NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
List the names of aircrafts and that won matches at least twice. | CREATE TABLE airport_aircraft (
id number,
airport_id number,
aircraft_id number
)
CREATE TABLE match (
round number,
location text,
country text,
date text,
fastest_qualifying text,
winning_pilot text,
winning_aircraft text
)
CREATE TABLE aircraft (
aircraft_id number,
... | SELECT T1.aircraft FROM aircraft AS T1 JOIN match AS T2 ON T1.aircraft_id = T2.winning_aircraft GROUP BY T2.winning_aircraft HAVING COUNT(*) >= 2 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3761,
834,
2256,
6696,
41,
3,
23,
26,
381,
6,
3761,
834,
23,
26,
381,
6,
6442,
834,
23,
26,
381,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
1588,
41,
1751,
381,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
332,
5411,
2256,
6696,
21680,
6442,
6157,
332,
536,
3,
15355,
3162,
1588,
6157,
332,
357,
9191,
332,
5411,
2256,
6696,
834,
23,
26,
3274,
332,
4416,
8163,
834,
2256,
6696,
350,
4630,
6880,
272,
476,
332,
4416,
8163,
... |
What are the dates that Falling Angel aired? | CREATE TABLE table_30778 (
"No." real,
"Name" text,
"Country" text,
"Original channel" text,
"No. of episodes" real,
"Running time" text,
"Launched" text,
"Date" text,
"IRST" text
) | SELECT "Date" FROM table_30778 WHERE "Name" = 'Falling Angel' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1458,
940,
3940,
41,
96,
4168,
535,
490,
6,
96,
23954,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
667,
3380,
10270,
4245,
121,
1499,
6,
96,
4168,
5,
13,
13562,
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,
308,
342,
121,
21680,
953,
834,
1458,
940,
3940,
549,
17444,
427,
96,
23954,
121,
3274,
3,
31,
371,
9,
12013,
5126,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What was the Kentucky Oaks attendance the year the Belmont Stakes had 64,949 attendance? | CREATE TABLE table_2988 (
"Year" real,
"Kentucky Derby" real,
"The Preakness Stakes" text,
"Kentucky Oaks" text,
"Belmont Stakes" text,
"Travers Stakes" text,
"Breeders Cup Saturday" text,
"Breeders Cup Friday" text
) | SELECT "Kentucky Oaks" FROM table_2988 WHERE "Belmont Stakes" = '64,949' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
4060,
41,
96,
476,
2741,
121,
490,
6,
96,
439,
295,
4636,
63,
21485,
121,
490,
6,
96,
634,
1266,
1639,
655,
180,
4914,
7,
121,
1499,
6,
96,
439,
295,
4636,
63,
78... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
439,
295,
4636,
63,
7858,
7,
121,
21680,
953,
834,
3166,
4060,
549,
17444,
427,
96,
2703,
40,
4662,
180,
4914,
7,
121,
3274,
3,
31,
4389,
6,
1298,
3647,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What School had 3a/2a as the value for IHSAA Class/ Football Class? | CREATE TABLE table_name_81 (
school VARCHAR,
ihsaa_class__football_class VARCHAR
) | SELECT school FROM table_name_81 WHERE ihsaa_class__football_class = "3a/2a" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4959,
41,
496,
584,
4280,
28027,
6,
3,
23,
107,
7,
9,
9,
834,
4057,
834,
834,
6259,
3184,
834,
4057,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
36... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0... | [
3,
23143,
14196,
496,
21680,
953,
834,
4350,
834,
4959,
549,
17444,
427,
3,
23,
107,
7,
9,
9,
834,
4057,
834,
834,
6259,
3184,
834,
4057,
3274,
96,
519,
9,
13311,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name all the team clasification where the combination classification is mederic clain | CREATE TABLE table_15088557_1 (
team_classification VARCHAR,
combination_classification VARCHAR
) | SELECT team_classification FROM table_15088557_1 WHERE combination_classification = "Mederic Clain" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1808,
4018,
4433,
3436,
834,
536,
41,
372,
834,
4057,
2420,
584,
4280,
28027,
6,
2711,
834,
4057,
2420,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
66,
8,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
372,
834,
4057,
2420,
21680,
953,
834,
1808,
4018,
4433,
3436,
834,
536,
549,
17444,
427,
2711,
834,
4057,
2420,
3274,
96,
20123,
15,
2234,
7781,
77,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
How many grids had a constructor of renault and less than 4 laps? | CREATE TABLE table_name_35 (grid INTEGER, constructor VARCHAR, laps VARCHAR) | SELECT SUM(grid) FROM table_name_35 WHERE constructor = "renault" AND laps < 4 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2469,
41,
3496,
26,
3,
21342,
17966,
6,
6774,
127,
584,
4280,
28027,
6,
14941,
7,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
8634,
7,
141,
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,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
180,
6122,
599,
3496,
26,
61,
21680,
953,
834,
4350,
834,
2469,
549,
17444,
427,
6774,
127,
3274,
96,
1536,
10335,
121,
3430,
14941,
7,
3,
2,
314,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Which Score has a Date of may 4? | CREATE TABLE table_46173 (
"Date" text,
"Opponent" text,
"Score" text,
"Result" text,
"Record" text
) | SELECT "Score" FROM table_46173 WHERE "Date" = 'may 4' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4448,
2517,
519,
41,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
1649,
7621,
121,
1499,
3,
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,
0,
0,
0... | [
3,
23143,
14196,
96,
134,
9022,
121,
21680,
953,
834,
4448,
2517,
519,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
13726,
314,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the highest number of wins when draws are larger than 1, and byes are larger than 0? | CREATE TABLE table_name_59 (wins INTEGER, draws VARCHAR, byes VARCHAR) | SELECT MAX(wins) FROM table_name_59 WHERE draws > 1 AND byes > 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3390,
41,
3757,
7,
3,
21342,
17966,
6,
14924,
584,
4280,
28027,
6,
57,
15,
7,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2030,
381,
13,
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,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
3757,
7,
61,
21680,
953,
834,
4350,
834,
3390,
549,
17444,
427,
14924,
2490,
209,
3430,
57,
15,
7,
2490,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the number of patients whose diagnoses long title is other and unspecified agents primarily affecting the cardiovascular system causing adverse effects in therapeutic use? | 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 WHERE diagnoses.long_title = "Other and unspecified agents primarily affecting the cardiovascular system causing adverse effects in therapeutic use" | [
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,
5... |
What is Type, when Newspaper/Magazine is Telecoms & It Magazine? | CREATE TABLE table_76720 (
"Newspaper/Magazine" text,
"Type" text,
"Language" text,
"Headquarter" text,
"Status" text
) | SELECT "Type" FROM table_76720 WHERE "Newspaper/Magazine" = 'telecoms & it magazine' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3959,
18517,
41,
96,
6861,
7,
19587,
87,
24773,
15,
121,
1499,
6,
96,
25160,
121,
1499,
6,
96,
434,
1468,
76,
545,
121,
1499,
6,
96,
3845,
9,
26,
19973,
121,
1499,
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,
25160,
121,
21680,
953,
834,
3959,
18517,
549,
17444,
427,
96,
6861,
7,
19587,
87,
24773,
15,
121,
3274,
3,
31,
1931,
287,
7,
3,
184,
34,
3835,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is Run 4, when Run 2 is 1:29.00? | CREATE TABLE table_name_12 (run_4 VARCHAR, run_2 VARCHAR) | SELECT run_4 FROM table_name_12 WHERE run_2 = "1:29.00" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2122,
41,
4312,
834,
591,
584,
4280,
28027,
6,
661,
834,
357,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
7113,
6464,
116,
7113,
204,
19,
30651,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
661,
834,
591,
21680,
953,
834,
4350,
834,
2122,
549,
17444,
427,
661,
834,
357,
3274,
96,
536,
10,
3166,
4200,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the date enacted for N.S. of 10 and normal total of 104 | CREATE TABLE table_name_73 (
date_enacted VARCHAR,
ns VARCHAR,
normal_total VARCHAR
) | SELECT date_enacted FROM table_name_73 WHERE ns = "10" AND normal_total = "104" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4552,
41,
833,
834,
35,
9925,
584,
4280,
28027,
6,
3,
29,
7,
584,
4280,
28027,
6,
1389,
834,
235,
1947,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0... | [
3,
23143,
14196,
833,
834,
35,
9925,
21680,
953,
834,
4350,
834,
4552,
549,
17444,
427,
3,
29,
7,
3274,
96,
1714,
121,
3430,
1389,
834,
235,
1947,
3274,
96,
