NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
What country had the runner abubaker kaki khamis in lane 5? | CREATE TABLE table_44638 (
"Heat" real,
"Lane" real,
"Name" text,
"Country" text,
"Mark" text
) | SELECT "Country" FROM table_44638 WHERE "Lane" = '5' AND "Name" = 'abubaker kaki khamis' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
4448,
3747,
41,
96,
3845,
144,
121,
490,
6,
96,
434,
152,
15,
121,
490,
6,
96,
23954,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
19762,
121,
1499,
3,
61,
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,
10628,
651,
121,
21680,
953,
834,
591,
4448,
3747,
549,
17444,
427,
96,
434,
152,
15,
121,
3274,
3,
31,
755,
31,
3430,
96,
23954,
121,
3274,
3,
31,
9,
3007,
19272,
49,
3,
157,
11259,
3,
157,
1483,
159,
31,
... |
has patient 006-80884 had any procedures undergone in 2105? | CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE vitalperiodic (
vitalp... | SELECT COUNT(*) > 0 FROM treatment WHERE treatment.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '006-80884')) AND STRFTIME('%y', treatment.treatmenttime) = '2105' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
50,
9824,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
7690,
4350,
1499,
6,
50,
1999,
7,
83,
17,
381,
6,
50,
1999,
7,
83,
17,
715,
97,
3,
61,
3,
32102,
32103,
32102,
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,
2847,
17161,
599,
1935,
61,
2490,
3,
632,
21680,
1058,
549,
17444,
427,
1058,
5,
10061,
15129,
21545,
23,
26,
3388,
41,
23143,
14196,
1868,
5,
10061,
15129,
21545,
23,
26,
21680,
1868,
549,
17444,
427,
1868,
5,
10061,... |
What was the away team's score when Collingwood was the home team? | CREATE TABLE table_51839 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT "Away team score" FROM table_51839 WHERE "Home team" = 'collingwood' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
2606,
3288,
41,
96,
19040,
372,
121,
1499,
6,
96,
19040,
372,
2604,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
188,
1343,
372,
2604,
121,
1499,
6,
96,
553,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
188,
1343,
372,
2604,
121,
21680,
953,
834,
755,
2606,
3288,
549,
17444,
427,
96,
19040,
372,
121,
3274,
3,
31,
3297,
697,
2037,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the MWEHL Team on Round 2, with player Nicolas Kerdiles? | CREATE TABLE table_name_49 (mwehl_team VARCHAR, round VARCHAR, player VARCHAR) | SELECT mwehl_team FROM table_name_49 WHERE round = "2" AND player = "nicolas kerdiles" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3647,
41,
51,
1123,
107,
40,
834,
11650,
584,
4280,
28027,
6,
1751,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
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,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
51,
1123,
107,
40,
834,
11650,
21680,
953,
834,
4350,
834,
3647,
549,
17444,
427,
1751,
3274,
96,
357,
121,
3430,
1959,
3274,
96,
29,
23,
12600,
7,
3,
2304,
26,
699,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-... |
What is the total best for Bruno junqueira | CREATE TABLE table_name_32 (
best INTEGER,
name VARCHAR
) | SELECT SUM(best) FROM table_name_32 WHERE name = "bruno junqueira" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
200,
3,
21342,
17966,
6,
564,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
792,
200,
21,
22425,
3,
6959,
2436,
15809,
1,
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,
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,
180,
6122,
599,
9606,
61,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
564,
3274,
96,
9052,
29,
32,
3,
6959,
2436,
15809,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Visualize a bar chart about the distribution of Date_of_Birth and Height , and could you rank names from low to high order please? | CREATE TABLE candidate (
Candidate_ID int,
People_ID int,
Poll_Source text,
Date text,
Support_rate real,
Consider_rate real,
Oppose_rate real,
Unsure_rate real
)
CREATE TABLE people (
People_ID int,
Sex text,
Name text,
Date_of_Birth text,
Height real,
Weight re... | SELECT Date_of_Birth, Height FROM people ORDER BY Date_of_Birth | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4775,
41,
25833,
17,
15,
834,
4309,
16,
17,
6,
2449,
834,
4309,
16,
17,
6,
14457,
834,
23799,
1499,
6,
7678,
1499,
6,
4224,
834,
2206,
490,
6,
9151,
834,
2206,
490,
6,
4495,
2748,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7678,
834,
858,
834,
279,
23,
52,
189,
6,
24231,
21680,
151,
4674,
11300,
272,
476,
7678,
834,
858,
834,
279,
23,
52,
189,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
what was the name of the only player with the position listed as s ? | CREATE TABLE table_203_291 (
id number,
"round" number,
"pick" number,
"player" text,
"position" text,
"school/club team" text
) | SELECT "player" FROM table_203_291 WHERE "position" = 's' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
357,
4729,
41,
3,
23,
26,
381,
6,
96,
7775,
121,
381,
6,
96,
17967,
121,
381,
6,
96,
20846,
121,
1499,
6,
96,
4718,
121,
1499,
6,
96,
6646,
87,
13442,
372,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
20846,
121,
21680,
953,
834,
23330,
834,
357,
4729,
549,
17444,
427,
96,
4718,
121,
3274,
3,
31,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Who is the artist with catalog number ZK 34354? | CREATE TABLE table_61433 (
"Artist" text,
"Album" text,
"Country" text,
"Year" real,
"Catalog #" text,
"Format" text
) | SELECT "Artist" FROM table_61433 WHERE "Catalog #" = 'zk 34354' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
948,
2534,
4201,
41,
96,
7754,
343,
121,
1499,
6,
96,
25691,
440,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
476,
2741,
121,
490,
6,
96,
18610,
9,
2152,
1713,
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,
7754,
343,
121,
21680,
953,
834,
948,
2534,
4201,
549,
17444,
427,
96,
18610,
9,
2152,
1713,
121,
3274,
3,
31,
172,
157,
220,
4906,
5062,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
count the number of patients whose diagnoses short title is crbl art ocl nos w infrc and drug route is oral? | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE diagnoses.short_title = "Crbl art ocl NOS w infrc" AND prescriptions.route = "ORAL" | [
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,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
3... |
What was the reward when immunity went to martin and finish is 13th voted out 8th jury member day 46? | CREATE TABLE table_27265 (
"Air date" text,
"Reward" text,
"Immunity" text,
"Eliminated" text,
"Vote" text,
"Finish" text
) | SELECT "Reward" FROM table_27265 WHERE "Immunity" = 'Martin' AND "Finish" = '13th Voted Out 8th Jury Member Day 46' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
357,
4122,
41,
96,
20162,
833,
121,
1499,
6,
96,
1649,
2239,
121,
1499,
6,
96,
196,
635,
202,
485,
121,
1499,
6,
96,
427,
4941,
77,
920,
121,
1499,
6,
96,
553,
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,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
1649,
2239,
121,
21680,
953,
834,
2555,
357,
4122,
549,
17444,
427,
96,
196,
635,
202,
485,
121,
3274,
3,
31,
29838,
31,
3430,
96,
371,
77,
1273,
121,
3274,
3,
31,
2368,
189,
3152,
1054,
3387,
505,
189,
15598,... |
Which Date has a Set 3 of 21 25? | CREATE TABLE table_37918 (
"Date" text,
"Score" text,
"Set 1" text,
"Set 2" text,
"Set 3" text,
"Total" text
) | SELECT "Date" FROM table_37918 WHERE "Set 3" = '21–25' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
4440,
2606,
41,
96,
308,
342,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
17175,
209,
121,
1499,
6,
96,
17175,
204,
121,
1499,
6,
96,
17175,
220,
121,
1499,
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,
308,
342,
121,
21680,
953,
834,
519,
4440,
2606,
549,
17444,
427,
96,
17175,
220,
121,
3274,
3,
31,
2658,
104,
1828,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Who was the home team that played in Victoria Park? | CREATE TABLE table_name_32 (home_team VARCHAR, venue VARCHAR) | SELECT home_team FROM table_name_32 WHERE venue = "victoria park" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
5515,
834,
11650,
584,
4280,
28027,
6,
5669,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
8,
234,
372,
24,
1944,
16,
7488,
1061,
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,
234,
834,
11650,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
5669,
3274,
96,
7287,
3600,
9,
2447,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
