NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
What team did Alireza mansourian leave? | CREATE TABLE table_22297198_3 (
team VARCHAR,
outgoing_manager VARCHAR
) | SELECT team FROM table_22297198_3 WHERE outgoing_manager = "Alireza Mansourian" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26144,
4327,
24151,
834,
519,
41,
372,
584,
4280,
28027,
6,
91,
9545,
834,
24185,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
372,
410,
5429,
2638,
9,
388,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
372,
21680,
953,
834,
26144,
4327,
24151,
834,
519,
549,
17444,
427,
91,
9545,
834,
24185,
3274,
96,
188,
40,
23,
2638,
9,
1140,
7,
1063,
5288,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the lowest amount of points driver Romain Grosjean, who has an average pre-2010 less than 0, has? | CREATE TABLE table_name_49 (points INTEGER, driver VARCHAR, average_pre_2010 VARCHAR) | SELECT MIN(points) FROM table_name_49 WHERE driver = "romain grosjean" AND average_pre_2010 < 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3647,
41,
2700,
7,
3,
21342,
17966,
6,
2535,
584,
4280,
28027,
6,
1348,
834,
2026,
834,
14926,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
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,
3,
17684,
599,
2700,
7,
61,
21680,
953,
834,
4350,
834,
3647,
549,
17444,
427,
2535,
3274,
96,
3522,
9,
77,
9752,
26459,
121,
3430,
1348,
834,
2026,
834,
14926,
3,
2,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,... |
What was the score in the match against Sanaz Marand? | CREATE TABLE table_78350 (
"Outcome" text,
"Date" text,
"Tournament" text,
"Surface" text,
"Opponent" text,
"Score" text
) | SELECT "Score" FROM table_78350 WHERE "Opponent" = 'sanaz marand' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3940,
16975,
41,
96,
15767,
287,
15,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
134,
450,
4861,
121,
1499,
6,
96,
667,
102,
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,
134,
9022,
121,
21680,
953,
834,
3940,
16975,
549,
17444,
427,
96,
667,
102,
9977,
121,
3274,
3,
31,
7,
152,
9,
172,
3157,
232,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Provide me the list of patients who had percutaneous liver aspiration that stayed in hospital for more than 2 days. | 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 (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE 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 procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.days_stay > "2" AND procedures.short_title = "Percutan liver aspirat" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
18730,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
Which Opponent has a Round larger than 1, and an Event of king of the cage 31? | CREATE TABLE table_name_3 (opponent VARCHAR, round VARCHAR, event VARCHAR) | SELECT opponent FROM table_name_3 WHERE round > 1 AND event = "king of the cage 31" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
519,
41,
32,
102,
9977,
584,
4280,
28027,
6,
1751,
584,
4280,
28027,
6,
605,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
4495,
9977,
65,
3,
9,
960... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
15264,
21680,
953,
834,
4350,
834,
519,
549,
17444,
427,
1751,
2490,
209,
3430,
605,
3274,
96,
1765,
13,
8,
17276,
2664,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What first class team does sanath jayasuriya play for? | CREATE TABLE table_name_51 (first_class_team VARCHAR, player VARCHAR) | SELECT first_class_team FROM table_name_51 WHERE player = "sanath jayasuriya" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5553,
41,
14672,
834,
4057,
834,
11650,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
166,
853,
372,
405,
3,
7,
152,
9,
18... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
166,
834,
4057,
834,
11650,
21680,
953,
834,
4350,
834,
5553,
549,
17444,
427,
1959,
3274,
96,
7,
152,
9,
189,
2662,
63,
9,
7,
459,
63,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the lowest overall year? | CREATE TABLE table_20953 (
"Year" real,
"Edmonton Hundred" real,
"Elthorne Hundred" real,
"Gore Hundred" real,
"Isleworth Hundred" real,
"Holborn Division" real,
"Finsbury Division" real,
"Kensington Division" real,
"Tower Division" real,
"Spelthorne Hundred" real,
"Within the Walls" real,
"Without the Walls" real,
"Inns of Court and Chancery" real,
"Westminster City and Liberty" real,
"Total" real
) | SELECT MIN("Year") FROM table_20953 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1755,
3301,
519,
41,
96,
476,
2741,
121,
490,
6,
96,
427,
26,
4662,
106,
14587,
1271,
121,
490,
6,
96,
10991,
17,
6293,
15,
14587,
1271,
121,
490,
6,
96,
6221,
60,
14587,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
476,
2741,
8512,
21680,
953,
834,
1755,
3301,
519,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the position of the player born on May 13, 1983 who played for the Los Angeles Kings during 2009-2010? | CREATE TABLE table_40027 (
"Position" text,
"Jersey #" real,
"Name" text,
"Height (cm)" real,
"Weight (kg)" real,
"Birthdate" text,
"Birthplace" text,
"2009\u20132010 Team" text
) | SELECT "Position" FROM table_40027 WHERE "2009\u20132010 Team" = 'los angeles kings' AND "Birthdate" = 'may 13, 1983' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5548,
2555,
41,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
683,
277,
15,
63,
1713,
121,
490,
6,
96,
23954,
121,
1499,
6,
96,
3845,
2632,
41,
75,
51,
61,
121,
490,
6,
96,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
345,
32,
7,
4749,
121,
21680,
953,
834,
5548,
2555,
549,
17444,
427,
96,
16660,
2,
76,
11138,
14926,
2271,
121,
3274,
3,
31,
2298,
11831,
15,
7,
3,
1765,
7,
31,
3430,
96,
279,
23,
52,
189,
5522,
121,
3274,
... |
what is the first creature -lrb- other planes -rrb- after page 40 ? | CREATE TABLE table_204_427 (
id number,
"creature (other planes)" text,
"page" text,
"other appearances" text,
"variants" text,
"description" text
) | SELECT "creature (other planes)" FROM table_204_427 WHERE "page" > 40 ORDER BY id LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
591,
2555,
41,
3,
23,
26,
381,
6,
96,
5045,
9,
2693,
41,
9269,
6112,
7,
61,
121,
1499,
6,
96,
6492,
121,
1499,
6,
96,
9269,
3179,
7,
121,
1499,
6,
96,
950... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
5045,
9,
2693,
41,
9269,
6112,
7,
61,
121,
21680,
953,
834,
26363,
834,
591,
2555,
549,
17444,
427,
96,
6492,
121,
2490,
1283,
4674,
11300,
272,
476,
3,
23,
26,
8729,
12604,
209,
1,
-100,
-100,
-100,
-100,
-10... |
Which country has had 6 miss universe's? | CREATE TABLE table_30638 (
"Rank" real,
"Country" text,
"Miss Universe" text,
"1st Runner-up" real,
"2nd Runner-up" real,
"3rd Runner-up" real,
"4th Runner-up" real,
"Semifinalists" real,
"Total" real
) | SELECT "Country" FROM table_30638 WHERE "Miss Universe" = '6' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1458,
948,
3747,
41,
96,
22557,
121,
490,
6,
96,
10628,
651,
121,
1499,
6,
96,
329,
159,
7,
20713,
121,
1499,
6,
96,
536,
7,
17,
3,
23572,
18,
413,
121,
490,
6,
96,
3... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
10628,
651,
121,
21680,
953,
834,
1458,
948,
3747,
549,
17444,
427,
96,
329,
159,
7,
20713,
121,
3274,
3,
31,
948,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the title of the story published on October 19, 2011? | CREATE TABLE table_41117 (
"Issue" text,
"Date" text,
"Title" text,
"Story" text,
"Color" text
) | SELECT "Story" FROM table_41117 WHERE "Date" = 'october 19, 2011' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4853,
20275,
41,
96,
196,
7,
7,
76,
15,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
134,
10972,
121,
1499,
6,
96,
3881,
322,
121,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
134,
10972,
121,
21680,
953,
834,
4853,
20275,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
32,
75,
235,
1152,
12370,
2722,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Which leage has higher average salaries for player? | CREATE TABLE player (
player_id text,
birth_year text,
birth_month text,
birth_day text,
birth_country text,
birth_state text,
birth_city text,
death_year text,
death_month text,
death_day text,
death_country text,
death_state text,
death_city text,
name_first text,
name_last text,
name_given text,
weight text
)
CREATE TABLE salary (
year number,
team_id text,
league_id text,
player_id text,
salary number
)
CREATE TABLE player_award (
player_id text,
award_id text,
year number,
league_id text,
tie text,
notes text
)
CREATE TABLE player_award_vote (
award_id text,
year number,
league_id text,
player_id text,
points_won number,
points_max number,
votes_first text
)
CREATE TABLE hall_of_fame (
player_id text,
yearid number,
votedby text,
ballots text,
needed text,
votes text,
inducted text,
category text,
needed_note text
) | SELECT league_id FROM salary GROUP BY league_id ORDER BY AVG(salary) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1959,
41,
1959,
834,
23,
26,
1499,
6,
3879,
834,
1201,