15442,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the highest week with 84,856 in attendance? | CREATE TABLE table_name_96 (
week INTEGER,
attendance VARCHAR
) | SELECT MAX(week) FROM table_name_96 WHERE attendance = "84,856" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4314,
41,
471,
3,
21342,
17966,
6,
11364,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2030,
471,
28,
3,
4608,
6,
4433,
948,
16,
11364,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
8041,
61,
21680,
953,
834,
4350,
834,
4314,
549,
17444,
427,
11364,
3274,
96,
4608,
6,
4433,
948,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
for patients aged 72 or below, specify the minimum duration of hospital stay | 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 MIN(demographic.days_stay) FROM demographic WHERE demographic.age >= "72" | [
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,
3,
17684,
599,
1778,
16587,
5,
1135,
7,
834,
21545,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
545,
2490,
2423,
96,
5865,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
The prize of 1,000,000 was given by an event in what city? | CREATE TABLE table_70223 (
"Date" text,
"City" text,
"Event" text,
"Winner" text,
"Prize" text
) | SELECT "City" FROM table_70223 WHERE "Prize" = '£1,000,000' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2518,
357,
2773,
41,
96,
308,
342,
121,
1499,
6,
96,
254,
485,
121,
1499,
6,
96,
427,
2169,
121,
1499,
6,
96,
18455,
687,
121,
1499,
6,
96,
7855,
776,
121,
1499,
3,
61,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
254,
485,
121,
21680,
953,
834,
2518,
357,
2773,
549,
17444,
427,
96,
7855,
776,
121,
3274,
3,
31,
19853,
536,
23916,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
calculate the number of patients with chest pain - r/o pericardial disease diagnosed until 2 years ago. | CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE l... | SELECT COUNT(DISTINCT patient.uniquepid) FROM patient WHERE patient.patientunitstayid IN (SELECT diagnosis.patientunitstayid FROM diagnosis WHERE diagnosis.diagnosisname = 'chest pain - r/o pericardial disease' AND DATETIME(diagnosis.diagnosistime) <= DATETIME(CURRENT_TIME(), '-2 year')) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1058,
41,
1058,
23,
26,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
1058,
4350,
1499,
6,
1058,
715,
97,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
583,
41,
583,
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,
2847,
17161,
599,
15438,
25424,
6227,
1868,
5,
202,
1495,
12417,
61,
21680,
1868,
549,
17444,
427,
1868,
5,
10061,
15129,
21545,
23,
26,
3388,
41,
23143,
14196,
8209,
5,
10061,
15129,
21545,
23,
26,
21680,
8209,
549,
... |
what is the number of patients whose discharge location is home and diagnoses short title is hx of breast malignancy? | 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 WHERE demographic.discharge_location = "HOME" AND diagnoses.short_title = "Hx of breast malignancy" | [
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,
5... |
When did they play Miami? | CREATE TABLE table_17323042_8 (
date VARCHAR,
team VARCHAR
) | SELECT date FROM table_17323042_8 WHERE team = "Miami" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
2668,
1458,
4165,
834,
927,
41,
833,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
410,
79,
577,
8327,
58,
1,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
833,
21680,
953,
834,
2517,
2668,
1458,
4165,
834,
927,
549,
17444,
427,
372,
3274,
96,
329,
23,
3690,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Name the date for grass surface for quarterfinal at the nsw building society open tournament | CREATE TABLE table_name_36 (date VARCHAR, tournament VARCHAR, surface VARCHAR, round VARCHAR) | SELECT date FROM table_name_36 WHERE surface = "grass" AND round = "quarterfinal" AND tournament = "nsw building society open" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3420,
41,
5522,
584,
4280,
28027,
6,
5892,
584,
4280,
28027,
6,
1774,
584,
4280,
28027,
6,
1751,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
833,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
833,
21680,
953,
834,
4350,
834,
3420,
549,
17444,
427,
1774,
3274,
96,
16446,
121,
3430,
1751,
3274,
96,
19973,
12406,
121,
3430,
5892,
3274,
96,
29,
7,
210,
740,
2710,
539,
121,
1,
-100,
-100,
-100,
-100,
-100,
-1... |
Please show the trend of the number of the church by open date (bin into the year) using a line chart. | CREATE TABLE people (
People_ID int,
Name text,
Country text,
Is_Male text,
Age int
)
CREATE TABLE wedding (
Church_ID int,
Male_ID int,
Female_ID int,
Year int
)
CREATE TABLE church (
Church_ID int,
Name text,
Organized_by text,
Open_Date int,
Continuation_of t... | SELECT Open_Date, COUNT(Open_Date) FROM church | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
151,
41,
2449,
834,
4309,
16,
17,
6,
5570,
1499,
6,
6993,
1499,
6,
27,
7,
834,
329,
9,
109,
1499,
6,
7526,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
168... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2384,
834,
308,
342,
6,
2847,
17161,
599,
22696,
834,
308,
342,
61,
21680,
2078,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Show the description of the transaction type that occurs most frequently. | CREATE TABLE lots (
lot_id number,
investor_id number,
lot_details text
)
CREATE TABLE ref_transaction_types (
transaction_type_code text,
transaction_type_description text
)
CREATE TABLE purchases (
purchase_transaction_id number,
purchase_details text
)
CREATE TABLE transactions_lots (
... | SELECT T1.transaction_type_description FROM ref_transaction_types AS T1 JOIN transactions AS T2 ON T1.transaction_type_code = T2.transaction_type_code GROUP BY T1.transaction_type_code ORDER BY COUNT(*) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1995,
41,
418,
834,
23,
26,
381,
6,
12024,
834,
23,
26,
381,
6,
418,
834,
221,
5756,
7,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
6273,
834,
7031,
4787,
834... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
332,
5411,
7031,
4787,
834,
6137,
834,
221,
11830,
21680,
6273,
834,
7031,
4787,
834,
6137,
7,
6157,
332,
536,
3,
15355,
3162,
6413,
6157,
332,
357,
9191,
332,
5411,
7031,
4787,
834,
6137,
834,
4978,
3274,
332,
4416,
... |
What is the Hometown for Villanova College? | CREATE TABLE table_name_11 (
hometown VARCHAR,
college VARCHAR
) | SELECT hometown FROM table_name_11 WHERE college = "villanova" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2596,
41,
22295,
584,
4280,
28027,
6,
1900,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1210,
3540,
21,
8850,
14979,
1888,
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,
22295,
21680,
953,
834,
4350,
834,
2596,
549,
17444,
427,
1900,
3274,
96,
24887,
14979,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the name of the baseball stadium for the school with the Murray Center basketball arena? | CREATE TABLE table_23257 (
"School" text,
"Baseball stadium" text,
"Softball stadium" text,
"Basketball arena" text,
"Capacity" text
) | SELECT "Baseball stadium" FROM table_23257 WHERE "Basketball arena" = 'The Murray Center' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23188,
3436,
41,
96,
29364,
121,
1499,
6,
96,
14885,
15,
3184,
14939,
121,
1499,
6,
96,
28017,
3184,
14939,
121,
1499,
6,
96,
14885,
8044,
3184,
15134,
121,
1499,
6,
96,
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,
1... | [
3,
23143,
14196,
96,
14885,
15,
3184,
14939,
121,
21680,
953,
834,
23188,
3436,
549,
17444,
427,
96,
14885,
8044,
3184,
15134,
121,
3274,
3,
31,
634,
15497,
1166,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the result of the match with an attendance of 73,855? | CREATE TABLE table_name_9 (
result VARCHAR,
attendance VARCHAR
) | SELECT result FROM table_name_9 WHERE attendance = "73,855" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1298,
41,
741,
584,
4280,
28027,
6,
11364,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
741,
13,
8,
1588,
28,
46,
11364,
13,
3,
4552,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
741,
21680,
953,
834,
4350,
834,
1298,
549,
17444,
427,
11364,
3274,
96,
4552,
6,
4433,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the driver for Laps less than 9 and a grid of 13 | CREATE TABLE table_52277 (
"Driver" text,
"Constructor" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
) | SELECT "Driver" FROM table_52277 WHERE "Laps" < '9' AND "Grid" = '13' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5373,
357,
4013,
41,
96,
20982,
52,
121,
1499,
6,
96,
4302,
7593,