subjects with severe renal impairment ( creatinine clearance less than 30 ml / min ) | CREATE TABLE table_train_41 (
"id" int,
"pulmonary_embolization" bool,
"hiv_infection" bool,
"neutrophil_count" int,
"renal_disease" bool,
"liver_disease" bool,
"serum_creatinine" float,
"myocardial_infarction" bool,
"NOUSE" float
) | SELECT * FROM table_train_41 WHERE renal_disease = 1 OR serum_creatinine < 30 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
9719,
834,
4853,
41,
96,
23,
26,
121,
16,
17,
6,
96,
26836,
834,
15,
51,
4243,
1707,
121,
3,
12840,
40,
6,
96,
107,
23,
208,
834,
77,
17856,
121,
3,
12840,
40,
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,
1429,
21680,
953,
834,
9719,
834,
4853,
549,
17444,
427,
23328,
834,
26,
159,
14608,
3274,
209,
4674,
20725,
834,
5045,
144,
77,
630,
3,
2,
604,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
subject is a male or female between the ages of 50 and 80 with a body mass index ( bmi ) below 31 . female must be post _ menopausal at least 1 year or surgically sterilized. | CREATE TABLE table_train_84 (
"id" int,
"gender" string,
"mini_mental_state_examination_mmse" int,
"modified_hachinski_ischemia_scale" int,
"post_menopausal" bool,
"allergy_to_rifaximin" bool,
"surgically_sterilized" bool,
"body_mass_index_bmi" float,
"age" float,
"NOUSE" float
) | SELECT * FROM table_train_84 WHERE (gender = 'male' OR (gender = 'female' AND (post_menopausal >= 1 OR surgically_sterilized = 1))) AND (age >= 50 AND age <= 80) AND body_mass_index_bmi < 31 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
9719,
834,
4608,
41,
96,
23,
26,
121,
16,
17,
6,
96,
122,
3868,
121,
6108,
6,
96,
7619,
834,
13974,
834,
5540,
834,
994,
9,
14484,
834,
635,
7,
15,
121,
16,
17,
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,
1429,
21680,
953,
834,
9719,
834,
4608,
549,
17444,
427,
41,
122,
3868,
3274,
3,
31,
13513,
31,
4674,
41,
122,
3868,
3274,
3,
31,
89,
15,
13513,
31,
3430,
41,
5950,
834,
904,
32,
102,
2064,
138,
2490,
2423,
209,
... |
What number of patients who had procedure under icd9 code 4632 died in or before the year 2155? | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.dod_year <= "2155.0" AND procedures.icd9_code = "4632" | [
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,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
give me the list of patients with lab test item id 50824 who died in or before 2115. | 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,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.dod_year <= "2115.0" AND lab.itemid = "50824" | [
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,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
7690,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7690,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
What was the theme during the week # of top 24 (12 men) | CREATE TABLE table_name_73 (theme VARCHAR, week__number VARCHAR) | SELECT theme FROM table_name_73 WHERE week__number = "top 24 (12 men)" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4552,
41,
532,
526,
584,
4280,
28027,
6,
471,
834,
834,
5525,
1152,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
3800,
383,
8,
471,
1713,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3800,
21680,
953,
834,
4350,
834,
4552,
549,
17444,
427,
471,
834,
834,
5525,
1152,
3274,
96,
2916,
997,
16465,
1076,
61,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
is leonard messel or royalty larger in size ? | CREATE TABLE table_203_699 (
id number,
"name" text,
"parentage" text,
"size" text,
"flower colour" text,
"flower type" text
) | SELECT "name" FROM table_203_699 WHERE "name" IN ('leonard messel', 'royalty') ORDER BY "size" DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
948,
3264,
41,
3,
23,
26,
381,
6,
96,
4350,
121,
1499,
6,
96,
12352,
545,
121,
1499,
6,
96,
7991,
121,
1499,
6,
96,
14923,
3243,
121,
1499,
6,
96,
14923,
68... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4350,
121,
21680,
953,
834,
23330,
834,
948,
3264,
549,
17444,
427,
96,
4350,
121,
3388,
41,
31,
109,
106,
986,
140,
9816,
31,
6,
3,
31,
8170,
2920,
63,
31,
61,
4674,
11300,
272,
476,
96,
7991,
121,
309,
250... |
find the female patients who have procedure icd9 code 3727. | 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,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.gender = "F" AND procedures.icd9_code = "3727" | [
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,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
What scores happened on February 11? | CREATE TABLE table_23486853_7 (score VARCHAR, date VARCHAR) | SELECT score FROM table_23486853_7 WHERE date = "February 11" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2773,
3707,
3651,
4867,
834,
940,
41,
7,
9022,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
7586,
2817,
30,
2083,
850,
58,
1,
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,
2604,
21680,
953,
834,
2773,
3707,
3651,
4867,
834,
940,
549,
17444,
427,
833,
3274,
96,
31122,
850,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Find all movies featuring both ' Matt Damon ' and ' Ben Affleck | CREATE TABLE genre (
gid int,
genre text
)
CREATE TABLE actor (
aid int,
gender text,
name text,
nationality text,
birth_city text,
birth_year int
)
CREATE TABLE writer (
wid int,
gender text,
name text,
nationality text,
birth_city text,
birth_year int
)
CREAT... | SELECT movie.title FROM actor AS ACTOR_0, actor AS ACTOR_1, cast AS CAST_0, cast AS CAST_1, movie WHERE ACTOR_0.name = 'Matt Damon' AND ACTOR_1.name = 'Ben Affleck' AND CAST_0.aid = ACTOR_0.aid AND CAST_1.aid = ACTOR_1.aid AND movie.mid = CAST_0.msid AND movie.mid = CAST_1.msid | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
5349,
41,
3,
122,
23,
26,
16,
17,
6,
5349,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
7556,
41,
3052,
16,
17,
6,
7285,
1499,
6,
564,
1499,
6,
1157,
485,
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,
1974,
5,
21869,
21680,
7556,
6157,
5686,
16442,
834,
632,
6,
7556,
6157,
5686,
16442,
834,
4347,
4061,
6157,
205,
12510,
834,
632,
6,
4061,
6157,
205,
12510,
834,
4347,
1974,
549,
17444,
427,
5686,
16442,
834,
632,
5,... |
What is the average Bronze, when Silver is 0, when Rank is 19, and when Total is greater than 2? | CREATE TABLE table_50303 (
"Rank" text,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT AVG("Bronze") FROM table_50303 WHERE "Silver" = '0' AND "Rank" = '19' AND "Total" > '2' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1752,
23335,
41,
96,
22557,
121,
1499,
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,
3696,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
22780,
29,
776,
8512,
21680,
953,
834,
1752,
23335,
549,
17444,
427,
96,
134,
173,
624,
121,
3274,
3,
31,
632,
31,
3430,
96,
22557,
121,
3274,
3,
31,
2294,
31,
3430,
96,
3696,
1947,
121,
2490,... |
Which 1st Member has an Election of 1895? | CREATE TABLE table_12842 (
"Election" text,
"1st Member" text,
"1st Party" text,
"2nd Member" text,
"2nd Party" text
) | SELECT "1st Member" FROM table_12842 WHERE "Election" = '1895' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
4608,
357,
41,
96,
427,
12252,
121,
1499,
6,
96,
536,
7,
17,
8541,
121,
1499,
6,
96,
536,
7,
17,
3450,
121,
1499,
6,
96,
357,
727,
8541,
121,
1499,
6,
96,
357,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
8541,
121,
21680,
953,
834,
2122,
4608,
357,
549,
17444,
427,
96,
427,
12252,
121,
3274,
3,
31,
2606,
3301,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which Top-25 has a Top-5 larger than 9, and Wins smaller than 11? | CREATE TABLE table_35980 (
"Tournament" text,
"Wins" real,
"Top-5" real,
"Top-10" real,
"Top-25" real,
"Events" real,
"Cuts made" real
) | SELECT SUM("Top-25") FROM table_35980 WHERE "Top-5" > '9' AND "Wins" < '11' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
3390,
2079,
41,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
18455,
7,
121,
490,
6,
96,
22481,
18,
17395,
490,
6,
96,
22481,
4536,
121,
490,
6,
96,
22481,
14855,
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,
180,
6122,
599,
121,
22481,
14855,
8512,
21680,
953,
834,
519,
3390,
2079,
549,
17444,
427,
96,
22481,
18,
17395,
2490,
3,
31,
1298,
31,
3430,
96,
18455,
7,
121,
3,
2,
3,
31,
2596,
31,
1,
-100,
-100,
-100,
-100,
... |
how many patients on nu route of drug administration have diagnoses icd9 code e9429? | 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,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE diagnoses.icd9_code = "E9429" AND prescriptions.route = "NU" | [
