NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
Name the airport for ICAO of flls | CREATE TABLE table_name_6 (
airport VARCHAR,
icao VARCHAR
) | SELECT airport FROM table_name_6 WHERE icao = "flls" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
3761,
584,
4280,
28027,
6,
3,
2617,
32,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
3761,
21,
3,
15038,
667,
13,
3,
89,
195,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3761,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
3,
2617,
32,
3274,
96,
89,
195,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Find the name of the source user with the highest average trust score. | CREATE TABLE useracct (
name VARCHAR,
u_id VARCHAR
)
CREATE TABLE trust (
source_u_id VARCHAR
) | SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.source_u_id GROUP BY T2.source_u_id ORDER BY AVG(trust) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1139,
6004,
17,
41,
564,
584,
4280,
28027,
6,
3,
76,
834,
23,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
2019,
41,
1391,
834,
76,
834,
23,
26... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
332,
5411,
4350,
21680,
1139,
6004,
17,
6157,
332,
536,
3,
15355,
3162,
2019,
6157,
332,
357,
9191,
332,
5411,
76,
834,
23,
26,
3274,
332,
4416,
7928,
834,
76,
834,
23,
26,
350,
4630,
6880,
272,
476,
332,
4416,
79... |
What is Record, when Location Attendance is "Pepsi Center 19,749"? | CREATE TABLE table_name_97 (record VARCHAR, location_attendance VARCHAR) | SELECT record FROM table_name_97 WHERE location_attendance = "pepsi center 19,749" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4327,
41,
60,
7621,
584,
4280,
28027,
6,
1128,
834,
15116,
663,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
11392,
6,
116,
10450,
22497,
663,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1368,
21680,
953,
834,
4350,
834,
4327,
549,
17444,
427,
1128,
834,
15116,
663,
3274,
96,
855,
102,
7,
23,
1530,
12370,
940,
3647,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who were the successors when the date the successors were installed was February 23, 1870? | CREATE TABLE table_2417345_3 (successor VARCHAR, date_of_successors_formal_installation VARCHAR) | SELECT successor FROM table_2417345_3 WHERE date_of_successors_formal_installation = "February 23, 1870" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2266,
2517,
519,
2128,
834,
519,
41,
7,
17431,
24901,
584,
4280,
28027,
6,
833,
834,
858,
834,
7,
17431,
24901,
7,
834,
2032,
138,
834,
14790,
584,
4280,
28027,
61,
3,
3210... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
22261,
21680,
953,
834,
2266,
2517,
519,
2128,
834,
519,
549,
17444,
427,
833,
834,
858,
834,
7,
17431,
24901,
7,
834,
2032,
138,
834,
14790,
3274,
96,
31122,
12992,
507,
2518,
121,
1,
-100,
-100,
-100,
-100,
-100,
... |
When was 'Tell You When' released? | CREATE TABLE table_16859758_1 (
release_date VARCHAR,
title VARCHAR
) | SELECT release_date FROM table_16859758_1 WHERE title = "Tell You When" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
4433,
4327,
3449,
834,
536,
41,
1576,
834,
5522,
584,
4280,
28027,
6,
2233,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
47,
3,
31,
382,
3820,
148,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1576,
834,
5522,
21680,
953,
834,
2938,
4433,
4327,
3449,
834,
536,
549,
17444,
427,
2233,
3274,
96,
382,
3820,
148,
366,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
When was moray firth built? | CREATE TABLE table_name_32 (
whenbuilt VARCHAR,
name VARCHAR
) | SELECT whenbuilt FROM table_name_32 WHERE name = "moray firth" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
116,
16152,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
47,
2288,
2866,
3,
14581,
189,
1192,
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,
116,
16152,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
564,
3274,
96,
2528,
9,
63,
3,
14581,
189,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the result of the election with incumbent bob barr? | CREATE TABLE table_29544 (
"District" text,
"Incumbent" text,
"Party" text,
"Elected" real,
"Status" text,
"Result" text
) | SELECT "Result" FROM table_29544 WHERE "Incumbent" = 'Bob Barr' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3301,
3628,
41,
96,
308,
23,
20066,
121,
1499,
6,
96,
1570,
75,
5937,
295,
121,
1499,
6,
96,
13725,
63,
121,
1499,
6,
96,
21543,
15,
26,
121,
490,
6,
96,
134,
17,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
20119,
121,
21680,
953,
834,
357,
3301,
3628,
549,
17444,
427,
96,
1570,
75,
5937,
295,
121,
3274,
3,
31,
279,
32,
115,
13384,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
provide the number of patients whose diagnoses icd9 code is 07054 and lab test fluid is ascites? | 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 diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE diagnoses.icd9_code = "07054" AND lab.fluid = "Ascites" | [
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,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
3... |
At what venue did the away team score 12.9 (81) with a crowd larger than 12,786? | CREATE TABLE table_12058 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT "Venue" FROM table_12058 WHERE "Crowd" > '12,786' AND "Away team score" = '12.9 (81)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
15518,
3449,
41,
96,
19040,
372,
121,
1499,
6,
96,
19040,
372,
2604,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
188,
1343,
372,
2604,
121,
1499,
6,
96,
553,
35,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
553,
35,
76,
15,
121,
21680,
953,
834,
15518,
3449,
549,
17444,
427,
96,
254,
3623,
26,
121,
2490,
3,
31,
2122,
6,
940,
3840,
31,
3430,
96,
188,
1343,
372,
2604,
121,
3274,
3,
31,
9368,
1298,
13642,
6982,
31... |
What were GD Mcgrath's bowling figures? | CREATE TABLE table_56382 (
"Bowling figures Wickets-Runs (Overs)" text,
"Bowler" text,
"Versus" text,
"Venue" text,
"Date" text
) | SELECT "Bowling figures Wickets-Runs (Overs)" FROM table_56382 WHERE "Bowler" = 'gd mcgrath' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4834,
3747,
357,
41,
96,
279,
2381,
697,
5638,
18602,
15,
17,
7,
18,
448,
202,
7,
41,
23847,
7,
61,
121,
1499,
6,
96,
279,
2381,
1171,
121,
1499,
6,
96,
5000,
7,
302,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
279,
2381,
697,
5638,
18602,
15,
17,
7,
18,
448,
202,
7,
41,
23847,
7,
61,
121,
21680,
953,
834,
4834,
3747,
357,
549,
17444,
427,
96,
279,
2381,
1171,
121,
3274,
3,
31,
122,
26,
3,
51,
75,
3484,
189,
31,
... |
What is the Score of the of the Tournament against Tim Gullikson with Outcome of runner-up? | CREATE TABLE table_name_68 (
score VARCHAR,
outcome VARCHAR,
opponent VARCHAR
) | SELECT score FROM table_name_68 WHERE outcome = "runner-up" AND opponent = "tim gullikson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
2604,
584,
4280,
28027,
6,
6138,
584,
4280,
28027,
6,
15264,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
17763,
13,
8,
13,
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,
2604,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
6138,
3274,
96,
10806,
18,
413,
121,
3430,
15264,
3274,
96,
2998,
3,
6106,
8654,
739,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the average Position for which the amount Drawn was less than 0? | CREATE TABLE table_name_88 (position INTEGER, drawn INTEGER) | SELECT AVG(position) FROM table_name_88 WHERE drawn < 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4060,
41,
4718,
3,
21342,
17966,
6,
6796,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1348,
14258,
21,
84,
8,
866,
19183,
29,
47,
705,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
71,
17217,
599,
4718,
61,
21680,
953,
834,
4350,
834,
4060,
549,
17444,
427,
6796,
3,
2,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
For each zip code, return how many times max wind speed reached 25? | CREATE TABLE station (
id number,
name text,
lat number,
long number,
dock_count number,
city text,
installation_date text
)
CREATE TABLE trip (
id number,
duration number,
start_date text,
start_station_name text,
start_station_id number,
end_date text,
end_stat... | SELECT zip_code, COUNT(*) FROM weather WHERE max_wind_speed_mph >= 25 GROUP BY zip_code | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2478,
41,
3,
23,
26,
381,
6,
564,
1499,
6,
50,
17,
381,
6,
307,
381,
6,
12908,
834,
13362,
381,
6,
690,
1499,
6,
2545,
834,
5522,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
10658,
834,
4978,
6,
2847,
17161,
599,
1935,
61,
21680,
1969,
549,
17444,
427,
9858,
834,
5165,
834,
9993,
834,
7656,
2490,
2423,
944,
350,
4630,
6880,
272,
476,
10658,
834,
4978,
1,
-100,
-100,
-100,
-100,
-100,
-100... |
what's the chroma format with name being high profile | CREATE TABLE table_1376890_2 (