127,
121,
1499,
6,
96,
3612,
102,
7,
121,
490,
6,
96,
13368,
87,
1649,
11809,
26,
121,
1499,
6,
96,
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,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
20982,
52,
121,
21680,
953,
834,
5373,
357,
4013,
549,
17444,
427,
96,
3612,
102,
7,
121,
3,
2,
3,
31,
1298,
31,
3430,
96,
13313,
26,
121,
3274,
3,
31,
2368,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
List all the places that the Apocalypstix occupied when the Denim Demons were 2nd. | CREATE TABLE table_31269 (
"Season" real,
"Apocalypstix" text,
"Denim Demons" text,
"Sake Tuyas" text,
"Toxic Shocks" text
) | SELECT "Apocalypstix" FROM table_31269 WHERE "Denim Demons" = '2nd' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
2122,
3951,
41,
96,
134,
15,
9,
739,
121,
490,
6,
96,
188,
10496,
9,
120,
102,
2248,
226,
121,
1499,
6,
96,
308,
35,
603,
15782,
29,
7,
121,
1499,
6,
96,
134,
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,
188,
10496,
9,
120,
102,
2248,
226,
121,
21680,
953,
834,
519,
2122,
3951,
549,
17444,
427,
96,
308,
35,
603,
15782,
29,
7,
121,
3274,
3,
31,
357,
727,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Give me a bar chart for all_games_percent of each team name, and list Team_Name from low to high order. | CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
CREATE TABLE university (
Scho... | SELECT Team_Name, All_Games_Percent FROM basketball_match ORDER BY Team_Name | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
8498,
834,
19515,
41,
2271,
834,
4309,
16,
17,
6,
1121,
834,
4309,
16,
17,
6,
2271,
834,
23954,
1499,
6,
3,
14775,
834,
17748,
4885,
834,
134,
15,
9,
739,
1499,
6,
3,
14775,
834,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2271,
834,
23954,
6,
432,
834,
23055,
7,
834,
12988,
3728,
21680,
8498,
834,
19515,
4674,
11300,
272,
476,
2271,
834,
23954,
1,
-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 procedure icd9 code is 8960. | 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 INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.admission_type = "URGENT" AND procedures.icd9_code = "8960" | [
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,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
What country did mario lemieux play for in 1994? | CREATE TABLE table_name_17 (country VARCHAR, player VARCHAR, year VARCHAR) | SELECT country FROM table_name_17 WHERE player = "mario lemieux" AND year = 1994 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2517,
41,
17529,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
684,
410,
2774,
32,
90,
51,
11891,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
684,
21680,
953,
834,
4350,
834,
2517,
549,
17444,
427,
1959,
3274,
96,
17289,
32,
90,
51,
11891,
121,
3430,
215,
3274,
7520,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the most wins when the number of losses was less than 4 and there was more than 0 ties? | CREATE TABLE table_name_77 (wins INTEGER, losses VARCHAR, ties VARCHAR) | SELECT MAX(wins) FROM table_name_77 WHERE losses < 4 AND ties > 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4013,
41,
3757,
7,
3,
21342,
17966,
6,
8467,
584,
4280,
28027,
6,
3,
3010,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
167,
9204,
116,
8,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
3757,
7,
61,
21680,
953,
834,
4350,
834,
4013,
549,
17444,
427,
8467,
3,
2,
314,
3430,
3,
3010,
2490,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What was the maximum OTL if L is 28? | CREATE TABLE table_2233872_1 (
Otl INTEGER,
l VARCHAR
) | SELECT MAX(Otl) FROM table_2233872_1 WHERE l = 28 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
20879,
4225,
357,
834,
536,
41,
411,
17,
40,
3,
21342,
17966,
6,
3,
40,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2411,
411,
12733,
3,
99,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4800,
4,
599,
667,
17,
40,
61,
21680,
953,
834,
357,
20879,
4225,
357,
834,
536,
549,
17444,
427,
3,
40,
3274,
2059,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
In the Open Championship with more than 3 cuts made, what is the average wins? | CREATE TABLE table_name_15 (
wins INTEGER,
tournament VARCHAR,
cuts_made VARCHAR
) | SELECT AVG(wins) FROM table_name_15 WHERE tournament = "the open championship" AND cuts_made > 3 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1808,
41,
9204,
3,
21342,
17966,
6,
5892,
584,
4280,
28027,
6,
8620,
834,
4725,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
86,
8,
2384,
7666,
28,
72... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
71,
17217,
599,
3757,
7,
61,
21680,
953,
834,
4350,
834,
1808,
549,
17444,
427,
5892,
3274,
96,
532,
539,
10183,
121,
3430,
8620,
834,
4725,
2490,
220,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What GWR is associated with 4? | CREATE TABLE table_11336 (
"Manufacturer" text,
"Type" text,
"Quantity" real,
"SHT Nos." text,
"GWR Nos." text
) | SELECT "GWR Nos." FROM table_11336 WHERE "Quantity" = '4' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
20522,
3420,
41,
96,
7296,
76,
8717,
450,
49,
121,
1499,
6,
96,
25160,
121,
1499,
6,
96,
5991,
288,
485,
121,
490,
6,
96,
134,
10966,
465,
7,
535,
1499,
6,
96,
517,
154... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
517,
15472,
465,
7,
535,
21680,
953,
834,
20522,
3420,
549,
17444,
427,
96,
5991,
288,
485,
121,
3274,
3,
31,
591,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What was the highest attendance against Real Juventud? | CREATE TABLE table_name_14 (attendance INTEGER, away VARCHAR) | SELECT MAX(attendance) FROM table_name_14 WHERE away = "real juventud" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2534,
41,
15116,
663,
3,
21342,
17966,
6,
550,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2030,
11364,
581,
2977,
446,
4348,
76,
26,
58,
1,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
15116,
663,
61,
21680,
953,
834,
4350,
834,
2534,
549,
17444,
427,
550,
3274,
96,
6644,
3,
354,
4348,
76,
26,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the lowest silver that has 2 as the bronze, with a total greater than 4? | CREATE TABLE table_name_33 (
silver INTEGER,
bronze VARCHAR,
total VARCHAR
) | SELECT MIN(silver) FROM table_name_33 WHERE bronze = 2 AND total > 4 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4201,
41,
4294,
3,
21342,
17966,
6,
13467,
584,
4280,
28027,
6,
792,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
7402,
4294,
24,
65,
204,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
7,
173,
624,
61,
21680,
953,
834,
4350,
834,
4201,
549,
17444,
427,
13467,
3274,
204,
3430,
792,
2490,
314,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
count the number of patients whose year of death is less than or equal to 2155 and item id is 50811? | 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 INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.dod_year <= "2155.0" AND lab.itemid = "50811" | [
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,
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 name of the last specimen test patient 025-44495 received? | CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,... | SELECT microlab.culturesite FROM microlab WHERE microlab.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '025-44495')) ORDER BY microlab.culturetakentime DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2179,
9339,
41,
2179,
521,
9824,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
1543,
3585,
1499,
6,
9329,
1499,
6,
1543,
4914,
29,
715,
97,
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,
2179,
9339,
5,
10547,
3585,
21680,
2179,
9339,
549,
17444,
427,
2179,
9339,
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,
1... |
Total average with less than 105 points, 1993-1994 less than 30, and the team of gimnasia y tiro? | CREATE TABLE table_44529 (
"Team" text,
"Average" real,
"Points" real,
"Played" real,
"1991-92" text,
"1992-93" text,
"1993-94" real
) | SELECT SUM("Average") FROM table_44529 WHERE "Points" < '105' AND "Team" = 'gimnasia y tiro' AND "1993-94" < '30' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
2128,
3166,
41,
96,
18699,
121,
1499,
6,
96,
188,
624,
545,
121,
490,
6,
96,
22512,
7,
121,
490,
6,
96,
15800,
15,
26,
121,
490,
6,
96,
2294,
4729,
18,
4508,
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,
188,
624,
545,
8512,
21680,
953,
834,
591,
2128,
3166,
549,
17444,
427,
96,
22512,
7,
121,
3,
2,
3,
31,
12869,
31,
3430,
96,
18699,
121,
3274,
3,
31,
122,
603,
29,
15974,
3,
63,
11857,
32,
... |