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,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
3... |
What is the attendance in week 15? | CREATE TABLE table_11109 (
"Week" text,
"Date" text,
"Opponent" text,
"Result" text,
"Kickoff [a ]" text,
"Game site" text,
"Attendance" text,
"Record" text
) | SELECT "Attendance" FROM table_11109 WHERE "Week" = '15' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2596,
17304,
41,
96,
518,
10266,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
439,
3142,
1647,
784,
9,
3,
90... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
188,
17,
324,
26,
663,
121,
21680,
953,
834,
2596,
17304,
549,
17444,
427,
96,
518,
10266,
121,
3274,
3,
31,
1808,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the title of the show with director Paul Annett? | CREATE TABLE table_2582519_6 (
title VARCHAR,
director VARCHAR
) | SELECT title FROM table_2582519_6 WHERE director = "Paul Annett" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3449,
1828,
2294,
834,
948,
41,
2233,
584,
4280,
28027,
6,
2090,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2233,
13,
8,
504,
28,
2090,
1838,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2233,
21680,
953,
834,
357,
3449,
1828,
2294,
834,
948,
549,
17444,
427,
2090,
3274,
96,
23183,
389,
10544,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the number of naming for anomic aphasia | CREATE TABLE table_2088_1 (naming VARCHAR, type_of_aphasia VARCHAR) | SELECT COUNT(naming) FROM table_2088_1 WHERE type_of_aphasia = "Anomic aphasia" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1755,
4060,
834,
536,
41,
21990,
584,
4280,
28027,
6,
686,
834,
858,
834,
9,
6977,
7,
23,
9,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
381,
13,
3,
219... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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... | [
3,
23143,
14196,
2847,
17161,
599,
21990,
61,
21680,
953,
834,
1755,
4060,
834,
536,
549,
17444,
427,
686,
834,
858,
834,
9,
6977,
7,
23,
9,
3274,
96,
188,
3114,
447,
3,
9,
6977,
7,
23,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
... |
what is the number of patients whose diagnoses icd9 code is v202 and lab test fluid is urine? | 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
)
C... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE diagnoses.icd9_code = "V202" AND lab.fluid = "Urine" | [
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,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
3... |
What Date after 2007 had the San Francisco 49ers as the Visiting Team? | CREATE TABLE table_name_17 (
date VARCHAR,
visiting_team VARCHAR,
year VARCHAR
) | SELECT date FROM table_name_17 WHERE visiting_team = "san francisco 49ers" AND year > 2007 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2517,
41,
833,
584,
4280,
28027,
6,
3644,
834,
11650,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
7678,
227,
4101,
141,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
833,
21680,
953,
834,
4350,
834,
2517,
549,
17444,
427,
3644,
834,
11650,
3274,
96,
7,
152,
2515,
11389,
3523,
9526,
277,
121,
3430,
215,
2490,
4101,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
how many times was the points 18? | CREATE TABLE table_name_69 (place VARCHAR, points VARCHAR) | SELECT COUNT(place) FROM table_name_69 WHERE points = 18 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3951,
41,
4687,
584,
4280,
28027,
6,
979,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
149,
186,
648,
47,
8,
979,
507,
58,
1,
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,
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... | [
3,
23143,
14196,
2847,
17161,
599,
4687,
61,
21680,
953,
834,
4350,
834,
3951,
549,
17444,
427,
979,
3274,
507,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What's the nationality of Henry Carr having a time of 20.3y? | CREATE TABLE table_name_82 (
nationality VARCHAR,
athlete VARCHAR,
time VARCHAR
) | SELECT nationality FROM table_name_82 WHERE athlete = "henry carr" AND time = "20.3y" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4613,
41,
1157,
485,
584,
4280,
28027,
6,
17893,
584,
4280,
28027,
6,
97,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
31,
7,
8,
1157,
485,
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,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1157,
485,
21680,
953,
834,
4350,
834,
4613,
549,
17444,
427,
17893,
3274,
96,
3225,
651,
443,
52,
121,
3430,
97,
3274,
96,
357,
19997,
63,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
In what round smaller than 10, was the center les studdard picked in? | CREATE TABLE table_name_97 (pick INTEGER, round VARCHAR, position VARCHAR, name VARCHAR) | SELECT MIN(pick) FROM table_name_97 WHERE position = "center" AND name = "les studdard" AND round < 10 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4327,
41,
17967,
3,
21342,
17966,
6,
1751,
584,
4280,
28027,
6,
1102,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
86,
125,
1751,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3,
17684,
599,
17967,
61,
21680,
953,
834,
4350,
834,
4327,
549,
17444,
427,
1102,
3274,
96,
13866,
121,
3430,
564,
3274,
96,
965,
3,
8637,
26,
986,
121,
3430,
1751,
3,
2,
335,
1,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the highest possible level? | CREATE TABLE table_1751142_2 (
level INTEGER
) | SELECT MAX(level) FROM table_1751142_2 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
5553,
24978,
834,
357,
41,
593,
3,
21342,
17966,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2030,
487,
593,
58,
1,
0,
0,
0,
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,
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,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
4563,
61,
21680,
953,
834,
2517,
5553,
24978,
834,
357,
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,
... |
What's Jorge Santana's elimination? | CREATE TABLE table_66541 (
"Elimination" text,
"Wrestler" text,
"Team" text,
"Eliminated by" text,
"Elimination move" text,
"Time" text
) | SELECT "Elimination" FROM table_66541 WHERE "Wrestler" = 'jorge santana' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3539,
5062,
536,
41,
96,
10991,
23,
14484,
121,
1499,
6,
96,
518,
6216,
1171,
121,
1499,
6,
96,
18699,
121,
1499,
6,
96,
427,
4941,
77,
920,
57,
121,
1499,
6,
96,
10991,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
10991,
23,
14484,
121,
21680,
953,
834,
3539,
5062,
536,
549,
17444,
427,
96,
518,
6216,
1171,
121,
3274,
3,
31,
12775,
397,
3,
7,
288,
152,
9,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the pick # for Dimelon Westfield? | CREATE TABLE table_31615 (
"Pick #" real,
"MLS team" text,
"Player" text,
"Position" text,
"Affiliation" text
) | SELECT MIN("Pick #") FROM table_31615 WHERE "Player" = 'dimelon westfield' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25946,
1808,
41,
96,
345,
3142,
1713,
121,
490,
6,
96,
17976,
372,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
188,
89,
8027,
23,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
345,
3142,
1713,
8512,
21680,
953,
834,
25946,
1808,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
26,
23,
2341,
106,
4653,
1846,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
tell me the number of patients who had delta abnormal lab test status and were born before 2097. | 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 procedures (
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.dob_year < "2097" AND lab.flag = "delta" | [
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,
7690,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7690,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
Create a bar chart showing how many class across class, and list from high to low by the x-axis please. | CREATE TABLE track (
Track_ID int,
Name text,
Location text,
Seating real,
Year_Opened real
)
CREATE TABLE race (
Race_ID int,
Name text,
Class text,
Date text,
Track_ID text
) | SELECT Class, COUNT(Class) FROM race GROUP BY Class ORDER BY Class DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1463,
41,
8799,
834,
4309,
16,
17,
6,
5570,
1499,
6,
10450,
1499,
6,
15915,
53,
490,
6,
2929,
834,
22696,
15,
26,
490,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
21486,
61,
21680,
1964,
350,
4630,
6880,
272,
476,
4501,
4674,
11300,
272,
476,
4501,
309,
25067,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the episode number for episode title Leave Takers? | CREATE TABLE table_3387 (
