREATE TABLE table_name_23 (pick__number VARCHAR, college VARCHAR) | SELECT pick__number FROM table_name_23 WHERE college = "south dakota" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2773,
41,
17967,
834,
834,
5525,
1152,
584,
4280,
28027,
6,
1900,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1432,
4663,
45,
1013,
16711,
190... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1432,
834,
834,
5525,
1152,
21680,
953,
834,
4350,
834,
2773,
549,
17444,
427,
1900,
3274,
96,
7,
670,
107,
836,
15414,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what's current club with height being 2.09 | CREATE TABLE table_12962773_1 (current_club VARCHAR, height VARCHAR) | SELECT current_club FROM table_12962773_1 WHERE height = "2.09" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
4314,
2555,
4552,
834,
536,
41,
14907,
834,
13442,
584,
4280,
28027,
6,
3902,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
125,
31,
7,
750,
1886,
28,
3902,
271,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
750,
834,
13442,
21680,
953,
834,
2122,
4314,
2555,
4552,
834,
536,
549,
17444,
427,
3902,
3274,
96,
4416,
4198,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the maximum apogee for samos f3-3? | CREATE TABLE table_12141496_1 (apogee__km_ INTEGER, name VARCHAR) | SELECT MAX(apogee__km_) FROM table_12141496_1 WHERE name = "SAMOS F3-3" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
2534,
2534,
4314,
834,
536,
41,
9521,
397,
15,
834,
834,
5848,
834,
3,
21342,
17966,
6,
564,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2411,
3,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
9521,
397,
15,
834,
834,
5848,
834,
61,
21680,
953,
834,
2122,
2534,
2534,
4314,
834,
536,
549,
17444,
427,
564,
3274,
96,
134,
4815,
3638,
377,
519,
3486,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the segment for Netflix episode S08E04? | CREATE TABLE table_name_94 (segment_a VARCHAR, netflix VARCHAR) | SELECT segment_a FROM table_name_94 WHERE netflix = "s08e04" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4240,
41,
7,
15,
122,
297,
834,
9,
584,
4280,
28027,
6,
3134,
89,
17591,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
5508,
21,
11894,
5640,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
5508,
834,
9,
21680,
953,
834,
4350,
834,
4240,
549,
17444,
427,
3134,
89,
17591,
3274,
96,
7,
4018,
15,
6348,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Where did Tyler Haws, 2009 Utah Mr. Basketball, go to high school? | CREATE TABLE table_77588 (
"Year" real,
"Utah Mr. Basketball" text,
"High school" text,
"Class" text,
"College" text
) | SELECT "High school" FROM table_77588 WHERE "Utah Mr. Basketball" = 'tyler haws' AND "Year" = '2009' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
940,
3072,
4060,
41,
96,
476,
2741,
121,
490,
6,
96,
1265,
17,
9,
107,
1363,
5,
21249,
121,
1499,
6,
96,
21417,
496,
121,
1499,
6,
96,
21486,
121,
1499,
6,
96,
9939,
78... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
21417,
496,
121,
21680,
953,
834,
940,
3072,
4060,
549,
17444,
427,
96,
1265,
17,
9,
107,
1363,
5,
21249,
121,
3274,
3,
31,
17,
63,
1171,
4244,
210,
7,
31,
3430,
96,
476,
2741,
121,
3274,
3,
31,
16660,
31,
... |
Name the played with losing bonus of 3 and points against of 426 | CREATE TABLE table_name_37 (
played VARCHAR,
losing_bonus VARCHAR,
points_against VARCHAR
) | SELECT played FROM table_name_37 WHERE losing_bonus = "3" AND points_against = "426" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4118,
41,
1944,
584,
4280,
28027,
6,
5489,
834,
5407,
302,
584,
4280,
28027,
6,
979,
834,
9,
16720,
7,
17,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1944,
21680,
953,
834,
4350,
834,
4118,
549,
17444,
427,
5489,
834,
5407,
302,
3274,
96,
519,
121,
3430,
979,
834,
9,
16720,
7,
17,
3274,
96,
591,
2688,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many entries is under 50s column when the average is 39.60? | CREATE TABLE table_28846752_8 (average VARCHAR) | SELECT 50 AS s FROM table_28846752_8 WHERE average = "39.60" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2577,
4608,
3708,
5373,
834,
927,
41,
28951,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
10066,
19,
365,
943,
7,
6710,
116,
8,
1348,
19,
6352,
5,
3328,
5... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
943,
6157,
3,
7,
21680,
953,
834,
2577,
4608,
3708,
5373,
834,
927,
549,
17444,
427,
1348,
3274,
96,
3288,
5,
3328,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Show me about the distribution of All_Games and Team_ID in a bar chart, and list Team_ID from low to high order please. | CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
)
CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
) | SELECT All_Games, Team_ID FROM basketball_match ORDER BY Team_ID | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3819,
41,
1121,
834,
4309,
16,
17,
6,
1121,
1499,
6,
10450,
1499,
6,
3,
20100,
490,
6,
71,
89,
8027,
23,
257,
1499,
6,
695,
4046,
297,
490,
6,
7486,
4350,
1499,
6,
14542,
834,
28... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
432,
834,
23055,
7,
6,
2271,
834,
4309,
21680,
8498,
834,
19515,
4674,
11300,
272,
476,
2271,
834,
4309,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Show me a scatter plot of id and meter_100 for . | CREATE TABLE event (
ID int,
Name text,
Stadium_ID int,
Year text
)
CREATE TABLE record (
ID int,
Result text,
Swimmer_ID int,
Event_ID int
)
CREATE TABLE swimmer (
ID int,
name text,
Nationality text,
meter_100 real,
meter_200 text,
meter_300 text,
meter_400 text,
meter_500 text,
meter_600 text,
meter_700 text,
Time text
)
CREATE TABLE stadium (
ID int,
name text,
Capacity int,
City text,
Country text,
Opening_year int