1499,
6,
3879,
834,
7393,
1499,
6,
3879,
834,
1135,
1499,
6,
3879,
834,
17529,
1499,
6,
3879,
834,
5540,
1499,
6,
3879,
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,
5533,
834,
23,
26,
21680,
9090,
350,
4630,
6880,
272,
476,
5533,
834,
23,
26,
4674,
11300,
272,
476,
71,
17217,
599,
7,
138,
1208,
61,
309,
25067,
8729,
12604,
209,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What was the result of the home game against Derby County? | CREATE TABLE table_69082 (
"Date" text,
"Team" text,
"Venue" text,
"Win/Draw/Lose" text,
"Score" text
) | SELECT "Win/Draw/Lose" FROM table_69082 WHERE "Venue" = 'home' AND "Team" = 'derby county' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3951,
4018,
357,
41,
96,
308,
342,
121,
1499,
6,
96,
18699,
121,
1499,
6,
96,
553,
35,
76,
15,
121,
1499,
6,
96,
18455,
87,
308,
10936,
87,
434,
32,
7,
15,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
18455,
87,
308,
10936,
87,
434,
32,
7,
15,
121,
21680,
953,
834,
3951,
4018,
357,
549,
17444,
427,
96,
553,
35,
76,
15,
121,
3274,
3,
31,
5515,
31,
3430,
96,
18699,
121,
3274,
3,
31,
588,
969,
5435,
31,
1,... |
what is the least density (per km ) when the rank is 5 and the Area (km ) is less than 125,755? | CREATE TABLE table_name_77 (
density__per_km²_ INTEGER,
rank VARCHAR,
area__km²_ VARCHAR
) | SELECT MIN(density__per_km²_) FROM table_name_77 WHERE rank = "5" AND area__km²_ < 125 OFFSET 755 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4013,
41,
11048,
834,
834,
883,
834,
5848,
357,
834,
3,
21342,
17966,
6,
11003,
584,
4280,
28027,
6,
616,
834,
834,
5848,
357,
834,
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,
3,
17684,
599,
537,
7,
485,
834,
834,
883,
834,
5848,
357,
834,
61,
21680,
953,
834,
4350,
834,
4013,
549,
17444,
427,
11003,
3274,
96,
17395,
3430,
616,
834,
834,
5848,
357,
834,
3,
2,
3,
10124,
3,
15316,
20788,
... |
Which opponent has a record of 78-60? | CREATE TABLE table_name_62 (
opponent VARCHAR,
record VARCHAR
) | SELECT opponent FROM table_name_62 WHERE record = "78-60" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4056,
41,
15264,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
15264,
65,
3,
9,
1368,
13,
3,
3940,
19516,
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,
15264,
21680,
953,
834,
4350,
834,
4056,
549,
17444,
427,
1368,
3274,
96,
3940,
19516,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Which points has place smaller than 2? | CREATE TABLE table_64103 (
"Draw" real,
"Language" text,
"Artist" text,
"Song" text,
"English translation" text,
"Place" real,
"Points" real
) | SELECT "Points" FROM table_64103 WHERE "Place" < '2' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
17864,
41,
96,
308,
10936,
121,
490,
6,
96,
434,
1468,
76,
545,
121,
1499,
6,
96,
7754,
343,
121,
1499,
6,
96,
134,
2444,
121,
1499,
6,
96,
26749,
7314,
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,
22512,
7,
121,
21680,
953,
834,
4389,
17864,
549,
17444,
427,
96,
345,
11706,
121,
3,
2,
3,
31,
357,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which Time/Retired has Laps smaller than 14, and a Rider of darren barton? | CREATE TABLE table_name_78 (
time_retired VARCHAR,
laps VARCHAR,
rider VARCHAR
) | SELECT time_retired FROM table_name_78 WHERE laps < 14 AND rider = "darren barton" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3940,
41,
97,
834,
10682,
1271,
584,
4280,
28027,
6,
14941,
7,
584,
4280,
28027,
6,
2564,
52,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
2900,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
97,
834,
10682,
1271,
21680,
953,
834,
4350,
834,
3940,
549,
17444,
427,
14941,
7,
3,
2,
968,
3430,
2564,
52,
3274,
96,
3439,
1536,
1207,
17,
106,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Clean & jerk for the snatch less than 150 and a Bodyweight of 76.18? | CREATE TABLE table_name_82 (
clean_ VARCHAR,
_jerk VARCHAR,
snatch VARCHAR,
bodyweight VARCHAR
) | SELECT clean_ & _jerk FROM table_name_82 WHERE snatch < 150 AND bodyweight = 76.18 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4613,
41,
1349,
834,
584,
4280,
28027,
6,
3,
834,
12488,
157,
584,
4280,
28027,
6,
3,
7,
29,
14547,
584,
4280,
28027,
6,
643,
9378,
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,
1349,
834,
3,
184,
3,
834,
12488,
157,
21680,
953,
834,
4350,
834,
4613,
549,
17444,
427,
3,
7,
29,
14547,
3,
2,
4261,
3430,
643,
9378,
3274,
3,
3959,
5,
2606,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the region for the 38xa-5 catalog? | CREATE TABLE table_name_6 (region VARCHAR, catalog VARCHAR) | SELECT region FROM table_name_6 WHERE catalog = "38xa-5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
18145,
584,
4280,
28027,
6,
10173,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1719,
21,
8,
6654,
226,
9,
4525,
10173,
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,
1719,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
10173,
3274,
96,
3747,
226,
9,
18,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Where was the game when the home team scored 25.17 (167)? | CREATE TABLE table_33474 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT "Venue" FROM table_33474 WHERE "Home team score" = '25.17 (167)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
3710,
4581,
41,
96,
19040,
372,
121,
1499,
6,
96,
19040,
372,
2604,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
188,
1343,
372,
2604,
121,
1499,
6,
96,
553,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
553,
35,
76,
15,
121,
21680,
953,
834,
519,
3710,
4581,
549,
17444,
427,
96,
19040,
372,
2604,
121,
3274,
3,
31,
1828,
5,
2517,
19198,
12703,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is kannada name of tamil name anusham | CREATE TABLE table_201400_2 (
kannada_name_ಕನ್ನಡ VARCHAR,
tamil_name_தமிழ் VARCHAR
) | SELECT kannada_name_ಕನ್ನಡ FROM table_201400_2 WHERE tamil_name_தமிழ் = "Anusham அனுஷம்" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
10218,
1206,
834,
357,
41,
675,
9,
26,
9,
834,
4350,
834,
2,
584,
4280,
28027,
6,
3,
17,
265,
173,
834,
4350,
834,
2,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
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,
0,
0... | [
3,
23143,
14196,
675,
9,
26,
9,
834,
4350,
834,
2,
21680,
953,
834,
10218,
1206,
834,
357,
549,
17444,
427,
3,
17,
265,
173,
834,
4350,
834,
2,
3274,
96,
188,
29,
302,
1483,
3,
2,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
how many patients are with diagnosis cl skul base fx coma nos? | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE diagnoses.short_title = "Cl skul base fx-coma NOS" | [
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... |
What was the report in the race where the winning team was Roush Fenway Racing? | CREATE TABLE table_2220432_1 (report VARCHAR, team VARCHAR) | SELECT report FROM table_2220432_1 WHERE team = "Roush Fenway Racing" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2884,
26363,
2668,
834,
536,
41,
60,
1493,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
934,
16,
8,
1964,
213,
8,
3447,
372,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
934,
21680,
953,
834,
2884,
26363,
2668,
834,
536,
549,
17444,
427,
372,
3274,
96,
448,
1162,
107,
377,
35,
1343,
16046,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Which product has been ordered most number of times? | CREATE TABLE addresses (
address_id number,
address_content text,
city text,
zip_postcode text,
state_province_county text,
country text,
other_address_details text
)
CREATE TABLE customer_addresses (
customer_id number,
address_id number,
date_address_from time,
address_type text,
date_address_to time
)
CREATE TABLE customer_orders (
order_id number,
customer_id number,
order_status text,
order_date time,
order_details text
)
CREATE TABLE products (
product_id number,
product_details 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 customers (
customer_id number,
payment_method text,
customer_name text,
date_became_customer time,
other_customer_details text
)
CREATE TABLE order_items (
order_id number,
product_id number,
order_quantity text
) | SELECT t2.product_details FROM order_items AS t1 JOIN products AS t2 ON t1.product_id = t2.product_id GROUP BY t1.product_id ORDER BY COUNT(*) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7181,
41,
1115,
834,
23,
26,
381,
6,
1115,
834,
14819,
1499,
6,
690,
1499,
6,
10658,
834,
5950,
4978,
1499,
6,
538,
834,
1409,
2494,
565,
834,
13362,
63,
1499,
6,
684,
1499,
6,
119... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17,
4416,
15892,
834,
221,
5756,
7,
21680,
455,
834,
23,
3524,
7,
6157,
3,
17,
536,
3,
15355,
3162,
494,
6157,
3,
17,
357,
9191,
3,
17,
5411,
15892,
834,
23,
26,
3274,
3,
17,
4416,
15892,
834,
23,
26,
350,
... |
What ist the Away Leg with an Opposition that is aarhus gymnastik forening? | CREATE TABLE table_36720 (
"Competition" text,
"Round" text,
"Opposition" text,
"Home Leg" text,
"Away Leg" text
) | SELECT "Away Leg" FROM table_36720 WHERE "Opposition" = 'aarhus gymnastik forening' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3420,
