NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
what is the maximum age of patients whose marital status is divorced and admission type is emergency? | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT MAX(demographic.age) FROM demographic WHERE demographic.marital_status = "DIVORCED" AND demographic.admission_type = "EMERGENCY" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14798,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
564,
1499,
6,
2774,
1947,
834,
8547,
302,
1499,
6,
1246,
1499,
6,
103,
115,
1499,
6,
7285,
1499,
6,
1612,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
1778,
16587,
5,
545,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
1635,
9538,
834,
8547,
302,
3274,
96,
308,
7589,
2990,
254,
2326,
121,
3430,
14798,
5,
9,
26,
5451,
834,
6137,
3274,
96,
427,
13098,
... |
how many games did the bombers win ? | CREATE TABLE table_204_227 (
id number,
"week" number,
"date" text,
"opponent" text,
"score" text,
"result" text,
"record" text
) | SELECT COUNT(*) FROM table_204_227 WHERE "result" = 'win' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
357,
2555,
41,
3,
23,
26,
381,
6,
96,
8041,
121,
381,
6,
96,
5522,
121,
1499,
6,
96,
32,
102,
9977,
121,
1499,
6,
96,
7,
9022,
121,
1499,
6,
96,
60,
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,
2847,
17161,
599,
1935,
61,
21680,
953,
834,
26363,
834,
357,
2555,
549,
17444,
427,
96,
60,
7,
83,
17,
121,
3274,
3,
31,
3757,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Show all customer ids and the number of accounts for each customer. | CREATE TABLE financial_transactions (
transaction_id number,
previous_transaction_id number,
account_id number,
card_id number,
transaction_type text,
transaction_date time,
transaction_amount number,
transaction_comment text,
other_transaction_details text
)
CREATE TABLE customers ... | SELECT customer_id, COUNT(*) FROM accounts GROUP BY customer_id | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
981,
834,
7031,
4787,
7,
41,
5878,
834,
23,
26,
381,
6,
1767,
834,
7031,
4787,
834,
23,
26,
381,
6,
905,
834,
23,
26,
381,
6,
895,
834,
23,
26,
381,
6,
5878,
834,
6137,
1499,
6... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
884,
834,
23,
26,
6,
2847,
17161,
599,
1935,
61,
21680,
3744,
350,
4630,
6880,
272,
476,
884,
834,
23,
26,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
who has the largest amount of teams , men 's , women , or mixed ? | CREATE TABLE table_204_132 (
id number,
"year" number,
"location" text,
"men's individual" text,
"women's individual" text,
"men's team" text,
"women's team" text,
"mixed team" text,
"ref" number
) | SELECT "men's team" FROM table_204_132 GROUP BY "men's team" ORDER BY COUNT(*) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
23757,
41,
3,
23,
26,
381,
6,
96,
1201,
121,
381,
6,
96,
14836,
121,
1499,
6,
96,
904,
31,
7,
928,
121,
1499,
6,
96,
210,
32,
904,
31,
7,
928,
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,
904,
31,
7,
372,
121,
21680,
953,
834,
26363,
834,
23757,
350,
4630,
6880,
272,
476,
96,
904,
31,
7,
372,
121,
4674,
11300,
272,
476,
2847,
17161,
599,
1935,
61,
309,
25067,
8729,
12604,
209,
1,
-100,
-100,
-1... |
For those records from the products and each product's manufacturer, draw a bar chart about the distribution of headquarter and the sum of price , and group by attribute headquarter, I want to sort y axis in desc order. | CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
)
CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
) | SELECT Headquarter, SUM(Price) FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY Headquarter ORDER BY SUM(Price) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7554,
41,
3636,
3,
21342,
17966,
6,
5570,
584,
4280,
28027,
599,
25502,
201,
5312,
3396,
254,
26330,
434,
6,
15248,
3,
21342,
17966,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3642,
19973,
6,
180,
6122,
599,
345,
4920,
61,
21680,
7554,
6157,
332,
536,
3,
15355,
3162,
15248,
7,
6157,
332,
357,
9191,
332,
5411,
7296,
76,
8717,
450,
49,
3274,
332,
4416,
22737,
350,
4630,
6880,
272,
476,
3642... |
What is the leading cause of wildfires? | CREATE TABLE fires (
fire_year number,
discovery_date number,
discovery_doy number,
discovery_time text,
stat_cause_code number,
stat_cause_descr text,
cont_date text,
cont_doy text,
cont_time text,
fire_size number,
fire_size_class text,
latitude number,
longitude nu... | SELECT stat_cause_descr FROM fires GROUP BY stat_cause_descr ORDER BY COUNT(*) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1472,
7,
41,
1472,
834,
1201,
381,
6,
9087,
834,
5522,
381,
6,
9087,
834,
26,
32,
63,
381,
6,
9087,
834,
715,
1499,
6,
3089,
834,
658,
1074,
834,
4978,
381,
6,
3089,
834,
658,
10... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3089,
834,
658,
1074,
834,
26,
1579,
52,
21680,
1472,
7,
350,
4630,
6880,
272,
476,
3089,
834,
658,
1074,
834,
26,
1579,
52,
4674,
11300,
272,
476,
2847,
17161,
599,
1935,
61,
309,
25067,
8729,
12604,
209,
1,
-100,
... |
what number of patients have been discharged from the hospital in 2101? | CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE intakeoutput (
intakeo... | SELECT COUNT(DISTINCT patient.uniquepid) FROM patient WHERE NOT patient.hospitaldischargetime IS NULL AND STRFTIME('%y', patient.hospitaldischargetime) = '2101' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
50,
9824,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
7690,
4350,
1499,
6,
50,
1999,
7,
83,
17,
381,
6,
50,
1999,
7,
83,
17,
715,
97,
3,
61,
3,
32102,
32103,
32102,
2... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
1868,
5,
202,
1495,
12417,
61,
21680,
1868,
549,
17444,
427,
4486,
1868,
5,
31386,
26,
159,
7993,
715,
6827,
13046,
10376,
3430,
3,
13733,
6245,
15382,
599,
31,
1454,
63,
31,
6,
... |
What was the aggregate score for the game against Dynamo Dresden? | CREATE TABLE table_name_66 (
aggregate_score VARCHAR,
opposition VARCHAR
) | SELECT aggregate_score FROM table_name_66 WHERE opposition = "dynamo dresden" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3539,
41,
12955,
834,
7,
9022,
584,
4280,
28027,
6,
8263,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
12955,
2604,
21,
8,
467,
581,
13967... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
12955,
834,
7,
9022,
21680,
953,
834,
4350,
834,
3539,
549,
17444,
427,
8263,
3274,
96,
24805,
51,
32,
3,
26,
60,
7,
537,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many patients whose death status is 1 and diagnoses short title is fall nos? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.expire_flag = "1" AND diagnoses.short_title = "Fall NOS" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
How many games were held on January 5? | CREATE TABLE table_29734 (
"Game" real,
"Date" text,
"Team" text,
"Score" text,
"High points" text,
"High rebounds" text,
"High assists" text,
"Location Attendance" text,
"Record" text
) | SELECT COUNT("Game") FROM table_29734 WHERE "Date" = 'January 5' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
4327,
3710,
41,
96,
23055,
121,
490,
6,
96,
308,
342,
121,
1499,
6,
96,
18699,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
21417,
979,
121,
1499,
6,
96,
21417,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
23055,
8512,
21680,
953,
834,
357,
4327,
3710,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
30404,
305,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What county is the town with a rank of 205 located in? | CREATE TABLE table_name_78 (county VARCHAR, population_rank VARCHAR) | SELECT county FROM table_name_78 WHERE population_rank = 205 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3940,
41,
13362,
63,
584,
4280,
28027,
6,
2074,
834,
6254,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
5435,
19,
8,
1511,
28,
3,
9,
11003,
13,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
5435,
21680,
953,
834,
4350,
834,
3940,
549,
17444,
427,
2074,
834,
6254,
3274,
3,
23201,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the series of the episode directed by Abe Levitow released on 1959-06-27? | CREATE TABLE table_name_63 (
series VARCHAR,
director VARCHAR,
release_date VARCHAR
) | SELECT series FROM table_name_63 WHERE director = "abe levitow" AND release_date = "1959-06-27" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3891,
41,
939,
584,
4280,
28027,
6,
2090,
584,
4280,
28027,
6,
1576,
834,
5522,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
939,
13,