) | SELECT ID, meter_100 FROM swimmer | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
605,
41,
4699,
16,
17,
6,
5570,
1499,
6,
12750,
834,
4309,
16,
17,
6,
2929,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
1368,
41,
4699,
16,
17,
6,
3,
20119,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4699,
6,
3,
4401,
834,
2915,
21680,
27424,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the 1st leg with a 4-3 agg.? | CREATE TABLE table_76696 (
"Position" text,
"Team #1" text,
"Agg." text,
"Team #2" text,
"1st leg" text,
"2nd leg" text
) | SELECT "1st leg" FROM table_76696 WHERE "Agg." = '4-3' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
940,
3539,
4314,
41,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
18699,
7172,
121,
1499,
6,
96,
188,
4102,
535,
1499,
6,
96,
18699,
15493,
121,
1499,
6,
96,
536,
7,
17,
455... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
536,
7,
17,
4553,
121,
21680,
953,
834,
940,
3539,
4314,
549,
17444,
427,
96,
188,
4102,
535,
3274,
3,
31,
591,
3486,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who were the comptrollers of the parties associated with the delegates from district 1 or district 2? | CREATE TABLE election (
election_id number,
counties_represented text,
district number,
delegate text,
party number,
first_elected number,
committee text
)
CREATE TABLE party (
party_id number,
year number,
party text,
governor text,
lieutenant_governor text,
comptroller text,
attorney_general text,
us_senate text
)
CREATE TABLE county (
county_id number,
county_name text,
population number,
zip_code text
) | SELECT T2.comptroller FROM election AS T1 JOIN party AS T2 ON T1.party = T2.party_id WHERE T1.district = 1 OR T1.district = 2 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4356,
41,
4356,
834,
23,
26,
381,
6,
16227,
834,
29845,
1499,
6,
3939,
381,
6,
20,
8791,
1499,
6,
1088,
381,
6,
166,
834,
19971,
381,
6,
4492,
1499,
3,
61,
3,
32102,
32103,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
332,
4416,
7699,
17,
4046,
49,
21680,
4356,
6157,
332,
536,
3,
15355,
3162,
1088,
6157,
332,
357,
9191,
332,
5411,
8071,
3274,
332,
4416,
8071,
834,
23,
26,
549,
17444,
427,
332,
5411,
26,
23,
20066,
3274,
209,
4674... |
what is the maximum value of bun in patient 012-31116's body during their first hospital encounter? | CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
) | SELECT MAX(lab.labresult) FROM lab WHERE lab.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '012-31116' AND NOT patient.hospitaldischargetime IS NULL ORDER BY patient.hospitaladmittime LIMIT 1)) AND lab.labname = 'bun' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3362,
4267,
32,
4370,
41,
3362,
4267,
32,
26,
1294,
26,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
2912,
381,
6,
3,
7,
9,
32,
357,
381,
6,
842,
2206,
381,
6,
14114,
257,
381,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
9339,
5,
9339,
60,
7,
83,
17,
61,
21680,
7690,
549,
17444,
427,
7690,
5,
10061,
15129,
21545,
23,
26,
3388,
41,
23143,
14196,
1868,
5,
10061,
15129,
21545,
23,
26,
21680,
1868,
549,
17444,
427,
1868,
... |
Rank for viewers larger than 1.244? | CREATE TABLE table_name_21 (nightly_rank VARCHAR, viewers__millions_ INTEGER) | SELECT nightly_rank FROM table_name_21 WHERE viewers__millions_ > 1.244 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2658,
41,
7602,
120,
834,
6254,
584,
4280,
28027,
6,
13569,
834,
834,
17030,
7,
834,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
3,
22557,
21,
13569,
2186,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
706,
120,
834,
6254,
21680,
953,
834,
4350,
834,
2658,
549,
17444,
427,
13569,
834,
834,
17030,
7,
834,
2490,
3,
10917,
3628,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Who wrote the episode that has a production code 3x7557? | CREATE TABLE table_22347090_6 (
written_by VARCHAR,
production_code VARCHAR
) | SELECT written_by FROM table_22347090_6 WHERE production_code = "3X7557" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2884,
3710,
2518,
2394,
834,
948,
41,
1545,
834,
969,
584,
4280,
28027,
6,
999,
834,
4978,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
2832,
8,
5640,
24,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1545,
834,
969,
21680,
953,
834,
2884,
3710,
2518,
2394,
834,
948,
549,
17444,
427,
999,
834,
4978,
3274,
96,
519,
4,
3072,
3436,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the score for the game played between Cleveland and Orlando at Cleveland? | CREATE TABLE table_name_26 (
score VARCHAR,
home VARCHAR,
visitor VARCHAR
) | SELECT score FROM table_name_26 WHERE home = "cleveland" AND visitor = "orlando" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2688,
41,
2604,
584,
4280,
28027,
6,
234,
584,
4280,
28027,
6,
7019,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2604,
21,
8,
467,
1944,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
21680,
953,
834,
4350,
834,
2688,
549,
17444,
427,
234,
3274,
96,
75,
4563,
232,
121,
3430,
7019,
3274,
96,
32,
7721,
32,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Give me a bar chart for the total number of each class, and order x axis in asc order. | CREATE TABLE race (
Race_ID int,
Name text,
Class text,
Date text,
Track_ID text
)
CREATE TABLE track (
Track_ID int,
Name text,
Location text,
Seating real,
Year_Opened real
) | SELECT Class, COUNT(*) FROM race GROUP BY Class ORDER BY Class | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1964,
41,
10949,
834,
4309,
16,
17,
6,
5570,
1499,
6,
4501,
1499,
6,
7678,
1499,
6,
8799,
834,
4309,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
1463,
41,
8799,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4501,
6,
2847,
17161,
599,
1935,
61,
21680,
1964,
350,
4630,
6880,
272,
476,
4501,
4674,
11300,
272,
476,