18517,
41,
96,
5890,
4995,
4749,
121,
1499,
6,
96,
448,
32,
1106,
121,
1499,
6,
96,
667,
102,
4718,
121,
1499,
6,
96,
19040,
18978,
121,
1499,
6,
96,
188,
1343,
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,
188,
1343,
18978,
121,
21680,
953,
834,
3420,
18517,
549,
17444,
427,
96,
667,
102,
4718,
121,
3274,
3,
31,
9,
291,
11823,
23379,
4414,
21,
35,
53,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees who do not work in departments with managers that have ids between 100 and 200, draw a bar chart about the distribution of first_name and department_id , and show in descending by the DEPARTMENT_ID. | CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE 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),
REGION_NAME varchar(25)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
) | SELECT FIRST_NAME, DEPARTMENT_ID FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY DEPARTMENT_ID DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3248,
41,
301,
5618,
8015,
834,
4309,
7908,
1982,
599,
8525,
632,
201,
3,
13733,
26418,
834,
24604,
12200,
134,
3,
4331,
4059,
599,
2445,
201,
3,
16034,
16359,
834,
5911,
5596,
3,
4331... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
30085,
834,
567,
17683,
6,
3396,
19846,
11810,
834,
4309,
21680,
1652,
549,
17444,
427,
4486,
3396,
19846,
11810,
834,
4309,
3388,
41,
23143,
14196,
3396,
19846,
11810,
834,
4309,
21680,
10521,
549,
17444,
427,
283,
15610... |
When was shippensburg university Colonized? | CREATE TABLE table_name_56 (colonized VARCHAR, school VARCHAR) | SELECT colonized FROM table_name_56 WHERE school = "shippensburg university" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4834,
41,
8135,
29,
1601,
584,
4280,
28027,
6,
496,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
366,
47,
4383,
3801,
4824,
3819,
3043,
106,
1601,
58,
1,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
6718,
1601,
21680,
953,
834,
4350,
834,
4834,
549,
17444,
427,
496,
3274,
96,
2009,
3801,
4824,
3819,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Show the number of products with price higher than 1000 or lower than 500 for each product name in a bar chart. | CREATE TABLE Products (
product_id INTEGER,
product_type_code VARCHAR(15),
product_name VARCHAR(80),
product_price DOUBLE
)
CREATE TABLE Customer_Address_History (
customer_id INTEGER,
address_id INTEGER,
date_from DATETIME,
date_to DATETIME
)
CREATE TABLE Customers (
customer_id INTEGER,
payment_method_code VARCHAR(15),
customer_number VARCHAR(20),
customer_name VARCHAR(80),
customer_address VARCHAR(255),
customer_phone VARCHAR(80),
customer_email VARCHAR(80)
)
CREATE TABLE Addresses (
address_id INTEGER,
line_1_number_building VARCHAR(80),
city VARCHAR(50),
zip_postcode VARCHAR(20),
state_province_county VARCHAR(50),
country VARCHAR(50)
)
CREATE TABLE Customer_Orders (
order_id INTEGER,
customer_id INTEGER,
order_date DATETIME,
order_status_code VARCHAR(15)
)
CREATE TABLE Contacts (
contact_id INTEGER,
customer_id INTEGER,
gender VARCHAR(1),
first_name VARCHAR(80),
last_name VARCHAR(50),
contact_phone VARCHAR(80)
)
CREATE TABLE Order_Items (
order_item_id INTEGER,
order_id INTEGER,
product_id INTEGER,
order_quantity VARCHAR(80)
) | SELECT product_name, COUNT(product_name) FROM Products WHERE product_price > 1000 OR product_price < 500 GROUP BY product_name | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7554,
41,
556,
834,
23,
26,
3,
21342,
17966,
6,
556,
834,
6137,
834,
4978,
584,
4280,
28027,
599,
1808,
201,
556,
834,
4350,
584,
4280,
28027,
599,
2079,
201,
556,
834,
102,
4920,
60... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
556,
834,
4350,
6,
2847,
17161,
599,
15892,
834,
4350,
61,
21680,
7554,
549,
17444,
427,
556,
834,
102,
4920,
2490,
5580,
4674,
556,
834,
102,
4920,
3,
2,
2899,
350,
4630,
6880,
272,
476,
556,
834,
4350,
1,
-100,
... |
Name the driver for 3 rounds | CREATE TABLE table_58569 (
"Entrant" text,
"Constructor" text,
"Chassis" text,
"Engine" text,
"Tyre" text,
"Driver" text,
"Rounds" text
) | SELECT "Driver" FROM table_58569 WHERE "Rounds" = '3' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3449,
755,
3951,
41,
96,
16924,
3569,
121,
1499,
6,
96,
4302,
7593,
127,
121,
1499,
6,
96,
3541,
6500,
7,
121,
1499,
6,
96,
31477,
121,
1499,
6,
96,
382,
63,
60,
121,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
20982,
52,
121,
21680,
953,
834,
3449,
755,
3951,
549,
17444,
427,
96,
448,
32,
1106,
7,
121,
3274,
3,
31,
519,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What percentage of the EU's population lives in the country with a population density of 110.8 people per square kilometer? | CREATE TABLE table_24066938_1 (population__percentage_of_eu VARCHAR, pop_density_people_km_2 VARCHAR) | SELECT population__percentage_of_eu FROM table_24066938_1 WHERE pop_density_people_km_2 = "110.8" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2266,
5176,
3951,
3747,
834,
536,
41,
9791,
7830,
834,
834,
883,
3728,
545,
834,
858,
834,
15,
76,
584,
4280,
28027,
6,
2783,
834,
537,
7,
485,
834,
16588,
834,
5848,
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,
2074,
834,
834,
883,
3728,
545,
834,
858,
834,
15,
76,
21680,
953,
834,
2266,
5176,
3951,
3747,
834,
536,
549,
17444,
427,
2783,
834,
537,
7,
485,
834,
16588,
834,
5848,
834,
357,
3274,
96,
2596,
22384,
121,
1,
-1... |
count the number of patients whose insurance is medicare and diagnoses short title is hydronephrosis? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.insurance = "Medicare" AND diagnoses.short_title = "Hydronephrosis" | [
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... |
Which aircraft Weapon Systems Officer Capt Charles B. Debellevue belongs on? | CREATE TABLE table_name_27 (aircraft VARCHAR, weapon_systems_officer VARCHAR) | SELECT aircraft FROM table_name_27 WHERE weapon_systems_officer = "capt charles b. debellevue" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2555,
41,
2256,
6696,
584,
4280,
28027,
6,
10931,
834,
3734,
7,
834,
19632,
52,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
6442,
30785,
5479,
6027,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
6442,
21680,
953,
834,
4350,
834,
2555,
549,
17444,
427,
10931,
834,
3734,
7,
834,
19632,
52,
3274,
96,
4010,
17,
3,
4059,
965,
3,
115,
5,
20,
2370,
10912,
76,
15,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Who was the general classification leader when the young rider classification leader was Salvatore Commesso and the winner was Erik Dekker? | CREATE TABLE table_25229 (
"Stage" real,
"Winner" text,
"General classification" text,
"Points classification" text,
"Mountains classification" text,
"Young rider classification" text,
"Team classification" text,
"Combativity award" text
) | SELECT "General classification" FROM table_25229 WHERE "Young rider classification" = 'Salvatore Commesso' AND "Winner" = 'Erik Dekker' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1828,
357,
3166,
41,
96,
134,
6505,
121,
490,
6,
96,
18455,
687,
121,
1499,
6,
96,
20857,
13774,
121,
1499,
6,
96,
22512,
7,
13774,
121,
1499,
6,
96,
329,
32,
14016,
77,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
20857,
13774,
121,
21680,
953,
834,
1828,
357,
3166,
549,
17444,
427,
96,
3774,
1725,
2564,
52,
13774,
121,
3274,
3,
31,
134,
138,
208,
1016,
15,
8192,
7,
7,
32,
31,
3430,
96,
18455,
687,
121,
3274,
3,
31,
4... |
What is the highest Round that has a Position of Tackle and the Player Fred Neilsen? | CREATE TABLE table_5021 (
"Round" real,
"Pick" real,
"Player" text,
"Position" text,
"School/Club Team" text
) | SELECT MAX("Round") FROM table_5021 WHERE "Position" = 'tackle' AND "Player" = 'fred neilsen' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1752,
2658,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
345,
3142,
121,
490,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
29364,
87,
254,
11158,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
448,
32,
1106,
8512,
21680,
953,
834,
1752,
2658,
549,
17444,
427,
96,
345,
32,
7,
4749,
121,
3274,
3,
31,
17,
9,
19376,
31,
3430,
96,
15800,
49,
121,
3274,
3,
31,
89,
1271,
3,
29,
15,
1558,... |
Name the D 44 for when it has D 41 of r 41 + | CREATE TABLE table_53302 (
"D 50 O" text,
"D 49 \u221a" text,
"D 48 \u221a" text,
"D 47 \u221a" text,
"D 46 \u221a" text,
"D 45 \u221a" text,
"D 44 \u221a" text,
"D 43 \u221a" text,
"D 42 \u221a" text,
"D 41 \u221a" text
) | SELECT "D 44 \u221a" FROM table_53302 WHERE "D 41 \u221a" = 'r 41 +' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4867,
1458,
357,
41,
96,
308,
943,
411,
121,
1499,
6,
96,
308,
9526,
3,
2,
76,
357,
2658,
9,
121,
1499,
6,
96,
308,
4678,
3,
2,
76,
357,
2658,
9,
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,
308,
8537,
3,
2,
76,
357,
2658,
9,
121,
21680,
953,
834,
4867,
1458,
357,
549,
17444,
427,
96,
308,
8798,
3,
2,
76,
357,
2658,
9,
121,
3274,
3,
31,
52,
8798,
1768,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100... |