Which actor played on Home and Away for 20 years? | CREATE TABLE table_79211 (
"Actor" text,
"Character" text,
"Soap Opera" text,
"Years" text,
"Duration" text
) | SELECT "Actor" FROM table_79211 WHERE "Duration" = '20 years' AND "Soap Opera" = 'home and away' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4440,
27278,
41,
96,
188,
5317,
121,
1499,
6,
96,
18947,
2708,
49,
121,
1499,
6,
96,
5231,
9,
102,
6411,
121,
1499,
6,
96,
476,
2741,
7,
121,
1499,
6,
96,
12998,
2661,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
5317,
121,
21680,
953,
834,
4440,
27278,
549,
17444,
427,
96,
12998,
2661,
121,
3274,
3,
31,
1755,
203,
31,
3430,
96,
5231,
9,
102,
6411,
121,
3274,
3,
31,
5515,
11,
550,
31,
1,
-100,
-100,
-100,
-100,
... |
Who was the runner-up when the winning score was 28 (66-67-68-64-67=332)? | CREATE TABLE table_35059 (
"Date" text,
"Tournament" text,
"Winning score" text,
"Margin of victory" text,
"Runner(s)-up" text
) | SELECT "Runner(s)-up" FROM table_35059 WHERE "Winning score" = '–28 (66-67-68-64-67=332)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
16975,
3390,
41,
96,
308,
342,
121,
1499,
6,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
518,
10503,
2604,
121,
1499,
6,
96,
7286,
122,
77,
13,
6224,
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,
23572,
599,
7,
61,
18,
413,
121,
21680,
953,
834,
16975,
3390,
549,
17444,
427,
96,
518,
10503,
2604,
121,
3274,
3,
31,
104,
2577,
41,
3539,
18,
3708,
18,
3651,
18,
4389,
18,
3708,
2423,
4201,
7318,
31,
1,
-... |
What is the location where shocker was the winner? | CREATE TABLE table_64583 (
"Wager" text,
"Winner" text,
"Loser" text,
"Location" text,
"Date" text
) | SELECT "Location" FROM table_64583 WHERE "Winner" = 'shocker' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
3449,
519,
41,
96,
518,
9754,
121,
1499,
6,
96,
18455,
687,
121,
1499,
6,
96,
434,
32,
7,
49,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
308,
342,
12... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
434,
32,
75,
257,
121,
21680,
953,
834,
4389,
3449,
519,
549,
17444,
427,
96,
18455,
687,
121,
3274,
3,
31,
5630,
3383,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which Points have a Lost smaller than 1, and Games larger than 7? | CREATE TABLE table_36134 (
"Games" real,
"Drawn" real,
"Lost" real,
"Points difference" text,
"Points" real
) | SELECT MAX("Points") FROM table_36134 WHERE "Lost" < '1' AND "Games" > '7' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3420,
23747,
41,
96,
23055,
7,
121,
490,
6,
96,
308,
10936,
29,
121,
490,
6,
96,
434,
3481,
121,
490,
6,
96,
22512,
7,
1750,
121,
1499,
6,
96,
22512,
7,
121,
490,
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,
4800,
4,
599,
121,
22512,
7,
8512,
21680,
953,
834,
3420,
23747,
549,
17444,
427,
96,
434,
3481,
121,
3,
2,
3,
31,
536,
31,
3430,
96,
23055,
7,
121,
2490,
3,
31,
940,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the companion for the author Dave Stone? | CREATE TABLE table_name_7 (
companion_s_ VARCHAR,
author VARCHAR
) | SELECT companion_s_ FROM table_name_7 WHERE author = "dave stone" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
940,
41,
9663,
834,
7,
834,
584,
4280,
28027,
6,
2291,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
9663,
21,
8,
2291,
8545,
5614,
58,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
9663,
834,
7,
834,
21680,
953,
834,
4350,
834,
940,
549,
17444,
427,
2291,
3274,
96,
26,
9,
162,
3372,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Name the most number of leitrim | CREATE TABLE table_1705429_1 (no INTEGER, constituency VARCHAR) | SELECT MAX(no) FROM table_1705429_1 WHERE constituency = "Leitrim" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
3076,
591,
3166,
834,
536,
41,
29,
32,
3,
21342,
17966,
6,
6439,
4392,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
167,
381,
13,
90,
155,
5397,
1,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4800,
4,
599,
29,
32,
61,
21680,
953,
834,
2517,
3076,
591,
3166,
834,
536,
549,
17444,
427,
6439,
4392,
3274,
96,
2796,
155,
5397,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What did the team score when playing against home in geelong? | CREATE TABLE table_name_72 (home_team VARCHAR, away_team VARCHAR) | SELECT home_team AS score FROM table_name_72 WHERE away_team = "geelong" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5865,
41,
5515,
834,
11650,
584,
4280,
28027,
6,
550,
834,
11650,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
410,
8,
372,
2604,
116,
1556,
581,
234,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
234,
834,
11650,
6157,
2604,
21680,
953,
834,
4350,
834,
5865,
549,
17444,
427,
550,
834,
11650,
3274,
96,
397,
15,
2961,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the highest attendance for games with stevenage borough at home? | CREATE TABLE table_78227 (
"Tie no" real,
"Home team" text,
"Score" text,
"Away team" text,
"Attendance" real
) | SELECT MAX("Attendance") FROM table_78227 WHERE "Home team" = 'stevenage borough' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3940,
357,
2555,
41,
96,
382,
23,
15,
150,
121,
490,
6,
96,
19040,
372,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
188,
17,
324,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
188,
17,
324,
26,
663,
8512,
21680,
953,
834,
3940,
357,
2555,
549,
17444,
427,
96,
19040,
372,
121,
3274,
3,
31,
849,
1926,
545,
3,
12823,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What's the nationality of jim les? | CREATE TABLE table_58474 (
"Player" text,
"Nationality" text,
"Position" text,
"Years for Jazz" text,
"School/Club Team" text
) | SELECT "Nationality" FROM table_58474 WHERE "Player" = 'jim les' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3449,
4177,
591,
41,
96,
15800,
49,
121,
1499,
6,
96,
24732,
485,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
476,
2741,
7,
21,
12313,
121,
1499,
6,
96,
29364... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3449,
4177,
591,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
354,
603,
110,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Name the year 2007 for 668 being 2008-q1 | CREATE TABLE table_26902 (
"Items" text,
"2008 - Q1" text,
"2008-Q2" text,
"2008-Q3" text,
"extrapol. 08" text,
"year 2007" text
) | SELECT "year 2007" FROM table_26902 WHERE "2008 - Q1" = '668' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
2394,
357,
41,
96,
196,
3524,
7,
121,
1499,
6,
96,
16128,
3,
18,
1593,
536,
121,
1499,
6,
96,
16128,
18,
2247,
357,
121,
1499,
6,
96,
16128,
18,
2247,
519,
121,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
1201,
4101,
121,
21680,
953,
834,
2688,
2394,
357,
549,
17444,
427,
96,
16128,
3,
18,
1593,
536,
121,
3274,
3,
31,
3539,
927,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
A scatter chart shows the correlation between ACC_Percent and All_Games_Percent , and group by attribute All_Home. | CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
CREATE TABLE university (
Scho... | SELECT ACC_Percent, All_Games_Percent FROM basketball_match GROUP BY All_Home | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
8498,
834,
19515,
41,
2271,
834,
4309,
16,
17,
6,
1121,
834,
4309,
16,
17,
6,
2271,
834,
23954,
1499,
6,
3,
14775,
834,
17748,
4885,
834,
134,
15,
9,
739,
1499,
6,
3,
14775,
834,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
14775,
834,
12988,
3728,
6,
432,
834,
23055,
7,
834,
12988,
3728,
21680,
8498,
834,
19515,
350,
4630,
6880,
272,
476,
432,
834,
19040,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What Chassis code has a 200d model and a Power of ps (kw; hp) @ 4200? | CREATE TABLE table_name_63 (chassis_code VARCHAR, power VARCHAR, model VARCHAR) | SELECT chassis_code FROM table_name_63 WHERE power = "ps (kw; hp) @ 4200" AND model = "200d" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3891,
41,
524,
6500,
7,
834,
4978,
584,
4280,
28027,
6,
579,
584,
4280,
28027,
6,
825,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
4004,
6500,
7,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
22836,
834,
4978,
21680,
953,
834,
4350,
834,
3891,
549,
17444,
427,
579,
3274,
96,
102,
7,
41,
157,
210,
117,
3,
107,
102,
61,
3320,
314,
3632,
121,
3430,
825,
3274,
96,
3632,
26,
121,
1,
-100,
-100,
-100,
-100,
... |
What is the original of the ipa ( s o paulo ) translation d t i t mad su m n ? | CREATE TABLE table_23915_4 (
translation VARCHAR,
ipa___são_paulo__ VARCHAR
) | SELECT translation FROM table_23915_4 WHERE ipa___são_paulo__ = "dɐ̃ːˈtɕiɣɐ ˈtɐ̃ʊ̯̃ ɐ̃ˈmadɐ ˈsuɐ ɦõ̞ˈmənə" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3288,