4501,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many significant relationships list Will as a virtue? | CREATE TABLE table_64 (
"Approximate Age" text,
"Virtues" text,
"Psycho Social Crisis" text,
"Significant Relationship" text,
"Existential Question [ not in citation given ]" text,
"Examples" text
) | SELECT COUNT("Significant Relationship") FROM table_64 WHERE "Virtues" = 'Will' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
41,
96,
9648,
12907,
23,
5058,
7526,
121,
1499,
6,
96,
21031,
17,
76,
15,
7,
121,
1499,
6,
96,
21513,
32,
2730,
29668,
121,
1499,
6,
96,
134,
3191,
3286,
288,
28898... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
134,
3191,
3286,
288,
28898,
2009,
8512,
21680,
953,
834,
4389,
549,
17444,
427,
96,
21031,
17,
76,
15,
7,
121,
3274,
3,
31,
518,
1092,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
When was the episode with a 1,036,000 BARB rating first aired in Denmark? | CREATE TABLE table_26591309_3 (
first_broadcast_denmark___dr1__ VARCHAR,
official_barb_ratings VARCHAR
) | SELECT first_broadcast_denmark___dr1__ FROM table_26591309_3 WHERE official_barb_ratings = "1,036,000" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
3390,
2368,
4198,
834,
519,
41,
166,
834,
115,
8635,
5254,
834,
537,
3920,
834,
834,
834,
26,
52,
536,
834,
834,
584,
4280,
28027,
6,
2314,
834,
1047,
115,
834,
52,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
166,
834,
115,
8635,
5254,
834,
537,
3920,
834,
834,
834,
26,
52,
536,
834,
834,
21680,
953,
834,
2688,
3390,
2368,
4198,
834,
519,
549,
17444,
427,
2314,
834,
1047,
115,
834,
52,
1014,
7,
3274,
96,
4347,
4928,
14... |
If the number of floors is 70, what is the height? | CREATE TABLE table_27067379_1 (
height VARCHAR,
number_of_floors VARCHAR
) | SELECT height FROM table_27067379_1 WHERE number_of_floors = 70 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
17485,
3708,
519,
4440,
834,
536,
41,
3902,
584,
4280,
28027,
6,
381,
834,
858,
834,
20924,
7,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
156,
8,
381,
13,
8242... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3902,
21680,
953,
834,
17485,
3708,
519,
4440,
834,
536,
549,
17444,
427,
381,
834,
858,
834,
20924,
7,
3274,
2861,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Which character was in the sexiest female category of the British Soap Awards? | CREATE TABLE table_57410 (
"Year" real,
"Result" text,
"Award" text,
"Category" text,
"Film or series" text,
"Character" text
) | SELECT "Character" FROM table_57410 WHERE "Category" = 'sexiest female' AND "Award" = 'british soap awards' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3436,
24175,
41,
96,
476,
2741,
121,
490,
6,
96,
20119,
121,
1499,
6,
96,
188,
2239,
121,
1499,
6,
96,
18610,
6066,
651,
121,
1499,
6,
96,
371,
173,
51,
42,
939,
121,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
18947,
2708,
49,
121,
21680,
953,
834,
3436,
24175,
549,
17444,
427,
96,
18610,
6066,
651,
121,
3274,
3,
31,
7,
994,
23,
222,
3955,
31,
3430,
96,
188,
2239,
121,
3274,
3,
31,
2160,
17,
1273,
10758,
6120,
31,
... |
What is the total height of the peak with a prominence of 12,867 ft and a prominence in m greater than 3,922? | CREATE TABLE table_44210 (
"Name of peak" text,
"Height (m)" real,
"Height (ft)" real,
"Prominence (m)" real,
"Prominence (ft)" real,
"Nearest Higher Neighbor" text
) | SELECT COUNT("Height (m)") FROM table_44210 WHERE "Prominence (ft)" = '12,867' AND "Prominence (m)" > '3,922' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3628,
15239,
41,
96,
23954,
13,
6734,
121,
1499,
6,
96,
3845,
2632,
41,
51,
61,
121,
490,
6,
96,
3845,
2632,
41,
89,
17,
61,
121,
490,
6,
96,
3174,
1109,
1433,
41,
51,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
3845,
2632,
41,
51,
61,
8512,
21680,
953,
834,
3628,
15239,
549,
17444,
427,
96,
3174,
1109,
1433,
41,
89,
17,
61,
121,
3274,
3,
31,
2122,
6,
927,
3708,
31,
3430,
96,
3174,
1109,
1433,
41,
... |
What is the Martin mcGuinness with a Sean Gallagher that is 29.6%? | CREATE TABLE table_name_3 (
martin_mcguinness VARCHAR,
seán_gallagher VARCHAR
) | SELECT martin_mcguinness FROM table_name_3 WHERE seán_gallagher = "29.6%" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
519,
41,
3157,
17,
77,
834,
51,
75,
17996,
655,
584,
4280,
28027,
6,
142,
12916,
834,
6191,
5430,
760,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
36... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3157,
17,
77,
834,
51,
75,
17996,
655,
21680,
953,
834,
4350,
834,
519,
549,
17444,
427,
142,
12916,
834,
6191,
5430,
760,
3274,
96,
3166,
5,
6370,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is Scorers, when Attendance is greater than 11,091, and when Round is R3? | CREATE TABLE table_45600 (
"Date" text,
"Round" text,
"Opponent" text,
"Venue" text,
"Result" text,
"Attendance" real,
"Scorers" text
) | SELECT "Scorers" FROM table_45600 WHERE "Attendance" > '11,091' AND "Round" = 'r3' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2128,
6007,
41,
96,
308,
342,
121,
1499,
6,
96,
448,
32,
1106,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
553,
35,
76,
15,
121,
1499,
6,
96,
20119,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
134,
5715,
277,
121,
21680,
953,
834,
2128,
6007,
549,
17444,
427,
96,
188,
17,
324,
26,
663,
121,
2490,
3,
31,
2596,
6,
4198,
536,
31,
3430,
96,
448,
32,
1106,
121,
3274,
3,
31,
52,
519,
31,
1,
-100,
-100... |
What is the Class for the ERP W of more than 2 and the call sign of w223au? | CREATE TABLE table_37356 (
"Call sign" text,
"Frequency MHz" real,
"City of license" text,
"ERP W" real,
"Class" text,
"FCC info" text
) | SELECT "Class" FROM table_37356 WHERE "ERP W" > '2' AND "Call sign" = 'w223au' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4118,