Where was the venue that had 274 runs? | CREATE TABLE table_34000 (
"Rank" text,
"Runs" text,
"Player" text,
"Opponent" text,
"Venue" text,
"Season" text
) | SELECT "Venue" FROM table_34000 WHERE "Runs" = '274' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3710,
2313,
41,
96,
22557,
121,
1499,
6,
96,
448,
202,
7,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
553,
35,
76,
15,
121,
1499,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
553,
35,
76,
15,
121,
21680,
953,
834,
3710,
2313,
549,
17444,
427,
96,
448,
202,
7,
121,
3274,
3,
31,
2555,
591,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What was the Sp of the 2nd Position? | CREATE TABLE table_22265261_1 (
sp VARCHAR,
position VARCHAR
) | SELECT COUNT(sp) FROM table_22265261_1 WHERE position = "2nd" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2884,
2688,
5373,
4241,
834,
536,
41,
3,
7,
102,
584,
4280,
28027,
6,
1102,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2526,
13,
8,
204,
727,
142... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
7,
102,
61,
21680,
953,
834,
2884,
2688,
5373,
4241,
834,
536,
549,
17444,
427,
1102,
3274,
96,
357,
727,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who is the away team when the home team scored 14.14 (98)? | CREATE TABLE table_56653 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT "Away team" FROM table_56653 WHERE "Home team score" = '14.14 (98)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4834,
4122,
519,
41,
96,
19040,
372,
121,
1499,
6,
96,
19040,
372,
2604,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
188,
1343,
372,
2604,
121,
1499,
6,
96,
553,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
188,
1343,
372,
121,
21680,
953,
834,
4834,
4122,
519,
549,
17444,
427,
96,
19040,
372,
2604,
121,
3274,
3,
31,
2534,
5,
2534,
41,
3916,
61,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
When did the episode titled 'Lucky Strike' air for the first time? | CREATE TABLE table_16271 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text,
"U.S. viewers (millions)" text
) | SELECT "Original air date" FROM table_16271 WHERE "Title" = 'Lucky Strike' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
2555,
536,
41,
96,
4168,
5,
16,
939,
121,
490,
6,
96,
4168,
5,
16,
774,
121,
490,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
15,
26,
57,
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,
667,
3380,
10270,
799,
833,
121,
21680,
953,
834,
2938,
2555,
536,
549,
17444,
427,
96,
382,
155,
109,
121,
3274,
3,
31,
11748,
3781,
5500,
5208,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
show me the number of female patients who underwent atrial cardioversion. | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.gender = "F" AND procedures.long_title = "Atrial cardioversion" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
how many patients whose procedure short title is radical cystectomy? | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE 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 procedures ON demographic.hadm_id = procedures.hadm_id WHERE procedures.short_title = "Radical cystectomy" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
how many total medals has the united states won in women 's figure skating ? | CREATE TABLE table_203_104 (
id number,
"athlete" text,
"nation" text,
"olympics" text,
"gold" number,
"silver" number,
"bronze" number,
"total" number
) | SELECT SUM("total") FROM table_203_104 WHERE "nation" = 'united states' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
15442,
41,
3,
23,
26,
381,
6,
96,
26170,
15,
121,
1499,
6,
96,
29,
257,
121,
1499,
6,
96,
32,
120,
51,
6174,
7,
121,
1499,
6,
96,
14910,
121,
381,
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,
180,
6122,
599,
121,
235,
1947,
8512,
21680,
953,
834,
23330,
834,
15442,
549,
17444,
427,
96,
29,
257,
121,
3274,
3,
31,
15129,
15,
26,
2315,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
When london irish was eliminated from competition who proceeded to quarter final? | CREATE TABLE table_30178 (
"Proceed to Quarter-final" text,
"Match points" text,
"Aggregate score" text,
"Points margin" real,
"Eliminated from competition" text
) | SELECT "Proceed to Quarter-final" FROM table_30178 WHERE "Eliminated from competition" = 'London Irish' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1458,
27640,
41,
96,
3174,
75,
6958,
12,
17610,
18,
12406,
121,
1499,
6,
96,
329,
14547,
979,
121,
1499,
6,
96,
188,
122,
18301,
342,
2604,
121,
1499,
6,
96,
22512,
7,
63... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
75,
6958,
12,
17610,
18,
12406,
121,
21680,
953,
834,
1458,
27640,
549,
17444,
427,
96,
427,
4941,
77,
920,
45,
2259,
121,
3274,
3,
31,
29712,
7262,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What lane is from Great Britain and a 57.78 time? | CREATE TABLE table_name_95 (lane VARCHAR, nationality VARCHAR, time VARCHAR) | SELECT COUNT(lane) FROM table_name_95 WHERE nationality = "great britain" AND time > 57.78 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3301,
41,
8102,
584,
4280,
28027,
6,
1157,
485,
584,
4280,
28027,
6,
97,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
3,
8102,
19,
45,
1651,
7190,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
8102,
61,
21680,
953,
834,
4350,
834,
3301,
549,
17444,
427,
1157,
485,
3274,
96,
20288,
3,
115,
10694,
77,
121,
3430,
97,
2490,
3,
3436,
5,
3940,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the primary disease and diagnosis icd9 code of Josette Orr? | CREATE TABLE procedures (
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 diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
) | SELECT demographic.diagnosis, diagnoses.icd9_code FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Josette Orr" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
14798,
5,
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... |
Give me the comparison about meter_100 over the meter_400 , could you show by the meter_100 in ascending? | CREATE TABLE record (
ID int,
Result text,
Swimmer_ID int,
Event_ID int
)
CREATE TABLE swimmer (
ID int,
name text,
Nationality text,
meter_100 real,
meter_200 text,
meter_300 text,
meter_400 text,
meter_500 text,
meter_600 text,
meter_700 text,
Time text
)
CREATE TABLE event (
ID int,
Name text,
Stadium_ID int,
Year text
)
CREATE TABLE stadium (
ID int,
name text,
Capacity int,
City text,
Country text,
Opening_year int
) | SELECT meter_400, meter_100 FROM swimmer ORDER BY meter_100 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1368,
41,
4699,
16,
17,
6,
3,
20119,
1499,
6,
27813,
935,
834,
4309,
16,
17,
6,
8042,
834,
4309,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
27424,
41,
4699... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4401,
834,
5548,
6,
3,
4401,
834,
2915,
21680,
27424,
4674,
11300,
272,
476,
3,
4401,
834,
2915,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the air dates of the show in ABS-CBN? | CREATE TABLE table_27487310_5 (air_dates VARCHAR, network VARCHAR) | SELECT air_dates FROM table_27487310_5 WHERE network = "ABS-CBN" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
3707,
4552,
1714,
834,
755,
41,
2256,
834,
5522,
7,
584,
4280,
28027,
6,
1229,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
33,
8,
799,
5128,
13,
8,
504,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
799,
834,
5522,
7,
21680,
953,
834,
2555,
3707,
4552,
1714,
834,
755,
549,
17444,
427,
1229,
3274,
96,
5359,
134,
18,
254,
19174,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
The 51 points against, how many are for? | CREATE TABLE table_name_36 (
points_for VARCHAR,
points_against VARCHAR
) | SELECT points_for FROM table_name_36 WHERE points_against = "51" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3420,
41,
979,
834,
1161,
584,
4280,
28027,
6,
979,
834,
9,
16720,
7,
17,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
37,
11696,
979,
581,
6,
149,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
979,
834,
1161,
21680,
953,
834,
4350,
834,
3420,
549,
17444,
427,
979,
834,
9,
16720,
7,
17,
3274,
96,
5553,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Give me the comparison about the sum of Height over the Sex , and group by attribute Sex by a bar chart, rank by the Y in ascending please. | CREATE TABLE candidate (
Candidate_ID int,
People_ID int,
Poll_Source text,
Date text,
Support_rate real,
Consider_rate real,
Oppose_rate real,
Unsure_rate real
)
CREATE TABLE people (
People_ID int,
Sex text,
Name text,
Date_of_Birth text,
Height real,
Weight real
) | SELECT Sex, SUM(Height) FROM people GROUP BY Sex ORDER BY SUM(Height) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4775,
41,
25833,
17,
15,
834,
4309,
16,
17,
6,
2449,
834,
4309,
16,
17,
6,
14457,
834,
23799,
1499,
6,
7678,
1499,
6,
4224,
834,
2206,
490,
6,
9151,
834,
2206,
490,
6,
4495,
2748,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
679,
226,
6,
180,
6122,
599,
3845,
2632,
61,