"Episode #" text,
"Original Air Date (UK)" text,
"Episode Title" text,
"Director" text,
"Writer" text,
"Cast" text
) | SELECT "Episode #" FROM table_3387 WHERE "Episode Title" = 'Leave Takers' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4201,
4225,
41,
96,
427,
102,
159,
32,
221,
1713,
121,
1499,
6,
96,
667,
3380,
10270,
1761,
7678,
41,
15787,
61,
121,
1499,
6,
96,
427,
102,
159,
32,
221,
11029,
121,
149... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
427,
102,
159,
32,
221,
1713,
121,
21680,
953,
834,
4201,
4225,
549,
17444,
427,
96,
427,
102,
159,
32,
221,
11029,
121,
3274,
3,
31,
2796,
9,
162,
2321,
52,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the series # when the director is john showalter? | CREATE TABLE table_29747178_2 (series__number VARCHAR, directed_by VARCHAR) | SELECT series__number FROM table_29747178_2 WHERE directed_by = "John Showalter" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
4581,
4450,
3940,
834,
357,
41,
10833,
7,
834,
834,
5525,
1152,
584,
4280,
28027,
6,
6640,
834,
969,
584,
4280,
28027,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
939,
834,
834,
5525,
1152,
21680,
953,
834,
3166,
4581,
4450,
3940,
834,
357,
549,
17444,
427,
6640,
834,
969,
3274,
96,
18300,
3111,
8818,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
For those employees who do not work in departments with managers that have ids between 100 and 200, find hire_date and the sum of department_id bin hire_date by weekday, and visualize them by a bar chart, and show y axis in ascending order. | 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(... | SELECT HIRE_DATE, SUM(DEPARTMENT_ID) FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY SUM(DEPARTMENT_ID) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1652,
41,
262,
5244,
5017,
476,
5080,
834,
4309,
7908,
1982,
599,
11071,
632,
201,
30085,
834,
567,
17683,
3,
4331,
4059,
599,
1755,
201,
301,
12510,
834,
567,
17683,
3,
4331,
4059,
59... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
180,
6122,
599,
5596,
19846,
11810,
834,
4309,
61,
21680,
1652,
549,
17444,
427,
4486,
3396,
19846,
11810,
834,
4309,
3388,
41,
23143,
14196,
3396,
19846,
11810,
834,
4309,
21680,
10521,
5... |
What was the first leg score in the 2nd round? | CREATE TABLE table_name_41 (first_leg VARCHAR, round VARCHAR) | SELECT first_leg FROM table_name_41 WHERE round = "2nd" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4853,
41,
14672,
834,
5772,
584,
4280,
28027,
6,
1751,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
166,
4553,
2604,
16,
8,
204,
727,
1751,
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,
166,
834,
5772,
21680,
953,
834,
4350,
834,
4853,
549,
17444,
427,
1751,
3274,
96,
357,
727,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
give me the number of patients whose primary disease is cerebral aneurysm/sda and admission year is less than 2200? | 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
)
C... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "CEREBRAL ANEURYSM/SDA" AND demographic.admityear < "2200" | [
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,
549,
17444,
427,
14798,
5,
25930,
4844,
159,
3274,
96,
4770,
4386,
279,
21415,
3,
5033,
26296,
476,
4212,
87,
134,
4296,
121,... |
What is Year, when Location is Philadelphia Municipal Stadium? | CREATE TABLE table_name_89 (
year VARCHAR,
location VARCHAR
) | SELECT year FROM table_name_89 WHERE location = "philadelphia municipal stadium" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3914,
41,
215,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
2929,
6,
116,
10450,
19,
9511,
16492,
12750,
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,
215,
21680,
953,
834,
4350,
834,
3914,
549,
17444,
427,
1128,
3274,
96,
18118,
15311,
11692,
9,
10516,
14939,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the Time of the Rowers from Finland with a Rank of less than 4? | CREATE TABLE table_name_28 (time VARCHAR, rank VARCHAR, country VARCHAR) | SELECT time FROM table_name_28 WHERE rank < 4 AND country = "finland" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2577,
41,
715,
584,
4280,
28027,
6,
11003,
584,
4280,
28027,
6,
684,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2900,
13,
8,
11768,
277,
45... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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... | [
3,
23143,
14196,
97,
21680,
953,
834,
4350,
834,
2577,
549,
17444,
427,
11003,
3,
2,
314,
3430,
684,
3274,
96,
89,
25948,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the record of the game on July 3? | CREATE TABLE table_name_44 (record VARCHAR, date VARCHAR) | SELECT record FROM table_name_44 WHERE date = "july 3" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3628,
41,
60,
7621,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1368,
13,
8,
467,
30,
1718,
220,
58,
1,
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,
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,
1368,
21680,
953,
834,
4350,
834,
3628,
549,
17444,
427,
833,
3274,
96,
2047,
120,
220,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
provide the number of patients whose primary disease is copd exacerbation? | 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,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "COPD EXACERBATION" | [
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,
549,
17444,
427,
14798,
5,
25930,
4844,
159,
3274,
96,
25032,
308,
262,
4,
11539,
12108,
8015,
121,
1,
-100,
-100,
-100,
-100... |
What was the venue for the game on 10-09-2012? | CREATE TABLE table_name_71 (
venue VARCHAR,
date VARCHAR
) | SELECT venue FROM table_name_71 WHERE date = "10-09-2012" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4450,
41,
5669,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
5669,
21,
8,
467,
30,
9445,
4198,
18,
12172,
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... | [
3,
23143,
14196,
5669,
21680,
953,
834,
4350,
834,
4450,
549,
17444,
427,
833,
3274,
96,
1714,
18,
4198,
18,
12172,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the Republican seat plurality of the state with a ratio of 12/4 Republicans to Democrats? | CREATE TABLE table_name_30 (republican_seat_plurality VARCHAR, republican__democratic VARCHAR) | SELECT republican_seat_plurality FROM table_name_30 WHERE republican__democratic = "12/4" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1458,
41,
60,
15727,
152,
834,
7,
1544,
834,
12456,
52,
10355,
584,
4280,
28027,
6,
20237,
152,
834,
834,
23319,
447,
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,
20237,
152,
834,
7,
1544,
834,
12456,
52,
10355,
21680,
953,
834,
4350,
834,
1458,
549,
17444,
427,
20237,
152,
834,
834,
23319,
447,
3274,
96,
2122,
13572,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Name the 2012 for 2011 being qf | CREATE TABLE table_70331 (
"Tournament" text,
"2008" text,
"2010" text,
"2011" text,
"2012" text,
"2013" text
) | SELECT "2012" FROM table_70331 WHERE "2011" = 'qf' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2518,
519,
3341,
41,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
16128,
121,
1499,
6,
96,
14926,
121,
1499,
6,
96,
13907,
121,
1499,
6,
96,
12172,
121,
1499,
6,
96,
11138... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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... | [
3,
23143,
14196,
96,
12172,
121,
21680,
953,
834,
2518,
519,
3341,
549,
17444,
427,
96,
13907,
121,
3274,
3,
31,
1824,
89,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
provide the number of patients whose admission type is urgent and item id is 50980? | 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 procedures (
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.admission_type = "URGENT" AND lab.itemid = "50980" | [
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,
7690,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7690,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
Which name has Years of 1 8, a Decile of 9, and a Roll smaller than 141? | CREATE TABLE table_name_20 (
name VARCHAR,
roll VARCHAR,
years VARCHAR,
decile VARCHAR
) | SELECT name FROM table_name_20 WHERE years = "1–8" AND decile = 9 AND roll < 141 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1755,
41,
564,
584,
4280,
28027,
6,
3812,
584,
4280,
28027,
6,
203,
584,
4280,
28027,
6,
7908,
109,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
564,
21680,
953,
834,
4350,
834,
1755,
549,
17444,
427,
203,
3274,
96,
536,
104,
927,
121,
3430,
7908,