8,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0... | [
3,
23143,
14196,
939,
21680,
953,
834,
4350,
834,
3891,
549,
17444,
427,
2090,
3274,
96,
9,
346,
90,
5566,
2381,
121,
3430,
1576,
834,
5522,
3274,
96,
2294,
3390,
18,
5176,
18,
2555,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Who plays halfback? | CREATE TABLE table_63832 (
"Pick" real,
"Team" text,
"Player" text,
"Position" text,
"College" text
) | SELECT "Player" FROM table_63832 WHERE "Position" = 'halfback' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3891,
4591,
357,
41,
96,
345,
3142,
121,
490,
6,
96,
18699,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
9939,
7883,
121,
1499,
3,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
96,
15800,
49,
121,
21680,
953,
834,
3891,
4591,
357,
549,
17444,
427,
96,
345,
32,
7,
4749,
121,
3274,
3,
31,
17114,
1549,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What district re-elected a Republican? | CREATE TABLE table_59879 (
"District" text,
"Incumbent" text,
"Party" text,
"First elected" real,
"Results" text
) | SELECT "District" FROM table_59879 WHERE "Party" = 'republican' AND "Results" = 're-elected' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3916,
4440,
41,
96,
308,
23,
20066,
121,
1499,
6,
96,
1570,
75,
5937,
295,
121,
1499,
6,
96,
13725,
63,
121,
1499,
6,
96,
25171,
8160,
121,
490,
6,
96,
20119,
7,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
308,
23,
20066,
121,
21680,
953,
834,
755,
3916,
4440,
549,
17444,
427,
96,
13725,
63,
121,
3274,
3,
31,
60,
15727,
152,
31,
3430,
96,
20119,
7,
121,
3274,
3,
31,
60,
18,
19971,
31,
1,
-100,
-100,
-100,
-100... |
How many copies were sold where the position is lager than 1 in 1988? | CREATE TABLE table_35901 (
"Year" real,
"Album" text,
"Oricon position" real,
"1st week sales" text,
"Copies sold" text
) | SELECT "Copies sold" FROM table_35901 WHERE "Oricon position" > '1' AND "Year" = '1988' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2469,
2394,
536,
41,
96,
476,
2741,
121,
490,
6,
96,
25691,
440,
121,
1499,
6,
96,
7395,
23,
1018,
1102,
121,
490,
6,
96,
536,
7,
17,
471,
1085,
121,
1499,
6,
96,
3881,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3881,
8497,
1916,
121,
21680,
953,
834,
2469,
2394,
536,
549,
17444,
427,
96,
7395,
23,
1018,
1102,
121,
2490,
3,
31,
536,
31,
3430,
96,
476,
2741,
121,
3274,
3,
31,
2294,
4060,
31,
1,
-100,
-100,
-100,
-100,
... |
2007 of 8 4 is involved in what 2002? | CREATE TABLE table_name_69 (
Id VARCHAR
) | SELECT 2002 FROM table_name_69 WHERE 2007 = "8–4" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3951,
41,
27,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4101,
13,
505,
314,
19,
1381,
16,
125,
4407,
58,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4407,
21680,
953,
834,
4350,
834,
3951,
549,
17444,
427,
4101,
3274,
96,
927,
104,
20364,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the score of the game played on August 5? | CREATE TABLE table_name_66 (score VARCHAR, date VARCHAR) | SELECT score FROM table_name_66 WHERE date = "august 5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3539,
41,
7,
9022,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2604,
13,
8,
467,
1944,
30,
1660,
305,
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,
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,
2604,
21680,
953,
834,
4350,
834,
3539,
549,
17444,
427,
833,
3274,
96,
402,
17198,
3,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many actors have appeared in each musical?, and list from low to high by the y-axis please. | CREATE TABLE actor (
Actor_ID int,
Name text,
Musical_ID int,
Character text,
Duration text,
age int
)
CREATE TABLE musical (
Musical_ID int,
Name text,
Year int,
Award text,
Category text,
Nominee text,
Result text
) | SELECT T2.Name, COUNT(*) FROM actor AS T1 JOIN musical AS T2 ON T1.Musical_ID = T2.Musical_ID GROUP BY T1.Musical_ID ORDER BY COUNT(*) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7556,
41,
1983,
127,
834,
4309,
16,
17,
6,
5570,
1499,
6,
22307,
834,
4309,
16,
17,
6,
20087,
1499,
6,
20610,
1499,
6,
1246,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
332,
4416,
23954,
6,
2847,
17161,
599,
1935,
61,
21680,
7556,
6157,
332,
536,
3,
15355,
3162,
4183,
6157,
332,
357,
9191,
332,
5411,
29035,
138,
834,
4309,
3274,
332,
4416,
29035,
138,
834,
4309,
350,
4630,
6880,
272,... |
Who are the outgoing head coaches whose manner of departure is Gardening Leave 1? | CREATE TABLE table_29171931_3 (
outgoing_head_coach VARCHAR,
manner_of_departure VARCHAR
) | SELECT outgoing_head_coach FROM table_29171931_3 WHERE manner_of_departure = "Gardening leave 1" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
2517,
2294,
3341,
834,
519,
41,
91,
9545,
834,
3313,
834,
509,
1836,
584,
4280,
28027,
6,
3107,
834,
858,
834,
221,
2274,
1462,
584,
4280,
28027,
3,
61,
3,
32102,
321... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
91,
9545,
834,
3313,
834,
509,
1836,
21680,
953,
834,
3166,
2517,
2294,
3341,
834,
519,
549,
17444,
427,
3107,
834,
858,
834,
221,
2274,
1462,
3274,
96,
21846,
537,
53,
1175,
209,
121,
1,
-100,
-100,
-100,
-100,
-10... |
Who was the developer(s) of the genre Adventure? | CREATE TABLE table_name_22 (developer_s_ VARCHAR, genre VARCHAR) | SELECT developer_s_ FROM table_name_22 WHERE genre = "adventure" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2884,
41,
29916,
49,
834,
7,
834,
584,
4280,
28027,
6,
5349,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
8,
7523,
599,
7,
61,
13,
8,
5349,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7523,
834,
7,
834,
21680,
953,
834,
4350,
834,
2884,
549,
17444,
427,
5349,
3274,
96,
9,
26,
2169,
1462,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
1980 smaller than 719, and a 1960 smaller than 205, and a 1996[2] smaller than 364, and a 1970 larger than 251 is what 1990 highest? | CREATE TABLE table_36166 (
"1950" real,
"1960" real,
"1970" real,
"1980" real,
"1990" real,
"1996[2]" real
) | SELECT MAX("1990") FROM table_36166 WHERE "1980" < '719' AND "1960" < '205' AND "1996[2]" < '364' AND "1970" > '251' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3420,
26811,
41,
96,
2294,
1752,
121,
490,
6,
96,
2294,
3328,
121,
490,
6,
96,
2294,
2518,
121,
490,
6,
96,
2294,
2079,
121,
490,
6,
96,
2294,
2394,
121,
490,
6,
96,
22... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
2294,
2394,
8512,
21680,
953,
834,
3420,
26811,
549,
17444,
427,
96,
2294,
2079,
121,
3,
2,
3,
31,
940,
2294,
31,
3430,
96,
2294,
3328,
121,
3,
2,
3,
31,
23201,
31,
3430,
96,
2294,
4314,
6306,... |
What time did team kawasaki zx10 1000cc have? | CREATE TABLE table_name_72 (time VARCHAR, team VARCHAR) | SELECT time FROM table_name_72 WHERE team = "kawasaki zx10 1000cc" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5865,
41,
715,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
97,
410,
372,
3,
1258,
9491,
11259,
3,
172,
226,
1714,
5580,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
97,
21680,
953,
834,
4350,
834,
5865,
549,
17444,
427,
372,
3274,
96,
1258,
9491,
11259,
3,
172,
226,
1714,
5580,
75,
75,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the class when the frequency is 560 AM? | CREATE TABLE table_name_57 (
class VARCHAR,
frequency VARCHAR
) | SELECT class FROM table_name_57 WHERE frequency = "560 am" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3436,
41,
853,
584,
4280,
28027,
6,
7321,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
853,
116,
8,
7321,
19,
305,
3328,
5422,
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,
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,
853,
21680,
953,
834,
4350,
834,
3436,
549,
17444,
427,
7321,
3274,
96,
755,
3328,
183,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What Best Bowl is it that has 151 Matches and 1 100s? | CREATE TABLE table_15732 (
"Matches" real,
"Runs" real,
"Bat Ave" real,
"High Score" text,
"100s" real,
"Wickets" real,
"Bowl Ave" real,
"Best Bowl" text
) | SELECT "Best Bowl" FROM table_15732 WHERE "100s" = '1' AND "Matches" = '151' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
27452,
2668,
41,
96,
329,
144,
2951,
121,
490,
6,
96,
448,
202,
7,
121,
490,
6,
96,
279,
144,
8945,
121,
490,
6,
96,
21417,
17763,
121,
1499,
6,
96,
2915,
7,
121,
490,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
17278,
9713,
121,
21680,
953,
834,
27452,
2668,
549,
17444,
427,
96,
2915,
7,
121,
3274,
3,
31,
536,
31,
3430,
96,
329,
144,
2951,
121,