2469,
948,
41,
96,
254,
1748,
1320,
121,
1499,
6,
96,
371,
60,
835,
11298,
3,
20210,
121,
490,
6,
96,
254,
485,
13,
3344,
121,
1499,
6,
96,
3316,
345,
549,
121,
4... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
21486,
121,
21680,
953,
834,
4118,
2469,
948,
549,
17444,
427,
96,
3316,
345,
549,
121,
2490,
3,
31,
357,
31,
3430,
96,
254,
1748,
1320,
121,
3274,
3,
31,
210,
357,
2773,
402,
31,
1,
-100,
-100,
-100,
-100,
... |
What is the highest Draws with less than 18 losses for north melbourne later than 1926? | CREATE TABLE table_name_45 (
draws INTEGER,
season VARCHAR,
losses VARCHAR,
team VARCHAR
) | SELECT MAX(draws) FROM table_name_45 WHERE losses < 18 AND team = "north melbourne" AND season > 1926 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2128,
41,
14924,
3,
21342,
17966,
6,
774,
584,
4280,
28027,
6,
8467,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
19489,
7,
61,
21680,
953,
834,
4350,
834,
2128,
549,
17444,
427,
8467,
3,
2,
507,
3430,
372,
3274,
96,
29,
127,
189,
3,
2341,
26255,
121,
3430,
774,
2490,
957,
2688,
1,
-100,
-100,
-100,
-100,
-100,
... |
Who was the leading scorer on November 2, 2007? | CREATE TABLE table_name_62 (leading_scorer VARCHAR, date VARCHAR) | SELECT leading_scorer FROM table_name_62 WHERE date = "november 2, 2007" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4056,
41,
17103,
834,
7,
5715,
49,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
8,
1374,
2604,
52,
30,
1671,
3547,
41... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1374,
834,
7,
5715,
49,
21680,
953,
834,
4350,
834,
4056,
549,
17444,
427,
833,
3274,
96,
5326,
18247,
3547,
4101,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
who was the opponent after hatsu kioki ? | CREATE TABLE table_203_844 (
id number,
"res." text,
"record" text,
"opponent" text,
"method" text,
"event" text,
"date" text,
"round" number,
"time" text,
"location" text,
"notes" text
) | SELECT "opponent" FROM table_203_844 WHERE "date" > (SELECT "date" FROM table_203_844 WHERE "opponent" = 'hatsu hioki') ORDER BY "date" LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
4608,
591,
41,
3,
23,
26,
381,
6,
96,
60,
7,
535,
1499,
6,
96,
60,
7621,
121,
1499,
6,
96,
32,
102,
9977,
121,
1499,
6,
96,
23152,
121,
1499,
6,
96,
15,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
32,
102,
9977,
121,
21680,
953,
834,
23330,
834,
4608,
591,
549,
17444,
427,
96,
5522,
121,
2490,
41,
23143,
14196,
96,
5522,
121,
21680,
953,
834,
23330,
834,
4608,
591,
549,
17444,
427,
96,
32,
102,
9977,
121,... |
Where did Richmond play as the away team? | CREATE TABLE table_name_57 (
venue VARCHAR,
away_team VARCHAR
) | SELECT venue FROM table_name_57 WHERE away_team = "richmond" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3436,
41,
5669,
584,
4280,
28027,
6,
550,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2840,
410,
17247,
577,
38,
8,
550,
372,
58,
1,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
5669,
21680,
953,
834,
4350,
834,
3436,
549,
17444,
427,
550,
834,
11650,
3274,
96,
3723,
6764,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what are the methods of consumption of carvedilol 3.125 mg tab? | CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
) | SELECT DISTINCT medication.routeadmin FROM medication WHERE medication.drugname = 'carvedilol 3.125 mg tab' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1058,
41,
1058,
23,
26,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
1058,
4350,
1499,
6,
1058,
715,
97,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
7757,
41,
7757,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
15438,
25424,
6227,
7757,
5,
20300,
20466,
29,
21680,
7757,
549,
17444,
427,
7757,
5,
26,
13534,
4350,
3274,
3,
31,
19619,
173,
32,
40,
1877,
10124,
5453,
3808,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Name what was completed on 12 april 1934 | CREATE TABLE table_name_28 (completed VARCHAR, launched VARCHAR) | SELECT completed FROM table_name_28 WHERE launched = "12 april 1934" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2577,
41,
25288,
26,
584,
4280,
28027,
6,
3759,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
125,
47,
2012,
30,
586,
3,
9,
2246,
40,
28828,
1,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2012,
21680,
953,
834,
4350,
834,
2577,
549,
17444,
427,
3759,
3274,
96,
2122,
3,
9,
2246,
40,
28828,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the total of Golds with more bronzes than 1 and totaled larger than 4? | CREATE TABLE table_name_64 (
gold VARCHAR,
bronze VARCHAR,
total VARCHAR
) | SELECT COUNT(gold) FROM table_name_64 WHERE bronze > 1 AND total > 4 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4389,
41,
2045,
584,
4280,
28027,
6,
13467,
584,
4280,
28027,
6,
792,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
792,
13,
2540,
7,
28,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
14910,
61,
21680,
953,
834,
4350,
834,
4389,
549,
17444,
427,
13467,
2490,
209,
3430,
792,
2490,
314,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many people were in Mt Morgan earlier than 1933 when the Total Region had 44,501? | CREATE TABLE table_69208 (
"Year" real,
"Total Region" real,
"Rockhampton" real,
"Livingstone" real,
"Fitzroy" real,
"Mt Morgan" real
) | SELECT COUNT("Mt Morgan") FROM table_69208 WHERE "Total Region" = '44,501' AND "Year" < '1933' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3951,
23946,
41,
96,
476,
2741,
121,
490,
6,
96,
3696,
1947,
6163,
121,
490,
6,
96,
23349,
1483,
11632,
121,
490,
6,
96,
434,
23,
3745,
3009,
121,
490,
6,
96,
371,
5615,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
329,
17,
11147,
8512,
21680,
953,
834,
3951,
23946,
549,
17444,
427,
96,
3696,
1947,
6163,