21680,
151,
350,
4630,
6880,
272,
476,
679,
226,
4674,
11300,
272,
476,
180,
6122,
599,
3845,
2632,
61,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Give me the comparison about ID over the meter_500 , and list by the meter_500 in descending. | CREATE TABLE record (
ID int,
Result text,
Swimmer_ID int,
Event_ID int
)
CREATE TABLE swimmer (
ID int,
name text,
Nationality text,
meter_100 real,
meter_200 text,
meter_300 text,
meter_400 text,
meter_500 text,
meter_600 text,
meter_700 text,
Time text
)
CREATE TABLE event (
ID int,
Name text,
Stadium_ID int,
Year text
)
CREATE TABLE stadium (
ID int,
name text,
Capacity int,
City text,
Country text,
Opening_year int
) | SELECT meter_500, ID FROM swimmer ORDER BY meter_500 DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1368,
41,
4699,
16,
17,
6,
3,
20119,
1499,
6,
27813,
935,
834,
4309,
16,
17,
6,
8042,
834,
4309,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
27424,
41,
4699... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4401,
834,
2560,
6,
4699,
21680,
27424,
4674,
11300,
272,
476,
3,
4401,
834,
2560,
309,
25067,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What are the most wins of Terang with the draws less than 0? | CREATE TABLE table_63530 (
"Club" text,
"Wins" real,
"Losses" real,
"Draws" real,
"Against" real
) | SELECT MAX("Wins") FROM table_63530 WHERE "Club" = 'terang' AND "Draws" < '0' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3891,
26918,
41,
96,
254,
11158,
121,
1499,
6,
96,
18455,
7,
121,
490,
6,
96,
434,
13526,
7,
121,
490,
6,
96,
308,
10936,
7,
121,
490,
6,
96,
20749,
121,
490,
3,
61,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
18455,
7,
8512,
21680,
953,
834,
3891,
26918,
549,
17444,
427,
96,
254,
11158,
121,
3274,
3,
31,
449,
1468,
31,
3430,
96,
308,
10936,
7,
121,
3,
2,
3,
31,
632,
31,
1,
-100,
-100,
-100,
-100,
... |
how many Semantic Parsing papers in ACL 2014 | CREATE TABLE dataset (
datasetid int,
datasetname varchar
)
CREATE TABLE journal (
journalid int,
journalname varchar
)
CREATE TABLE paperdataset (
paperid int,
datasetid int
)
CREATE TABLE paper (
paperid int,
title varchar,
venueid int,
year int,
numciting int,
numcitedby int,
journalid int
)
CREATE TABLE paperfield (
fieldid int,
paperid int
)
CREATE TABLE paperkeyphrase (
paperid int,
keyphraseid int
)
CREATE TABLE writes (
paperid int,
authorid int
)
CREATE TABLE cite (
citingpaperid int,
citedpaperid int
)
CREATE TABLE author (
authorid int,
authorname varchar
)
CREATE TABLE keyphrase (
keyphraseid int,
keyphrasename varchar
)
CREATE TABLE venue (
venueid int,
venuename varchar
)
CREATE TABLE field (
fieldid int
) | SELECT DISTINCT COUNT(paper.paperid) FROM keyphrase, paper, paperkeyphrase, venue WHERE keyphrase.keyphrasename = 'Semantic Parsing' AND paperkeyphrase.keyphraseid = keyphrase.keyphraseid AND paper.paperid = paperkeyphrase.paperid AND paper.year = 2014 AND venue.venueid = paper.venueid AND venue.venuename = 'ACL' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
17953,
41,
17953,
23,
26,
16,
17,
6,
17953,
4350,
3,
4331,
4059,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
6378,
41,
6378,
23,
26,
16,
17,
6,
6378,
4350,
3,
4331,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2847,
17161,
599,
19587,
5,
19587,
23,
26,
61,
21680,
843,
27111,
6,
1040,
6,
1040,
4397,
27111,
6,
5669,
549,
17444,
427,
843,
27111,
5,
4397,
27111,
4350,
3274,
3,
31,
134,
15,
348,
1225,
... |
What is the title of the July 2 song that is downloaded as Crazy Frog? | CREATE TABLE table_70186 (
"Week" real,
"Issue Date" text,
"Artist" text,
"Single" text,
"Download" text,
"Title" text
) | SELECT "Title" FROM table_70186 WHERE "Download" = 'crazy frog' AND "Issue Date" = 'july 2' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2518,
25398,
41,
96,
518,
10266,
121,
490,
6,
96,
196,
7,
7,
76,
15,
7678,
121,
1499,
6,
96,
7754,
343,
121,
1499,
6,
96,
134,
53,
109,
121,
1499,
6,
96,
28380,
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,
382,
155,
109,
121,
21680,
953,
834,
2518,
25398,
549,
17444,
427,
96,
28380,
121,
3274,
3,
31,
2935,
4164,
3,
89,
3822,
31,
3430,
96,
196,
7,
7,
76,
15,
7678,
121,
3274,
3,
31,
2047,
120,
204,
31,
1,
-100... |
How many districts does riley joseph wilson? | CREATE TABLE table_1342315_17 (district VARCHAR, incumbent VARCHAR) | SELECT COUNT(district) FROM table_1342315_17 WHERE incumbent = "Riley Joseph Wilson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23747,
2773,
1808,
834,
2517,
41,
26,
23,
20066,
584,
4280,
28027,
6,
28406,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
14126,
405,
3,
5493,
63,
7406,
15,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
26,
23,
20066,
61,
21680,
953,
834,
23747,
2773,
1808,
834,
2517,
549,
17444,
427,
28406,
3274,
96,
448,
23,
1306,
6187,
9439,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the total number of Wins, when Losses is "6", and when Draws is greater than "0"? | CREATE TABLE table_name_70 (wins VARCHAR, losses VARCHAR, draws VARCHAR) | SELECT COUNT(wins) FROM table_name_70 WHERE losses = 6 AND draws > 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2518,
41,
3757,
7,
584,
4280,
28027,
6,
8467,
584,
4280,
28027,
6,
14924,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
792,
381,
13,
4871,
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,
0... | [
3,
23143,
14196,
2847,
17161,
599,
3757,
7,
61,
21680,
953,
834,
4350,
834,
2518,
549,
17444,
427,
8467,
3274,
431,
3430,
14924,
2490,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What home has 122-28 as the score? | CREATE TABLE table_name_96 (
home VARCHAR,
score VARCHAR
) | SELECT home FROM table_name_96 WHERE score = "122-28" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4314,
41,
234,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
234,
65,
3,
20889,
18,
2577,
38,
8,
2604,
58,
1,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
234,
21680,
953,
834,
4350,
834,
4314,
549,
17444,
427,
2604,
3274,
96,
20889,
18,
2577,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the most number | CREATE TABLE table_26914076_2 (no INTEGER) | SELECT MAX(no) FROM table_26914076_2 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
4729,
2445,
3959,
834,
357,
41,
29,
32,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
167,
381,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
29,
32,
61,
21680,
953,
834,
2688,
4729,
2445,
3959,
834,
357,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the result for the district missouri 2? | CREATE TABLE table_1341663_26 (
result VARCHAR,
district VARCHAR
) | SELECT result FROM table_1341663_26 WHERE district = "Missouri 2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23747,
2938,
3891,
834,
2688,
41,
741,
584,
4280,
28027,
6,
3939,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
741,
21,
8,
3939,
3041,
32,
459,
204,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
741,
21680,
953,
834,
23747,
2938,
3891,
834,
2688,
549,
17444,
427,
3939,
3274,
96,
329,
159,
7,
32,
459,
204,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the next pennant after f172 ? | CREATE TABLE table_204_568 (
id number,
"pennant" text,
"name" text,
"hull builder" text,
"ordered" text,
"laid down" text,
"launched" text,
"accepted into service" text,
"commissioned" text,
"est. building cost" text,
"fate" text
) | SELECT "pennant" FROM table_204_568 WHERE id = (SELECT id FROM table_204_568 WHERE "pennant" = 'f172') + 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
755,
3651,
41,
3,
23,
26,
381,
6,
96,
3208,
29,
288,
121,
1499,
6,
96,
4350,
121,
1499,
6,
96,
22699,
918,
49,
121,
1499,
6,
96,
9397,
15,
26,
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,
3208,
29,
288,
121,
21680,
953,
834,
26363,
834,
755,
3651,
549,
17444,
427,
3,
23,
26,
3274,
41,
23143,
14196,
3,
23,
26,
21680,
953,
834,
26363,
834,
755,
3651,
549,
17444,
427,
96,
3208,
29,
288,
121,
3274,... |
What name has an overall less than 268, and 1 as the round? | CREATE TABLE table_39257 (
"Round" real,
"Pick #" real,
"Overall" real,
"Name" text,
"Position" text,
"College" text
) | SELECT "Name" FROM table_39257 WHERE "Overall" < '268' AND "Round" = '1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3288,
357,
3436,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
345,
3142,
1713,
121,
490,
6,
96,
23847,
1748,
121,
490,
6,
96,
23954,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
23954,
121,
21680,
953,
834,
3288,
357,
3436,
549,
17444,
427,
96,
23847,
1748,
121,
3,
2,
3,
31,
357,
3651,
31,
3430,
96,
448,
32,
1106,
121,
3274,
3,
31,
536,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the score in 1929? | CREATE TABLE table_43870 (
"Score" text,
"Batsmen" text,
"Against" text,
"Location" text,
"Year" text
) | SELECT "Score" FROM table_43870 WHERE "Year" = '1929' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
3747,
2518,
41,
96,
134,
9022,
121,
1499,
6,
96,
279,
144,
7,
904,
121,
1499,
6,
96,
20749,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