109,
3274,
668,
3430,
3812,
3,
2,
3,
26059,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
what was phil lockyer 's party ? | CREATE TABLE table_203_407 (
id number,
"name" text,
"party" text,
"province" text,
"term expires" number,
"years in office" text
) | SELECT "party" FROM table_203_407 WHERE "name" = 'phil lockyer' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
2445,
940,
41,
3,
23,
26,
381,
6,
96,
4350,
121,
1499,
6,
96,
8071,
121,
1499,
6,
96,
1409,
2494,
565,
121,
1499,
6,
96,
1987,
8982,
15,
7,
121,
381,
6,
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,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
8071,
121,
21680,
953,
834,
23330,
834,
2445,
940,
549,
17444,
427,
96,
4350,
121,
3274,
3,
31,
18118,
6081,
7975,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the largest numbered? | CREATE TABLE table_14723382_1 (
division INTEGER
) | SELECT MAX(division) FROM table_14723382_1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24719,
20879,
4613,
834,
536,
41,
4889,
3,
21342,
17966,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2015,
3,
22412,
58,
1,
0,
0,
0,
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,
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,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
26,
23,
6610,
61,
21680,
953,
834,
24719,
20879,
4613,
834,
536,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What was the percentage of muslims during a time where there were 614 registered mosques? | CREATE TABLE table_1532779_1 (
muslim___percentage_of_total_population_ VARCHAR,
registered_mosques VARCHAR
) | SELECT muslim___percentage_of_total_population_ FROM table_1532779_1 WHERE registered_mosques = 614 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
27025,
2555,
4440,
834,
536,
41,
3,
3252,
4941,
834,
834,
834,
883,
3728,
545,
834,
858,
834,
235,
1947,
834,
9791,
7830,
834,
584,
4280,
28027,
6,
3366,
834,
3972,
7771,
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,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
3252,
4941,
834,
834,
834,
883,
3728,
545,
834,
858,
834,
235,
1947,
834,
9791,
7830,
834,
21680,
953,
834,
27025,
2555,
4440,
834,
536,
549,
17444,
427,
3366,
834,
3972,
7771,
3274,
431,
2534,
1,
-100,
-100,
-10... |
Which game took place on April 22? | CREATE TABLE table_name_8 (game VARCHAR, date VARCHAR) | SELECT game FROM table_name_8 WHERE date = "april 22" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
927,
41,
7261,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
467,
808,
286,
30,
1186,
1630,
58,
1,
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,
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... | [
3,
23143,
14196,
467,
21680,
953,
834,
4350,
834,
927,
549,
17444,
427,
833,
3274,
96,
9,
2246,
40,
1630,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees who do not work in departments with managers that have ids between 100 and 200, visualize a bar chart about the distribution of last_name and employee_id , show in asc by the y-axis please. | 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 regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
... | SELECT LAST_NAME, EMPLOYEE_ID FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY EMPLOYEE_ID | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
613,
834,
10193,
10972,
41,
262,
5244,
5017,
476,
5080,
834,
4309,
7908,
1982,
599,
11071,
632,
201,
5097,
8241,
834,
308,
6048,
833,
6,
3,
14920,
834,
308,
6048,
833,
6,
446,
10539,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
301,
12510,
834,
567,
17683,
6,
262,
5244,
5017,
476,
5080,
834,
4309,
21680,
1652,
549,
17444,
427,
4486,
3396,
19846,
11810,
834,
4309,
3388,
41,
23143,
14196,
3396,
19846,
11810,
834,
4309,
21680,
10521,
549,
17444,
... |
what is the nationality when the heat is less than 3 and the time is 2:35.31? | CREATE TABLE table_46299 (
"Rank" real,
"Heat" real,
"Name" text,
"Nationality" text,
"Time" text
) | SELECT "Nationality" FROM table_46299 WHERE "Heat" < '3' AND "Time" = '2:35.31' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4448,
357,
3264,
41,
96,
22557,
121,
490,
6,
96,
3845,
144,
121,
490,
6,
96,
23954,
121,
1499,
6,
96,
24732,
485,
121,
1499,
6,
96,
13368,
121,
1499,
3,
61,
3,
32102,
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,
24732,
485,
121,
21680,
953,
834,
4448,
357,
3264,
549,
17444,
427,
96,
3845,
144,
121,
3,
2,
3,
31,
519,
31,
3430,
96,
13368,
121,
3274,
3,
31,
357,
10,
2469,
5,
3341,
31,
1,
-100,
-100,
-100,
-100,
-100,
... |
Which First elected has a District of illinois 3? | CREATE TABLE table_name_52 (first_elected INTEGER, district VARCHAR) | SELECT MAX(first_elected) FROM table_name_52 WHERE district = "illinois 3" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5373,
41,
14672,
834,
19971,
3,
21342,
17966,
6,
3939,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
1485,
8160,
65,
3,
9,
3570,
13,
3,
1092,
77,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
14672,
834,
19971,
61,
21680,
953,
834,
4350,
834,
5373,
549,
17444,
427,
3939,
3274,
96,
1092,
77,
32,
159,
220,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
calculate the total number of patients diagnosed with dermatitis nos | 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,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE diagnoses.short_title = "Dermatitis NOS" | [
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,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
who produced the most tracks ? | CREATE TABLE table_203_228 (
id number,
"#" number,
"title" text,
"songwriters" text,
"producer(s)" text,
"performer (s)" text
) | SELECT "producer(s)" FROM table_203_228 GROUP BY "producer(s)" ORDER BY COUNT("title") DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
357,
2577,
41,
3,
23,
26,
381,
6,
96,
4663,
121,
381,
6,
96,
21869,
121,
1499,
6,
96,
21101,
7,
121,
1499,
6,
96,
1409,
4817,
49,
599,
7,
61,
121,
1499,
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,
1409,
4817,
49,
599,
7,
61,
121,
21680,
953,
834,
23330,
834,
357,
2577,
350,
4630,
6880,
272,
476,
96,
1409,
4817,
49,
599,
7,
61,
121,
4674,
11300,
272,
476,
2847,
17161,
599,
121,
21869,
8512,
309,
25067,
8... |
How much audience did the 7th Pride of Britain Awards ceremony have? | CREATE TABLE table_19043 (
"Episode" text,
"Original Air Date" text,
"Viewers (millions)" text,
"Presenter" text,
"Location" text
) | SELECT COUNT("Viewers (millions)") FROM table_19043 WHERE "Episode" = '7th Pride of Britain Awards' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
11776,
4906,
41,
96,
427,
102,
159,
32,
221,
121,
1499,
6,
96,
667,
3380,
10270,
1761,
7678,
121,
1499,
6,
96,
15270,
277,
41,
17030,
7,
61,
121,
1499,
6,
96,
10572,
5277... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
15270,
277,
41,
17030,
7,
61,
8512,
21680,
953,
834,
11776,
4906,
549,
17444,
427,
96,
427,
102,
159,
32,
221,
121,
3274,
3,
31,
940,
189,
24252,
13,
7190,
6580,
31,
1,
-100,
-100,
-100,
-10... |
Who is the writer for Red Rose Chain LTD? | CREATE TABLE table_69402 (
"Film" text,
"Director(s)" text,
"Producer(s)" text,
"Writer(s)" text,
"Recipient" text,
"Award" text
) | SELECT "Writer(s)" FROM table_69402 WHERE "Recipient" = 'red rose chain ltd' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3951,
2445,
357,
41,
96,
371,
173,
51,
121,
1499,
6,
96,
23620,
127,
599,
7,
61,
121,
1499,
6,
96,
3174,
4817,
49,
599,
7,
61,
121,
1499,
6,
96,
24965,
49,
599,
7,
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,
96,
24965,
49,
599,
7,
61,
121,
21680,
953,
834,
3951,
2445,
357,
549,
17444,
427,
96,
1649,
3389,
4741,
121,
3274,
3,
31,
1271,
4659,
3741,
3,
40,
17,
26,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the sum of Year, when Role is "himself", and when Notes is "celebrity guest alongside yg family"? | CREATE TABLE table_name_39 (year INTEGER, role VARCHAR, notes VARCHAR) | SELECT SUM(year) FROM table_name_39 WHERE role = "himself" AND notes = "celebrity guest alongside yg family" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3288,
41,
1201,
3,
21342,
17966,
6,
1075,
584,
4280,
28027,
6,
3358,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
4505,
13,
2929,
6,
116,
215... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
180,
6122,
599,
1201,
61,
21680,
953,
834,
4350,
834,
3288,
549,
17444,
427,
1075,
3274,
96,
10813,
7703,
121,
3430,
3358,
3274,
96,
75,
400,
2160,
17,
63,
3886,
5815,
3,
63,
122,
384,
121,
1,
-100,
-100,
-100,
-1... |