3274,
3,
31,
26578,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What score did vasil levski national stadium, sofia, which was friendly during competition, earn? | CREATE TABLE table_31553 (
"Date" text,
"Venue" text,
"Score" text,
"Result" text,
"Competition" text
) | SELECT "Score" FROM table_31553 WHERE "Competition" = 'friendly' AND "Venue" = 'vasil levski national stadium, sofia' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
1808,
4867,
41,
96,
308,
342,
121,
1499,
6,
96,
553,
35,
76,
15,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
5890,
4995,
4749,
121,
149... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
134,
9022,
121,
21680,
953,
834,
519,
1808,
4867,
549,
17444,
427,
96,
5890,
4995,
4749,
121,
3274,
3,
31,
4905,
31,
3430,
96,
553,
35,
76,
15,
121,
3274,
3,
31,
9856,
173,
3,
10912,
4009,
1157,
14939,
6,
78... |
How many silver medals were won in 1938? | CREATE TABLE table_44889 (
"Year" text,
"Gold" text,
"Silver" text,
"Bronze" text,
"Total" text
) | SELECT "Silver" FROM table_44889 WHERE "Year" = '1938' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
3707,
3914,
41,
96,
476,
2741,
121,
1499,
6,
96,
23576,
121,
1499,
6,
96,
134,
173,
624,
121,
1499,
6,
96,
22780,
29,
776,
121,
1499,
6,
96,
3696,
1947,
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,
0,
0... | [
3,
23143,
14196,
96,
134,
173,
624,
121,
21680,
953,
834,
591,
3707,
3914,
549,
17444,
427,
96,
476,
2741,
121,
3274,
3,
31,
2294,
3747,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
give the discharge location of kelly gallardo. | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT demographic.discharge_location FROM demographic WHERE demographic.name = "Kelly Gallardo" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14798,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
564,
1499,
6,
2774,
1947,
834,
8547,
302,
1499,
6,
1246,
1499,
6,
103,
115,
1499,
6,
7285,
1499,
6,
1612,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
14798,
5,
26,
159,
7993,
834,
14836,
21680,
14798,
549,
17444,
427,
14798,
5,
4350,
3274,
96,
439,
15,
6073,
10987,
986,
32,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the total number of every ship type by categorizing by nationality?, list by the bar in ascending. | CREATE TABLE mission (
Mission_ID int,
Ship_ID int,
Code text,
Launched_Year int,
Location text,
Speed_knots int,
Fate text
)
CREATE TABLE ship (
Ship_ID int,
Name text,
Type text,
Nationality text,
Tonnage int
) | SELECT Type, COUNT(Type) FROM ship GROUP BY Nationality, Type ORDER BY Type | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2253,
41,
8960,
834,
4309,
16,
17,
6,
15508,
834,
4309,
16,
17,
6,
3636,
1499,
6,
17113,
15,
26,
834,
476,
2741,
16,
17,
6,
10450,
1499,
6,
9913,
834,
157,
2264,
7,
16,
17,
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,
6632,
6,
2847,
17161,
599,
25160,
61,
21680,
4383,
350,
4630,
6880,
272,
476,
868,
485,
6,
6632,
4674,
11300,
272,
476,
6632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Which city has a First season of current spell in Segunda Divisi n smaller than 2013? | CREATE TABLE table_name_69 (
city VARCHAR,
first_season_of_current_spell_in_segunda_división INTEGER
) | SELECT city FROM table_name_69 WHERE first_season_of_current_spell_in_segunda_división < 2013 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3951,
41,
690,
584,
4280,
28027,
6,
166,
834,
9476,
834,
858,
834,
14907,
834,
7,
19510,
834,
77,
834,
7,
15,
122,
1106,
9,
834,
8481,
159,
23,
15742,
3,
21342... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
690,
21680,
953,
834,
4350,
834,
3951,
549,
17444,
427,
166,
834,
9476,
834,
858,
834,
14907,
834,
7,
19510,
834,
77,
834,
7,
15,
122,
1106,
9,
834,
8481,
159,
23,
15742,
3,
2,
2038,
1,
-100,
-100,
-100,
-100,
-... |
For the player that scored 27 goals, what years did he score them? | CREATE TABLE table_60920 (
"Ranking" text,
"Nationality" text,
"Name" text,
"Years" text,
"Goals" real
) | SELECT "Years" FROM table_60920 WHERE "Goals" = '27' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3328,
27749,
41,
96,
22557,
53,
121,
1499,
6,
96,
24732,
485,
121,
1499,
6,
96,
23954,
121,
1499,
6,
96,
476,
2741,
7,
121,
1499,
6,
96,
6221,
5405,
121,
490,
3,
61,
3,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
476,
2741,
7,
121,
21680,
953,
834,
3328,
27749,
549,
17444,
427,
96,
6221,
5405,
121,
3274,
3,
31,
2555,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many draws were there in played games? | CREATE TABLE table_22019 (
"Club" text,
"Played" text,
"Won" text,
"Drawn" text,
"Lost" text,
"Points for" text,
"Points against" text,
"Tries for" text,
"Tries against" text,
"Try bonus" text,
"Losing bonus" text,
"Points" text
) | SELECT "Drawn" FROM table_22019 WHERE "Played" = 'Played' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
8584,
41,
96,
254,
11158,
121,
1499,
6,
96,
15800,
15,
26,
121,
1499,
6,
96,
518,
106,
121,
1499,
6,
96,
308,
10936,
29,
121,
1499,
6,
96,
434,
3481,
121,
1499,
6,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
308,
10936,
29,
121,
21680,
953,
834,
357,
8584,
549,
17444,
427,
96,
15800,
15,
26,
121,
3274,
3,
31,
15800,
15,
26,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the lowest year that has hypo-meeting as the tournament, with 8002 as the points? | CREATE TABLE table_name_52 (
year INTEGER,
tournament VARCHAR,
points VARCHAR
) | SELECT MIN(year) FROM table_name_52 WHERE tournament = "hypo-meeting" AND points = "8002" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5373,
41,
215,
3,
21342,
17966,
6,
5892,
584,
4280,
28027,
6,
979,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
7402,
215,
24,
65,
10950,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
1201,
61,
21680,
953,
834,
4350,
834,
5373,
549,
17444,
427,
5892,
3274,
96,
13397,
32,
18,
526,
15,
1222,
121,
3430,
979,
3274,
96,
6192,
357,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What Silver has the Location of Guangzhou? | CREATE TABLE table_74888 (
"Year" real,
"Location" text,
"Gold" text,
"Silver" text,
"Bronze" text
) | SELECT "Silver" FROM table_74888 WHERE "Location" = 'guangzhou' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4581,
10927,
41,
96,
476,
2741,
121,
490,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
23576,
121,
1499,
6,
96,
134,
173,
624,
121,
1499,
6,
96,
22780,
29,
776,
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,
0... | [
3,
23143,
14196,
96,
134,
173,
624,
121,
21680,
953,
834,
4581,
10927,
549,
17444,
427,
96,
434,
32,
75,
257,
121,
3274,
3,
31,
1744,
1468,
25303,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
give me the number of patients with diagnoses icd9 code 59654 who were hospitalized for more than 6 days. | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.days_stay > "6" AND diagnoses.icd9_code = "59654" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
What ship was built by Palmers Shipbuilding and Iron Company for the Royal Navy? | CREATE TABLE table_13009 (
"Country" text,
"Builder" text,
"Location" text,
"Ship" text,
"Class / type" text
) | SELECT "Ship" FROM table_13009 WHERE "Country" = 'royal navy' AND "Builder" = 'palmers shipbuilding and iron company' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
21448,
4198,
41,
96,
10628,
651,
121,
1499,
6,
96,
24752,
49,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
134,
10462,
121,
1499,
6,
96,
21486,
3,
87,
686,
121... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
134,
10462,
121,
21680,
953,
834,
21448,
4198,
549,
17444,
427,
96,
10628,
651,
121,
3274,
3,
31,
8170,
138,
23118,
31,
3430,
96,
24752,
49,
121,
3274,
3,
31,
6459,
5567,
4383,
10905,
11,
3575,
349,
31,
1,
-10... |
What Conference was during the NCAA Tournament? | CREATE TABLE table_5285 (
"Date" text,
"Opponent" text,
"Location" text,
"Result" text,
"Overall" text,
"Conf." text
) | SELECT "Conf." FROM table_5285 WHERE "Date" = 'ncaa tournament' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5373,
4433,
41,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
23847,
1748,
121,
1499,
6... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
4302,
89,
535,
21680,
953,
834,
5373,
4433,
549,
17444,
427,
96,
308,
342,
121,
3274,
3,
31,
29,
658,
9,
5892,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
How many Matches have Balls smaller than 224, and an Average larger than 38.25, and an S/Rate larger than 139.09? | CREATE TABLE table_name_87 (
matches INTEGER,