476,
2741,
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,
0,
0,
0... | [
3,
23143,
14196,
96,
134,
9022,
121,
21680,
953,
834,
591,
3747,
2518,
549,
17444,
427,
96,
476,
2741,
121,
3274,
3,
31,
2294,
3166,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the total number of earnings for golfers who have 28 events and more than 2 wins? | CREATE TABLE table_5153 (
"Rank" real,
"Player" text,
"Country" text,
"Earnings ( $ )" real,
"Events" real,
"Wins" real
) | SELECT COUNT("Earnings ( $ )") FROM table_5153 WHERE "Events" = '28' AND "Wins" > '2' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5553,
4867,
41,
96,
22557,
121,
490,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
427,
291,
29,
53,
7,
41,
1514,
3,
61,
121,
490,
6,
96,
427,
216... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
427,
291,
29,
53,
7,
41,
1514,
3,
61,
8512,
21680,
953,
834,
5553,
4867,
549,
17444,
427,
96,
427,
2169,
7,
121,
3274,
3,
31,
2577,
31,
3430,
96,
18455,
7,
121,
2490,
3,
31,
357,
31,
1,
... |
what number of patients have been diagnosed with lower urinary tract infection - likely bacterial in 2104? | CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
) | SELECT COUNT(DISTINCT patient.uniquepid) FROM patient WHERE patient.patientunitstayid IN (SELECT diagnosis.patientunitstayid FROM diagnosis WHERE diagnosis.diagnosisname = 'lower urinary tract infection - likely bacterial' AND STRFTIME('%y', diagnosis.diagnosistime) = '2104') | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1868,
41,
775,
12417,
1499,
6,
1868,
15878,
3734,
21545,
23,
26,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
7285,
1499,
6,
1246,
1499,
6,
11655,
485,
1499,
6,
2833,
23,
26,
381,
6... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
1868,
5,
202,
1495,
12417,
61,
21680,
1868,
549,
17444,
427,
1868,
5,
10061,
15129,
21545,
23,
26,
3388,
41,
23143,
14196,
8209,
5,
10061,
15129,
21545,
23,
26,
21680,
8209,
549,
... |
What is the full name ( first name and last name ) for those employees who gets more salary than the employee whose id is 163? | CREATE TABLE employees (
first_name VARCHAR,
last_name VARCHAR,
salary INTEGER,
employee_id VARCHAR
) | SELECT first_name, last_name FROM employees WHERE salary > (SELECT salary FROM employees WHERE employee_id = 163) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1652,
41,
166,
834,
4350,
584,
4280,
28027,
6,
336,
834,
4350,
584,
4280,
28027,
6,
9090,
3,
21342,
17966,
6,
3490,
834,
23,
26,
584,
4280,
28027,
3,
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,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
166,
834,
4350,
6,
336,
834,
4350,
21680,
1652,
549,
17444,
427,
9090,
2490,
41,
23143,
14196,
9090,
21680,
1652,
549,
17444,
427,
3490,
834,
23,
26,
3274,
898,
5268,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the Spanish word for cas [ˈkas]? | CREATE TABLE table_26614365_1 (spanish VARCHAR, central VARCHAR) | SELECT spanish FROM table_26614365_1 WHERE central = "cas [ˈkas]" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3539,
2534,
10402,
834,
536,
41,
7,
2837,
1273,
584,
4280,
28027,
6,
2069,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
5093,
1448,
21,
1990,
784,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
8438,
1273,
21680,
953,
834,
357,
3539,
2534,
10402,
834,
536,
549,
17444,
427,
2069,
3274,
96,
6769,
784,
2,
1258,
7,
908,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Streak in the game with a Record of 20–16? | CREATE TABLE table_name_42 (streak VARCHAR, record VARCHAR) | SELECT streak FROM table_name_42 WHERE record = "20–16" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4165,
41,
7,
929,
1639,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
472,
60,
1639,
16,
8,
467,
28,
3,
9,
11392,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
18631,
21680,
953,
834,
4350,
834,
4165,
549,
17444,
427,
1368,
3274,
96,
1755,
104,
2938,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Can you tell me the sum of the Pick # that has the CFL Team of edmonton? | CREATE TABLE table_8949 (
"Pick #" real,
"CFL Team" text,
"Player" text,
"Position" text,
"College" text
) | SELECT SUM("Pick #") FROM table_8949 WHERE "CFL Team" = 'edmonton' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3914,
3647,
41,
96,
345,
3142,
1713,
121,
490,
6,
96,
254,
10765,
2271,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
9939,
7883,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
345,
3142,
1713,
8512,
21680,
953,
834,
3914,
3647,
549,
17444,
427,
96,
254,
10765,
2271,
121,
3274,
3,
31,
15,
26,
4662,
106,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the number of losses for the team with a points difference of -25? | CREATE TABLE table_name_24 (
lost VARCHAR,
points_difference VARCHAR
) | SELECT lost FROM table_name_24 WHERE points_difference = "-25" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2266,
41,
1513,
584,
4280,
28027,
6,
979,
834,
26,
99,
11788,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
381,
13,
8467,
21,
8,
372,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1513,
21680,
953,
834,
4350,
834,
2266,
549,
17444,
427,
979,
834,
26,
99,
11788,
3274,
96,
14855,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
provide the number of patients whose diagnoses short title is abn react-renal dialysis and drug route is iv? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE diagnoses.short_title = "Abn react-renal dialysis" AND prescriptions.route = "IV" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
18730,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
3... |
What zip codes have a station with a max temperature greater than or equal to 80 and when did it reach that temperature? | 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_station_name text,
end_station_id number,
bike_id number,
subscription_type text,
zip_code number
)
CREATE TABLE weather (
date text,
max_temperature_f number,
mean_temperature_f number,
min_temperature_f number,
max_dew_point_f number,
mean_dew_point_f number,
min_dew_point_f number,
max_humidity number,
mean_humidity number,
min_humidity number,
max_sea_level_pressure_inches number,
mean_sea_level_pressure_inches number,
min_sea_level_pressure_inches number,
max_visibility_miles number,
mean_visibility_miles number,
min_visibility_miles number,
max_wind_speed_mph number,
mean_wind_speed_mph number,
max_gust_speed_mph number,
precipitation_inches number,
cloud_cover number,
events text,
wind_dir_degrees number,
zip_code number
)
CREATE TABLE status (
station_id number,
bikes_available number,
docks_available number,
time text
) | SELECT date, zip_code FROM weather WHERE max_temperature_f >= 80 | [
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,
833,
6,
10658,
834,
4978,
21680,
1969,
549,
17444,
427,
9858,
834,
21010,
15,
834,
89,
2490,
2423,
2775,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the gender of the teacher with last name "Medhurst"? | CREATE TABLE TEACHERS (gender VARCHAR, last_name VARCHAR) | SELECT gender FROM TEACHERS WHERE last_name = "Medhurst" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
332,
29027,
9984,
41,
122,
3868,
584,
4280,
28027,
6,
336,
834,
4350,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
7285,
13,
8,
3145,
28,
336,
564,
96,
20123,
237... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7285,
21680,
332,
29027,
9984,
549,
17444,
427,
336,
834,
4350,
3274,
96,
20123,
23765,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
How many number in series's are written by Greg Haddrick? | CREATE TABLE table_24535 (
"No. in total" text,
"No. in series" text,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text
) | SELECT COUNT("No. in series") FROM table_24535 WHERE "Written by" = 'Greg Haddrick' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
2128,
2469,
41,
96,
4168,
5,
16,
792,
121,
1499,
6,
96,
4168,
5,
16,
939,
121,
1499,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
15,
26,
57,
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,
2847,
17161,
599,
121,
4168,
5,
16,
939,
8512,
21680,
953,
834,
357,
2128,
2469,
549,
17444,
427,
96,
24965,
324,
57,
121,
3274,
3,
31,
517,
60,
122,
10118,
26,
5206,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
How many are named River Esk | CREATE TABLE table_952 (
"No." text,
"Name" text,
"Livery" text,
"Arrival" real,
"Type" text,
"Configuration" text,
"Builder" text,
"Built" real,
"Status" text,
"Location" text
) | SELECT COUNT("Built") FROM table_952 WHERE "Name" = 'River Esk' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3301,
357,
41,
96,
4168,
535,
1499,
6,
96,
23954,
121,
1499,
6,
96,
24179,
651,
121,
1499,
6,
96,
188,
52,
25295,
121,
490,
6,
96,
25160,
121,
1499,
6,
96,
4302,
26703,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7793,
173,
17,
8512,
21680,
953,
834,
3301,
357,
549,
17444,
427,
96,
23954,
121,
3274,
3,
31,
448,
23,
624,
1122,