Which Time has a Set 3 of 24–26, and a Score of 0–3? | CREATE TABLE table_name_68 (time VARCHAR, set_3 VARCHAR, score VARCHAR) | SELECT time FROM table_name_68 WHERE set_3 = "24–26" AND score = "0–3" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
715,
584,
4280,
28027,
6,
356,
834,
519,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
2900,
65,
3,
9,
2821,
22... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
97,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
356,
834,
519,
3274,
96,
2266,
104,
2688,
121,
3430,
2604,
3274,
96,
632,
104,
519,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What was the manner of departure for notts county with an incoming manager of martin allen | CREATE TABLE table_29126 (
"Team" text,
"Outgoing manager" text,
"Manner of departure" text,
"Date of vacancy" text,
"Incoming manager" text,
"Date of appointment" text,
"Position in table" text
) | SELECT "Manner of departure" FROM table_29126 WHERE "Team" = 'Notts County' AND "Incoming manager" = 'Martin Allen' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
21976,
41,
96,
18699,
121,
1499,
6,
96,
15767,
9545,
2743,
121,
1499,
6,
96,
7296,
687,
13,
12028,
121,
1499,
6,
96,
308,
342,
13,
3,
29685,
121,
1499,
6,
96,
1570,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7296,
687,
13,
12028,
121,
21680,
953,
834,
3166,
21976,
549,
17444,
427,
96,
18699,
121,
3274,
3,
31,
10358,
17,
7,
1334,
31,
3430,
96,
1570,
10622,
2743,
121,
3274,
3,
31,
29838,
10618,
31,
1,
-100,
-100,
-1... |
Visualize a bar chart for what are the ids and names of the web accelerators that are compatible with two or more browsers?, and rank in ascending by the names. | CREATE TABLE Web_client_accelerator (
id int,
name text,
Operating_system text,
Client text,
Connection text
)
CREATE TABLE browser (
id int,
name text,
market_share real
)
CREATE TABLE accelerator_compatible_browser (
accelerator_id int,
browser_id int,
compatible_since_ye... | SELECT name, id FROM Web_client_accelerator AS T1 JOIN accelerator_compatible_browser AS T2 ON T2.accelerator_id = T1.id ORDER BY name | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1620,
834,
26693,
834,
6004,
15,
1171,
1016,
41,
3,
23,
26,
16,
17,
6,
564,
1499,
6,
21606,
834,
3734,
1499,
6,
6371,
1499,
6,
19466,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
564,
6,
3,
23,
26,
21680,
1620,
834,
26693,
834,
6004,
15,
1171,
1016,
6157,
332,
536,
3,
15355,
3162,
30202,
834,
25383,
834,
14853,
7,
49,
6157,
332,
357,
9191,
332,
4416,
6004,
15,
1171,
1016,
834,
23,
26,
3274... |
Who was the rider with a grid of 36? | CREATE TABLE table_41270 (
"Rider" text,
"Bike" text,
"Laps" real,
"Time" text,
"Grid" real
) | SELECT "Rider" FROM table_41270 WHERE "Grid" = '36' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4853,
17485,
41,
96,
448,
23,
588,
121,
1499,
6,
96,
279,
5208,
121,
1499,
6,
96,
3612,
102,
7,
121,
490,
6,
96,
13368,
121,
1499,
6,
96,
13313,
26,
121,
490,
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,
0... | [
3,
23143,
14196,
96,
448,
23,
588,
121,
21680,
953,
834,
4853,
17485,
549,
17444,
427,
96,
13313,
26,
121,
3274,
3,
31,
3420,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What was the lowest attendance when Fitzroy was the home team? | CREATE TABLE table_name_44 (
crowd INTEGER,
home_team VARCHAR
) | SELECT MIN(crowd) FROM table_name_44 WHERE home_team = "fitzroy" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3628,
41,
4374,
3,
21342,
17966,
6,
234,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
7402,
11364,
116,
9783,
172,
8170,
47,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
75,
3623,
26,
61,
21680,
953,
834,
4350,
834,
3628,
549,
17444,
427,
234,
834,
11650,
3274,
96,
89,
5615,
8170,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many were drawn when 13 were lost? | CREATE TABLE table_17625749_3 (drawn VARCHAR, lost VARCHAR) | SELECT drawn FROM table_17625749_3 WHERE lost = "13" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
4056,
3436,
3647,
834,
519,
41,
19489,
29,
584,
4280,
28027,
6,
1513,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
130,
6796,
116,
1179,
130,
1513,
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... | [
3,
23143,
14196,
6796,
21680,
953,
834,
2517,
4056,
3436,
3647,
834,
519,
549,
17444,
427,
1513,
3274,
96,
2368,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is admission time and diagnoses short title of subject name robert clayton? | 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 demographic.admittime, diagnoses.short_title FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Robert Clayton" | [
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,
14798,
5,
20466,
17,
715,
6,
18730,
7,
5,
7,
14184,
834,
21869,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
549,
17444,
4... |
Which R 51 O value corresponds to a D 42 O value of r 19? | CREATE TABLE table_name_8 (r_51_o VARCHAR, d_42_o VARCHAR) | SELECT r_51_o FROM table_name_8 WHERE d_42_o = "r 19" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
927,
41,
52,
834,
5553,
834,
32,
584,
4280,
28027,
6,
3,
26,
834,
4165,
834,
32,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
391,
11696,
411,
701,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3,
52,
834,
5553,
834,
32,
21680,
953,
834,
4350,
834,
927,
549,
17444,
427,
3,
26,
834,
4165,
834,
32,
3274,
96,
52,
957,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Name the number of high assists for july 1 | CREATE TABLE table_21299 (
"Game" real,
"Date" text,
"Opponent" text,
"Score" text,
"High points" text,
"High rebounds" text,
"High assists" text,
"Location/Attendance" text,
"Record" text
) | SELECT COUNT("High assists") FROM table_21299 WHERE "Date" = 'July 1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24837,
3264,
41,
96,
23055,
121,
490,
6,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
21417,
979,
121,
1499,
6,
96,
21... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
21417,
13041,
8512,
21680,
953,
834,
24837,
3264,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
683,
83,
63,
209,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
how many patients aged below 81 were black/african american? | 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
)
C... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.ethnicity = "BLACK/AFRICAN AMERICAN" AND demographic.age < "81" | [
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,
15,
189,
2532,
485,
3274,
96,
8775,
15339,
87,
6282,
5593,
11425,
3,
17683,
5593,
11425,
121,
3430... |
What is the average medal total when the rank is less than 5 and less than 7 bronze medals were won? | CREATE TABLE table_13102 (
"Rank" real,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT AVG("Total") FROM table_13102 WHERE "Rank" < '5' AND "Bronze" < '7' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2368,
14388,
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,
3696,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3696,
1947,
8512,
21680,
953,
834,
2368,
14388,
549,
17444,
427,
96,
22557,
121,
3,
2,
3,
31,
755,
31,
3430,
96,
22780,
29,
776,
121,
3,
2,
3,
31,
940,
31,
1,
-100,
-100,
-100,
-100,
-100,
... |
Which Date has a Score of 6–1 7–6 (8–6)? | CREATE TABLE table_name_11 (date VARCHAR, score VARCHAR) | SELECT date FROM table_name_11 WHERE score = "6–1 7–6 (8–6)" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2596,
41,
5522,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
7678,
65,
3,
9,
17763,
13,
431,
104,
536,
489,
104,
948,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
833,
21680,
953,
834,
4350,
834,
2596,
549,
17444,
427,
2604,
3274,
96,
948,
104,
536,
489,
104,
948,
13642,
104,
10938,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the episode number where Jim Sweeney was performer 1 and Mike Mcshane was performer 4? | CREATE TABLE table_name_25 (episode INTEGER, performer_1 VARCHAR, performer_4 VARCHAR) | SELECT SUM(episode) FROM table_name_25 WHERE performer_1 = "jim sweeney" AND performer_4 = "mike mcshane" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1828,
41,
15,
102,
159,
32,
221,
3,
21342,
17966,
6,
1912,
49,
834,
536,
584,
4280,
28027,
6,
1912,
49,
834,
591,
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,
180,
6122,
599,
15,
102,
159,
32,
221,
61,
21680,
953,
834,
4350,
834,
1828,
549,
17444,
427,
1912,
49,
834,
536,
3274,
96,
354,
603,
3,
7,
1123,
15,
3186,
121,
3430,
1912,
49,
834,
591,
3274,
96,
20068,
15,
3,
... |