chroma_format VARCHAR,
name VARCHAR
) | SELECT chroma_format FROM table_1376890_2 WHERE name = "High profile" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24636,
3651,
2394,
834,
357,
41,
3,
10363,
51,
9,
834,
8995,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
125,
31,
7,
8,
3,
10363,
51... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
10363,
51,
9,
834,
8995,
21680,
953,
834,
24636,
3651,
2394,
834,
357,
549,
17444,
427,
564,
3274,
96,
21417,
3278,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which Ages have an Ofsted larger than 106172, and a School of oakgrove school? | CREATE TABLE table_name_45 (ages VARCHAR, ofsted VARCHAR, school VARCHAR) | SELECT ages FROM table_name_45 WHERE ofsted > 106172 AND school = "oakgrove school" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2128,
41,
2568,
584,
4280,
28027,
6,
13,
6265,
584,
4280,
28027,
6,
496,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
7526,
7,
43,
46,
1129,
6265,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
2568,
21680,
953,
834,
4350,
834,
2128,
549,
17444,
427,
13,
6265,
2490,
3,
16431,
27156,
3430,
496,
3274,
96,
32,
1639,
20254,
496,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the place that had a main railway station of banbury and a population bigger than 28,672? | CREATE TABLE table_65502 (
"Place" text,
"Population" real,
"Ceremonial County" text,
"Main Railway station" text,
"Motorway junction" text
) | SELECT "Place" FROM table_65502 WHERE "Population" > '28,672' AND "Main Railway station" = 'banbury' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4122,
1752,
357,
41,
96,
345,
11706,
121,
1499,
6,
96,
27773,
7830,
121,
490,
6,
96,
254,
17106,
32,
7419,
1334,
121,
1499,
6,
96,
21978,
29,
18025,
2478,
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,
345,
11706,
121,
21680,
953,
834,
4122,
1752,
357,
549,
17444,
427,
96,
27773,
7830,
121,
2490,
3,
31,
2577,
6,
3708,
357,
31,
3430,
96,
21978,
29,
18025,
2478,
121,
3274,
3,
31,
3478,
7165,
31,
1,
-100,
-100,... |
What's the HR number when the LMS number is 14758? | CREATE TABLE table_name_36 (hr_no VARCHAR, lms_no VARCHAR) | SELECT hr_no FROM table_name_36 WHERE lms_no = 14758 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3420,
41,
107,
52,
834,
29,
32,
584,
4280,
28027,
6,
3,
40,
51,
7,
834,
29,
32,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
31,
7,
8,
8383,
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,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
107,
52,
834,
29,
32,
21680,
953,
834,
4350,
834,
3420,
549,
17444,
427,
3,
40,
51,
7,
834,
29,
32,
3274,
3,
24719,
3449,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Get me the number of married patients who have been diagnosed with uncontrolled diabetes with hyperosmolarity, type II or unspecified. | 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 procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.marital_status = "MARRIED" AND diagnoses.short_title = "DMII hprosmlr uncontrold" | [
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,
5... |
A bar chart for what are the number of the dates of transactions with at least 100 share count or amount bigger than 100?, I want to display Y-axis in ascending order. | CREATE TABLE Investors (
investor_id INTEGER,
Investor_details VARCHAR(255)
)
CREATE TABLE Purchases (
purchase_transaction_id INTEGER,
purchase_details VARCHAR(255)
)
CREATE TABLE Ref_Transaction_Types (
transaction_type_code VARCHAR(10),
transaction_type_description VARCHAR(80)
)
CREATE TAB... | SELECT date_of_transaction, COUNT(date_of_transaction) FROM Transactions WHERE share_count >= 100 OR amount_of_transaction >= 100 ORDER BY COUNT(date_of_transaction) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
16873,
7,
41,
12024,
834,
23,
26,
3,
21342,
17966,
6,
16873,
834,
221,
5756,
7,
584,
4280,
28027,
599,
25502,
61,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
14839,
7... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
833,
834,
858,
834,
7031,
4787,
6,
2847,
17161,
599,
5522,
834,
858,
834,
7031,
4787,
61,
21680,
21469,
7,
549,
17444,
427,
698,
834,
13362,
2490,
2423,
910,
4674,
866,
834,
858,
834,
7031,
4787,
2490,
2423,
910,
46... |
give me the number of patients whose admission year is less than 2155 and diagnoses long title is other specified gastritis, with hemorrhage? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.admityear < "2155" AND diagnoses.long_title = "Other specified gastritis, with hemorrhage" | [
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... |
For those employees who was hired before 2002-06-21, return a bar chart about the distribution of hire_date and the average of department_id bin hire_date by weekday, list by the Y in ascending please. | CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
... | SELECT HIRE_DATE, AVG(DEPARTMENT_ID) FROM employees WHERE HIRE_DATE < '2002-06-21' ORDER BY AVG(DEPARTMENT_ID) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1440,
41,
2847,
17161,
11824,
834,
4309,
3,
4331,
4059,
16426,
6,
2847,
17161,
11824,
834,
567,
17683,
3,
4331,
4059,
599,
2445,
201,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
1714,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
454,
14132,
834,
308,
6048,
6,
71,
17217,
599,
5596,
19846,
11810,
834,
4309,
61,
21680,
1652,
549,
17444,
427,
454,
14132,
834,
308,
6048,
3,
2,
3,
31,
24898,
18,
5176,
16539,
31,
4674,
11300,
272,
476,
71,
17217,
... |
How many capacities are possible for the 1.6 Duratec model/engine? | CREATE TABLE table_1212189_1 (capacity VARCHAR, model_engine VARCHAR) | SELECT COUNT(capacity) FROM table_1212189_1 WHERE model_engine = "1.6 Duratec" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
2122,
25312,
834,
536,
41,
4010,
9,
6726,
584,
4280,
28027,
6,
825,
834,
20165,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
23875,
33,
487,
21,
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,
2847,
17161,
599,
4010,
9,
6726,
61,
21680,
953,
834,
2122,
2122,
25312,
834,
536,
549,
17444,
427,
825,
834,
20165,
3274,
96,
15062,
970,
2206,
75,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How did Tim Herron place? | CREATE TABLE table_name_83 (place VARCHAR, player VARCHAR) | SELECT place FROM table_name_83 WHERE player = "tim herron" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4591,
41,
4687,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
410,
4485,
8816,
106,
286,
58,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
286,
21680,
953,
834,
4350,
834,
4591,
549,
17444,
427,
1959,
3274,
96,
2998,
160,
52,
106,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Score F–A of 3–0, and a Date of 31 july 2007 had what opponents? | CREATE TABLE table_name_13 (opponents VARCHAR, score_f_a VARCHAR, date VARCHAR) | SELECT opponents FROM table_name_13 WHERE score_f_a = "3–0" AND date = "31 july 2007" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2368,
41,
32,
102,
9977,
7,
584,
4280,
28027,
6,
2604,
834,
89,
834,
9,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
17763,
377... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
16383,
21680,
953,
834,
4350,
834,
2368,
549,
17444,
427,
2604,
834,
89,
834,
9,
3274,
96,
519,
104,
632,
121,
3430,
833,
3274,
96,
3341,
3,
2047,
120,
4101,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the loss of the game attended by 29,704? | CREATE TABLE table_name_21 (
loss VARCHAR,
attendance VARCHAR
) | SELECT loss FROM table_name_21 WHERE attendance = "29,704" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2658,
41,
1453,
584,
4280,
28027,
6,
11364,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1453,
13,
8,
467,
5526,
57,
14405,
2518,
591,
58,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1453,
21680,
953,
834,
4350,
834,
2658,
549,
17444,
427,
11364,
3274,
96,
3166,
6,
2518,
20364,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What's the sum of all phil mickelson's game scores? | CREATE TABLE table_name_36 (
score INTEGER,
player VARCHAR
) | SELECT SUM(score) FROM table_name_36 WHERE player = "phil mickelson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3420,
41,
2604,
3,
21342,
17966,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
31,
7,
8,
4505,
13,
66,
3,
18118,
1337,
15259,
739,
31,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
180,
6122,
599,
7,
9022,
61,
21680,
953,
834,
4350,
834,
3420,
549,
17444,
427,
1959,
3274,
96,
18118,
1337,
15259,
739,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
For those records from the products and each product's manufacturer, return a bar chart about the distribution of name and the sum of manufacturer , and group by attribute name, show in descending by the Y-axis. | CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
)
CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
) | SELECT T2.Name, T1.Manufacturer FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY T2.Name ORDER BY T1.Manufacturer DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
15248,
7,
41,
3636,
3,
21342,
17966,
6,
5570,
584,
4280,
28027,
599,
25502,
201,
3642,
19973,
584,
4280,
28027,
599,
25502,
201,
3,
19145,
584,
4280,
28027,
599,
25502,
201,
19764,
17833... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
332,
4416,
23954,
6,
332,
5411,
7296,
76,
8717,
450,
49,
21680,
7554,
6157,
332,
536,
3,
15355,
3162,
15248,
7,
6157,
332,
357,
9191,
332,
5411,
7296,
76,
8717,
450,
49,
3274,
332,
4416,
22737,
350,
4630,
6880,
272,... |
How many clubs have tries for count of 50? | CREATE TABLE table_17859 (
"Club" text,
"Played" text,
"Won" text,
"Drawn" text,
"Lost" text,
"Points for" text,
"Points against" text,
"Tries for" text,
"Tries against" text,
"Try bonus" text,
"Losing bonus" text,
"Points" text
) | SELECT COUNT("Played") FROM table_17859 WHERE "Tries for" = '50' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
27640,
3390,
41,
96,
254,
11158,
121,
1499,
6,
96,
15800,
15,
26,
121,
1499,
6,
96,
518,
106,
121,
1499,
6,
96,
308,
10936,
29,
121,
1499,
6,
96,
434,
3481,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
15800,
15,
26,
8512,
21680,
953,
834,
27640,
3390,
549,
17444,
427,
96,
382,
2593,
21,
121,
3274,
3,
31,
1752,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Which champion has sentosa golf club as the tournament location? | CREATE TABLE table_name_55 (
champion VARCHAR,
tournament_location VARCHAR
) | SELECT champion FROM table_name_55 WHERE tournament_location = "sentosa golf club" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3769,
41,
6336,
584,
4280,
28027,
6,
5892,
834,
14836,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
6336,
65,
1622,
32,
7,
9,
4319,
1886,
38,
8,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
6336,
21680,
953,
834,
4350,
834,
3769,
549,
17444,
427,
5892,
834,
14836,
3274,
96,
5277,
32,
7,
9,
4319,
1886,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the minimum derby county goals | CREATE TABLE table_19949 (
"Competition" text,
"Played" real,
"Derby County" real,
"Draw" real,
"Nottingham Forest" real,
"Derby County Goals" real,
"Nottingham Forest Goals" real
) | SELECT MIN("Derby County Goals") FROM table_19949 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19479,
3647,
41,
96,
5890,
4995,
4749,
121,
1499,
6,
96,
15800,
15,
26,
121,
490,
6,
96,
308,
49,
969,
1334,
121,
490,
6,
96,
308,
10936,
121,
490,
6,
96,
10358,
17,
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,
3,
17684,
599,
121,
308,
49,
969,
1334,
17916,
7,
8512,
21680,
953,
834,
19479,
3647,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the city of the Museum that houses the specimen discovered by Jane Solem? | CREATE TABLE table_name_28 (museum VARCHAR, discoverer VARCHAR) | SELECT museum AS city FROM table_name_28 WHERE discoverer = "jane solem" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2577,
41,
25581,
584,
4280,
28027,
6,
2928,
49,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
690,
13,
8,
3312,
24,
4790,
8,
19622,
3883,
57,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7071,
6157,
690,
21680,
953,
834,
4350,
834,
2577,
549,
17444,
427,
2928,
49,
3274,
96,
7066,
15,
4199,
51,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What were the drawn with points against at 416? | CREATE TABLE table_12828723_5 (
drawn VARCHAR,
points_against VARCHAR
) | SELECT drawn FROM table_12828723_5 WHERE points_against = "416" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
4613,
4225,
2773,
834,
755,
41,
6796,
584,
4280,
28027,
6,
979,
834,
9,
16720,
7,
17,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
130,
8,
6796,
28,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
6796,
21680,
953,
834,
2122,
4613,
4225,
2773,
834,
755,
549,
17444,
427,
979,
834,
9,
16720,
7,
17,
3274,
96,
591,
2938,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Visa 4 has besart berisha as Visa 1? | CREATE TABLE table_name_42 (visa_4 VARCHAR, visa_1 VARCHAR) | SELECT visa_4 FROM table_name_42 WHERE visa_1 = "besart berisha" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4165,
41,
3466,
9,
834,
591,
584,
4280,
28027,
6,
8359,
834,
536,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
14203,
314,
65,
36,
7,
1408,
3,
1152... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
8359,
834,
591,
21680,
953,
834,
4350,
834,
4165,
549,
17444,
427,
8359,
834,
536,
3274,
96,
346,
7,
1408,
3,
1152,
1273,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What numbered episode is titled 'naomi gaines'? | CREATE TABLE table_73971 (
"No." real,
"#" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Patient Portrayer" text,
"Original air date" text,
"Production code" real
) | SELECT "No." FROM table_73971 WHERE "Title" = 'Naomi Gaines' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4552,
4327,
536,
41,
96,
4168,
535,
490,
6,
96,
4663,
121,
490,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
15,
26,
57,
121,
1499,
6,
96,
24965,
324,
57,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
4168,
535,
21680,
953,
834,
4552,
4327,
536,
549,
17444,
427,
96,
382,
155,
109,
121,
3274,
3,
31,
567,
9,
32,
51,
23,
22097,
15,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
what is the number of patients whose primary disease is pituitary bleed and drug route is ou? | 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 prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.diagnosis = "PITUITARY BLEED" AND prescriptions.route = "OU" | [
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,
7744,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7744,
7,
5,
8399,
51,
834,
23,
26,
549... |
What are the details of all products? | CREATE TABLE order_items (
order_id number,
product_id number,
order_quantity text
)
CREATE TABLE customer_contact_channels (
customer_id number,
channel_code text,
active_from_date time,
active_to_date time,
contact_number text
)
CREATE TABLE customer_orders (
order_id number,
... | SELECT DISTINCT product_details FROM products | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
455,
834,
23,
3524,
7,
41,
455,
834,
23,
26,
381,
6,
556,
834,
23,
26,
381,
6,
455,
834,
13158,
485,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
884,
834,
2... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
15438,
25424,
6227,
556,
834,
221,
5756,
7,
21680,
494,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the score of the home team of carlton? | CREATE TABLE table_name_60 (home_team VARCHAR) | SELECT home_team AS score FROM table_name_60 WHERE home_team = "carlton" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3328,
41,
5515,
834,
11650,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2604,
13,
8,
234,
372,
13,
443,
7377,
58,
1,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
234,
834,
11650,
6157,
2604,
21680,
953,
834,
4350,
834,
3328,
549,
17444,
427,
234,
834,
11650,
3274,
96,
1720,
7377,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Count the number of Annual Meeting events that took place in the region of the United Kingdom. | CREATE TABLE party (
party_id number,
minister text,
took_office text,
left_office text,
region_id number,
party_name text
)
CREATE TABLE region (
region_id number,
region_name text,
date text,
label text,
format text,
catalogue text
)
CREATE TABLE member (
member_i... | SELECT COUNT(*) FROM region AS t1 JOIN party AS t2 ON t1.region_id = t2.region_id JOIN party_events AS t3 ON t2.party_id = t3.party_id WHERE t1.region_name = "United Kingdom" AND t3.event_name = "Annaual Meeting" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1088,
41,
1088,
834,
23,
26,
381,
6,
6323,
1499,
6,
808,
834,
19632,
1499,
6,
646,
834,
19632,
1499,
6,
1719,
834,
23,
26,
381,
6,
1088,
834,
4350,
1499,
3,
61,
3,
32102,
32103,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
1935,
61,
21680,
1719,
6157,
3,
17,
536,
3,
15355,
3162,
1088,
6157,
3,
17,
357,
9191,
3,
17,
5411,
18145,
834,
23,
26,
3274,
3,
17,
4416,
18145,
834,
23,
26,
3,
15355,
3162,
1088,
834,
15,
216... |
How many year was the venue in stockholm, sweden used? | CREATE TABLE table_name_65 (
year VARCHAR,
venue VARCHAR
) | SELECT COUNT(year) FROM table_name_65 WHERE venue = "stockholm, sweden" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4122,
41,
215,
584,
4280,
28027,
6,
5669,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
215,
47,
8,
5669,
16,
1519,
2831,
51,
6,
3,
7,
1123... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
1201,
61,
21680,
953,
834,
4350,
834,
4122,
549,
17444,
427,
5669,
3274,
96,
7149,
2831,
51,
6,
3,
7,
1123,