157,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What Opponent has the Attendance of 14,029? | CREATE TABLE table_name_77 (
opponent VARCHAR,
attendance VARCHAR
) | SELECT opponent FROM table_name_77 WHERE attendance = "14,029" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4013,
41,
15264,
584,
4280,
28027,
6,
11364,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
4495,
9977,
65,
8,
22497,
663,
13,
11363,
632,
3166,
58,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
15264,
21680,
953,
834,
4350,
834,
4013,
549,
17444,
427,
11364,
3274,
96,
2534,
6,
632,
3166,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who wrote episode 23 of the season? | CREATE TABLE table_29436007_1 (written_by VARCHAR, no_in_season VARCHAR) | SELECT written_by FROM table_29436007_1 WHERE no_in_season = 23 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
4906,
6007,
940,
834,
536,
41,
14973,
834,
969,
584,
4280,
28027,
6,
150,
834,
77,
834,
9476,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
2832,
5640,
190... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1545,
834,
969,
21680,
953,
834,
3166,
4906,
6007,
940,
834,
536,
549,
17444,
427,
150,
834,
77,
834,
9476,
3274,
1902,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Who did the high rebounds in the game in which Brandon Jennings (8) did the high assists? | CREATE TABLE table_22871316_6 (high_rebounds VARCHAR, high_assists VARCHAR) | SELECT high_rebounds FROM table_22871316_6 WHERE high_assists = "Brandon Jennings (8)" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2884,
4225,
2368,
2938,
834,
948,
41,
6739,
834,
23768,
584,
4280,
28027,
6,
306,
834,
6500,
7,
17,
7,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
410,
8,
30... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0... | [
3,
23143,
14196,
306,
834,
23768,
21680,
953,
834,
2884,
4225,
2368,
2938,
834,
948,
549,
17444,
427,
306,
834,
6500,
7,
17,
7,
3274,
96,
18304,
29,
2029,
1022,
9416,
7,
3,
28007,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the job titles, and range of salaries for jobs with maximum salary between 12000 and 18000 Plot them as bar chart, and rank by the Y-axis from high to low. | CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
) | SELECT JOB_TITLE, MAX_SALARY - MIN_SALARY FROM jobs WHERE MAX_SALARY BETWEEN 12000 AND 18000 ORDER BY MAX_SALARY - MIN_SALARY DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
613,
834,
10193,
10972,
41,
262,
5244,
5017,
476,
5080,
834,
4309,
7908,
1982,
599,
11071,
632,
201,
5097,
8241,
834,
308,
6048,
833,
6,
3,
14920,
834,
308,
6048,
833,
6,
446,
10539,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
446,
10539,
834,
382,
3177,
3765,
6,
4800,
4,
834,
134,
4090,
24721,
3,
18,
3,
17684,
834,
134,
4090,
24721,
21680,
2476,
549,
17444,
427,
4800,
4,
834,
134,
4090,
24721,
272,
7969,
518,
23394,
586,
2313,
3430,
507,... |
Name the To par for leland gibson | CREATE TABLE table_name_59 (
to_par VARCHAR,
player VARCHAR
) | SELECT to_par FROM table_name_59 WHERE player = "leland gibson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3390,
41,
12,
834,
1893,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
304,
260,
21,
90,
40,
232,
31257,
739,
1,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
12,
834,
1893,
21680,
953,
834,
4350,
834,
3390,
549,
17444,
427,
1959,
3274,
96,
109,
40,
232,
31257,
739,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Name the number of poles for 15th position | CREATE TABLE table_26863 (
"Season" real,
"Series" text,
"Team" text,
"Races" real,
"Wins" real,
"Poles" real,
"FLaps" real,
"Podiums" real,
"Points" text,
"Position" text
) | SELECT COUNT("Poles") FROM table_26863 WHERE "Position" = '15th' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3651,
3891,
41,
96,
134,
15,
9,
739,
121,
490,
6,
96,
12106,
7,
121,
1499,
6,
96,
18699,
121,
1499,
6,
96,
448,
9,
2319,
121,
490,
6,
96,
18455,
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,
2847,
17161,
599,
121,
8931,
15,
7,
8512,
21680,
953,
834,
357,
3651,
3891,
549,
17444,
427,
96,
345,
32,
7,
4749,
121,
3274,
3,
31,
1808,
189,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Visualize a scatter chart about the correlation between People_ID and Weight , and group by attribute Sex. | CREATE TABLE candidate (
Candidate_ID int,
People_ID int,
Poll_Source text,
Date text,
Support_rate real,
Consider_rate real,
Oppose_rate real,
Unsure_rate real
)
CREATE TABLE people (
People_ID int,
Sex text,
Name text,
Date_of_Birth text,
Height real,
Weight real
) | SELECT People_ID, Weight FROM people GROUP BY Sex | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4775,
41,
25833,
17,
15,
834,
4309,
16,
17,
6,
2449,
834,
4309,
16,
17,
6,
14457,
834,
23799,
1499,
6,
7678,
1499,
6,
4224,
834,
2206,
490,
6,
9151,
834,
2206,
490,
6,
4495,
2748,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2449,
834,
4309,
6,
14230,
21680,
151,
350,
4630,
6880,
272,
476,
679,
226,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Nation when the Athlete was emma george, and a Record of 4.58m(15ft0¼in)? | CREATE TABLE table_name_62 (nation VARCHAR, athlete VARCHAR, record VARCHAR) | SELECT nation FROM table_name_62 WHERE athlete = "emma george" AND record = "4.58m(15ft0¼in)" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4056,
41,
29,
257,
584,
4280,
28027,
6,
17893,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
11046,
116,
8,
71,
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,
2982,
21680,
953,
834,
4350,
834,
4056,
549,
17444,
427,
17893,
3274,
96,
15,
635,
9,
873,
1677,
15,
121,
3430,
1368,
3274,
96,
12451,
927,
51,
599,
1808,
89,
17,
4542,
2,
591,
77,
61,
121,
1,
-100,
-100,
-100,
... |
What is the average Gold where the Nation is Russia (rus) and the number of silver is less than 2? | CREATE TABLE table_name_99 (gold INTEGER, nation VARCHAR, silver VARCHAR) | SELECT AVG(gold) FROM table_name_99 WHERE nation = "russia (rus)" AND silver < 2 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3264,
41,
14910,
3,
21342,
17966,
6,
2982,
584,
4280,
28027,
6,
4294,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1348,
2540,
213,
8,
11046,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
71,
17217,
599,
14910,
61,
21680,
953,
834,
4350,
834,
3264,
549,
17444,
427,
2982,
3274,
96,
26165,
41,
4502,
61,
121,
3430,
4294,
3,
2,
204,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
When chase harrison category:articles with hcards is the name what is the year? | CREATE TABLE table_74417 (
"Name" text,
"Country" text,
"Years" text,
"Games" real,
"Minutes" real,
"Conceded" real,
"Shutouts" real,
"Int. caps" real
) | SELECT "Years" FROM table_74417 WHERE "Name" = 'Chase Harrison Category:Articles with hCards' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4581,
591,
2517,
41,
96,
23954,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
476,
2741,
7,
121,
1499,
6,
96,
23055,
7,
121,
490,
6,
96,
12858,
2810,
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,
96,
476,
2741,
7,
121,
21680,
953,
834,
4581,
591,
2517,
549,
17444,
427,
96,
23954,
121,
3274,
3,
31,
3541,
9,
7,
15,
20429,
17459,
10,
7754,
447,
965,
28,
3,
107,
6936,
26,
7,
31,
1,
-100,
-100,
-100,
-100,
... |
Show the maximum amount of transaction. | CREATE TABLE TRANSACTIONS (amount_of_transaction INTEGER) | SELECT MAX(amount_of_transaction) FROM TRANSACTIONS | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
26585,
30518,
134,
41,
9,
11231,
834,
858,
834,
7031,
4787,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
3111,
8,
2411,
866,
13,
5878,
5,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
9,
11231,
834,
858,
834,
7031,
4787,
61,
21680,
26585,
30518,
134,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the best finish where the scoring rank is 97? | CREATE TABLE table_15431122_2 (best_finish VARCHAR, scoring_rank VARCHAR) | SELECT best_finish FROM table_15431122_2 WHERE scoring_rank = "97" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
27308,
3341,
20889,
834,
357,
41,
9606,
834,
25535,
584,
4280,
28027,
6,
10389,
834,
6254,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
200,
1992,
213,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
200,
834,
25535,
21680,
953,
834,
27308,
3341,
20889,
834,
357,
549,
17444,
427,
10389,
834,
6254,
3274,
96,
4327,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who is the Best dancer with the Worst dancer of Jerry Springer, a Best score of 29, and the Dance was the Quickstep? | CREATE TABLE table_name_47 (
best_dancer VARCHAR,
dance VARCHAR,
worst_dancer VARCHAR,
best_score VARCHAR
) | SELECT best_dancer FROM table_name_47 WHERE worst_dancer = "jerry springer" AND best_score = 29 AND dance = "quickstep" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4177,
41,
200,
834,
3768,
2110,
584,
4280,
28027,
6,
2595,
584,
4280,
28027,
6,
6025,
834,
3768,
2110,
584,
4280,
28027,
6,
200,
834,
7,
9022,
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,
200,
834,
3768,
2110,
21680,
953,
834,
4350,
834,
4177,
549,
17444,