1808,
834,
591,
41,
7314,
584,
4280,
28027,
6,
3,
23,
102,
9,
834,
834,
834,
7,
2,
32,
834,
102,
9,
83,
32,
834,
834,
584,
4280,
28027,
3,
61,
3,
32102,
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,
7314,
21680,
953,
834,
357,
3288,
1808,
834,
591,
549,
17444,
427,
3,
23,
102,
9,
834,
834,
834,
7,
2,
32,
834,
102,
9,
83,
32,
834,
834,
3274,
96,
26,
2,
17,
2,
23,
2,
3,
2,
17,
2,
3,
2,
11374,
2,
3,
... |
What Vehicle Flight # has Pilot Peterson and Velocity (km/h) of 649? | CREATE TABLE table_name_31 (
vehicle_flight__number VARCHAR,
pilot VARCHAR,
velocity__km_h_ VARCHAR
) | SELECT vehicle_flight__number FROM table_name_31 WHERE pilot = "peterson" AND velocity__km_h_ = 649 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3341,
41,
1689,
834,
89,
2242,
834,
834,
5525,
1152,
584,
4280,
28027,
6,
4487,
584,
4280,
28027,
6,
22924,
834,
834,
5848,
834,
107,
834,
584,
4280,
28027,
3,
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,
1689,
834,
89,
2242,
834,
834,
5525,
1152,
21680,
953,
834,
4350,
834,
3341,
549,
17444,
427,
4487,
3274,
96,
4995,
13515,
121,
3430,
22924,
834,
834,
5848,
834,
107,
834,
3274,
431,
3647,
1,
-100,
-100,
-100,
-100,
... |
How many Losses have a Geelong FL of newtown & chilwell, and more than 11 wins? | CREATE TABLE table_61771 (
"Geelong FL" text,
"Wins" real,
"Byes" real,
"Losses" real,
"Draws" real,
"Against" real
) | SELECT COUNT("Losses") FROM table_61771 WHERE "Geelong FL" = 'newtown & chilwell' AND "Wins" > '11' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4241,
4013,
536,
41,
96,
517,
15,
15,
2961,
7212,
121,
1499,
6,
96,
18455,
7,
121,
490,
6,
96,
279,
10070,
121,
490,
6,
96,
434,
13526,
7,
121,
490,
6,
96,
308,
10936,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
434,
13526,
7,
8512,
21680,
953,
834,
4241,
4013,
536,
549,
17444,
427,
96,
517,
15,
15,
2961,
7212,
121,
3274,
3,
31,
5534,
3540,
3,
184,
3,
1436,
40,
2091,
31,
3430,
96,
18455,
7,
121,
2... |
Which films participated when the category was Best Newcomer? | CREATE TABLE table_31286 (
"Film Festival" text,
"Date of ceremony" text,
"Category" text,
"Participants/Recipients" text,
"Result" text
) | SELECT "Participants/Recipients" FROM table_31286 WHERE "Category" = 'Best Newcomer' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
2122,
3840,
41,
96,
371,
173,
51,
3397,
121,
1499,
6,
96,
308,
342,
13,
7252,
121,
1499,
6,
96,
18610,
6066,
651,
121,
1499,
6,
96,
13725,
23,
3389,
2366,
87,
1649,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
13725,
23,
3389,
2366,
87,
1649,
3389,
4741,
7,
121,
21680,
953,
834,
519,
2122,
3840,
549,
17444,
427,
96,
18610,
6066,
651,
121,
3274,
3,
31,
17278,
368,
287,
49,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Year has a Game of resident evil 4? | CREATE TABLE table_14157 (
"Year" real,
"Game" text,
"Genre" text,
"Platform(s)" text,
"Developer(s)" text
) | SELECT AVG("Year") FROM table_14157 WHERE "Game" = 'resident evil 4' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2534,
27452,
41,
96,
476,
2741,
121,
490,
6,
96,
23055,
121,
1499,
6,
96,
13714,
60,
121,
1499,
6,
96,
10146,
2032,
599,
7,
61,
121,
1499,
6,
96,
2962,
162,
8745,
49,
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,
71,
17217,
599,
121,
476,
2741,
8512,
21680,
953,
834,
2534,
27452,
549,
17444,
427,
96,
23055,
121,
3274,
3,
31,
15704,
8293,
314,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many positions in 2009? | CREATE TABLE table_10705060_1 (
position VARCHAR,
season VARCHAR
) | SELECT COUNT(position) FROM table_10705060_1 WHERE season = "2009" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1714,
2518,
1752,
3328,
834,
536,
41,
1102,
584,
4280,
28027,
6,
774,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
149,
186,
4655,
16,
2464,
58,
1,
0,
0,
0,
0,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4718,
61,
21680,
953,
834,
1714,
2518,
1752,
3328,
834,
536,
549,
17444,
427,
774,
3274,
96,
16660,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Name the vacator for kentucky 2nd | CREATE TABLE table_26639 (
"District" text,
"Vacator" text,
"Reason for change" text,
"Successor" text,
"Date successor seated" text
) | SELECT "Vacator" FROM table_26639 WHERE "District" = 'Kentucky 2nd' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3539,
3288,
41,
96,
308,
23,
20066,
121,
1499,
6,
96,
25203,
1016,
121,
1499,
6,
96,
1649,
9,
739,
21,
483,
121,
1499,
6,
96,
134,
17431,
24901,
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,
25203,
1016,
121,
21680,
953,
834,
357,
3539,
3288,
549,
17444,
427,
96,
308,
23,
20066,
121,
3274,
3,
31,
439,
295,
4636,
63,
204,
727,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What activities does Clear Channel Entertainment Facilitation Limited engage in? | CREATE TABLE table_1756264_2 (description_of_activities VARCHAR, company_name VARCHAR) | SELECT description_of_activities FROM table_1756264_2 WHERE company_name = "CLEAR CHANNEL ENTERTAINMENT FACILITATION LIMITED" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
4834,
26755,
834,
357,
41,
221,
11830,
834,
858,
834,
8463,
2197,
584,
4280,
28027,
6,
349,
834,
4350,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
1087,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4210,
834,
858,
834,
8463,
2197,
21680,
953,
834,
2517,
4834,
26755,
834,
357,
549,
17444,
427,
349,
834,
4350,
3274,
96,
22704,
4280,
3,
25000,
4171,
434,
3,
6431,
24203,
13570,
11810,
377,
5173,
3502,
3177,
8015,
31... |
What is the sum of all mintage created by Pierre Leduc? | CREATE TABLE table_name_61 (
mintage INTEGER,
artist VARCHAR
) | SELECT SUM(mintage) FROM table_name_61 WHERE artist = "pierre leduc" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4241,
41,
13983,
545,
3,
21342,
17966,
6,
2377,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
4505,
13,
66,
13983,
545,
990,
57,
11867,
312... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
180,
6122,
599,
1109,
6505,
61,
21680,
953,
834,
4350,
834,
4241,
549,
17444,
427,
2377,
3274,
96,
8343,
60,
90,
4817,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Show the names of editors that are on the committee of journals with sales bigger than 3000, and count them by a pie chart | CREATE TABLE journal_committee (
Editor_ID int,
Journal_ID int,
Work_Type text
)
CREATE TABLE journal (
Journal_ID int,
Date text,
Theme text,
Sales int
)
CREATE TABLE editor (
Editor_ID int,
Name text,
Age real
) | SELECT Name, COUNT(Name) FROM journal_committee AS T1 JOIN editor AS T2 ON T1.Editor_ID = T2.Editor_ID JOIN journal AS T3 ON T1.Journal_ID = T3.Journal_ID WHERE T3.Sales > 3000 GROUP BY Name | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
6378,
834,
287,
1538,
17,
15,
15,
41,
11953,
834,
4309,
16,
17,
6,
3559,
834,
4309,
16,
17,
6,
3118,
834,
25160,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
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,
5570,
6,
2847,
17161,
599,
23954,
61,
21680,
6378,
834,
287,
1538,
17,
15,
15,
6157,
332,
536,
3,
15355,
3162,
6005,
6157,
332,
357,
9191,
332,
5411,
26527,
127,
834,
4309,
3274,
332,
4416,
26527,
127,
834,
4309,
3,... |
Which Venue has an Event of marathon, and a Year larger than 1995, and a Position of 4th? | CREATE TABLE table_8753 (
"Year" real,
"Competition" text,
"Venue" text,
"Position" text,
"Event" text
) | SELECT "Venue" FROM table_8753 WHERE "Event" = 'marathon' AND "Year" > '1995' AND "Position" = '4th' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4225,
4867,
41,
96,
476,
2741,
121,
490,
6,
96,
5890,
4995,
4749,
121,
1499,
6,
96,
553,
35,
76,
15,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
427,
2169,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
553,
35,
76,
15,
121,
21680,
953,
834,
4225,
4867,
549,
17444,
427,
96,
427,
2169,
121,
3274,
3,
31,
1635,
24718,
31,
3430,
96,
476,
2741,
121,
2490,
3,
31,
2294,
3301,
31,
3430,
96,
345,
32,
7,
4749,
121,
... |
When was the tournament that was won with a score of 204 (-6) played? | CREATE TABLE table_16969 (
"Date" text,
"Tournament" text,
"Location" text,
"Purse( $ )" real,
"Winner" text,
"Score" text,
"1st Prize( $ )" real
) | SELECT "Date" FROM table_16969 WHERE "Score" = '204 (-6)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
27096,
3951,
41,
96,
308,
342,
121,
1499,
6,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
345,
3589,
15,
599,
1514,
3,
61,
121,
490,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
308,
342,
121,
21680,
953,
834,
27096,
3951,
549,
17444,
427,
96,
134,
9022,
121,
3274,
3,
31,