121,
3274,
3,
31,
3628,
6,
20176,
31,
3430,
96,
476,
2741,
121,
3,
2,
3,
31,
2294,
4201,
31,
1,
-... |
Find the name of the customer that has been involved in the most policies. | CREATE TABLE customers (
customer_details VARCHAR,
customer_id VARCHAR
)
CREATE TABLE policies (
customer_id VARCHAR
) | SELECT t2.customer_details FROM policies AS t1 JOIN customers AS t2 ON t1.customer_id = t2.customer_id GROUP BY t2.customer_details ORDER BY COUNT(*) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
722,
41,
884,
834,
221,
5756,
7,
584,
4280,
28027,
6,
884,
834,
23,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
3101,
41,
884,
834,
23,
26,
58... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17,
4416,
25697,
49,
834,
221,
5756,
7,
21680,
3101,
6157,
3,
17,
536,
3,
15355,
3162,
722,
6157,
3,
17,
357,
9191,
3,
17,
5411,
25697,
49,
834,
23,
26,
3274,
3,
17,
4416,
25697,
49,
834,
23,
26,
350,
4630,... |
Which Date performed has a Main contestant of karanvir bohra? | CREATE TABLE table_name_58 (date_performed VARCHAR, main_contestant VARCHAR) | SELECT date_performed FROM table_name_58 WHERE main_contestant = "karanvir bohra" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3449,
41,
5522,
834,
883,
10816,
584,
4280,
28027,
6,
711,
834,
1018,
4377,
288,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
7678,
3032,
65,
3,
9,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
833,
834,
883,
10816,
21680,
953,
834,
4350,
834,
3449,
549,
17444,
427,
711,
834,
1018,
4377,
288,
3274,
96,
4031,
152,
5771,
3005,
107,
52,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Tell me the report for circuit of modena | CREATE TABLE table_name_25 (
report VARCHAR,
circuit VARCHAR
) | SELECT report FROM table_name_25 WHERE circuit = "modena" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1828,
41,
934,
584,
4280,
28027,
6,
4558,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
8779,
140,
8,
934,
21,
4558,
13,
2175,
29,
9,
1,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
934,
21680,
953,
834,
4350,
834,
1828,
549,
17444,
427,
4558,
3274,
96,
7360,
35,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
How many games were held on March 12? | CREATE TABLE table_27715173_10 (
game VARCHAR,
date VARCHAR
) | SELECT COUNT(game) FROM table_27715173_10 WHERE date = "March 12" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
4013,
26578,
4552,
834,
1714,
41,
467,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
1031,
130,
1213,
30,
1332,
586,
58,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
7261,
61,
21680,
953,
834,
357,
4013,
26578,
4552,
834,
1714,
549,
17444,
427,
833,
3274,
96,
25019,
586,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the rank that has 1 bronze and 1 silver? | CREATE TABLE table_40904 (
"Rank" real,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT COUNT("Rank") FROM table_40904 WHERE "Bronze" = '1' AND "Silver" > '1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2445,
2394,
591,
41,
96,
22557,
121,
490,
6,
96,
567,
257,
121,
1499,
6,
96,
23576,
121,
490,
6,
96,
134,
173,
624,
121,
490,
6,
96,
22780,
29,
776,
121,
490,
6,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
22557,
8512,
21680,
953,
834,
2445,
2394,
591,
549,
17444,
427,
96,
22780,
29,
776,
121,
3274,
3,
31,
536,
31,
3430,
96,
134,
173,
624,
121,
2490,
3,
31,
536,
31,
1,
-100,
-100,
-100,
-100,
... |
What was the constructor for the fastest nelson piquet? | CREATE TABLE table_51680 (
"Race" text,
"Date" text,
"Location" text,
"Pole Position" text,
"Fastest Lap" text,
"Race Winner" text,
"Constructor" text,
"Report" text
) | SELECT "Constructor" FROM table_51680 WHERE "Fastest Lap" = 'nelson piquet' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
2938,
2079,
41,
96,
448,
3302,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
8931,
15,
14258,
121,
1499,
6,
96,
371,
9,
7,
43... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
4302,
7593,
127,
121,
21680,
953,
834,
755,
2938,
2079,
549,
17444,
427,
96,
371,
9,
7,
4377,
325,
102,
121,
3274,
3,
31,
29,
3573,
106,
3,
102,
1495,
17,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is 2001, when 1990 is A, when 1987 is NME, and when 1997 is 1R? | CREATE TABLE table_41091 (
"Tournament" text,
"1987" text,
"1988" text,
"1989" text,
"1990" text,
"1991" text,
"1992" text,
"1993" text,
"1994" text,
"1995" text,
"1996" text,
"1997" text,
"1998" text,
"1999" text,
"2000" text,
"2001" text,
"2002" text,
"2003" text,
"Career SR" text,
"Career Win-Loss" text
) | SELECT "2001" FROM table_41091 WHERE "1990" = 'a' AND "1987" = 'nme' AND "1997" = '1r' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24175,
4729,
41,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
2294,
4225,
121,
1499,
6,
96,
2294,
4060,
121,
1499,
6,
96,
2294,
3914,
121,
1499,
6,
96,
2294,
2394,
121,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
23658,
121,
21680,
953,
834,
24175,
4729,
549,
17444,
427,
96,
2294,
2394,
121,
3274,
3,
31,
9,
31,
3430,
96,
2294,
4225,
121,
3274,
3,
31,
29,
526,
31,
3430,
96,
2294,
4327,
121,
3274,
3,
31,
536,
52,
31,
... |
What is the total number of Silver with a Total that is smaller than 1? | CREATE TABLE table_75837 (
"Rank" real,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT COUNT("Silver") FROM table_75837 WHERE "Total" < '1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3072,
927,
4118,
41,
96,
22557,
121,
490,
6,
96,
567,
257,
121,
1499,
6,
96,
23576,
121,
490,
6,
96,
134,
173,
624,
121,
490,
6,
96,
22780,
29,
776,
121,
490,
6,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
134,
173,
624,
8512,
21680,
953,
834,
3072,
927,
4118,
549,
17444,
427,
96,
3696,
1947,
121,
3,
2,
3,
31,