537,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Name the school for Season Outcome of loss in first round of div. i playoffs | CREATE TABLE table_name_73 (school VARCHAR, season_outcome VARCHAR) | SELECT school FROM table_name_73 WHERE season_outcome = "loss in first round of div. i playoffs" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4552,
41,
6646,
584,
4280,
28027,
6,
774,
834,
670,
287,
15,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
496,
21,
7960,
3387,
287,
15,
13,
1453... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
496,
21680,
953,
834,
4350,
834,
4552,
549,
17444,
427,
774,
834,
670,
287,
15,
3274,
96,
2298,
7,
16,
166,
1751,
13,
3,
8481,
5,
3,
23,
15289,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
provide the number of patients whose ethnicity is black/african american and diagnoses icd9 code is 34982? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id t... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.ethnicity = "BLACK/AFRICAN AMERICAN" AND diagnoses.icd9_code = "34982" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
What was the score on march 11? | CREATE TABLE table_name_50 (score VARCHAR, date VARCHAR) | SELECT score FROM table_name_50 WHERE date = "march 11" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1752,
41,
7,
9022,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2604,
30,
10556,
850,
58,
1,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
21680,
953,
834,
4350,
834,
1752,
549,
17444,
427,
833,
3274,
96,
51,
7064,
850,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many played where the points were 80? | CREATE TABLE table_12807904_5 (
played VARCHAR,
points VARCHAR
) | SELECT played FROM table_12807904_5 WHERE points = "80" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
2079,
4440,
6348,
834,
755,
41,
1944,
584,
4280,
28027,
6,
979,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
1944,
213,
8,
979,
130,
2775,
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,
1944,
21680,
953,
834,
2122,
2079,
4440,
6348,
834,
755,
549,
17444,
427,
979,
3274,
96,
2079,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many total years did sir patrick duncan serve in office ? | CREATE TABLE table_203_89 (
id number,
"#" number,
"name\n(birth-death)" text,
"took office" text,
"left office" text,
"monarch" text,
"prime minister" text
) | SELECT "left office" - "took office" FROM table_203_89 WHERE "name\n(birth-death)" = 'sir patrick duncan' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
3914,
41,
3,
23,
26,
381,
6,
96,
4663,
121,
381,
6,
96,
4350,
2,
29,
599,
20663,
18,
221,
9,
189,
61,
121,
1499,
6,
96,
235,
1825,
828,
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,
17068,
828,
121,
3,
18,
96,
235,
1825,
828,
121,
21680,
953,
834,
23330,
834,
3914,
549,
17444,
427,
96,
4350,
2,
29,
599,
20663,
18,
221,
9,
189,
61,
121,
3274,
3,
31,
7,
23,
52,
6234,
5206,
146,
29,
1608... |
What Report has the Date September 3, 2005? | CREATE TABLE table_name_8 (
report VARCHAR,
date VARCHAR
) | SELECT report FROM table_name_8 WHERE date = "september 3, 2005" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
927,
41,
934,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
3750,
65,
8,
7678,
1600,
6180,
3105,
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,
934,
21680,
953,
834,
4350,
834,
927,
549,
17444,
427,
833,
3274,
96,
7,
6707,
18247,
6180,
3105,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What township is located at longitude -99.287270? | CREATE TABLE table_18600760_9 (township VARCHAR, longitude VARCHAR) | SELECT township FROM table_18600760_9 WHERE longitude = "-99.287270" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24700,
4560,
3328,
834,
1298,
41,
3540,
2009,
584,
4280,
28027,
6,
307,
20341,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
1511,
2009,
19,
1069,
44,
307,
20341,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1511,
2009,
21680,
953,
834,
24700,
4560,
3328,
834,
1298,
549,
17444,
427,
307,
20341,
3274,
96,
18,
3264,
5,
357,
4225,
17485,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
List the company name and rank for all companies in the decreasing order of their sales in a bar chart. | CREATE TABLE station_company (
Station_ID int,
Company_ID int,
Rank_of_the_Year int
)
CREATE TABLE company (
Company_ID int,
Rank int,
Company text,
Headquarters text,
Main_Industry text,
Sales_billion real,
Profits_billion real,
Assets_billion real,
Market_Value real
)
... | SELECT Company, Rank FROM company ORDER BY Sales_billion DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2478,
834,
29179,
41,
5939,
834,
4309,
16,
17,
6,
1958,
834,
4309,
16,
17,
6,
3,
22557,
834,
858,
834,
532,
834,
476,
2741,
16,
17,
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,
1958,
6,
3,
22557,
21680,
349,
4674,
11300,
272,
476,
7107,
834,
115,
14916,
309,
25067,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is Samuel Smith's party? | CREATE TABLE table_2668329_11 (
party VARCHAR,
incumbent VARCHAR
) | SELECT party FROM table_2668329_11 WHERE incumbent = "Samuel Smith" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
3651,
519,
3166,
834,
2596,
41,
1088,
584,
4280,
28027,
6,
28406,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
15718,
3931,
31,
7,
1088,
58,
1,
0,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1088,
21680,
953,
834,
2688,
3651,
519,
3166,
834,
2596,
549,
17444,
427,
28406,
3274,
96,
134,
265,
76,
15,
40,
3931,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the lifespan of Stefanie Rabatsch? | CREATE TABLE table_name_93 (life VARCHAR, name VARCHAR) | SELECT life FROM table_name_93 WHERE name = "stefanie rabatsch" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4271,
41,
4597,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
27617,
13,
14189,
23,
15,
22730,
9,
10904,
58,
1,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
280,
21680,
953,
834,
4350,
834,
4271,
549,
17444,
427,
564,
3274,
96,
7,
24018,
23,
15,
3,
7093,
9,
10904,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Name the total fat which has a polyunsaturated fat of 11g and monounsaturated fat of 45g | CREATE TABLE table_name_60 (
total_fat VARCHAR,
polyunsaturated_fat VARCHAR,
monounsaturated_fat VARCHAR
) | SELECT total_fat FROM table_name_60 WHERE polyunsaturated_fat = "11g" AND monounsaturated_fat = "45g" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3328,
41,
792,
834,
6589,
584,
4280,
28027,
6,
4251,
202,
7,
6010,
920,
834,
6589,
584,
4280,
28027,
6,
7414,
202,
7,
6010,
920,
834,
6589,
584,
4280,
28027,
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,
792,
834,
6589,
21680,
953,
834,
4350,
834,
3328,
549,
17444,
427,
4251,
202,
7,
6010,
920,
834,
6589,
3274,
96,
2596,
122,
121,
3430,
7414,
202,
7,
6010,
920,
834,
6589,
3274,
96,
2128,
122,
121,
1,
-100,
-100,
-... |
What is the 2007 value at the 2012 Grand Slam Tournaments? | CREATE TABLE table_name_26 (
Id VARCHAR
) | SELECT 2007 FROM table_name_26 WHERE 2012 = "grand slam tournaments" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2688,
41,
27,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
4101,
701,
44,
8,
1673,
2698,
29291,
20502,
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,
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,
4101,
21680,
953,
834,
4350,
834,
2688,
549,
17444,
427,
1673,
3274,
96,
15448,
3,
7,
40,
265,
5892,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the affiliation when the institution was ohio christian university? | CREATE TABLE table_73631 (
"Institution" text,
"Location" text,
"Team Name" text,
"Founded" real,
"Affiliation" text,
"Enrollment" real,
"Year Joined" real
) | SELECT "Affiliation" FROM table_73631 WHERE "Institution" = 'Ohio Christian University' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4552,
3891,
536,
41,
96,
1570,
17448,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
18699,
5570,
121,
1499,
6,
96,
20100,
121,
490,
6,
96,
188,
89,
8027,
23,
25... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
89,
8027,
23,
257,
121,
21680,
953,
834,
4552,
3891,
536,
549,
17444,
427,
96,
1570,
17448,
121,
3274,
3,
31,
15046,
23,
32,
2826,
636,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Number of people 1991 has a Percent of Slovenes 1991 of 14.4%? | CREATE TABLE table_name_67 (
number_of_people_1991 INTEGER,
percent_of_slovenes_1991 VARCHAR
) | SELECT MAX(number_of_people_1991) FROM table_name_67 WHERE percent_of_slovenes_1991 = "14.4%" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3708,
41,
381,
834,
858,
834,
16588,
834,
2294,
4729,
3,
21342,
17966,
6,
1093,
834,
858,
834,
7,
5850,
35,
15,
7,
834,
2294,
4729,
584,
4280,
28027,
3,
61,
3,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
5525,
1152,
834,
858,
834,