26363,
41,
18,
10938,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What shows for 202 when the 1994 is A, the 1989 is NME, and the 199 is 2R? | CREATE TABLE table_name_3 (
Id VARCHAR
) | SELECT 2002 FROM table_name_3 WHERE 1994 = "a" AND 1989 = "nme" AND 1999 = "2r" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
519,
41,
27,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
1267,
21,
3,
19818,
116,
8,
7520,
19,
71,
6,
8,
9975,
19,
445,
4369,
6,
11,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4407,
21680,
953,
834,
4350,
834,
519,
549,
17444,
427,
7520,
3274,
96,
9,
121,
3430,
9975,
3274,
96,
29,
526,
121,
3430,
5247,
3274,
96,
357,
52,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
provide the number of patients with lab test item id 50803 having abnormal lab test status. | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE lab.itemid = "50803" AND lab.flag = "abnormal" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14798,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
564,
1499,
6,
2774,
1947,
834,
8547,
302,
1499,
6,
1246,
1499,
6,
103,
115,
1499,
6,
7285,
1499,
6,
1612,
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,
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,... |
how long did it take piotr to run the medley relay in 2001 ? | CREATE TABLE table_204_622 (
id number,
"year" number,
"competition" text,
"venue" text,
"position" text,
"event" text,
"notes" text
) | SELECT "notes" FROM table_204_622 WHERE "event" = 'medley relay' AND "year" = 2001 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
4056,
357,
41,
3,
23,
26,
381,
6,
96,
1201,
121,
381,
6,
96,
287,
4995,
4749,
121,
1499,
6,
96,
15098,
121,
1499,
6,
96,
4718,
121,
1499,
6,
96,
15,
2169,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7977,
7,
121,
21680,
953,
834,
26363,
834,
4056,
357,
549,
17444,
427,
96,
15,
2169,
121,
3274,
3,
31,
2726,
1306,
16010,
31,
3430,
96,
1201,
121,
3274,
4402,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the time/retired when the laps is 6, the grid is less than 18 and the driver is clay regazzoni? | CREATE TABLE table_name_79 (time_retired VARCHAR, driver VARCHAR, laps VARCHAR, grid VARCHAR) | SELECT time_retired FROM table_name_79 WHERE laps = 6 AND grid < 18 AND driver = "clay regazzoni" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4440,
41,
715,
834,
10682,
1271,
584,
4280,
28027,
6,
2535,
584,
4280,
28027,
6,
14941,
7,
584,
4280,
28027,
6,
8634,
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,
97,
834,
10682,
1271,
21680,
953,
834,
4350,
834,
4440,
549,
17444,
427,
14941,
7,
3274,
431,
3430,
8634,
3,
2,
507,
3430,
2535,
3274,
96,
4651,
63,
3,
60,
21805,
8892,
23,
121,
1,
-100,
-100,
-100,
-100,
-100,
-1... |
List the race time for may 11. | CREATE TABLE table_28178756_1 (
race_time VARCHAR,
date VARCHAR
) | SELECT race_time FROM table_28178756_1 WHERE date = "May 11" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2577,
2517,
4225,
4834,
834,
536,
41,
1964,
834,
715,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
6792,
8,
1964,
97,
21,
164,
7806,
1,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1964,
834,
715,
21680,
953,
834,
2577,
2517,
4225,
4834,
834,
536,
549,
17444,
427,
833,
3274,
96,
15881,
850,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What week was the game that had an attendance of 24,242? | CREATE TABLE table_name_34 (week VARCHAR, attendance VARCHAR) | SELECT week FROM table_name_34 WHERE attendance = "24,242" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3710,
41,
8041,
584,
4280,
28027,
6,
11364,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
471,
47,
8,
467,
24,
141,
46,
11364,
13,
14320,
2266,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
471,
21680,
953,
834,
4350,
834,
3710,
549,
17444,
427,
11364,
3274,
96,
2266,
6,
2266,
357,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What shows for 1993 when 1991 is grand slams? | CREATE TABLE table_name_6 (
Id VARCHAR
) | SELECT 1993 FROM table_name_6 WHERE 1991 = "grand slams" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
27,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
1267,
21,
8388,
116,
9957,
19,
1907,
3,
7,
40,
265,
7,
58,
1,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
8388,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
9957,
3274,
96,
15448,
3,
7,
40,
265,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Name the nfl team for eric williams | CREATE TABLE table_2508633_6 (
nfl_team VARCHAR,
player VARCHAR
) | SELECT nfl_team FROM table_2508633_6 WHERE player = "Eric Williams" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
11434,
3840,
4201,
834,
948,
41,
3,
29,
89,
40,
834,
11650,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
3,
29,
89,
40,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
29,
89,
40,
834,
11650,
21680,
953,
834,
11434,
3840,
4201,
834,
948,
549,
17444,
427,
1959,
3274,
96,
427,
2234,
6060,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
On what date was the race at Nazareth? | CREATE TABLE table_15736385_1 (
date VARCHAR,
location VARCHAR
) | SELECT date FROM table_15736385_1 WHERE location = "Nazareth" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1808,
4552,
3891,
4433,
834,
536,
41,
833,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
461,
125,
833,
47,
8,
1964,
44,
1823,
7061,
15... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
833,
21680,
953,
834,
1808,
4552,
3891,
4433,
834,
536,
549,
17444,
427,
1128,
3274,
96,
567,
5246,
60,
189,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What year was the timber trade? | CREATE TABLE table_58377 (
"Year" real,
"Theme" text,
"Artist" text,
"Mintage" real,
"Issue Price" text
) | SELECT SUM("Year") FROM table_58377 WHERE "Theme" = 'timber trade' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3449,
519,
4013,
41,
96,
476,
2741,
121,
490,
6,
96,
634,
526,
121,
1499,
6,
96,
7754,
343,
121,
1499,
6,
96,
12858,
6505,
121,
490,
6,
96,
196,
7,
7,
76,
15,
5312,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0... | [
3,
23143,
14196,
180,
6122,
599,
121,
476,
2741,
8512,
21680,
953,
834,
3449,
519,
4013,
549,
17444,
427,
96,
634,
526,
121,
3274,
3,
31,
2998,
1152,
1668,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the name of the school that has a player named Michael Dunigan? | CREATE TABLE table_name_79 (
school VARCHAR,
player VARCHAR
) | SELECT school FROM table_name_79 WHERE player = "michael dunigan" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4440,
41,
496,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
564,
13,
8,
496,
24,
65,
3,
9,
1959,
2650,
2457,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
496,
21680,
953,
834,
4350,
834,
4440,
549,
17444,
427,
1959,
3274,
96,
51,
362,
9,
15,
40,
146,
29,
12588,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the lowest overall number of hurricanes? | CREATE TABLE table_31083 (
"Year" real,
"Number of tropical storms" real,
"Number of hurricanes" real,
"Number of major hurricanes" real,
"Deaths" text,
"Strongest storm" text
) | SELECT MIN("Number of hurricanes") FROM table_31083 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19947,
4591,
41,
96,
476,
2741,
121,
490,
6,
96,
567,
5937,
49,
13,
10468,
5536,
7,
121,
490,
6,
96,
567,
5937,
49,
13,
20818,
7,
121,
490,
6,
96,
567,
5937,
49,
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,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
567,
5937,
49,
13,
20818,
7,
8512,
21680,
953,
834,
19947,
4591,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-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, a bar chart shows the distribution of first_name and department_id , and I want to list by the Y in descending. | CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25... | SELECT FIRST_NAME, DEPARTMENT_ID FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY DEPARTMENT_ID DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2476,
41,
446,
10539,
834,
4309,
3,
4331,
4059,
599,
16968,
6,
446,
10539,
834,
382,
3177,
3765,
3,
4331,
4059,
599,
2469,
201,
3,
17684,
834,
134,
4090,
24721,
7908,
1982,
599,
11071,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
30085,
834,
567,
17683,
6,
3396,
19846,
11810,
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,
427,
283,
15610... |
Which Position has an Against smaller than 49, and a Drawn of 4? | CREATE TABLE table_name_16 (position INTEGER, against VARCHAR, drawn VARCHAR) | SELECT MAX(position) FROM table_name_16 WHERE against < 49 AND drawn = 4 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2938,