What is the maximum fastest lap speed in race named 'Monaco Grand Prix' in 2008 ? | CREATE TABLE results (fastestlapspeed INTEGER, raceid VARCHAR); CREATE TABLE races (raceid VARCHAR, year VARCHAR, name VARCHAR) | SELECT MAX(T2.fastestlapspeed) FROM races AS T1 JOIN results AS T2 ON T1.raceid = T2.raceid WHERE T1.year = 2008 AND T1.name = "Monaco Grand Prix" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
772,
41,
11584,
222,
8478,
9993,
3,
21342,
17966,
6,
1964,
23,
26,
584,
4280,
28027,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
10879,
41,
12614,
23,
26,
584,
4280,
28027... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
382,
4416,
11584,
222,
8478,
9993,
61,
21680,
10879,
6157,
332,
536,
3,
15355,
3162,
772,
6157,
332,
357,
9191,
332,
5411,
12614,
23,
26,
3274,
332,
4416,
12614,
23,
26,
549,
17444,
427,
332,
5411,
120... |
What is the entry for Upper index Kcal/ Nm 3 for the row with an entry that has a Lower index MJ/ Nm 3 of 47.91, and an Upper index MJ/ Nm 3 larger than 53.28? | CREATE TABLE table_name_93 (upper_index_kcal__nm_3 INTEGER, lower_index_mj__nm_3 VARCHAR, upper_index_mj__nm_3 VARCHAR) | SELECT SUM(upper_index_kcal__nm_3) FROM table_name_93 WHERE lower_index_mj__nm_3 = 47.91 AND upper_index_mj__nm_3 > 53.28 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4271,
41,
15689,
834,
18288,
834,
157,
1489,
834,
834,
29,
51,
834,
519,
3,
21342,
17966,
6,
1364,
834,
18288,
834,
51,
354,
834,
834,
29,
51,
834,
519,
584,
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,
180,
6122,
599,
15689,
834,
18288,
834,
157,
1489,
834,
834,
29,
51,
834,
5268,
21680,
953,
834,
4350,
834,
4271,
549,
17444,
427,
1364,
834,
18288,
834,
51,
354,
834,
834,
29,
51,
834,
519,
3274,
10635,
5,
4729,
... |
What is the counting method for a network-centric basis? | CREATE TABLE table_name_89 (
counting_method VARCHAR,
basis VARCHAR
) | SELECT counting_method FROM table_name_89 WHERE basis = "network-centric" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3914,
41,
15899,
834,
23152,
584,
4280,
28027,
6,
1873,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
15899,
1573,
21,
3,
9,
1229,
18,
1745... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
15899,
834,
23152,
21680,
953,
834,
4350,
834,
3914,
549,
17444,
427,
1873,
3274,
96,
1582,
1981,
18,
17456,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees who did not have any job in the past, visualize a bar chart about the distribution of hire_date and the average of department_id bin hire_date by weekday, and sort by the the average of department id from high to low. | CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
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)
)
CREATE T... | SELECT HIRE_DATE, AVG(DEPARTMENT_ID) FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) ORDER BY AVG(DEPARTMENT_ID) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1440,
41,
2847,
17161,
11824,
834,
4309,
3,
4331,
4059,
16426,
6,
2847,
17161,
11824,
834,
567,
17683,
3,
4331,
4059,
599,
2445,
201,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
1714,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
71,
17217,
599,
5596,
19846,
11810,
834,
4309,
61,
21680,
1652,
549,
17444,
427,
4486,
262,
5244,
5017,
476,
5080,
834,
4309,
3388,
41,
23143,
14196,
262,
5244,
5017,
476,
5080,
834,
430... |
In what Week was the Attendance 39,434? | CREATE TABLE table_name_78 (week VARCHAR, attendance INTEGER) | SELECT COUNT(week) FROM table_name_78 WHERE attendance < 39 OFFSET 434 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3940,
41,
8041,
584,
4280,
28027,
6,
11364,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
86,
125,
6551,
47,
8,
22497,
663,
6352,
6,
591,
3710,
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,
2847,
17161,
599,
8041,
61,
21680,
953,
834,
4350,
834,
3940,
549,
17444,
427,
11364,
3,
2,
6352,
3,
15316,
20788,
314,
3710,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is Player, when Place is 'T5', and when Score is '69-72=141'? | CREATE TABLE table_9813 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text
) | SELECT "Player" FROM table_9813 WHERE "Place" = 't5' AND "Score" = '69-72=141' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3916,
2368,
41,
96,
345,
11706,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
3696,
260,
121,
1499,
3,
61,
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,
15800,
49,
121,
21680,
953,
834,
3916,
2368,
549,
17444,
427,
96,
345,
11706,
121,
3274,
3,
31,
17,
755,
31,
3430,
96,
134,
9022,
121,
3274,
3,
31,
3951,
18,
5865,
2423,
26059,
31,
1,
-100,
-100,
-100,
-100,
... |
Find all first-grade students who are NOT taught by OTHA MOYER. Report their first and last names. | CREATE TABLE list (firstname VARCHAR, lastname VARCHAR, classroom VARCHAR, grade VARCHAR); CREATE TABLE teachers (classroom VARCHAR, firstname VARCHAR, lastname VARCHAR) | SELECT DISTINCT T1.firstname, T1.lastname FROM list AS T1 JOIN teachers AS T2 ON T1.classroom = T2.classroom WHERE T1.grade = 1 EXCEPT SELECT T1.firstname, T1.lastname FROM list AS T1 JOIN teachers AS T2 ON T1.classroom = T2.classroom WHERE T2.firstname = "OTHA" AND T2.lastname = "MOYER" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
570,
41,
14672,
4350,
584,
4280,
28027,
6,
336,
4350,
584,
4280,
28027,
6,
4858,
584,
4280,
28027,
6,
2769,
584,
4280,
28027,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
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,
3,
15438,
25424,
6227,
332,
5411,
14672,
4350,
6,
332,
5411,
5064,
4350,
21680,
570,
6157,
332,
536,
3,
15355,
3162,
3081,
6157,
332,
357,
9191,
332,
5411,
4057,
3082,
3274,
332,
4416,
4057,
3082,
549,
17444,
427,
332... |
Who was the match played against in the final on March 14, 2008? | CREATE TABLE table_name_2 (
opponents_in_the_final VARCHAR,
date VARCHAR
) | SELECT opponents_in_the_final FROM table_name_2 WHERE date = "march 14, 2008" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
357,
41,
16383,
834,
77,
834,
532,
834,
12406,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
8,
1588,
1944,
581,
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,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
16383,
834,
77,
834,
532,
834,
12406,
21680,
953,
834,
4350,
834,
357,
549,
17444,
427,
833,
3274,
96,
51,
7064,
11363,
2628,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the height in inches if the represented is Erongo? | CREATE TABLE table_26167 (
"Represented" text,
"Contestant" text,
"Age" real,
"Height (in.)" text,
"Height (cm.)" real,
"Hometown" text
) | SELECT "Height (in.)" FROM table_26167 WHERE "Represented" = 'Erongo' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
27650,
41,
96,
1649,
12640,
15,
26,
121,
1499,
6,
96,
4302,
4377,
288,
121,
1499,
6,
96,
188,
397,
121,
490,
6,
96,
3845,
2632,
41,
77,
5,
61,
121,
1499,
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,
96,
3845,
2632,
41,
77,
5,
61,
121,
21680,
953,
834,
2688,
27650,
549,
17444,
427,
96,
1649,
12640,
15,
26,
121,
3274,
3,
31,
10575,
2444,
32,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Show the countries that have managers of age above 50 or below 46. | CREATE TABLE manager (Country VARCHAR, Age VARCHAR) | SELECT Country FROM manager WHERE Age > 50 OR Age < 46 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2743,
41,
10628,
651,
584,
4280,
28027,
6,
7526,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
3111,
8,
1440,
24,
43,
5903,
13,
1246,
756,
943,
42,
666,
9668,
5,
1,
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,
6993,
21680,
2743,
549,
17444,
427,
7526,
2490,
943,
4674,
7526,
3,
2,
9668,
1,
-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 English Meaning, when Full Word is "Shens Gamo"? | CREATE TABLE table_name_22 (english_meaning VARCHAR, full_word VARCHAR) | SELECT english_meaning FROM table_name_22 WHERE full_word = "shens gamo" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2884,
41,
4606,
40,
1273,
834,
27639,
584,
4280,
28027,
6,
423,
834,
6051,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
1566,
25148,
6,
116,
4043,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
22269,
834,
27639,
21680,
953,
834,
4350,
834,
2884,
549,
17444,
427,
423,
834,
6051,
3274,
96,
7,
3225,
7,
3,
8758,
32,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the enrollment ratio in tertiary in the region where the enrollment ration in secondary is 71.43? | CREATE TABLE table_25042332_22 (
tertiary__18_24_years_ VARCHAR,
secondary__14_17_years_ VARCHAR