536,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Chassis of the Honda Engine with a Motorola sponsor? | CREATE TABLE table_50547 (
"Team" text,
"Chassis" text,
"Engine" text,
"Tire" text,
"Sponsor" text
) | SELECT "Chassis" FROM table_50547 WHERE "Engine" = 'honda' AND "Sponsor" = 'motorola' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1752,
755,
4177,
41,
96,
18699,
121,
1499,
6,
96,
3541,
6500,
7,
121,
1499,
6,
96,
31477,
121,
1499,
6,
96,
382,
2060,
121,
1499,
6,
96,
134,
5041,
7,
127,
121,
1499,
3... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
3541,
6500,
7,
121,
21680,
953,
834,
1752,
755,
4177,
549,
17444,
427,
96,
31477,
121,
3274,
3,
31,
31782,
31,
3430,
96,
134,
5041,
7,
127,
121,
3274,
3,
31,
11188,
3491,
9,
31,
1,
-100,
-100,
-100,
-100,
-1... |
What was the result in a week lower than 10 with an opponent of Chicago Bears? | CREATE TABLE table_77304 (
"Week" real,
"Date" text,
"Opponent" text,
"Result" text,
"Attendance" real
) | SELECT "Result" FROM table_77304 WHERE "Week" < '10' AND "Opponent" = 'chicago bears' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4013,
23702,
41,
96,
518,
10266,
121,
490,
6,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
188,
17,
324,
26,
663,
121,
490... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
20119,
121,
21680,
953,
834,
4013,
23702,
549,
17444,
427,
96,
518,
10266,
121,
3,
2,
3,
31,
1714,
31,
3430,
96,
667,
102,
9977,
121,
3274,
3,
31,
1436,
658,
839,
4595,
7,
31,
1,
-100,
-100,
-100,
-100,
-100... |
what is the number of sites when the number of screens is 687 and rank is more than 7? | CREATE TABLE table_70060 (
"Rank" real,
"Circuit" text,
"Headquarters" text,
"Screens" real,
"Sites" real
) | SELECT AVG("Sites") FROM table_70060 WHERE "Screens" = '687' AND "Rank" > '7' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
9295,
3328,
41,
96,
22557,
121,
490,
6,
96,
254,
23,
52,
21560,
121,
1499,
6,
96,
3845,
9,
26,
19973,
7,
121,
1499,
6,
96,
134,
5045,
35,
7,
121,
490,
6,
96,
26030,
7... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
71,
17217,
599,
121,
26030,
7,
8512,
21680,
953,
834,
9295,
3328,
549,
17444,
427,
96,
134,
5045,
35,
7,
121,
3274,
3,
31,
3651,
940,
31,
3430,
96,
22557,
121,
2490,
3,
31,
940,
31,
1,
-100,
-100,
-100,
-100,
-1... |
Amal McCaskill who plays forward-center played for what school/club team? | CREATE TABLE table_name_55 (school_club_team VARCHAR, position VARCHAR, player VARCHAR) | SELECT school_club_team FROM table_name_55 WHERE position = "forward-center" AND player = "amal mccaskill" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3769,
41,
6646,
834,
13442,
834,
11650,
584,
4280,
28027,
6,
1102,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
736,
138,
7040,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
496,
834,
13442,
834,
11650,
21680,
953,
834,
4350,
834,
3769,
549,
17444,
427,
1102,
3274,
96,
26338,
18,
13866,
121,
3430,
1959,
3274,
96,
9,
1982,
3,
51,
12464,
7,
10824,
121,
1,
-100,
-100,
-100,
-100,
-100,
-10... |
Who had the high assists on october 6? | CREATE TABLE table_27756474_2 (
high_assists VARCHAR,
date VARCHAR
) | SELECT high_assists FROM table_27756474_2 WHERE date = "October 6" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
3072,
4389,
4581,
834,
357,
41,
306,
834,
6500,
7,
17,
7,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
141,
8,
306,
13041,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
306,
834,
6500,
7,
17,
7,
21680,
953,
834,
2555,
3072,
4389,
4581,
834,
357,
549,
17444,
427,
833,
3274,
96,
28680,
431,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is every value for Under-17 if Under-15 is Maria Elena Ubina? | CREATE TABLE table_26368963_2 (
under_17 VARCHAR,
under_15 VARCHAR
) | SELECT under_17 FROM table_26368963_2 WHERE under_15 = "Maria Elena Ubina" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
3420,
3914,
3891,
834,
357,
41,
365,
834,
2517,
584,
4280,
28027,
6,
365,
834,
1808,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
334,
701,
21,
35... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
365,
834,
2517,
21680,
953,
834,
2688,
3420,
3914,
3891,
834,
357,
549,
17444,
427,
365,
834,
1808,
3274,
96,
329,
6286,
22539,
412,
4517,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the admission time of the Paul Edwards? | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT demographic.admittime FROM demographic WHERE demographic.name = "Paul Edwards" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
14798,
5,
20466,
17,
715,
21680,
14798,
549,
17444,
427,
14798,
5,
4350,
3274,
96,
23183,
8200,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many times was Mike McIntyre elected? | CREATE TABLE table_1805191_34 (results VARCHAR, incumbent VARCHAR) | SELECT COUNT(results) FROM table_1805191_34 WHERE incumbent = "Mike McIntyre" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
20829,
5553,
4729,
834,
3710,
41,
60,
7,
83,
17,
7,
584,
4280,
28027,
6,
28406,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
648,
47,
4794,
3038,
1570,
17... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
60,
7,
83,
17,
7,
61,
21680,
953,
834,
20829,
5553,
4729,
834,
3710,
549,
17444,
427,
28406,
3274,
96,
329,
5208,
3038,
1570,
17,
63,
60,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Song of the Year was 42 on the UK charts prior to 1994? | CREATE TABLE table_65324 (
"Year" real,
"Artist" text,
"Song" text,
"UK Chart" text,
"At Eurovision" text
) | SELECT "Song" FROM table_65324 WHERE "Year" < '1994' AND "UK Chart" = '42' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4122,
519,
2266,
41,
96,
476,
2741,
121,
490,
6,
96,
7754,
343,
121,
1499,
6,
96,
134,
2444,
121,
1499,
6,
96,
15787,
15054,
121,
1499,
6,
96,
188,
17,
2430,
6610,