s_rate VARCHAR,
balls VARCHAR,
average VARCHAR
) | SELECT SUM(matches) FROM table_name_87 WHERE balls < 224 AND average > 38.25 AND s_rate > 139.09 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4225,
41,
6407,
3,
21342,
17966,
6,
3,
7,
834,
2206,
584,
4280,
28027,
6,
11607,
584,
4280,
28027,
6,
1348,
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,
180,
6122,
599,
19515,
15,
7,
61,
21680,
953,
834,
4350,
834,
4225,
549,
17444,
427,
11607,
3,
2,
3,
24622,
3430,
1348,
2490,
6654,
5,
1828,
3430,
3,
7,
834,
2206,
2490,
3,
24090,
5,
4198,
1,
-100,
-100,
-100,
-... |
how many patients with elective admission type were given the drug rosiglitazone maleate? | 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 demographic ... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.admission_type = "ELECTIVE" AND prescriptions.drug = "Rosiglitazone Maleate" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
7744,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7744,
7,
5,
8399,
51,
834,
23,
26,
549... |
What was the world rank by ARWU in 2013 of the University of T bingen? | CREATE TABLE table_29538 (
"Members" text,
"Country" text,
"Year Established" real,
"World Rank by THE-WUR , 2013" text,
"World Rank by ARWU , 2013" text,
"World Rank by QS , 2013" text
) | SELECT "World Rank by ARWU , 2013" FROM table_29538 WHERE "Members" = 'University of Tübingen' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3301,
3747,
41,
96,
329,
18247,
7,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
476,
2741,
25275,
121,
490,
6,
96,
17954,
3,
22557,
57,
1853,
18,
518,
5905,
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,
17954,
3,
22557,
57,
11155,
518,
1265,
3,
6,
2038,
121,
21680,
953,
834,
357,
3301,
3747,
549,
17444,
427,
96,
329,
18247,
7,
121,
3274,
3,
31,
8313,
485,
13,
332,
1272,
115,
53,
35,
31,
1,
-100,
-100,
-100,... |
What are the gaols(L/C/E) with an App(L/C/E) of 55 (47/5/3)? | CREATE TABLE table_46011 (
"Nat." text,
"Name" text,
"Since" text,
"App(L/C/E)" text,
"Goals(L/C/E)" text,
"Ends" real,
"Transfer fee" text
) | SELECT "Goals(L/C/E)" FROM table_46011 WHERE "App(L/C/E)" = '55 (47/5/3)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25991,
2596,
41,
96,
567,
144,
535,
1499,
6,
96,
23954,
121,
1499,
6,
96,
134,
77,
565,
121,
1499,
6,
96,
9648,
599,
434,
87,
254,
87,
427,
61,
121,
1499,
6,
96,
6221,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
6221,
5405,
599,
434,
87,
254,
87,
427,
61,
121,
21680,
953,
834,
25991,
2596,
549,
17444,
427,
96,
9648,
599,
434,
87,
254,
87,
427,
61,
121,
3274,
3,
31,
3769,
41,
4177,
16936,
87,
5268,
31,
1,
-100,
-100,... |
what is the number of patients whose procedure long title is other open incisional hernia repair with graft or prosthesis and lab test fluid is blood? | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE procedures.long_title = "Other open incisional hernia repair with graft or prosthesis" AND lab.fluid = "Blood" | [
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,
3388,
18206... |
What is the Weight of the person born 1981-02-24 from the Uralochka Zlatoust club ? | CREATE TABLE table_58679 (
"Name" text,
"Pos." text,
"Height" text,
"Weight" text,
"Date of Birth" text,
"Club" text
) | SELECT "Weight" FROM table_58679 WHERE "Club" = 'uralochka zlatoust' AND "Date of Birth" = '1981-02-24' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3840,
4440,
41,
96,
23954,
121,
1499,
6,
96,
345,
32,
7,
535,
1499,
6,
96,
3845,
2632,
121,
1499,
6,
96,
1326,
2632,
121,
1499,
6,
96,
308,
342,
13,
26337,
121,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
1326,
2632,
121,
21680,
953,
834,
755,
3840,
4440,
549,
17444,
427,
96,
254,
11158,
121,
3274,
3,
31,
9709,
6322,
1258,
3,
172,
40,
144,
1162,
17,
31,
3430,
96,
308,
342,
13,
26337,
121,
3274,
3,
31,
24151,
... |
calculate the number of patients to whom neo*iv*clindamycin was administered | 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 te... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE prescriptions.drug = "NEO*IV*Clindamycin" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7744,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
23,
1071,
21545,
834,
23,
26,
1499,
6,
2672,
834,
6137,
1499,
6,
2672,
1499,
6,
5403,
651,
834,
26,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
7744,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7744,
7,
5,
8399,
51,
834,
23,
26,
549... |
What was the earliest year for the 400 M Hurdles in Santiago, Chile? | CREATE TABLE table_name_71 (year INTEGER, venue VARCHAR, event VARCHAR) | SELECT MIN(year) FROM table_name_71 WHERE venue = "santiago, chile" AND event = "400 m hurdles" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4450,
41,
1201,
3,
21342,
17966,
6,
5669,
584,
4280,
28027,
6,
605,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
3,
16454,
215,
21,
8,
4837,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
1201,
61,
21680,
953,
834,
4350,
834,
4450,
549,
17444,
427,
5669,
3274,
96,
7,
5965,
9,
839,
6,
3,
1436,
109,
121,
3430,
605,
3274,
96,
5548,
3,
51,
23463,
7,
121,
1,
-100,
-100,
-100,
-100,
-100... |
Name the least amount of tackles for danny clark | CREATE TABLE table_15581223_8 (tackles INTEGER, player VARCHAR) | SELECT MIN(tackles) FROM table_15581223_8 WHERE player = "Danny Clark" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1808,
3449,
2122,
2773,
834,
927,
41,
17,
4365,
965,
3,
21342,
17966,
6,
1959,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
709,
866,
13,
8000,
7,
21,
1352... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
17,
4365,
965,
61,
21680,
953,
834,
1808,
3449,
2122,
2773,
834,
927,
549,
17444,
427,
1959,
3274,
96,
308,
15159,
8265,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the record when the game was at the Rose Garden? | CREATE TABLE table_name_75 (
record VARCHAR,
location VARCHAR
) | SELECT record FROM table_name_75 WHERE location = "rose garden" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3072,
41,
1368,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1368,
116,
8,
467,
47,
44,
8,
5088,
5072,
58,
1,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1368,
21680,
953,
834,
4350,
834,
3072,
549,
17444,
427,
1128,
3274,
96,
8115,
2004,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
WHAT IS THE GERMAN NAME OF LIBERALISM? | CREATE TABLE table_49042 (
"Name (English)" text,
"Name (German)" text,
"Abbr." text,
"Ideology" text,
"Position" text,
"Votes (2011)" text,
"Seats in Hamburgische B\u00fcrgerschaft" real
) | SELECT "Name (German)" FROM table_49042 WHERE "Ideology" = 'liberalism' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
2394,
4165,
41,
96,
23954,
41,
26749,
61,
121,
1499,
6,
96,
23954,
41,
24518,
61,
121,
1499,
6,
96,
8952,
115,
52,
535,
1499,
6,
96,
196,
221,
1863,
121,
1499,
6,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
23954,
41,
24518,
61,
121,
21680,
953,
834,
591,
2394,
4165,
549,
17444,
427,
96,
196,
221,
1863,
121,
3274,
3,
31,
10661,
6835,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Who replaced on the date of appointment 2 november 2010? | CREATE TABLE table_24231638_3 (replaced_by VARCHAR, date_of_appointment VARCHAR) | SELECT replaced_by FROM table_24231638_3 WHERE date_of_appointment = "2 November 2010" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2266,
2773,
2938,
3747,
834,
519,
41,
60,
4687,
26,
834,
969,
584,
4280,
28027,
6,
833,
834,
858,
834,
9,
102,
2700,
297,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
3210... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
5821,
834,
969,
21680,
953,
834,
2266,
2773,
2938,
3747,
834,
519,
549,
17444,
427,
833,
834,
858,
834,
9,
102,
2700,
297,
3274,
96,
357,
1671,
2735,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Which bubbles has an atribute of onlostpointercapture? | CREATE TABLE table_name_87 (
bubbles VARCHAR,
attribute VARCHAR
) | SELECT bubbles FROM table_name_87 WHERE attribute = "onlostpointercapture" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4225,
41,
11144,
7,
584,
4280,
28027,
6,
15816,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
11144,
7,
65,
46,
3,
9,
5135,
17,
15,
13,
30,
229... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
11144,
7,
21680,
953,
834,
4350,
834,
4225,
549,
17444,
427,
15816,
3274,
96,
106,
2298,
17,
2700,
49,
4010,
2693,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Find the names of all distinct wines that have appellations in North Coast area. | CREATE TABLE WINE (