16588,
834,
19479,
6982,
21680,
953,
834,
4350,
834,
3708,
549,
17444,
427,
1093,
834,
858,
834,
7,
5850,
35,
15,
7,
834,
2294,
4729,
3274,
96,
2534,
5,
5988,
121,
1,
-100,... |
What is the nickname of the team whose 2013/2014 enrollment is 436? | CREATE TABLE table_18304058_2 (
nickname_s_ VARCHAR,
enrollment__2013_14_ VARCHAR
) | SELECT nickname_s_ FROM table_18304058_2 WHERE enrollment__2013_14_ = 436 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2606,
1458,
2445,
3449,
834,
357,
41,
24649,
834,
7,
834,
584,
4280,
28027,
6,
17938,
834,
834,
11138,
834,
2534,
834,
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,
0,
0,
0,
0... | [
3,
23143,
14196,
24649,
834,
7,
834,
21680,
953,
834,
2606,
1458,
2445,
3449,
834,
357,
549,
17444,
427,
17938,
834,
834,
11138,
834,
2534,
834,
3274,
314,
3420,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What date did they play in Cleveland Municipal Stadium? | CREATE TABLE table_14423274_3 (
date VARCHAR,
game_site VARCHAR
) | SELECT date FROM table_14423274_3 WHERE game_site = "Cleveland Municipal Stadium" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
20885,
23188,
4581,
834,
519,
41,
833,
584,
4280,
28027,
6,
467,
834,
3585,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
833,
410,
79,
577,
16,
13160,
16492,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
833,
21680,
953,
834,
20885,
23188,
4581,
834,
519,
549,
17444,
427,
467,
834,
3585,
3274,
96,
254,
4563,
232,
16492,
12750,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Production Cost with a Date that is february 2000? | CREATE TABLE table_40002 (
"Date" text,
"Title" text,
"Director" text,
"Producer" text,
"Production Cost" text,
"Singapore Gross" text
) | SELECT "Production Cost" FROM table_40002 WHERE "Date" = 'february 2000' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5548,
4305,
41,
96,
308,
342,
121,
1499,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
127,
121,
1499,
6,
96,
3174,
4817,
49,
121,
1499,
6,
96,
3174,
8291,
6409,
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,
3174,
8291,
6409,
121,
21680,
953,
834,
5548,
4305,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
89,
15,
9052,
1208,
2766,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the lowest combined mpg in the US for the A6 transmission, a CO2 g/km under 303, engine capacity over 2461, and L/100km urban (cold) of 15.9? | CREATE TABLE table_name_11 (mpg_us_combined INTEGER, l_100km_urban__cold_ VARCHAR, engine_capacity VARCHAR, transmission VARCHAR, co_2_g_km VARCHAR) | SELECT MIN(mpg_us_combined) FROM table_name_11 WHERE transmission = "a6" AND co_2_g_km < 303 AND engine_capacity > 2461 AND l_100km_urban__cold_ = 15.9 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2596,
41,
1167,
122,
834,
302,
834,
287,
12712,
26,
3,
21342,
17966,
6,
3,
40,
834,
2915,
5848,
834,
19413,
834,
834,
3297,
26,
834,
584,
4280,
28027,
6,
1948,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1167,
122,
834,
302,
834,
287,
12712,
26,
61,
21680,
953,
834,
4350,
834,
2596,
549,
17444,
427,
5790,
3274,
96,
9,
948,
121,
3430,
576,
834,
357,
834,
122,
834,
5848,
3,
2,
3,
23335,
3430,
1948,
... |
What is the lowest number for the University of Dublin, having and administrative panel of 3, and a Cultural and Educational panel less than 2? | CREATE TABLE table_34677 (
"Administrative Panel" real,
"Agricultural Panel" real,
"Cultural and Educational Panel" real,
"Industrial and Commercial Panel" real,
"Labour Panel" real,
"National University of Ireland" real,
"University of Dublin" real,
"Nominated by the Taoiseach" real,
... | SELECT MIN("University of Dublin") FROM table_34677 WHERE "Administrative Panel" = '3' AND "Cultural and Educational Panel" < '2' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
4448,
4013,
41,
96,
16313,
343,
52,
1528,
9871,
121,
490,
6,
96,
24354,
9871,
121,
490,
6,
96,
254,
83,
17,
9709,
11,
19173,
9871,
121,
490,
6,
96,
1570,
8655,
17,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
8313,
485,
13,
14112,
8512,
21680,
953,
834,
519,
4448,
4013,
549,
17444,
427,
96,
16313,
343,
52,
1528,
9871,
121,
3274,
3,
31,
519,
31,
3430,
96,
254,
83,
17,
9709,
11,
19173,
9871,
121,
3,
... |
How many people attended the game in week 13? | CREATE TABLE table_name_60 (attendance VARCHAR, week VARCHAR) | SELECT attendance FROM table_name_60 WHERE week = 13 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3328,
41,
15116,
663,
584,
4280,
28027,
6,
471,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
151,
5526,
8,
467,
16,
471,
1179,
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,
11364,
21680,
953,
834,
4350,
834,
3328,
549,
17444,
427,
471,
3274,
1179,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
presence of systolic blood pressure > 190 or diastolic pressure > 95 | CREATE TABLE table_dev_2 (
"id" int,
"nutrient_absorption" bool,
"systolic_blood_pressure_sbp" int,
"active_metabolic" bool,
"hepatic_disease" bool,
"surgery" bool,
"diastolic_blood_pressure_dbp" int,
"gastrointestinal_disease" bool,
"organ_failure" bool,
"NOUSE" float
) | SELECT * FROM table_dev_2 WHERE systolic_blood_pressure_sbp > 190 OR diastolic_blood_pressure_dbp > 95 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
9776,
834,
357,
41,
96,
23,
26,
121,
16,
17,
6,
96,
8631,
295,
834,
9,
115,
15016,
121,
3,
12840,
40,
6,
96,
7,
63,
7,
235,
2176,
834,
27798,
834,
26866,
834,
7,
115,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
9776,
834,
357,
549,
17444,
427,
3,
7,
63,
7,
235,
2176,
834,
27798,
834,
26866,
834,
7,
115,
102,
2490,
3,
11776,
4674,
1227,
9,
7,
235,
2176,
834,
27798,
834,
26866,
834,
26,
115,
102,
2... |
For those records from the products and each product's manufacturer, a bar chart shows the distribution of headquarter and the average of revenue , and group by attribute headquarter, list by the X-axis in desc. | CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
)
CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
) | SELECT Headquarter, AVG(Revenue) FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY Headquarter ORDER BY Headquarter DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
15248,
7,
41,
3636,
3,
21342,
17966,
6,
5570,
584,
4280,
28027,
599,
25502,
201,
3642,
19973,
584,
4280,
28027,
599,
25502,
201,
3,
19145,
584,
4280,
28027,
599,
25502,
201,
19764,
17833... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3642,
19973,
6,
71,
17217,
599,
1649,
15098,
61,
21680,
7554,
6157,
332,
536,
3,
15355,
3162,
15248,
7,
6157,
332,
357,
9191,
332,
5411,
7296,
76,
8717,
450,
49,
3274,
332,
4416,
22737,
350,
4630,
6880,
272,
476,
36... |
What party was Kevin Brady? | CREATE TABLE table_1341395_44 (party VARCHAR, incumbent VARCHAR) | SELECT party FROM table_1341395_44 WHERE incumbent = "Kevin Brady" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23747,
2368,
3301,
834,
3628,
41,
8071,
584,
4280,
28027,
6,
28406,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
1088,
47,
8595,
24927,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1088,
21680,
953,
834,
23747,
2368,
3301,
834,
3628,
549,
17444,
427,
28406,
3274,
96,
439,
15,
2494,
24927,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the minimum losses for the Kansas City Chiefs? | CREATE TABLE table_19451173_1 (
losses INTEGER,
team VARCHAR
) | SELECT MIN(losses) FROM table_19451173_1 WHERE team = "Kansas City Chiefs" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2294,
2128,
2596,
4552,
834,
536,
41,
8467,
3,
21342,
17966,
6,
372,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2559,
8467,
21,
8,
10585,
896,
5116... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3,
17684,
599,
2298,
2260,
61,
21680,
953,
834,
2294,
2128,
2596,
4552,
834,
536,
549,
17444,
427,
372,
3274,
96,
439,
3247,
9,
7,
896,
5116,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Show the countries that have managers of age above 50 or below 46, and count them by a bar chart, could you rank the number of country from high to low order please? | CREATE TABLE manager (
Manager_ID int,
Name text,
Country text,
Working_year_starts text,
Age int,
Level int
)
CREATE TABLE train (
Train_ID int,
Train_Num text,
Name text,
From text,
Arrival text,
Railway_ID int
)
CREATE TABLE railway_manage (
Railway_ID int,
M... | SELECT Country, COUNT(Country) FROM manager WHERE Age > 50 OR Age < 46 GROUP BY Country ORDER BY COUNT(Country) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2743,
41,
3440,
834,
4309,
16,
17,
6,
5570,
1499,
6,
6993,
1499,
6,
7301,
834,
1201,
834,
10208,
7,
1499,
6,
7526,
16,
17,
6,
7166,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
43... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
6993,
6,
2847,
17161,
599,
10628,
651,
61,
21680,
2743,
549,
17444,
427,
7526,
2490,
943,