121,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
134,
2444,
121,
21680,
953,
834,
4122,
519,
2266,
549,
17444,
427,
96,
476,
2741,
121,
3,
2,
3,
31,
2294,
4240,
31,
3430,
96,
15787,
15054,
121,
3274,
3,
31,
4165,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the Seahawks record on September 18, 1983? | CREATE TABLE table_13258876_2 (
record VARCHAR,
date VARCHAR
) | SELECT record FROM table_13258876_2 WHERE date = "September 18, 1983" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2368,
1828,
4060,
3959,
834,
357,
41,
1368,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
3319,
14400,
7,
1368,
30,
1600,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1368,
21680,
953,
834,
2368,
1828,
4060,
3959,
834,
357,
549,
17444,
427,
833,
3274,
96,
27652,
14985,
15041,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
what is the date of birth and language of subject id 2560? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT demographic.dob, demographic.language FROM demographic WHERE demographic.subject_id = "2560" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
18730,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
14798,
5,
26,
32,
115,
6,
14798,
5,
24925,
21680,
14798,
549,
17444,
427,
14798,
5,
7304,
11827,
834,
23,
26,
3274,
96,
1828,
3328,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the least amount of yards when the average is less than 2.6? | CREATE TABLE table_36800 (
"Player" text,
"Attempts" real,
"Yards" real,
"Average" real,
"Long" real,
"Touchdowns" real
) | SELECT MIN("Yards") FROM table_36800 WHERE "Average" < '2.6' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3420,
6192,
41,
96,
15800,
49,
121,
1499,
6,
96,
31108,
7,
121,
490,
6,
96,
476,
986,
7,
121,
490,
6,
96,
188,
624,
545,
121,
490,
6,
96,
434,
2444,
121,
490,
6,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
476,
986,
7,
8512,
21680,
953,
834,
3420,
6192,
549,
17444,
427,
96,
188,
624,
545,
121,
3,
2,
3,
31,
22724,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Who is the coach of the team from Port Pirie? | CREATE TABLE table_name_6 (coach VARCHAR, location VARCHAR) | SELECT coach FROM table_name_6 WHERE location = "port pirie" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
509,
1836,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
19,
8,
3763,
13,
8,
372,
45,
3625,
2745,
1753,
58,
1,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3763,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
1128,
3274,
96,
1493,
2816,
1753,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Calculate the number of patients admitted before 2145 who had dialys | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.admityear < "2145" AND prescriptions.route = "DIALYS" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
7744,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7744,
7,
5,
8399,
51,
834,
23,
26,
549... |
What format is at frequency 99.5 FM? | CREATE TABLE table_36861 (
"Frequency" text,
"Name" text,
"Format" text,
"Call Sign" text,
"Covered Location" text
) | SELECT "Format" FROM table_36861 WHERE "Frequency" = '99.5 fm' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3420,
3840,
536,
41,
96,
371,
60,
835,
11298,
121,
1499,
6,
96,
23954,
121,
1499,
6,
96,
3809,
3357,
121,
1499,
6,
96,
254,
1748,
6365,
121,
1499,
6,
96,
3881,
162,
1271,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
3809,
3357,
121,
21680,
953,
834,
3420,
3840,
536,
549,
17444,
427,
96,
371,
60,
835,
11298,
121,
3274,
3,
31,
1298,
22321,
3,
89,
51,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
How many losses does the club with 539 points for have? | CREATE TABLE table_1676073_13 (
lost VARCHAR,
points_for VARCHAR
) | SELECT lost FROM table_1676073_13 WHERE points_for = "539" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
28212,
4552,
834,
2368,
41,
1513,
584,
4280,
28027,
6,
979,
834,
1161,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
8467,
405,
8,
1886,
28,
305,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1513,
21680,
953,
834,
2938,
28212,
4552,
834,
2368,
549,
17444,
427,
979,
834,
1161,
3274,
96,
755,
3288,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the population density of Siglunes when the change was smaller than -8.1 percent? | CREATE TABLE table_68178 (
"Name" text,
"Population (2011)" real,
"Population (2006)" real,
"Change (%)" real,
"Area (km\u00b2)" real,
"Population density" real
) | SELECT COUNT("Population density") FROM table_68178 WHERE "Name" = 'siglunes' AND "Change (%)" < '-8.1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3651,
27640,
41,
96,
23954,
121,
1499,
6,
96,
27773,
7830,
25163,
121,
490,
6,
96,
27773,
7830,
28272,
121,
490,
6,
96,
3541,
3280,
41,
6210,
121,
490,
6,
96,
188,
864,
4... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
27773,
7830,
11048,
8512,
21680,
953,
834,
3651,
27640,
549,
17444,
427,
96,
23954,
121,
3274,
3,
31,
13658,
40,
444,
7,
31,
3430,
96,
3541,
3280,
41,
6210,
121,
3,
2,
3,
31,
18,
20677,
31,
... |
What Time has a Show Name of mornings with neil mitchell? | CREATE TABLE table_78992 (
"Time" text,
"Show Name" text,
"Local/Networked" text,
"Ad Freq" text,
"News Freq" text
) | SELECT "Time" FROM table_78992 WHERE "Show Name" = 'mornings with neil mitchell' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3940,
3264,
357,
41,
96,
13368,
121,
1499,
6,
96,
134,
4067,
5570,
121,
1499,
6,
96,
434,
32,
1489,
87,
9688,
1981,
15,
26,
121,
1499,
6,
96,
188,
26,
5532,
1824,
121,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
13368,
121,
21680,
953,
834,
3940,
3264,
357,
549,
17444,
427,
96,
134,
4067,
5570,
121,
3274,
3,
31,
2528,
29,
53,
7,
28,
3,
29,
15,
173,
181,
1033,