Name VARCHAR,
Appelation VARCHAR
)
CREATE TABLE APPELLATIONs (
Appelation VARCHAR,
Area VARCHAR
) | SELECT DISTINCT T2.Name FROM APPELLATIONs AS T1 JOIN WINE AS T2 ON T1.Appelation = T2.Appelation WHERE T1.Area = "North Coast" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
549,
9730,
41,
5570,
584,
4280,
28027,
6,
3,
27794,
257,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
3,
13747,
12735,
8015,
7,
41,
3,
27794,
257,
58... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
15438,
25424,
6227,
332,
4416,
23954,
21680,
3,
13747,
12735,
8015,
7,
6157,
332,
536,
3,
15355,
3162,
549,
9730,
6157,
332,
357,
9191,
332,
5411,
27794,
257,
3274,
332,
4416,
27794,
257,
549,
17444,
427,
332,
5411... |
Which ZX Spectrum has a Year larger than 1984, and a Genre of arcade/strategy? | CREATE TABLE table_name_92 (
zx_spectrum VARCHAR,
year VARCHAR,
genre VARCHAR
) | SELECT zx_spectrum FROM table_name_92 WHERE year > 1984 AND genre = "arcade/strategy" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4508,
41,
3,
172,
226,
834,
5628,
2781,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
6,
5349,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
1027,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
172,
226,
834,
5628,
2781,
21680,
953,
834,
4350,
834,
4508,
549,
17444,
427,
215,
2490,
13480,
3430,
5349,
3274,
96,
291,
6615,
87,
7,
17,
2206,
122,
63,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the number of proto austronesian for *natu | CREATE TABLE table_15568886_14 (
proto_austronesian VARCHAR,
proto_oceanic VARCHAR
) | SELECT COUNT(proto_austronesian) FROM table_15568886_14 WHERE proto_oceanic = "*natu" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1808,
4834,
10927,
948,
834,
2534,
41,
23844,
834,
2064,
6255,
15,
10488,
584,
4280,
28027,
6,
23844,
834,
32,
8433,
2532,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
1409,
235,
834,
2064,
6255,
15,
10488,
61,
21680,
953,
834,
1808,
4834,
10927,
948,
834,
2534,
549,
17444,
427,
23844,
834,
32,
8433,
2532,
3274,
96,
1935,
29,
144,
76,
121,
1,
-100,
-100,
-100,
-1... |
Which Genre has a Year larger than 1999, and a Game of tony hawk's pro skater 2? | CREATE TABLE table_name_90 (
genre VARCHAR,
year VARCHAR,
game VARCHAR
) | SELECT genre FROM table_name_90 WHERE year > 1999 AND game = "tony hawk's pro skater 2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2394,
41,
5349,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
6,
467,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
5945,
60,
65,
3,
9,
2929,
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,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
5349,
21680,
953,
834,
4350,
834,
2394,
549,
17444,
427,
215,
2490,
5247,
3430,
467,
3274,
96,
17,
106,
63,
3,
14400,
31,
7,
813,
16573,
52,
204,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those records from the products and each product's manufacturer, draw a bar chart about the distribution of headquarter and the average of manufacturer , and group by attribute headquarter, and order by the y-axis in descending. | CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
)
CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
) | SELECT Headquarter, AVG(Manufacturer) FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY Headquarter ORDER BY AVG(Manufacturer) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7554,
41,
3636,
3,
21342,
17966,
6,
5570,
584,
4280,
28027,
599,
25502,
201,
5312,
3396,
254,
26330,
434,
6,
15248,
3,
21342,
17966,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3642,
19973,
6,
71,
17217,
599,
7296,
76,
8717,
450,
49,
61,
21680,
7554,
6157,
332,
536,
3,
15355,
3162,
15248,
7,
6157,
332,
357,
9191,
332,
5411,
7296,
76,
8717,
450,
49,
3274,
332,
4416,
22737,
350,
4630,
6880,
... |
Tell me the Laps for time/retired of +1:08.491 | CREATE TABLE table_name_39 (
laps VARCHAR,
time_retired VARCHAR
) | SELECT laps FROM table_name_39 WHERE time_retired = "+1:08.491" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3288,
41,
14941,
7,
584,
4280,
28027,
6,
97,
834,
10682,
1271,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
8779,
140,
8,
325,
102,
7,
21,
97,
87,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
14941,
7,
21680,
953,
834,
4350,
834,
3288,
549,
17444,
427,
97,
834,
10682,
1271,
3274,
96,
18446,
10,
15000,
3647,
536,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the Total number of medals for the Nation with 7 or less Bronze medals and 1 Silver medal with a Rank of 9 or larger? | CREATE TABLE table_name_90 (
total INTEGER,
rank VARCHAR,
bronze VARCHAR,
silver VARCHAR
) | SELECT MIN(total) FROM table_name_90 WHERE bronze < 7 AND silver = 1 AND rank > 9 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2394,
41,
792,
3,
21342,
17966,
6,
11003,
584,
4280,
28027,
6,
13467,
584,
4280,
28027,
6,
4294,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
235,
1947,
61,
21680,
953,
834,
4350,
834,
2394,
549,
17444,
427,
13467,
3,
2,
489,
3430,
4294,
3274,
209,
3430,
11003,
2490,
668,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For entries with a lost of 5, what is the sum of the draw entry? | CREATE TABLE table_name_23 (draw INTEGER, lost VARCHAR) | SELECT SUM(draw) FROM table_name_23 WHERE lost = 5 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2773,
41,
19489,
3,
21342,
17966,
6,
1513,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
242,
10066,
28,
3,
9,
1513,
13,
7836,
125,
19,
8,
4505,
13,
8,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
180,
6122,
599,
19489,
61,
21680,
953,
834,
4350,
834,
2773,
549,
17444,
427,
1513,
3274,
305,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the latest year any of the incumbents were first elected? | CREATE TABLE table_1342270_42 (first_elected INTEGER) | SELECT MAX(first_elected) FROM table_1342270_42 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2368,
4165,
17485,
834,
4165,
41,
14672,
834,
19971,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1251,
215,
136,
13,
8,
28406,
7,
130,
166,
8160,
58,
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,
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,
14672,
834,
19971,
61,
21680,
953,
834,
2368,
4165,
17485,
834,
4165,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What's the process technology of the Intel WiFi Link 5100 wireless LAN? | CREATE TABLE table_199666_1 (
process_technology VARCHAR,
wireless_lan VARCHAR
) | SELECT process_technology FROM table_199666_1 WHERE wireless_lan = "Intel WiFi Link 5100" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2294,
4314,
3539,
834,
536,
41,
433,
834,
18485,
584,
4280,
28027,
6,
5419,
834,
1618,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
31,
7,
8,
433,
748,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
433,
834,
18485,
21680,
953,
834,
2294,
4314,
3539,
834,
536,
549,
17444,
427,
5419,
834,
1618,
3274,
96,
1570,
1625,
13831,
7505,
305,
2915,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Time has a Round larger than 1, and an Event of total fighting alliance 2? | CREATE TABLE table_name_21 (
time VARCHAR,
round VARCHAR,
event VARCHAR
) | SELECT time FROM table_name_21 WHERE round > 1 AND event = "total fighting alliance 2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2658,
41,
97,
584,
4280,
28027,
6,
1751,
584,
4280,
28027,
6,
605,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
2900,
65,
3,
9,
9609,
2186,
145,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
97,
21680,
953,
834,
4350,
834,
2658,
549,
17444,
427,
1751,
2490,
209,
3430,
605,
3274,
96,
235,
1947,
6237,
15454,
204,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is Match Report, when Venue is 'Westfalenstadion , Dortmund'? | CREATE TABLE table_name_92 (
match_report VARCHAR,
venue VARCHAR
) | SELECT match_report FROM table_name_92 WHERE venue = "westfalenstadion , dortmund" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4508,
41,
1588,
834,
60,
1493,
584,
4280,
28027,
6,
5669,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
12296,
3750,
6,
116,
29940,
19,
3,
31,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1588,
834,
60,
1493,
21680,
953,
834,
4350,
834,
4508,
549,
17444,
427,
5669,
3274,
96,
12425,
89,
138,
35,
2427,
26,
23,
106,
3,
6,
5048,
51,
1106,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many flights in each destination city? Return a bar chart, and display x-axis in asc order please. | CREATE TABLE flight (