4674,
7526,
3,
2,
9668,
350,
4630,
6880,
272,
476,
6993,
4674,
11300,
272,
476,
2847,
17161,
599,
10628,
651,
61,
309,
25067,
... |
When the change (2011 to 2012) is -0.1% what is the country? | CREATE TABLE table_14752049_6 (
country VARCHAR,
change__2011_to_2012_ VARCHAR
) | SELECT country FROM table_14752049_6 WHERE change__2011_to_2012_ = "-0.1%" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24719,
25356,
3647,
834,
948,
41,
684,
584,
4280,
28027,
6,
483,
834,
834,
13907,
834,
235,
834,
12172,
834,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
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,
684,
21680,
953,
834,
24719,
25356,
3647,
834,
948,
549,
17444,
427,
483,
834,
834,
13907,
834,
235,
834,
12172,
834,
3274,
96,
18,
16029,
1454,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What country did the project, Bonga SW; Aparo with a shell operator take place? | CREATE TABLE table_name_53 (
country VARCHAR,
operator VARCHAR,
project_name VARCHAR
) | SELECT country FROM table_name_53 WHERE operator = "shell" AND project_name = "bonga sw; aparo" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4867,
41,
684,
584,
4280,
28027,
6,
7221,
584,
4280,
28027,
6,
516,
834,
4350,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
684,
410,
8,
516,
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,
0,
0,
0,
0... | [
3,
23143,
14196,
684,
21680,
953,
834,
4350,
834,
4867,
549,
17444,
427,
7221,
3274,
96,
17346,
121,
3430,
516,
834,
4350,
3274,
96,
115,
2444,
9,
3,
7,
210,
117,
9072,
32,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
what is the number of varsity sports at maryland | CREATE TABLE table_204_442 (
id number,
"institution" text,
"location" text,
"enrollment" number,
"nickname" text,
"varsity\nsports" number,
"rugby\nsince" text,
"head coach" text
) | SELECT "varsity\nsports" FROM table_204_442 WHERE "institution" = 'maryland' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
3628,
357,
41,
3,
23,
26,
381,
6,
96,
77,
17448,
121,
1499,
6,
96,
14836,
121,
1499,
6,
96,
35,
4046,
297,
121,
381,
6,
96,
11191,
4350,
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,
31336,
2,
29,
6661,
7,
121,
21680,
953,
834,
26363,
834,
3628,
357,
549,
17444,
427,
96,
77,
17448,
121,
3274,
3,
31,
1635,
28900,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Show names of actors in descending order of the year their musical is awarded. | CREATE TABLE musical (Musical_ID VARCHAR, Year VARCHAR); CREATE TABLE actor (Name VARCHAR, Musical_ID VARCHAR) | SELECT T1.Name FROM actor AS T1 JOIN musical AS T2 ON T1.Musical_ID = T2.Musical_ID ORDER BY T2.Year DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4183,
41,
29035,
138,
834,
4309,
584,
4280,
28027,
6,
2929,
584,
4280,
28027,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
7556,
41,
23954,
584,
4280,
28027,
6,
22307,
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,
23954,
21680,
7556,
6157,
332,
536,
3,
15355,
3162,
4183,
6157,
332,
357,
9191,
332,
5411,
29035,
138,
834,
4309,
3274,
332,
4416,
29035,
138,
834,
4309,
4674,
11300,
272,
476,
332,
4416,
476,
2741,
309,
25... |
What could a spanish coronel be addressed as in the commonwealth military? | CREATE TABLE table_18 (
"Equivalent NATO Rank Code" text,
"Rank in Spanish" text,
"Rank in English" text,
"Commonwealth equivalent" text,
"US Air Force equivalent" text
) | SELECT "Commonwealth equivalent" FROM table_18 WHERE "Rank in Spanish" = 'Coronel' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2606,
41,
96,
427,
1169,
15592,
17873,
3,
22557,
3636,
121,
1499,
6,
96,
22557,
16,
5093,
121,
1499,
6,
96,
22557,
16,
1566,
121,
1499,
6,
96,
10205,
106,
1123,
138,
189,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
10205,
106,
1123,
138,
189,
7072,
121,
21680,
953,
834,
2606,
549,
17444,
427,
96,
22557,
16,
5093,
121,
3274,
3,
31,
13026,
782,
40,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the yield in NTS Area U2R when the purpose is weapons development? | CREATE TABLE table_47769 (
"Name" text,
"Location" text,
"Elevation + Height" text,
"Delivery" text,
"Purpose" text,
"Yield" text
) | SELECT "Yield" FROM table_47769 WHERE "Purpose" = 'weapons development' AND "Location" = 'nts area u2r' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
4013,
3951,
41,
96,
23954,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
427,
10912,
257,
1768,
24231,
121,
1499,
6,
96,
2962,
7591,
651,
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,
476,
23,
8804,
121,
21680,
953,
834,
591,
4013,
3951,
549,
17444,
427,
96,
345,
450,
2748,
15,
121,
3274,
3,
31,
1123,
9,
5041,
7,
606,
31,
3430,
96,
434,
32,
75,
257,
121,
3274,
3,
31,
29,
17,
7,
616,
3... |
What is the attendance when the opponent was the Houston Oilers? | CREATE TABLE table_name_47 (attendance VARCHAR, opponent VARCHAR) | SELECT attendance FROM table_name_47 WHERE opponent = "houston oilers" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4177,
41,
15116,
663,
584,
4280,
28027,
6,
15264,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
11364,
116,
8,
15264,
47,
8,
8018,
6067,
277,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
11364,
21680,
953,
834,
4350,
834,
4177,
549,
17444,
427,
15264,
3274,
96,
9492,
4411,
1043,
277,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Which player won in 1987 and ended with a score of +9? | CREATE TABLE table_name_75 (total VARCHAR, to_par VARCHAR, year_s__won VARCHAR) | SELECT total FROM table_name_75 WHERE to_par = "+9" AND year_s__won = "1987" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3072,
41,
235,
1947,
584,
4280,
28027,
6,
12,
834,
1893,
584,
4280,
28027,
6,
215,
834,
7,
834,
834,
210,
106,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
3210... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
792,
21680,
953,
834,
4350,
834,
3072,
549,
17444,
427,
12,
834,
1893,
3274,
96,
1220,
1298,
121,
3430,
215,
834,
7,
834,
834,
210,
106,
3274,
96,
2294,
4225,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is primary disease and diagnoses icd9 code of subject name kelly gallardo? | 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 demographic.diagnosis, diagnoses.icd9_code FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Kelly Gallardo" | [
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,
14798,
5,
25930,
4844,
159,
6,
18730,
7,
5,
447,
26,
1298,
834,
4978,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
549,
17... |
Find all students taught by MARROTTE KIRK. Output first and last names of students. | CREATE TABLE list (
lastname text,
firstname text,
grade number,
classroom number
)
CREATE TABLE teachers (
lastname text,
firstname text,
classroom number
) | SELECT T1.firstname, T1.lastname FROM list AS T1 JOIN teachers AS T2 ON T1.classroom = T2.classroom WHERE T2.firstname = "MARROTTE" AND T2.lastname = "KIRK" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
570,
41,
336,
4350,
1499,
6,
166,
4350,
1499,
6,
2769,
381,
6,
4858,
381,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
3081,
41,
336,
4350,
1499,
6,
166,
4350,
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,
332,
5411,
14672,
4350,
6,
332,
5411,
5064,
4350,
21680,
570,
6157,
332,
536,
3,
15355,
3162,
3081,
6157,
332,
357,
9191,
332,
5411,
4057,
3082,
3274,
332,
4416,
4057,
3082,
549,
17444,
427,
332,
4416,
14672,
4350,
32... |
What is the highest number of League Cup goals that were scored by Hartlepool? | CREATE TABLE table_name_6 (league_cup_goals INTEGER, club VARCHAR) | SELECT MAX(league_cup_goals) FROM table_name_6 WHERE club = "hartlepool" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
29512,
834,
4658,
834,
839,
5405,
3,
21342,
17966,
6,
1886,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2030,
381,
13,
3815,
3802,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4800,
4,
599,
29512,
834,
4658,
834,
839,
5405,
61,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
1886,
3274,
96,
13626,
109,
13194,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is 2008, when 2006 is 'Grand Slam Tournaments'? | CREATE TABLE table_40792 (
"Tournament" text,
"2000" text,
"2001" text,
"2002" text,
"2003" text,
"2004" text,
"2005" text,
"2006" text,
"2007" text,
"2008" text,
"2009" text,
"2010" text,
"2011" text,
"2012" text
) | SELECT "2008" FROM table_40792 WHERE "2006" = 'grand slam tournaments' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2445,
4440,
357,
41,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
13527,
121,
1499,
6,
96,
23658,
121,
1499,
6,
96,
24898,
121,
1499,
6,
96,
23948,
121,
1499,
6,
96,
21653... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
16128,
121,
21680,
953,
834,
2445,
4440,
357,
549,
17444,
427,
96,
21196,
121,
3274,
3,
31,
15448,
3,
7,
40,
265,