195,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Wha commodity type of apple has the highest pesticide residues to consume? | CREATE TABLE sampledata15 (
sample_pk number,
state text,
year text,
month text,
day text,
site text,
commod text,
source_id text,
variety text,
origin text,
country text,
disttype text,
commtype text,
claim text,
quantity number,
growst text,
packst text,
distst text
)
CREATE TABLE resultsdata15 (
sample_pk number,
commod text,
commtype text,
lab text,
pestcode text,
testclass text,
concen number,
lod number,
conunit text,
confmethod text,
confmethod2 text,
annotate text,
quantitate text,
mean text,
extract text,
determin text
) | SELECT commtype FROM resultsdata15 WHERE commod = "AP" GROUP BY commtype ORDER BY SUM(concen) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3106,
6757,
1808,
41,
3106,
834,
102,
157,
381,
6,
538,
1499,
6,
215,
1499,
6,
847,
1499,
6,
239,
1499,
6,
353,
1499,
6,
3,
287,
7360,
1499,
6,
1391,
834,
23,
26,
1499,
6,
1196,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
287,
51,
6137,
21680,
772,
6757,
1808,
549,
17444,
427,
3,
287,
7360,
3274,
96,
2965,
121,
350,
4630,
6880,
272,
476,
3,
287,
51,
6137,
4674,
11300,
272,
476,
180,
6122,
599,
11620,
29,
61,
309,
25067,
8729,
12... |
What is the highest percent of yes Alberta, which had less than 60.2 vote no, has? | CREATE TABLE table_11114 (
"Jurisdiction" text,
"Voted Yes" real,
"Percent Yes" real,
"Voted No" real,
"Percent No" real
) | SELECT MAX("Percent Yes") FROM table_11114 WHERE "Jurisdiction" = 'alberta' AND "Percent No" < '60.2' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
15866,
2534,
41,
96,
683,
459,
7,
12472,
121,
1499,
6,
96,
553,
32,
1054,
2163,
121,
490,
6,
96,
12988,
3728,
2163,
121,
490,
6,
96,
553,
32,
1054,
465,
121,
490,
6,
96... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
12988,
3728,
2163,
8512,
21680,
953,
834,
15866,
2534,
549,
17444,
427,
96,
683,
459,
7,
12472,
121,
3274,
3,
31,
138,
7041,
9,
31,
3430,
96,
12988,
3728,
465,
121,
3,
2,
3,
31,
948,
18189,
31... |
When was incumbent John Thomas Wilson first elected? | CREATE TABLE table_1434788_5 (
first_elected VARCHAR,
incumbent VARCHAR
) | SELECT first_elected FROM table_1434788_5 WHERE incumbent = "John Thomas Wilson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25133,
4177,
4060,
834,
755,
41,
166,
834,
19971,
584,
4280,
28027,
6,
28406,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
47,
28406,
1079,
3576,
9439,
166,
8... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
166,
834,
19971,
21680,
953,
834,
25133,
4177,
4060,
834,
755,
549,
17444,
427,
28406,
3274,
96,
18300,
3576,
9439,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the career for 2007 3r, and 1999 1r? | CREATE TABLE table_name_80 (
career VARCHAR
) | SELECT career FROM table_name_80 WHERE 2007 = "3r" AND 1999 = "1r" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2079,
41,
1415,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1415,
21,
4101,
220,
52,
6,
11,
5247,
209,
52,
58,
1,
0,
0,
0,
0,
0,
0,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1415,
21680,
953,
834,
4350,
834,
2079,
549,
17444,
427,
4101,
3274,
96,
519,
52,
121,
3430,
5247,
3274,
96,
536,
52,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What's the technology when there are no moving parts but yes to toxic materials? | CREATE TABLE table_44925 (
"Technology" text,
"Moving Parts" text,
"Room Temperature" text,
"Flammable" text,
"Toxic Materials" text,
"In production" text,
"Rare metals" text
) | SELECT "Technology" FROM table_44925 WHERE "Toxic Materials" = 'yes' AND "Moving Parts" = 'no' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3628,
28456,
41,
96,
9542,
29,
1863,
121,
1499,
6,
96,
329,
32,
3745,
2733,
7,
121,
1499,
6,
96,
22778,
51,
12579,
15,
121,
1499,
6,
96,
371,
521,
635,
179,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
9542,
29,
1863,
121,
21680,
953,
834,
3628,
28456,
549,
17444,
427,
96,
3696,
226,
447,
16158,
121,
3274,
3,
31,
10070,
31,
3430,
96,
329,
32,
3745,
2733,
7,
121,
3274,
3,
31,
29,
32,
31,
1,
-100,
-100,
-100... |
how many patients admitted before the year 2194 followed the religion called chritian scientist? | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.religion = "CHRISTIAN SCIENTIST" AND demographic.admityear < "2194" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7744,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
23,
1071,
21545,
834,
23,
26,
1499,
6,
2672,
834,
6137,
1499,
6,
2672,
1499,
6,
5403,
651,
834,
26,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
60,
2825,
23,
106,
3274,
96,
254,
11120,
13582,
21758,
180,
3597,
6431,
13582,
121,
3430,
14798,
5... |
Name the 2011 with 2010 of 1r and 2012 of sf | CREATE TABLE table_name_35 (
Id VARCHAR
) | SELECT 2011 FROM table_name_35 WHERE 2010 = "1r" AND 2012 = "sf" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2469,
41,
27,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
2722,
28,
2735,
13,
209,
52,
11,
1673,
13,
3,
7,
89,
1,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2722,
21680,
953,
834,
4350,
834,
2469,
549,
17444,
427,
2735,
3274,
96,
536,
52,
121,
3430,
1673,
3274,
96,
7,
89,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the day 3 when day 4 is fr.? | CREATE TABLE table_name_45 (
day_3 VARCHAR,
day_4 VARCHAR
) | SELECT day_3 FROM table_name_45 WHERE day_4 = "fr." | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2128,
41,
239,
834,
519,
584,
4280,
28027,
6,
239,
834,
591,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
239,
220,
116,
239,
314,
19,
2... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
239,
834,
519,
21680,
953,
834,
4350,
834,
2128,
549,
17444,
427,
239,
834,
591,
3274,
96,
89,
52,
535,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.