41,
4718,
3,
21342,
17966,
6,
581,
584,
4280,
28027,
6,
6796,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
14258,
65,
46,
3,
20749,
2755,
145,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4800,
4,
599,
4718,
61,
21680,
953,
834,
4350,
834,
2938,
549,
17444,
427,
581,
3,
2,
9526,
3430,
6796,
3274,
314,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Tell me the average Rank for lossess less than 6 and wins less than 11 for michigan state | CREATE TABLE table_74477 (
"Rank" real,
"School" text,
"Appearances" real,
"Wins" real,
"Losses" real
) | SELECT AVG("Rank") FROM table_74477 WHERE "Losses" < '6' AND "Wins" < '11' AND "School" = 'michigan state' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4581,
591,
4013,
41,
96,
22557,
121,
490,
6,
96,
29364,
121,
1499,
6,
96,
9648,
2741,
663,
7,
121,
490,
6,
96,
18455,
7,
121,
490,
6,
96,
434,
13526,
7,
121,
490,
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,
71,
17217,
599,
121,
22557,
8512,
21680,
953,
834,
4581,
591,
4013,
549,
17444,
427,
96,
434,
13526,
7,
121,
3,
2,
3,
31,
948,
31,
3430,
96,
18455,
7,
121,
3,
2,
3,
31,
2596,
31,
3430,
96,
29364,
121,
3274,
3,... |
How many against when losses are 11 and wins are fewer than 5? | CREATE TABLE table_name_24 (against INTEGER, losses VARCHAR, wins VARCHAR) | SELECT AVG(against) FROM table_name_24 WHERE losses = 11 AND wins < 5 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2266,
41,
9,
16720,
7,
17,
3,
21342,
17966,
6,
8467,
584,
4280,
28027,
6,
9204,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
581,
116,
8467,
33... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
71,
17217,
599,
9,
16720,
7,
17,
61,
21680,
953,
834,
4350,
834,
2266,
549,
17444,
427,
8467,
3274,
850,
3430,
9204,
3,
2,
305,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
If the land square milage is 10.950, what is the longitude? | CREATE TABLE table_1925 (
"Township" text,
"County" text,
"Pop. (2010)" real,
"Land ( sqmi )" text,
"Water (sqmi)" text,
"Latitude" text,
"Longitude" text,
"GEO ID" real,
"ANSI code" real
) | SELECT "Longitude" FROM table_1925 WHERE "Land ( sqmi )" = '10.950' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2294,
1828,
41,
96,
382,
9197,
2009,
121,
1499,
6,
96,
10628,
63,
121,
1499,
6,
96,
27773,
5,
26118,
121,
490,
6,
96,
434,
232,
41,
11820,
51,
23,
3,
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,
434,
2444,
20341,
121,
21680,
953,
834,
2294,
1828,
549,
17444,
427,
96,
434,
232,
41,
11820,
51,
23,
3,
61,
121,
3274,
3,
31,
10415,
25188,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the lowest value for Wins, when South West DFL is 'Cavendish', and when Byes is less than 0? | CREATE TABLE table_12644 (
"South West DFL" text,
"Wins" real,
"Byes" real,
"Losses" real,
"Draws" real,
"Against" real
) | SELECT MIN("Wins") FROM table_12644 WHERE "South West DFL" = 'cavendish' AND "Byes" < '0' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
21976,
3628,
41,
96,
22081,
1244,
309,
10765,
121,
1499,
6,
96,
18455,
7,
121,
490,
6,
96,
279,
10070,
121,
490,
6,
96,
434,
13526,
7,
121,
490,
6,
96,
308,
10936,
7,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
18455,
7,
8512,
21680,
953,
834,
21976,
3628,
549,
17444,
427,
96,
22081,
1244,
309,
10765,
121,
3274,
3,
31,
658,
1926,
26,
1273,
31,
3430,
96,
279,
10070,
121,
3,
2,
3,
31,
632,
31,
1,
-100... |
What is the highest number of losses that a team who had an away record of 1-6 and more than 4 wins had? | CREATE TABLE table_name_6 (
losses INTEGER,
away VARCHAR,
wins VARCHAR
) | SELECT MAX(losses) FROM table_name_6 WHERE away = "1-6" AND wins > 4 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
8467,
3,
21342,
17966,
6,
550,
584,
4280,
28027,
6,
9204,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2030,
381,
13,
8467,
24,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
2298,
2260,
61,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
550,
3274,
96,
27019,
121,
3430,
9204,
2490,
314,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the lowest number of Drawn games for Team Mackenzie where the Played is less and 11 and the Points are greater than 7? | CREATE TABLE table_40118 (
"Position" real,
"Team" text,
"Points" real,
"Played" real,
"Drawn" real,
"Lost" real,
"Against" real,
"Difference" text
) | SELECT MIN("Drawn") FROM table_40118 WHERE "Played" < '11' AND "Points" > '7' AND "Team" = 'mackenzie' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2445,
20056,
41,
96,
345,
32,
7,
4749,
121,
490,
6,
96,
18699,
121,
1499,
6,
96,
22512,
7,
121,
490,
6,
96,
15800,
15,
26,
121,
490,
6,
96,
308,
10936,
29,
121,
490,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
308,
10936,
29,
8512,
21680,
953,
834,
2445,
20056,
549,
17444,
427,
96,
15800,
15,
26,
121,
3,
2,
3,
31,
2596,
31,
3430,
96,
22512,
7,
121,
2490,
3,
31,
940,
31,
3430,
96,
18699,
121,
3274,
... |
Who were the developers for the Action RPG made after 2010? | CREATE TABLE table_name_71 (
developer_s_ VARCHAR,
year VARCHAR,
genre VARCHAR
) | SELECT developer_s_ FROM table_name_71 WHERE year > 2010 AND genre = "action rpg" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4450,
41,
7523,
834,
7,
834,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
6,
5349,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
130,
8,
5564,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
7523,
834,
7,
834,
21680,
953,
834,
4350,
834,
4450,
549,
17444,
427,
215,
2490,
2735,
3430,
5349,
3274,
96,
4787,
3,
52,
102,
122,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Name the last time for club of newell's old boys | CREATE TABLE table_name_11 (last_title VARCHAR, club VARCHAR) | SELECT last_title FROM table_name_11 WHERE club = "newell's old boys" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2596,
41,
5064,
834,
21869,
584,
4280,
28027,
6,
1886,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
336,
97,
21,
1886,
13,
126,
3820,
31,
7,
625... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
336,
834,
21869,
21680,
953,
834,
4350,
834,
2596,
549,
17444,
427,
1886,
3274,
96,
29,
15,
2091,
31,
7,
625,
5234,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What was the score on march 11? | CREATE TABLE table_11337 (
"Date" text,
"Visitor" text,
"Score" text,
"Home" text,
"Decision" text,
"Attendance" real,
"Record" text
) | SELECT "Score" FROM table_11337 WHERE "Date" = 'march 11' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
20522,
4118,
41,
96,
308,
342,
121,
1499,
6,
96,
553,
159,
155,
127,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
19040,
121,
1499,
6,
96,
2962,
18901,
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,
134,
9022,
121,
21680,
953,
834,
20522,
4118,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
51,
7064,
850,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What was Gongbo's title? | CREATE TABLE table_name_37 (title VARCHAR, name VARCHAR) | SELECT title FROM table_name_37 WHERE name = "gongbo" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4118,
41,
21869,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
350,
2444,
115,
32,
31,
7,
2233,
58,
1,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2233,
21680,
953,
834,
4350,
834,
4118,
549,
17444,
427,
564,
3274,
96,
122,
2444,
115,
32,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
How many Airlines have a total distance of 705 (km)? | CREATE TABLE table_40568 (
"Rank" text,
"Route" text,
"Avg. Daily Flts" real,
"# of Airlines" real,
"Distance (km)" real,
"Market Share Leader" text
) | SELECT COUNT("# of Airlines") FROM table_40568 WHERE "Distance (km)" = '705' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
3076,
3651,
41,
96,
22557,
121,
1499,
6,
96,
448,
670,
15,
121,
1499,
6,
96,
188,
208,
122,
5,
8496,
5766,
17,
7,
121,
490,
6,
96,
4663,
13,
15738,
121,
490,
6,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
4663,
13,
15738,
8512,
21680,
953,
834,
591,
3076,
3651,
549,
17444,
427,
96,
308,
23,
8389,
41,
5848,
61,
121,
3274,
3,
31,
2518,
755,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the class of the w267an call sign? | CREATE TABLE table_33298 (
"Call sign" text,
"Frequency MHz" real,
"City of license" text,
"Facility ID" real,
"ERP W" real,
"Height m ( ft )" text,
"Class" text,
"FCC info" text
) | SELECT "Class" FROM table_33298 WHERE "Call sign" = 'w267an' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
2668,
3916,
41,
96,
254,
1748,
1320,
121,
1499,
6,
96,
371,
60,
835,
11298,
3,
20210,