flno number(4,0),
origin varchar2(20),
destination varchar2(20),
distance number(6,0),
departure_date date,
arrival_date date,
price number(7,2),
aid number(9,0)
)
CREATE TABLE aircraft (
aid number(9,0),
name varchar2(30),
distance number(6,0)
)
CREAT... | SELECT destination, COUNT(destination) FROM flight GROUP BY destination ORDER BY destination | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3777,
41,
3,
89,
40,
29,
32,
381,
599,
8525,
632,
201,
5233,
3,
4331,
4059,
357,
599,
1755,
201,
3954,
3,
4331,
4059,
357,
599,
1755,
201,
2357,
381,
599,
11071,
632,
201,
12028,
8... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3954,
6,
2847,
17161,
599,
13557,
257,
61,
21680,
3777,
350,
4630,
6880,
272,
476,
3954,
4674,
11300,
272,
476,
3954,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What type of state has a royal house of ji and has a ruler? | CREATE TABLE table_name_54 (type VARCHAR, royal_house VARCHAR, title VARCHAR) | SELECT type FROM table_name_54 WHERE royal_house = "ji" AND title = "ruler" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5062,
41,
6137,
584,
4280,
28027,
6,
11268,
834,
1840,
584,
4280,
28027,
6,
2233,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
686,
13,
538,
65,
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,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
686,
21680,
953,
834,
4350,
834,
5062,
549,
17444,
427,
11268,
834,
1840,
3274,
96,
354,
23,
121,
3430,
2233,
3274,
96,
5155,
49,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
When the date is July 8, and the score is 8-12, who is the opponent? | CREATE TABLE table_name_78 (
opponent VARCHAR,
date VARCHAR,
score VARCHAR
) | SELECT opponent FROM table_name_78 WHERE date = "july 8" AND score = "8-12" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3940,
41,
15264,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
8,
833,
19,
1718,
9478,
11,
8,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
15264,
21680,
953,
834,
4350,
834,
3940,
549,
17444,
427,
833,
3274,
96,
2047,
120,
505,
121,
3430,
2604,
3274,
96,
927,
5947,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What was the final number for the winning manufacturer with Mercedes-benz, and a circuit of hockenheimring? | CREATE TABLE table_name_18 (round VARCHAR, winning_manufacturer VARCHAR, circuit VARCHAR) | SELECT COUNT(round) FROM table_name_18 WHERE winning_manufacturer = "mercedes-benz" AND circuit = "hockenheimring" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2606,
41,
7775,
584,
4280,
28027,
6,
3447,
834,
348,
76,
8717,
450,
49,
584,
4280,
28027,
6,
4558,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7775,
61,
21680,
953,
834,
4350,
834,
2606,
549,
17444,
427,
3447,
834,
348,
76,
8717,
450,
49,
3274,
96,
935,
565,
1395,
18,
19738,
121,
3430,
4558,
3274,
96,
19076,
35,
3254,
1007,
121,
1,
-100,
... |
The match that went 1 round, and had a method of submission (rear-naked choke) had what record? | CREATE TABLE table_50247 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" real,
"Time" text,
"Location" text
) | SELECT "Record" FROM table_50247 WHERE "Round" = '1' AND "Method" = 'submission (rear-naked choke)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1752,
357,
4177,
41,
96,
1649,
7,
535,
1499,
6,
96,
1649,
7621,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
23351,
107,
32,
26,
121,
1499,
6,
96,
427,
2169,
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,
1649,
7621,
121,
21680,
953,
834,
1752,
357,
4177,
549,
17444,
427,
96,
448,
32,
1106,
121,
3274,
3,
31,
536,
31,
3430,
96,
23351,
107,
32,
26,
121,
3274,
3,
31,
7304,
5451,
41,
60,
291,
18,
29,
15461,
29787... |
In season 2007 08 who is the runner-up? | CREATE TABLE table_25058269_1 (
runner_up VARCHAR,
season VARCHAR
) | SELECT runner_up FROM table_25058269_1 WHERE season = "2007–08" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
11434,
3449,
357,
3951,
834,
536,
41,
3,
10806,
834,
413,
584,
4280,
28027,
6,
774,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
86,
774,
4101,
12046,
113,
19,
8... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
10806,
834,
413,
21680,
953,
834,
11434,
3449,
357,
3951,
834,
536,
549,
17444,
427,
774,
3274,
96,
20615,
104,
4018,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
how many of the patients aged below 68 were cape speaking? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.language = "CAPE" AND demographic.age < "68" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
24925,
3274,
96,
16986,
427,
121,
3430,
14798,
5,
545,
3,
2,
96,
3651,
121,
1,
-100,
-100,
-100,... |
What is the nationality of the player in round 4? | CREATE TABLE table_5191 (
"Round" real,
"Player" text,
"Position" text,
"Nationality" text,
"College/Junior/Club Team" text
) | SELECT "Nationality" FROM table_5191 WHERE "Round" = '4' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5553,
4729,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
24732,
485,
121,
1499,
6,
96,
9939,
7883,
87,
683,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
24732,
485,
121,
21680,
953,
834,
5553,
4729,
549,
17444,
427,
96,
448,
32,
1106,
121,
3274,
3,
31,
591,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
what is the place when the score is 68-67-73-68=276? | CREATE TABLE table_name_20 (
place VARCHAR,
score VARCHAR
) | SELECT place FROM table_name_20 WHERE score = 68 - 67 - 73 - 68 = 276 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1755,
41,
286,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
125,
19,
8,
286,
116,
8,
2604,
19,
3,
3651,
18,
3708,
18,
455... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
286,
21680,
953,
834,
4350,
834,
1755,
549,
17444,
427,
2604,
3274,
3,
3651,
3,
18,
3,
3708,
3,
18,
3,
4552,
3,
18,
3,
3651,
3274,
204,
3959,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the construction of Olivier Panis' car that retired due to a collision? | CREATE TABLE table_name_23 (
constructor VARCHAR,
time_retired VARCHAR,
driver VARCHAR
) | SELECT constructor FROM table_name_23 WHERE time_retired = "collision" AND driver = "olivier panis" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2773,
41,
6774,
127,
584,
4280,
28027,
6,
97,
834,
10682,
1271,
584,
4280,
28027,
6,
2535,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
6774,
127,
21680,
953,
834,
4350,
834,
2773,
549,
17444,
427,
97,
834,
10682,
1271,
3274,
96,
75,
20953,
1938,
121,
3430,
2535,
3274,
96,
4172,
5144,
2131,
159,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Give the maximum age of patients of black/african american ethnicity who died before the year 2148. | 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 demographic ... | SELECT MAX(demographic.age) FROM demographic WHERE demographic.ethnicity = "BLACK/AFRICAN AMERICAN" AND demographic.dod_year < "2148.0" | [
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,
4800,
4,
599,
1778,
16587,
5,
545,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
15,
189,
2532,
485,
3274,
96,
8775,
15339,
87,
6282,
5593,
11425,
3,
17683,
5593,
11425,
121,
3430,
14798,
5,
26,
32,
26,
834,
1201,
... |
If Villa Rivero Municipality if 7, what is the language? | CREATE TABLE table_27382 (
"Language" text,
"Punata Municipality" real,
"Villa Rivero Municipality" real,
"San Benito Municipality" real,
"Tacachi Municipality" real,
"Cuchumuela Municipality" real
) | SELECT "Language" FROM table_27382 WHERE "Villa Rivero Municipality" = '7' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
3747,
357,
41,
96,
434,
1468,
76,
545,
121,
1499,
6,
96,
345,
202,
144,
9,
16492,
485,
121,
490,
6,
96,
553,
1092,
9,
2473,
32,
16492,
485,
121,
490,
6,
96,
134,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
434,
1468,
76,
545,
121,
21680,
953,
834,
2555,
3747,
357,
549,
17444,
427,
96,
553,
1092,
9,
2473,
32,
16492,
485,
121,
3274,
3,
31,
940,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What team was the away team when Footscray was the home team? | CREATE TABLE table_11116 (
"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_11116 WHERE "Home team" = 'footscray' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
15866,
2938,
41,
96,
19040,
372,
121,
1499,
6,
96,
19040,
372,
2604,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
188,
1343,
372,
2604,
121,
1499,
6,
96,
553,
35,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
188,
1343,
372,
121,
21680,
953,
834,
15866,
2938,
549,
17444,
427,
96,
19040,