) | SELECT tertiary__18_24_years_ FROM table_25042332_22 WHERE secondary__14_17_years_ = "71.43" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
11434,
591,
2773,
2668,
834,
2884,
41,
3,
449,
17,
23,
1208,
834,
834,
2606,
834,
2266,
834,
1201,
7,
834,
584,
4280,
28027,
6,
6980,
834,
834,
2534,
834,
2517,
834,
1201,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
449,
17,
23,
1208,
834,
834,
2606,
834,
2266,
834,
1201,
7,
834,
21680,
953,
834,
11434,
591,
2773,
2668,
834,
2884,
549,
17444,
427,
6980,
834,
834,
2534,
834,
2517,
834,
1201,
7,
834,
3274,
96,
4450,
5,
4906,... |
What is the kit manufacturer with Walkers as the shirt sponsor? | CREATE TABLE table_70451 (
"Team" text,
"Manager 1" text,
"Captain" text,
"Kit manufacturer" text,
"Shirt sponsor" text
) | SELECT "Kit manufacturer" FROM table_70451 WHERE "Shirt sponsor" = 'walkers' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2518,
2128,
536,
41,
96,
18699,
121,
1499,
6,
96,
27272,
209,
121,
1499,
6,
96,
19566,
17,
9,
77,
121,
1499,
6,
96,
439,
155,
4818,
121,
1499,
6,
96,
16671,
9037,
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,
439,
155,
4818,
121,
21680,
953,
834,
2518,
2128,
536,
549,
17444,
427,
96,
16671,
9037,
121,
3274,
3,
31,
24063,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
How many times is the opponents in the final is beti sekulovski cindy watson? | CREATE TABLE table_26458137_2 (score VARCHAR, opponents_in_the_final VARCHAR) | SELECT COUNT(score) FROM table_26458137_2 WHERE opponents_in_the_final = "Beti Sekulovski Cindy Watson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26755,
3449,
24636,
834,
357,
41,
7,
9022,
584,
4280,
28027,
6,
16383,
834,
77,
834,
532,
834,
12406,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
648,
19,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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... | [
3,
23143,
14196,
2847,
17161,
599,
7,
9022,
61,
21680,
953,
834,
26755,
3449,
24636,
834,
357,
549,
17444,
427,
16383,
834,
77,
834,
532,
834,
12406,
3274,
96,
2703,
17,
23,
679,
2729,
5850,
4009,
27960,
18763,
121,
1,
-100,
-100,
-... |
what is the daily minimum of the weight of patient 028-55503 since 01/2104? | 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,
... | SELECT MIN(patient.admissionweight) FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '028-55503') AND NOT patient.admissionweight IS NULL AND STRFTIME('%y-%m', patient.unitadmittime) >= '2104-01' GROUP BY STRFTIME('%y-%m-%d', patien... | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
50,
9824,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
7690,
4350,
1499,
6,
50,
1999,
7,
83,
17,
381,
6,
50,
1999,
7,
83,
17,
715,
97,
3,
61,
3,
32102,
32103,
32102,
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,
3,
17684,
599,
10061,
5,
9,
26,
5451,
9378,
61,
21680,
1868,
549,
17444,
427,
1868,
5,
10061,
15878,
3734,
21545,
23,
26,
3388,
41,
23143,
14196,
1868,
5,
10061,
15878,
3734,
21545,
23,
26,
21680,
1868,
549,
17444,
... |
What average silver has belarus as the nation, with a total less than 1? | CREATE TABLE table_79711 (
"Rank" text,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT AVG("Silver") FROM table_79711 WHERE "Nation" = 'belarus' AND "Total" < '1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4440,
4450,
536,
41,
96,
22557,
121,
1499,
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,
71,
17217,
599,
121,
134,
173,
624,
8512,
21680,
953,
834,
4440,
4450,
536,
549,
17444,
427,
96,
567,
257,
121,
3274,
3,
31,
2370,
9,
4502,
31,
3430,
96,
3696,
1947,
121,
3,
2,
3,
31,
536,
31,
1,
-100,
-100,
-... |
What Nation had a more than 1 Total medal including less than 3 Silver, less than 4 Gold and a Rank of 4? | CREATE TABLE table_50461 (
"Rank" text,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT "Nation" FROM table_50461 WHERE "Silver" < '3' AND "Total" > '1' AND "Gold" < '4' AND "Rank" = '4' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1752,
4448,
536,
41,
96,
22557,
121,
1499,
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,
96,
567,
257,
121,
21680,
953,
834,
1752,
4448,
536,
549,
17444,
427,
96,
134,
173,
624,
121,
3,
2,
3,
31,
519,
31,
3430,
96,
3696,
1947,
121,
2490,
3,
31,
536,
31,
3430,
96,
23576,
121,
3,
2,
3,
31,
591,
31... |
Which model has a Fleet Series (Quantity) of 11081-11092 (12)? | CREATE TABLE table_name_1 (
model VARCHAR,
fleet_series__quantity_ VARCHAR
) | SELECT model FROM table_name_1 WHERE fleet_series__quantity_ = "11081-11092 (12)" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
536,
41,
825,
584,
4280,
28027,
6,
9111,
834,
10833,
7,
834,
834,
13158,
485,
834,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
825,
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,
1,
1,
1,
1,
0,
0,
0,
0... | [
3,
23143,
14196,
825,
21680,
953,
834,
4350,
834,
536,
549,
17444,
427,
9111,
834,
10833,
7,
834,
834,
13158,
485,
834,
3274,
96,
19277,
4959,
18,
19277,
4508,
16465,
61,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many rebounds did Tammy Sutton-Brown have? | CREATE TABLE table_25353861_5 (rebounds VARCHAR, player VARCHAR) | SELECT rebounds FROM table_25353861_5 WHERE player = "Tammy Sutton-Brown" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1828,
2469,
3747,
4241,
834,
755,
41,
23768,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
3,
23768,
410,
10903,
2258,
180,
12499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3,
23768,
21680,
953,
834,
1828,
2469,
3747,
4241,
834,
755,
549,
17444,
427,
1959,
3274,
96,
382,
265,
2258,
180,
12499,
18,
279,
3623,
29,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which vehicle had a class of car in years after 2009 with 0 stages won and position of 5? | CREATE TABLE table_name_87 (
vehicle VARCHAR,
position VARCHAR,
stages_won VARCHAR,
class VARCHAR,
year VARCHAR
) | SELECT vehicle FROM table_name_87 WHERE class = "car" AND year > 2009 AND stages_won = "0" AND position = "5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4225,
41,
1689,
584,
4280,
28027,
6,
1102,
584,
4280,
28027,
6,
6518,
834,
210,
106,
584,
4280,
28027,
6,
853,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
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,
1689,
21680,
953,
834,
4350,
834,
4225,
549,
17444,
427,
853,
3274,
96,
1720,
121,
3430,
215,
2490,
2464,
3430,
6518,
834,
210,
106,
3274,
96,
632,
121,
3430,
1102,
3274,
96,
17395,
1,
-100,
-100,
-100,
-100,
-100,
... |
Who was the opponent during the game that had more than 31,891 people in attendance? | CREATE TABLE table_name_80 (opponent VARCHAR, attendance INTEGER) | SELECT opponent FROM table_name_80 WHERE attendance > 31 OFFSET 891 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2079,
41,
32,
102,
9977,
584,
4280,
28027,
6,
11364,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
8,
15264,
383,
8,
467,
24,
141,
72,
145,
12074... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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... | [
3,
23143,
14196,
15264,
21680,
953,
834,
4350,
834,
2079,
549,
17444,
427,
11364,
2490,
2664,
3,
15316,
20788,
505,
4729,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the average round of the number 16 pick? | CREATE TABLE table_54067 (
"Round" real,
"Pick" text,
"Player" text,
"Position" text,
"School/Club Team" text
) | SELECT AVG("Round") FROM table_54067 WHERE "Pick" = '16' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25379,
3708,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
345,
3142,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
29364,
87,
254,
11158... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
448,
32,
1106,
8512,
21680,
953,
834,
25379,
3708,
549,
17444,
427,
96,
345,
3142,
121,
3274,
3,
31,
2938,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What was the finish with less than 200 laps in 1953? | CREATE TABLE table_14816 (
"Year" text,
"Start" text,
"Qual" text,
"Rank" text,
"Finish" text,
"Laps" real
) | SELECT "Finish" FROM table_14816 WHERE "Laps" < '200' AND "Year" = '1953' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24748,
2938,
41,
96,
476,
2741,
121,
1499,
6,
96,
7681,
17,
121,
1499,
6,
96,
5991,
138,
121,
1499,
6,
96,
22557,
121,
1499,
6,
96,
371,
77,
1273,
121,
1499,
6,
96,
361... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
371,
77,
1273,
121,
21680,
953,
834,
24748,
2938,
549,
17444,
427,
96,
3612,
102,
7,
121,
3,
2,
3,
31,
3632,
31,
3430,
96,
476,
2741,
121,
3274,
3,
31,
2294,
4867,
31,
1,
-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.