5892,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What was the value in 2009 when 2005 was A for the Australian Open? | CREATE TABLE table_name_5 (
tournament VARCHAR
) | SELECT 2009 FROM table_name_5 WHERE 2005 = "a" AND tournament = "australian open" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
755,
41,
5892,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
701,
16,
2464,
116,
3105,
47,
71,
21,
8,
3746,
2384,
58,
1,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2464,
21680,
953,
834,
4350,
834,
755,
549,
17444,
427,
3105,
3274,
96,
9,
121,
3430,
5892,
3274,
96,
402,
3109,
9928,
539,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the average league goals that have 2 (1) as the total apps? | CREATE TABLE table_64901 (
"Name" text,
"Position" text,
"League Apps" text,
"League Goals" real,
"FA Cup Apps" real,
"FA Cup Goals" real,
"League Cup Apps" text,
"League Cup Goals" real,
"Total Apps" text,
"Total Goals" real
) | SELECT AVG("League Goals") FROM table_64901 WHERE "Total Apps" = '2 (1)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
2394,
536,
41,
96,
23954,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
2796,
9,
5398,
2276,
7,
121,
1499,
6,
96,
2796,
9,
5398,
17916,
7,
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,
71,
17217,
599,
121,
2796,
9,
5398,
17916,
7,
8512,
21680,
953,
834,
4389,
2394,
536,
549,
17444,
427,
96,
3696,
1947,
2276,
7,
121,
3274,
3,
31,
357,
5637,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What country scored 71-66-66-71=274? | CREATE TABLE table_name_32 (
country VARCHAR,
score VARCHAR
) | SELECT country FROM table_name_32 WHERE score = 71 - 66 - 66 - 71 = 274 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
684,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
684,
5799,
3,
4450,
18,
3539,
18,
3539,
18,
4450,
2423,
25... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
684,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
2604,
3274,
3,
4450,
3,
18,
3,
3539,
3,
18,
3,
3539,
3,
18,
3,
4450,
3274,
204,
4581,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees who was hired before 2002-06-21, visualize a bar chart about the distribution of hire_date and the average of employee_id bin hire_date by weekday, and order the average of employee id in asc order. | CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date... | SELECT HIRE_DATE, AVG(EMPLOYEE_ID) FROM employees WHERE HIRE_DATE < '2002-06-21' ORDER BY AVG(EMPLOYEE_ID) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1440,
41,
2847,
17161,
11824,
834,
4309,
3,
4331,
4059,
16426,
6,
2847,
17161,
11824,
834,
567,
17683,
3,
4331,
4059,
599,
2445,
201,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
1714,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
454,
14132,
834,
308,
6048,
6,
71,
17217,
599,
6037,
345,
5017,
476,
5080,
834,
4309,
61,
21680,
1652,
549,
17444,
427,
454,
14132,
834,
308,
6048,
3,
2,
3,
31,
24898,
18,
5176,
16539,
31,
4674,
11300,
272,
476,
7... |
Which countries have a scouting organization that was founded in 1926, and joined WOSM in 1930? | CREATE TABLE table_104858_1 (
country VARCHAR,
year_current_scouting_organization_joined_wosm VARCHAR,
year_member_organization_was_founded VARCHAR
) | SELECT country FROM table_104858_1 WHERE year_current_scouting_organization_joined_wosm = "1930" AND year_member_organization_was_founded = "1926" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1714,
3707,
3449,
834,
536,
41,
684,
584,
4280,
28027,
6,
215,
834,
14907,
834,
7,
3422,
1222,
834,
17939,
257,
834,
1927,
630,
26,
834,
210,
32,
7,
51,
584,
4280,
28027,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
684,
21680,
953,
834,
1714,
3707,
3449,
834,
536,
549,
17444,
427,
215,
834,
14907,
834,
7,
3422,
1222,
834,
17939,
257,
834,
1927,
630,
26,
834,
210,
32,
7,
51,
3274,
96,
2294,
1458,
121,
3430,
215,
834,
12066,
8... |
Name the plaform for year more than 2006 and developer of 3g studios | CREATE TABLE table_name_33 (platform VARCHAR, year VARCHAR, developer VARCHAR) | SELECT platform FROM table_name_33 WHERE year > 2006 AND developer = "3g studios" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4201,
41,
29100,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
6,
7523,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
9564,
2032,
21,
215,
72,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1585,
21680,
953,
834,
4350,
834,
4201,
549,
17444,
427,
215,
2490,
3581,
3430,
7523,
3274,
96,
519,
122,
3100,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the score on 15 Aug with a 17:30 time? | CREATE TABLE table_name_66 (
score VARCHAR,
date VARCHAR,
time VARCHAR
) | SELECT score FROM table_name_66 WHERE date = "15 aug" AND time = "17:30" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3539,
41,
2604,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
6,
97,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2604,
30,
627,
6128,
28,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
21680,
953,
834,
4350,
834,
3539,
549,
17444,
427,
833,
3274,
96,
1808,
185,
122,
121,
3430,
97,
3274,
96,
536,
18078,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which 2nd Member has a 1st Party of liberal? | CREATE TABLE table_12840 (
"Election" text,
"1st Member" text,
"1st Party" text,
"2nd Member" text,
"2nd Party" text
) | SELECT "2nd Member" FROM table_12840 WHERE "1st Party" = 'liberal' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2122,
26311,
41,
96,
427,
12252,
121,
1499,
6,
96,
536,
7,
17,
8541,
121,
1499,
6,
96,
536,
7,
17,
3450,
121,
1499,
6,
96,
357,
727,
8541,
121,
1499,
6,
96,
357,
727,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
357,
727,
8541,
121,
21680,
953,
834,
2122,
26311,
549,
17444,
427,
96,
536,
7,
17,
3450,
121,
3274,
3,
31,
10661,
138,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the number of monarchs that had Yan Maw la Mon as the heir? | CREATE TABLE table_26460435_5 (
monarch VARCHAR,
heir VARCHAR
) | SELECT COUNT(monarch) FROM table_26460435_5 WHERE heir = "Yan Maw La Mon" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
25991,
591,
2469,
834,
755,
41,
28397,
584,
4280,
28027,
6,
3,
17265,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
381,
13,
28397,
7,
24,
141,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
2157,
7064,
61,
21680,
953,
834,
2688,
25991,
591,
2469,
834,
755,
549,
17444,
427,
3,
17265,
3274,
96,
476,
152,
1534,
210,
325,
2963,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many products are there under the category "Seeds"? | CREATE TABLE products (product_category_code VARCHAR) | SELECT COUNT(*) FROM products WHERE product_category_code = "Seeds" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
494,
41,
15892,
834,
8367,
839,
651,
834,
4978,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
494,
33,
132,
365,
8,
3295,
96,
18648,
26,
7,
121,
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,
2847,
17161,
599,
1935,
61,
21680,
494,
549,
17444,
427,
556,
834,
8367,
839,
651,
834,
4978,
3274,
96,
18648,
26,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Namee the title for production code for 4014 | CREATE TABLE table_16951593_1 (title VARCHAR, production_code VARCHAR) | SELECT title FROM table_16951593_1 WHERE production_code = "4014" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
3301,
1808,
4271,
834,
536,
41,
21869,
584,
4280,
28027,
6,
999,
834,
4978,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
15,
8,
2233,
21,
999,
1081,
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,
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,
2938,
3301,
1808,
4271,
834,
536,
549,
17444,
427,
999,
834,
4978,
3274,
96,
20016,
20364,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many students have each different allergy Show bar chart, could you list by the X-axis in asc please? | CREATE TABLE Student (
StuID INTEGER,
LName VARCHAR(12),
Fname VARCHAR(12),
Age INTEGER,
Sex VARCHAR(1),
Major INTEGER,
Advisor INTEGER,
city_code VARCHAR(3)
)
CREATE TABLE Allergy_Type (
Allergy VARCHAR(20),
AllergyType VARCHAR(20)
)
CREATE TABLE Has_Allergy (
StuID INTEGE... | SELECT Allergy, COUNT(*) FROM Has_Allergy GROUP BY Allergy ORDER BY Allergy | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
6341,
41,
3,
13076,
4309,
3,
21342,
17966,
6,
301,
23954,
584,
4280,
28027,
599,
2122,
201,
377,
4350,
584,
4280,
28027,
599,
2122,
201,
7526,
3,
21342,
17966,
6,
679,
226,
584,
4280,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
432,
49,
122,
63,
6,
2847,
17161,
599,
1935,
61,
21680,
4498,
834,
6838,
49,
122,
63,
350,
4630,
6880,
272,
476,
432,
49,
122,
63,
4674,
11300,
272,
476,
432,
49,
122,
63,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the 35mm EFL and the equivalent aperture of the lens(es) with a maximum aperture of f /2.5? | CREATE TABLE table_name_67 (