372,
121,
3274,
3,
31,
6259,
7,
2935,
63,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the largest crowd for North Melbourne home games? | CREATE TABLE table_53694 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT MAX("Crowd") FROM table_53694 WHERE "Home team" = 'north melbourne' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3420,
4240,
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,
4800,
4,
599,
121,
254,
3623,
26,
8512,
21680,
953,
834,
755,
3420,
4240,
549,
17444,
427,
96,
19040,
372,
121,
3274,
3,
31,
29,
127,
189,
3,
2341,
26255,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
Which episode had viewership of 0.296 million? | CREATE TABLE table_3948 (
"Order" real,
"Episode" text,
"Original airdate" text,
"Timeslot" text,
"Viewers (millions)" text,
"Nightly rank" real,
"Weekly rank" text
) | SELECT "Episode" FROM table_3948 WHERE "Viewers (millions)" = '0.296' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3288,
3707,
41,
96,
7395,
588,
121,
490,
6,
96,
427,
102,
159,
32,
221,
121,
1499,
6,
96,
667,
3380,
10270,
799,
5522,
121,
1499,
6,
96,
13368,
7,
3171,
121,
1499,
6,
9... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
427,
102,
159,
32,
221,
121,
21680,
953,
834,
3288,
3707,
549,
17444,
427,
96,
15270,
277,
41,
17030,
7,
61,
121,
3274,
3,
31,
18189,
4314,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many weeks total are there? | CREATE TABLE table_27248 (
"Week" real,
"Date" text,
"Kickoff" text,
"Opponent" text,
"Final score" text,
"Team record" text,
"Game site" text,
"Attendance" real
) | SELECT MAX("Week") FROM table_27248 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
357,
3707,
41,
96,
518,
10266,
121,
490,
6,
96,
308,
342,
121,
1499,
6,
96,
439,
3142,
1647,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
371,
10270,
2604,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
518,
10266,
8512,
21680,
953,
834,
2555,
357,
3707,
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 was the final score for the match with a partnering of Tessa Price? | CREATE TABLE table_name_48 (score_in_the_final VARCHAR, partnering VARCHAR) | SELECT score_in_the_final FROM table_name_48 WHERE partnering = "tessa price" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3707,
41,
7,
9022,
834,
77,
834,
532,
834,
12406,
584,
4280,
28027,
6,
3,
26361,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
804,
2604,
21,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
834,
77,
834,
532,
834,
12406,
21680,
953,
834,
4350,
834,
3707,
549,
17444,
427,
3,
26361,
3274,
96,
1422,
7,
9,
594,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
At the 2001 Davis Cup, what Opponent had less than 50 Aces? | CREATE TABLE table_name_93 (opponent VARCHAR, aces VARCHAR, event VARCHAR) | SELECT opponent FROM table_name_93 WHERE aces < 50 AND event = "2001 davis cup" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4271,
41,
32,
102,
9977,
584,
4280,
28027,
6,
3,
9,
2319,
584,
4280,
28027,
6,
605,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
486,
8,
4402,
8688,
3802... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
15264,
21680,
953,
834,
4350,
834,
4271,
549,
17444,
427,
3,
9,
2319,
3,
2,
943,
3430,
605,
3274,
96,
23658,
836,
3466,
4119,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
calculate the number of male patients diagnosed with malignant neoplasm in the descending colon. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.gender = "M" AND diagnoses.short_title = "Mal neo descend colon" | [
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... |
How many stadiums are not in country 'Russia'? | CREATE TABLE stadium (
country VARCHAR
) | SELECT COUNT(*) FROM stadium WHERE country <> 'Russia' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14939,
41,
684,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
14939,
7,
33,
59,
16,
684,
3,
31,
29613,
31,
58,
1,
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,
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,
2847,
17161,
599,
1935,
61,
21680,
14939,
549,
17444,
427,
684,
3,
2,
3155,
3,
31,
29613,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many elective hospital admission patients have had automatic implantable cardioverter/defibrillator (aicd) check? | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.admission_type = "ELECTIVE" AND procedures.long_title = "Automatic implantable cardioverter/defibrillator (AICD) check" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14798,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
564,
1499,
6,
2774,
1947,
834,
8547,
302,
1499,
6,
1246,
1499,
6,
103,
115,
1499,
6,
7285,
1499,
6,
1612,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
4293,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
4293,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
How many figures are there for density for Yucheng County? | CREATE TABLE table_2135222_2 (
density VARCHAR,
english_name VARCHAR
) | SELECT COUNT(density) FROM table_2135222_2 WHERE english_name = "Yucheng County" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2658,
2469,
26144,
834,
357,
41,
11048,
584,
4280,
28027,
6,
22269,
834,
4350,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
5638,
33,
132,
21,
11048,
21,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
537,
7,
485,
61,
21680,
953,
834,
2658,
2469,
26144,
834,
357,
549,
17444,
427,
22269,
834,
4350,
3274,
96,
476,
2295,
4606,
1334,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
provide the number of patients whose discharge location is long term care hospital and year of birth is less than 2058? | 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 WHERE demographic.discharge_location = "LONG TERM CARE HOSPITAL" AND demographic.dob_year < "2058" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7744,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
23,
1071,
21545,
834,
23,
26,
1499,
6,
2672,
834,
6137,
1499,
6,
2672,
1499,
6,
5403,
651,
834,
26,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
26,
159,
7993,
834,
14836,
3274,
96,
434,
15628,
3,
5946,
329,
3,
22443,
454,
3638,
4111,
16359,
... |
Name the number for db | CREATE TABLE table_23800 (
"Pick #" real,
"CFL Team" text,
"Player" text,
"Position" text,
"College" text
) | SELECT COUNT("Pick #") FROM table_23800 WHERE "Position" = 'DB' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2773,
6192,
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,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
121,
345,
3142,
1713,
8512,
21680,
953,
834,
2773,
6192,
549,
17444,
427,
96,
345,
32,
7,
4749,
121,
3274,
3,
31,
9213,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
When the grid is under 5 and justin wilson is driving for the team mi-jack conquest racing, what's the highest number of laps driven? | CREATE TABLE table_name_65 (laps INTEGER, grid VARCHAR, team VARCHAR, driver VARCHAR) | SELECT MAX(laps) FROM table_name_65 WHERE team = "mi-jack conquest racing" AND driver = "justin wilson" AND grid < 5 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4122,
41,
8478,
7,
3,
21342,
17966,
6,
8634,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
6,
2535,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
366,
8,
86... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
8478,
7,
61,
21680,
953,
834,
4350,
834,
4122,
549,
17444,
427,
372,
3274,
96,
51,
23,
18,
9325,
975,
10952,
8191,
121,
3430,
2535,
3274,
96,
4998,
77,
3,
210,
173,
739,
121,
3430,
8634,
3,
2,
305,... |
What was the date when the away team was Carlton? | CREATE TABLE table_name_65 (date VARCHAR, away_team VARCHAR) | SELECT date FROM table_name_65 WHERE away_team = "carlton" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4122,
41,
5522,
584,
4280,
28027,
6,
550,
834,
11650,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
833,
116,
8,
550,
372,
47,
3,
30339,
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,
833,
21680,
953,
834,
4350,
834,
4122,
549,
17444,
427,
550,
834,
11650,
3274,
96,
1720,
7377,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
When 24th is the final placing how many wins are there? | CREATE TABLE table_29038 (
"Season" real,
"Series" text,
"Team Name" text,
"Races" real,
"Wins" real,
"Poles" real,
"Podiums" real,
"Points" real,
"Final Placing" text
) | SELECT COUNT("Wins") FROM table_29038 WHERE "Final Placing" = '24th' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23838,
3747,
41,
96,
134,