121,
490,
6,
96,
254,
485,
13,
3344,
121,
1499,
6,
96,
371,
9,
75,
14277,
469... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
21486,
121,
21680,
953,
834,
519,
2668,
3916,
549,
17444,
427,
96,
254,
1748,
1320,
121,
3274,
3,
31,
210,
357,
3708,
152,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Who drove for team Circle Sport? | CREATE TABLE table_1266602_2 (
driver_s_ VARCHAR,
team VARCHAR
) | SELECT driver_s_ FROM table_1266602_2 WHERE team = "Circle Sport" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
21976,
3539,
4305,
834,
357,
41,
2535,
834,
7,
834,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
10719,
21,
372,
15697,
3349,
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,
2535,
834,
7,
834,
21680,
953,
834,
21976,
3539,
4305,
834,
357,
549,
17444,
427,
372,
3274,
96,
254,
23,
52,
2482,
3349,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
During which games did Tunisia win gold in the men's 5000 m? | CREATE TABLE table_name_24 (
games VARCHAR,
event VARCHAR,
medal VARCHAR
) | SELECT games FROM table_name_24 WHERE event = "men's 5000 m" AND medal = "gold" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2266,
41,
1031,
584,
4280,
28027,
6,
605,
584,
4280,
28027,
6,
9365,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
3,
2092,
84,
1031,
410,
22564,
23,
9... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1031,
21680,
953,
834,
4350,
834,
2266,
549,
17444,
427,
605,
3274,
96,
904,
31,
7,
3,
12814,
3,
51,
121,
3430,
9365,
3274,
96,
14910,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
resting heart rate > 100 or < 50 beats / min; | CREATE TABLE table_train_103 (
"id" int,
"systolic_blood_pressure_sbp" int,
"epilepsy" bool,
"diastolic_blood_pressure_dbp" int,
"heart_rate" int,
"seizure_disorder" bool,
"age" float,
"NOUSE" float
) | SELECT * FROM table_train_103 WHERE heart_rate > 100 OR heart_rate < 50 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
9719,
834,
17864,
41,
96,
23,
26,
121,
16,
17,
6,
96,
7,
63,
7,
235,
2176,
834,
27798,
834,
26866,
834,
7,
115,
102,
121,
16,
17,
6,
96,
15,
102,
699,
19819,
121,
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,
1429,
21680,
953,
834,
9719,
834,
17864,
549,
17444,
427,
842,
834,
2206,
2490,
910,
4674,
842,
834,
2206,
3,
2,
943,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the venue on october 28, 2008? | CREATE TABLE table_name_43 (venue VARCHAR, date VARCHAR) | SELECT venue FROM table_name_43 WHERE date = "october 28, 2008" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4906,
41,
15098,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
125,
19,
8,
5669,
30,
3,
32,
75,
235,
1152,
13719,
2628,
58,
1,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
5669,
21680,
953,
834,
4350,
834,
4906,
549,
17444,
427,
833,
3274,
96,
32,
75,
235,
1152,
13719,
2628,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What player was picked for Buffalo Sabres? | CREATE TABLE table_30820 (
"Pick" text,
"Player" text,
"Position" text,
"Nationality" text,
"NHL team" text,
"College/junior/club team" text
) | SELECT "Player" FROM table_30820 WHERE "NHL team" = 'Buffalo Sabres' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1458,
927,
1755,
41,
96,
345,
3142,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
24732,
485,
121,
1499,
6,
96,
15743,
434,
372,
12... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1458,
927,
1755,
549,
17444,
427,
96,
15743,
434,
372,
121,
3274,
3,
31,
279,
2999,
138,
32,
11315,
60,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the total when silver is more than 3, and rank is 2? | CREATE TABLE table_name_53 (total INTEGER, silver VARCHAR, rank VARCHAR) | SELECT MAX(total) FROM table_name_53 WHERE silver > 3 AND rank = "2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4867,
41,
235,
1947,
3,
21342,
17966,
6,
4294,
584,
4280,
28027,
6,
11003,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
792,
116,
4294,
19,
7... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
235,
1947,
61,
21680,
953,
834,
4350,
834,
4867,
549,
17444,
427,
4294,
2490,
220,
3430,
11003,
3274,
96,
357,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the median income for the region where 24.4% pf people make below 60% of the median income? | CREATE TABLE table_25042332_16 (
median_income___intl INTEGER,
below_60_percentage_of_median_income VARCHAR
) | SELECT MIN(median_income___intl) AS $__ FROM table_25042332_16 WHERE below_60_percentage_of_median_income = "24.4%" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
11434,
591,
2773,
2668,
834,
2938,
41,
15572,
834,
15759,
834,
834,
834,
77,
17,
40,
3,
21342,
17966,
6,
666,
834,
3328,
834,
883,
3728,
545,
834,
858,
834,
8172,
29,
834,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
8172,
29,
834,
15759,
834,
834,
834,
77,
17,
40,
61,
6157,
1514,
834,
834,
21680,
953,
834,
11434,
591,
2773,
2668,
834,
2938,
549,
17444,
427,
666,
834,
3328,
834,
883,
3728,
545,
834,
858,
834,
81... |
What is Score, when Date is February 5? | CREATE TABLE table_name_85 (
score VARCHAR,
date VARCHAR
) | SELECT score FROM table_name_85 WHERE date = "february 5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4433,
41,
2604,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
17763,
6,
116,
7678,
19,
2083,
305,
58,
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,
2604,
21680,
953,
834,
4350,
834,
4433,
549,
17444,
427,
833,
3274,
96,
89,
15,
9052,
1208,
3,
17395,
1,
-100,
-100,
-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, return a line chart about the change of commission_pct over hire_date , and order x-axis from high to low order. | CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
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 TABLE departments (
DEPARTME... | SELECT HIRE_DATE, COMMISSION_PCT FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) ORDER BY HIRE_DATE DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
6266,
41,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
11116,
632,
201,
4083,
517,
9215,
834,
567,
17683,
3,
4331,
4059,
599,
1828,
61,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3,
6657,
329,
16994,
9215,
834,
4051,
382,
21680,
1652,
549,
17444,
427,
4486,
262,
5244,
5017,
476,
5080,
834,
4309,
3388,
41,
23143,
14196,
262,
5244,
5017,
476,
5080,
834,
4309,
21680... |
For each film, show the price and group them by cinema name in a stacked bar chart. | CREATE TABLE film (
Film_ID int,
Rank_in_series int,
Number_in_season int,
Title text,
Directed_by text,
Original_air_date text,
Production_code text
)
CREATE TABLE cinema (
Cinema_ID int,
Name text,
Openning_year int,
Capacity int,
Location text
)
CREATE TABLE schedule... | SELECT Name, Price FROM schedule AS T1 JOIN film AS T2 ON T1.Film_ID = T2.Film_ID JOIN cinema AS T3 ON T1.Cinema_ID = T3.Cinema_ID GROUP BY Title, Name | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
814,
41,
3417,
834,
4309,
16,
17,
6,
3,
22557,
834,
77,
834,
10833,
7,
16,
17,
6,
7720,
834,
77,
834,
9476,
16,
17,
6,
11029,
1499,
6,
7143,
15,
26,
834,
969,
1499,
6,
8465,
83... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
5570,
6,
5312,
21680,
2023,
6157,
332,
536,
3,
15355,
3162,
814,
6157,
332,
357,
9191,
332,
5411,
371,
173,
51,
834,
4309,
3274,
332,
4416,
371,
173,
51,
834,
4309,
3,
15355,
3162,
10276,
6157,
332,
519,
9191,
332,
... |
Which Driver has less than 84 laps, more than 9 points and is on Rocketsports Racing Team? | CREATE TABLE table_name_68 (
driver VARCHAR,
team VARCHAR,
laps VARCHAR,
points VARCHAR
) | SELECT driver FROM table_name_68 WHERE laps < 84 AND points > 9 AND team = "rocketsports racing" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
2535,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
6,
14941,
7,
584,
4280,
28027,
6,
979,
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,
2535,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
14941,
7,
3,
2,
3,
4608,
3430,
979,
2490,
668,
3430,
372,
3274,
96,
6133,
15,
17,
6661,
7,
8191,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Report the number of patients on additive type drug prescriptions who have the diagnoses of chronic combined systolic and diastolic heart failure. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,... | 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 = "Chr syst/diastl hrt fail" AND prescriptions.drug_type = "ADDITIVE" | [
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,
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... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.