max_aperture VARCHAR
) | SELECT 35 AS mm_efl_and_equivalent_aperture FROM table_name_67 WHERE max_aperture = "f /2.5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3708,
41,
9858,
834,
9,
883,
2693,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
3097,
635,
262,
10765,
11,
8,
7072,
28931,
13,
8,
6888,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0... | [
3,
23143,
14196,
3097,
6157,
3,
635,
834,
15,
89,
40,
834,
232,
834,
15,
1169,
15592,
834,
9,
883,
2693,
21680,
953,
834,
4350,
834,
3708,
549,
17444,
427,
9858,
834,
9,
883,
2693,
3274,
96,
89,
3,
87,
15967,
121,
1,
-100,
-100,... |
with a Rider of marco melandri, and a Grid smaller than 10, what is the highest lap count? | CREATE TABLE table_name_85 (laps INTEGER, rider VARCHAR, grid VARCHAR) | SELECT MAX(laps) FROM table_name_85 WHERE rider = "marco melandri" AND grid < 10 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4433,
41,
8478,
7,
3,
21342,
17966,
6,
2564,
52,
584,
4280,
28027,
6,
8634,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
28,
3,
9,
25218,
13,
14124,
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,
4800,
4,
599,
8478,
7,
61,
21680,
953,
834,
4350,
834,
4433,
549,
17444,
427,
2564,
52,
3274,
96,
1635,
509,
3,
2341,
232,
52,
23,
121,
3430,
8634,
3,
2,
335,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What broadcast dates have a weekly rank of 73? | CREATE TABLE table_16072430_1 (air_date VARCHAR, weekly_rank VARCHAR) | SELECT COUNT(air_date) FROM table_16072430_1 WHERE weekly_rank = "73" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19129,
5865,
25449,
834,
536,
41,
2256,
834,
5522,
584,
4280,
28027,
6,
5547,
834,
6254,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
6878,
5128,
43,
3,
9,
5547,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
2256,
834,
5522,
61,
21680,
953,
834,
19129,
5865,
25449,
834,
536,
549,
17444,
427,
5547,
834,
6254,
3274,
96,
4552,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Show different teams of technicians and the number of technicians in each team, and could you sort X in asc order? | CREATE TABLE technician (
technician_id real,
Name text,
Team text,
Starting_Year real,
Age int
)
CREATE TABLE repair_assignment (
technician_id int,
repair_ID int,
Machine_ID int
)
CREATE TABLE repair (
repair_ID int,
name text,
Launch_Date text,
Notes text
)
CREATE T... | SELECT Team, COUNT(*) FROM technician GROUP BY Team ORDER BY Team | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
17730,
41,
17730,
834,
23,
26,
490,
6,
5570,
1499,
6,
2271,
1499,
6,
14362,
834,
476,
2741,
490,
6,
7526,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
2096,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
6,
2847,
17161,
599,
1935,
61,
21680,
17730,
350,
4630,
6880,
272,
476,
2271,
4674,
11300,
272,
476,
2271,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the altitude (meters) is associated with the Name Mount Launoit, with the range as Belgica Mountains? | CREATE TABLE table_63740 (
"Rank" real,
"Name" text,
"Altitude (meters)" real,
"Range" text,
"Parent Range" text
) | SELECT SUM("Altitude (meters)") FROM table_63740 WHERE "Range" = 'belgica mountains' AND "Name" = 'mount launoit' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3891,
940,
2445,
41,
96,
22557,
121,
490,
6,
96,
23954,
121,
1499,
6,
96,
188,
40,
6592,
41,
4401,
7,
61,
121,
490,
6,
96,
448,
3280,
121,
1499,
6,
96,
13212,
295,
1097... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
40,
6592,
41,
4401,
7,
61,
8512,
21680,
953,
834,
3891,
940,
2445,
549,
17444,
427,
96,
448,
3280,
121,
3274,
3,
31,
2370,
122,
2617,
8022,
31,
3430,
96,
23954,
121,
3274,
3,
31,
11231,
... |
How many draws occured with a record of 10 losses, and 6 wins? | CREATE TABLE table_name_38 (
draws VARCHAR,
losses VARCHAR,
wins VARCHAR
) | SELECT COUNT(draws) FROM table_name_38 WHERE losses = 10 AND wins > 6 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3747,
41,
14924,
584,
4280,
28027,
6,
8467,
584,
4280,
28027,
6,
9204,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
14924,
4093,
15,
26,
28,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
19489,
7,
61,
21680,
953,
834,
4350,
834,
3747,
549,
17444,
427,
8467,
3274,
335,
3430,
9204,
2490,
431,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
For player is adam wiesel mention all the college/junior/club team | CREATE TABLE table_29988 (
"Pick" real,
"Player" text,
"Position" text,
"Nationality" text,
"NHL team" text,
"College/junior/club team" text
) | SELECT "College/junior/club team" FROM table_29988 WHERE "Player" = 'Adam Wiesel' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3264,
4060,
41,
96,
345,
3142,
121,
490,
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,
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,
9939,
7883,
87,
6959,
23,
127,
87,
13442,
372,
121,
21680,
953,
834,
357,
3264,
4060,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
188,
7812,
2142,
20736,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many millions of U.S. viewers watched the episode with the production code of 6AKY07? | CREATE TABLE table_28027307_1 (
us_viewers__millions_ VARCHAR,
production_code VARCHAR
) | SELECT us_viewers__millions_ FROM table_28027307_1 WHERE production_code = "6AKY07" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
17518,
2555,
1458,
940,
834,
536,
41,
178,
834,
4576,
277,
834,
834,
17030,
7,
834,
584,
4280,
28027,
6,
999,
834,
4978,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
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,
178,
834,
4576,
277,
834,
834,
17030,
7,
834,
21680,
953,
834,
17518,
2555,
1458,
940,
834,
536,
549,
17444,
427,
999,
834,
4978,
3274,
96,
948,
12396,
476,
4560,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Which nation has the America 3 Foundation syndicate and the jayhawk yacht? | CREATE TABLE table_54699 (
"Sail" text,
"Yacht" text,
"Syndicate" text,
"Yacht Club" text,
"Nation" text
) | SELECT "Nation" FROM table_54699 WHERE "Syndicate" = 'america 3 foundation' AND "Yacht" = 'jayhawk' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
4448,
3264,
41,
96,
134,
9,
173,
121,
1499,
6,
96,
476,
9,
3997,
121,
1499,
6,
96,
31715,
342,
121,
1499,
6,
96,
476,
9,
3997,
1949,
121,
1499,
6,
96,
567,
257,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
567,
257,
121,
21680,
953,
834,
755,
4448,
3264,
549,
17444,
427,
96,
31715,
342,
121,
3274,
3,
31,
23064,
220,
3361,
31,
3430,
96,
476,
9,
3997,
121,
3274,
3,
31,
1191,
63,
14400,
31,
1,
-100,
-100,
-100,
-... |
Bar chart x axis name y axis the number of name, show in descending by the Y-axis please. | CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
)
CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
) | SELECT Name, COUNT(Name) FROM Products GROUP BY Name ORDER BY COUNT(Name) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
15248,
7,
41,
3636,
3,
21342,
17966,
6,
5570,
584,
4280,
28027,
599,
25502,
201,
3642,
19973,
584,
4280,
28027,
599,
25502,
201,
3,
19145,
584,
4280,
28027,
599,
25502,
201,
19764,
17833... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7554,
350,
4630,
6880,
272,
476,
5570,
4674,
11300,
272,
476,
2847,
17161,
599,
23954,
61,
309,
25067,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the total pick# played by Anton Rodin with a Reg GP over 0? | CREATE TABLE table_name_32 (
pick__number VARCHAR,
player VARCHAR,
reg_gp VARCHAR
) | SELECT COUNT(pick__number) FROM table_name_32 WHERE player = "anton rodin" AND reg_gp > 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
1432,
834,
834,
5525,
1152,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
6,
5925,
834,
122,
102,
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,
1... | [
3,
23143,
14196,
2847,
17161,
599,
17967,
834,
834,
5525,
1152,
61,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
1959,
3274,
96,
9,
6992,
6102,
77,
121,
3430,
5925,
834,
122,
102,
2490,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,... |
Who was the interview subject when the centerfold model was Sherry Arnett? | CREATE TABLE table_1566848_7 (interview_subject VARCHAR, centerfold_model VARCHAR) | SELECT COUNT(interview_subject) FROM table_1566848_7 WHERE centerfold_model = "Sherry Arnett" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25463,
3651,
3707,
834,
940,
41,
3870,
4576,
834,
7304,
11827,
584,
4280,
28027,
6,
1530,
10533,
834,
21770,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
8,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
3870,
4576,
834,
7304,
11827,
61,
21680,
953,
834,
25463,
3651,
3707,
834,
940,
549,
17444,
427,
1530,
10533,
834,
21770,
3274,
96,
134,
760,
651,
1533,
10544,
121,
1,
-100,
-100,
-100,
-100,
-100,
-... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.