15,
9,
739,
121,
490,
6,
96,
12106,
7,
121,
1499,
6,
96,
18699,
5570,
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,
18455,
7,
8512,
21680,
953,
834,
23838,
3747,
549,
17444,
427,
96,
371,
10270,
8422,
75,
53,
121,
3274,
3,
31,
2266,
189,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
calculate how many times patient 030-47098 has received a phenytoin laboratory test until 2102. | 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... | SELECT COUNT(*) FROM lab WHERE lab.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '030-47098')) AND lab.labname = 'phenytoin' AND STRFTIME('%y', lab.labresulttime) <= '2102' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
11963,
670,
2562,
41,
11963,
670,
2562,
23,
26,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
2358,
8292,
1499,
6,
2358,
40,
10333,
1499,
6,
2358,
7480,
35,
76,
17552,
381,
6,
11963,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
1935,
61,
21680,
7690,
549,
17444,
427,
7690,
5,
10061,
15129,
21545,
23,
26,
3388,
41,
23143,
14196,
1868,
5,
10061,
15129,
21545,
23,
26,
21680,
1868,
549,
17444,
427,
1868,
5,
10061,
15878,
3734,
... |
What zone has camp type D/S in area Bl9? | CREATE TABLE table_54333 (
"Area" text,
"Name" text,
"Zone" text,
"Group(s)" real,
"Parties" real,
"Max People" real,
"Camp Type" text
) | SELECT "Zone" FROM table_54333 WHERE "Camp Type" = 'd/s' AND "Area" = 'bl9' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5062,
23360,
41,
96,
188,
864,
121,
1499,
6,
96,
23954,
121,
1499,
6,
96,
956,
782,
121,
1499,
6,
96,
27247,
599,
7,
61,
121,
490,
6,
96,
13725,
725,
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,
956,
782,
121,
21680,
953,
834,
5062,
23360,
549,
17444,
427,
96,
24626,
6632,
121,
3274,
3,
31,
26,
87,
7,
31,
3430,
96,
188,
864,
121,
3274,
3,
31,
115,
40,
1298,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,... |
Name the away team score for lake oval | CREATE TABLE table_name_1 (
away_team VARCHAR,
venue VARCHAR
) | SELECT away_team AS score FROM table_name_1 WHERE venue = "lake oval" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
536,
41,
550,
834,
11650,
584,
4280,
28027,
6,
5669,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
550,
372,
2604,
21,
6957,
17986,
1,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
550,
834,
11650,
6157,
2604,
21680,
953,
834,
4350,
834,
536,
549,
17444,
427,
5669,
3274,
96,
16948,
17986,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the names of enzymes whose product is not 'Heme'? | CREATE TABLE enzyme (
id number,
name text,
location text,
product text,
chromosome text,
omim number,
porphyria text
)
CREATE TABLE medicine_enzyme_interaction (
enzyme_id number,
medicine_id number,
interaction_type text
)
CREATE TABLE medicine (
id number,
name text,... | SELECT name FROM enzyme WHERE product <> 'Heme' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
15735,
41,
3,
23,
26,
381,
6,
564,
1499,
6,
1128,
1499,
6,
556,
1499,
6,
3,
10363,
3972,
7159,
1499,
6,
3,
32,
51,
603,
381,
6,
5569,
6941,
52,
23,
9,
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,
564,
21680,
15735,
549,
17444,
427,
556,
3,
2,
3155,
3,
31,
3845,
526,
31,
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 year had a record of 4-21? | CREATE TABLE table_name_32 (
year VARCHAR,
record VARCHAR
) | SELECT year FROM table_name_32 WHERE record = "4-21" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
215,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
215,
141,
3,
9,
1368,
13,
314,
16539,
58,
1,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
215,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
1368,
3274,
96,
591,
16539,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What type had a beginning term of December 8, 1980 | CREATE TABLE table_1602620_1 (type VARCHAR, term_began VARCHAR) | SELECT type FROM table_1602620_1 WHERE term_began = "December 8, 1980" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19129,
2688,
1755,
834,
536,
41,
6137,
584,
4280,
28027,
6,
1657,
834,
346,
2565,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
686,
141,
3,
9,
1849,
1657,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
686,
21680,
953,
834,
19129,
2688,
1755,
834,
536,
549,
17444,
427,
1657,
834,
346,
2565,
3274,
96,
29835,
9478,
6694,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
count the number of medicaid patients who have bradycardia primary disease. | 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 WHERE demographic.insurance = "Medicaid" AND demographic.diagnosis = "BRADYCARDIA" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7744,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
23,
1071,
21545,
834,
23,
26,
1499,
6,
2672,
834,
6137,
1499,
6,
2672,
1499,
6,
5403,
651,
834,
26,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
29441,
3274,
96,
15789,
6146,
121,
3430,
14798,
5,
25930,
4844,
159,
3274,
96,
22899,
19409,
254,
... |
What is the value in 1987 when it is A in 1999, 1989, and 1997? | CREATE TABLE table_name_47 (Id VARCHAR) | SELECT 1987 FROM table_name_47 WHERE 1999 = "a" AND 1989 = "a" AND 1997 = "a" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4177,
41,
196,
26,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
701,
16,
12701,
116,
34,
19,
71,
16,
5247,
6,
9975,
6,
11,
6622,
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,
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,
12701,
21680,
953,
834,
4350,
834,
4177,
549,
17444,
427,
5247,
3274,
96,
9,
121,
3430,
9975,
3274,
96,
9,
121,
3430,
6622,
3274,
96,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What are dates of birth of all the guests whose gender is 'Male', and count them by a line chart | CREATE TABLE Apartment_Buildings (
building_id INTEGER,
building_short_name CHAR(15),
building_full_name VARCHAR(80),
building_description VARCHAR(255),
building_address VARCHAR(255),
building_manager VARCHAR(50),
building_phone VARCHAR(80)
)
CREATE TABLE View_Unit_Status (
apt_id INTEG... | SELECT date_of_birth, COUNT(date_of_birth) FROM Guests WHERE gender_code = "Male" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
15970,
834,
24752,
53,
7,
41,
740,
834,
23,
26,
3,
21342,
17966,
6,
740,
834,
7,
14184,
834,
4350,
3,
28027,
599,
1808,
201,
740,
834,
1329,
40,
834,
4350,
584,
4280,
28027,
599,
2... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
833,
834,
858,
834,
20663,
6,
2847,
17161,
599,
5522,
834,
858,
834,
20663,
61,
21680,
3,
22360,
549,
17444,
427,
7285,
834,
4978,
3274,
96,
329,
9,
109,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
How many institutions are there? | CREATE TABLE inst (
Id VARCHAR
) | SELECT COUNT(*) FROM inst | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
16,
7,
17,
41,
27,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
4222,
33,
132,
58,
1,
0,
0,
0,
0,
0,
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,
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,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
1935,
61,
21680,
16,
7,
17,
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,
... |
What is the average value for Rd 8 in a position less than 2 for Audi Sport Australia? | CREATE TABLE table_name_68 (rd_8 INTEGER, team VARCHAR, position VARCHAR) | SELECT AVG(rd_8) FROM table_name_68 WHERE team = "audi sport australia" AND position < 2 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
52,
26,
834,
927,
3,
21342,
17966,
6,
372,
584,
4280,
28027,
6,
1102,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1348,
701,
21,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
71,
17217,
599,
52,
26,
834,
13520,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
372,
3274,
96,
9,
5291,
2600,
23407,
121,
3430,
1102,
3,
2,
204,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the driver matched db for joseph grado signature | CREATE TABLE table_1601027_2 (
driver_matched_db VARCHAR,
headphone_class VARCHAR
) | SELECT driver_matched_db FROM table_1601027_2 WHERE headphone_class = "Joseph Grado Signature" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19129,
1714,
2555,
834,
357,
41,
2535,
834,
10304,
834,
26,
115,
584,
4280,
28027,
6,
819,
6399,
834,
4057,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2535,
834,
10304,
834,
26,
115,
21680,
953,
834,
19129,
1714,
2555,
834,
357,
549,
17444,
427,
819,
6399,
834,
4057,
3274,
96,
683,
32,
7,
15,
102,
107,
10771,
32,
22366,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.