427,
6025,
834,
3768,
2110,
3274,
96,
12488,
651,
2141,
49,
121,
3430,
200,
834,
7,
9022,
3274,
2838,
3430,
2595,
3274,
96,
1169,
2406,
7910,
121,
... |
what is diagnoses short title of subject name rafael stewart? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT diagnoses.short_title FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Rafael Stewart" | [
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,
18730,
7,
5,
7,
14184,
834,
21869,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
549,
17444,
427,
14798,
5,
4350,
3274,
96,
... |
What is the attendance number when the result is l 41-37? | CREATE TABLE table_name_32 (attendance VARCHAR, result VARCHAR) | SELECT attendance FROM table_name_32 WHERE result = "l 41-37" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
15116,
663,
584,
4280,
28027,
6,
741,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
11364,
381,
116,
8,
741,
19,
3,
40,
8798,
18,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
11364,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
741,
3274,
96,
40,
8798,
18,
4118,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Name the most weight | CREATE TABLE table_2062148_4 (weight__kg_ INTEGER) | SELECT MAX(weight__kg_) FROM table_2062148_4 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1755,
4056,
24748,
834,
591,
41,
9378,
834,
834,
8711,
834,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
167,
1293,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
9378,
834,
834,
8711,
834,
61,
21680,
953,
834,
1755,
4056,
24748,
834,
591,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
How many laps did car 23 do? | CREATE TABLE table_name_17 (
laps VARCHAR,
car_no VARCHAR
) | SELECT laps FROM table_name_17 WHERE car_no = "23" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2517,
41,
14941,
7,
584,
4280,
28027,
6,
443,
834,
29,
32,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
14941,
7,
410,
443,
1902,
103,
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,
14941,
7,
21680,
953,
834,
4350,
834,
2517,
549,
17444,
427,
443,
834,
29,
32,
3274,
96,
2773,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Year of Rio? | CREATE TABLE table_13745 (
"Year" real,
"Title" text,
"Director" text,
"Studio(s)" text,
"Notes" text
) | SELECT "Year" FROM table_13745 WHERE "Title" = 'rio' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24636,
2128,
41,
96,
476,
2741,
121,
490,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
127,
121,
1499,
6,
96,
13076,
26,
23,
32,
599,
7,
61,
121,
1499,
6,
96,
10358,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2741,
121,
21680,
953,
834,
24636,
2128,
549,
17444,
427,
96,
382,
155,
109,
121,
3274,
3,
31,
52,
23,
32,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
who is the driver that had winnings of $225,000? | CREATE TABLE table_27781212_1 (
driver VARCHAR,
winnings VARCHAR
) | SELECT driver FROM table_27781212_1 WHERE winnings = "$225,000" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
3940,
2122,
2122,
834,
536,
41,
2535,
584,
4280,
28027,
6,
3447,
7,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
113,
19,
8,
2535,
24,
141,
3447,
7,
13,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2535,
21680,
953,
834,
2555,
3940,
2122,
2122,
834,
536,
549,
17444,
427,
3447,
7,
3274,
96,
3229,
357,
24338,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the country for the player Tiger Woods? | CREATE TABLE table_67201 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text
) | SELECT "Country" FROM table_67201 WHERE "Player" = 'tiger woods' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3708,
22772,
41,
96,
345,
11706,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
3696,
260,
121,
1499,
3,
61,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0... | [
3,
23143,
14196,
96,
10628,
651,
121,
21680,
953,
834,
3708,
22772,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
17,
4424,
1679,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
who is the leading scorer where home is charlotte bobcats | CREATE TABLE table_11964047_5 (
leading_scorer VARCHAR,
home VARCHAR
) | SELECT leading_scorer FROM table_11964047_5 WHERE home = "Charlotte Bobcats" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19993,
23714,
4177,
834,
755,
41,
1374,
834,
7,
5715,
49,
584,
4280,
28027,
6,
234,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
113,
19,
8,
1374,
2604,
52,
213,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1374,
834,
7,
5715,
49,
21680,
953,
834,
19993,
23714,
4177,
834,
755,
549,
17444,
427,
234,
3274,
96,
18947,
21538,
5762,
2138,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What position that has a Height larger than 179, and Player is Ezgi Arslan? | CREATE TABLE table_name_54 (position VARCHAR, height VARCHAR, player VARCHAR) | SELECT position FROM table_name_54 WHERE height > 179 AND player = "ezgi arslan" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5062,
41,
4718,
584,
4280,
28027,
6,
3902,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
1102,
24,
65,
3,
9,
24231,
2186,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1102,
21680,
953,
834,
4350,
834,
5062,
549,
17444,
427,
3902,
2490,
3,
26593,
3430,
1959,
3274,
96,
457,
122,
23,
1584,
7,
1618,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What were the high assist on january 2? | CREATE TABLE table_name_61 (
high_assists VARCHAR,
date VARCHAR
) | SELECT high_assists FROM table_name_61 WHERE date = "january 2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4241,
41,
306,
834,
6500,
7,
17,
7,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
130,
8,
306,
2094,
30,
3,
7066,
76,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
306,
834,
6500,
7,
17,
7,
21680,
953,
834,
4350,
834,
4241,
549,
17444,
427,
833,
3274,
96,
7066,
76,
1208,
204,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Show the average population of all counties. | CREATE TABLE election (
election_id number,
counties_represented text,
district number,
delegate text,
party number,
first_elected number,
committee text
)
CREATE TABLE county (
county_id number,
county_name text,
population number,
zip_code text
)
CREATE TABLE party (
party_id number,
year number,
party text,
governor text,
lieutenant_governor text,
comptroller text,
attorney_general text,
us_senate text
) | SELECT AVG(population) FROM county | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4356,
41,
4356,
834,
23,
26,
381,
6,
16227,
834,
29845,
1499,
6,
3939,
381,
6,
20,
8791,
1499,
6,
1088,
381,
6,
166,
834,
19971,
381,
6,
4492,
1499,
3,
61,
3,
32102,
32103,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
71,
17217,
599,
9791,
7830,
61,
21680,
5435,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the lowest Grid for jj lehto with over 51 laps? | CREATE TABLE table_55852 (
"Driver" text,
"Constructor" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
) | SELECT MIN("Grid") FROM table_55852 WHERE "Laps" > '51' AND "Driver" = 'jj lehto' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3769,
4433,
357,
41,
96,
20982,
52,
121,
1499,
6,
96,
4302,
7593,
127,
121,
1499,
6,
96,
3612,
102,
7,
121,
490,
6,
96,
13368,
87,
1649,
11809,
26,
121,
1499,
6,
96,
13... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
121,
13313,
26,
8512,
21680,
953,
834,
3769,
4433,
357,
549,
17444,
427,
96,
3612,
102,
7,
121,
2490,
3,
31,
5553,
31,
3430,
96,
20982,
52,
121,
3274,
3,
31,
354,
354,
90,
107,
235,
31,
1,
-100,
... |
Tell me the average bronze for total less than 4 and silver more than 0 | CREATE TABLE table_name_96 (bronze INTEGER, total VARCHAR, silver VARCHAR) | SELECT AVG(bronze) FROM table_name_96 WHERE total < 4 AND silver > 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4314,
41,
13711,
776,
3,
21342,
17966,
6,
792,
584,
4280,
28027,
6,
4294,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
8779,
140,
8,
1348,
13467,
21,
792,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
71,
17217,
599,
13711,
776,
61,
21680,
953,
834,
4350,
834,
4314,
549,
17444,
427,
792,
3,
2,
314,
3430,
4294,
2490,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Which conference is in Jackson, Mississippi? | CREATE TABLE table_16182 (
"Institution" text,
"Location" text,
"Men\u2019s Nickname" text,
"Women\u2019s Nickname" text,
"Founded" real,
"Type" text,
"Enrollment" real,
"Joined" text,
"Left" text,
"Current Conference" text,
"Classification" text
) | SELECT "Current Conference" FROM table_16182 WHERE "Location" = 'Jackson, Mississippi' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
2606,
357,
41,
96,
1570,
17448,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
329,
35,
2,
76,
8584,
7,
7486,
4350,
121,
1499,
6,
96,
518,
32,
904,
2,
76... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
254,
450,
5320,
4379,
121,
21680,
953,
834,
2938,
2606,
357,
549,
17444,
427,
96,
434,
32,
75,
257,
121,
3274,
3,
31,
683,
4365,
739,
6,
14579,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.