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 part number of the model that has a frequency of 933mhz? | CREATE TABLE table_46517 (
"Model Number" text,
"sSpec Number" text,
"Frequency" text,
"L2 Cache" text,
"Mult" text,
"Voltage" text,
"Socket" text,
"Release Date" text,
"Part Number(s)" text
) | SELECT "Part Number(s)" FROM table_46517 WHERE "Frequency" = '933mhz' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
4122,
2517,
41,
96,
24663,
7720,
121,
1499,
6,
96,
7,
7727,
7720,
121,
1499,
6,
96,
371,
60,
835,
11298,
121,
1499,
6,
96,
434,
357,
205,
4933,
121,
1499,
6,
96,
3... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
13725,
7720,
599,
7,
61,
121,
21680,
953,
834,
591,
4122,
2517,
549,
17444,
427,
96,
371,
60,
835,
11298,
121,
3274,
3,
31,
4271,
519,
51,
107,
172,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Name the qual for year of 1960 | CREATE TABLE table_67827 (
"Year" text,
"Start" text,
"Qual" text,
"Rank" text,
"Finish" text,
"Laps" real
) | SELECT "Qual" FROM table_67827 WHERE "Year" = '1960' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3708,
927,
2555,
41,
96,
476,
2741,
121,
1499,
6,
96,
7681,
17,
121,
1499,
6,
96,
5991,
138,
121,
1499,
6,
96,
22557,
121,
1499,
6,
96,
371,
77,
1273,
121,
1499,
6,
96,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
5991,
138,
121,
21680,
953,
834,
3708,
927,
2555,
549,
17444,
427,
96,
476,
2741,
121,
3274,
3,
31,
2294,
3328,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What was the record when matt grice fought dennis bermudez with a time of 5:00? | CREATE TABLE table_name_36 (record VARCHAR, time VARCHAR, opponent VARCHAR) | SELECT record FROM table_name_36 WHERE time = "5:00" AND opponent = "dennis bermudez" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3420,
41,
60,
7621,
584,
4280,
28027,
6,
97,
584,
4280,
28027,
6,
15264,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
1368,
116,
6928,
17,
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,
0,
0,
0... | [
3,
23143,
14196,
1368,
21680,
953,
834,
4350,
834,
3420,
549,
17444,
427,
97,
3274,
96,
19870,
121,
3430,
15264,
3274,
96,
537,
29,
159,
3,
1152,
11557,
457,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the sum of year for swimming and first of mike | CREATE TABLE table_name_68 (
year INTEGER,
sport VARCHAR,
first VARCHAR
) | SELECT SUM(year) FROM table_name_68 WHERE sport = "swimming" AND first = "mike" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
215,
3,
21342,
17966,
6,
2600,
584,
4280,
28027,
6,
166,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
4505,
13,
215,
21,
5989,
11,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
180,
6122,
599,
1201,
61,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
2600,
3274,
96,
7,
210,
23,
635,
53,
121,
3430,
166,
3274,
96,
20068,
15,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the score on April 21? | CREATE TABLE table_name_12 (score VARCHAR, date VARCHAR) | SELECT score FROM table_name_12 WHERE date = "april 21" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2122,
41,
7,
9022,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2604,
30,
1186,
1401,
58,
1,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
21680,
953,
834,
4350,
834,
2122,
549,
17444,
427,
833,
3274,
96,
9,
2246,
40,
1401,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What country is Tom Kite from? | CREATE TABLE table_name_56 (
country VARCHAR,
player VARCHAR
) | SELECT country FROM table_name_56 WHERE player = "tom kite" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4834,
41,
684,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
684,
19,
3059,
5747,
15,
45,
58,
1,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
684,
21680,
953,
834,
4350,
834,
4834,
549,
17444,
427,
1959,
3274,
96,
235,
51,
3650,
15,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
what is the number of drivers that finished the 2008 canadian grand prix before jarno trulli ? | CREATE TABLE table_203_52 (
id number,
"pos" text,
"no" number,
"driver" text,
"constructor" text,
"laps" number,
"time/retired" text,
"grid" number,
"points" number
) | SELECT COUNT("driver") FROM table_203_52 WHERE "pos" < (SELECT "pos" FROM table_203_52 WHERE "driver" = 'jarno trulli') | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
5373,
41,
3,
23,
26,
381,
6,
96,
2748,
121,
1499,
6,
96,
29,
32,
121,
381,
6,
96,
13739,
52,
121,
1499,
6,
96,
15982,
5317,
121,
1499,
6,
96,
8478,
7,
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,
2847,
17161,
599,
121,
13739,
52,
8512,
21680,
953,
834,
23330,
834,
5373,
549,
17444,
427,
96,
2748,
121,
3,
2,
41,
23143,
14196,
96,
2748,
121,
21680,
953,
834,
23330,
834,
5373,
549,
17444,
427,
96,
13739,
52,
12... |
Who was hired to fill the spot that became vacant on 3 March 2009? | CREATE TABLE table_48701 (
"Team" text,
"Outgoing manager" text,
"Manner of departure" text,
"Date of vacancy" text,
"Replaced by" text,
"Date of appointment" text
) | SELECT "Replaced by" FROM table_48701 WHERE "Date of vacancy" = '3 march 2009' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3707,
2518,
536,
41,
96,
18699,
121,
1499,
6,
96,
15767,
9545,
2743,
121,
1499,
6,
96,
7296,
687,
13,
12028,
121,
1499,
6,
96,
308,
342,
13,
3,
29685,
121,
1499,
6,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4687,
26,
57,
121,
21680,
953,
834,
3707,
2518,
536,
549,
17444,
427,
96,
308,
342,
13,
3,
29685,
121,
3274,
3,
31,
519,
10556,
2464,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
did italy or spain receive a greater number of silver medals ? | CREATE TABLE table_203_374 (
id number,
"rank" number,
"nation" text,
"gold" number,
"silver" number,
"bronze" number,
"total" number
) | SELECT "nation" FROM table_203_374 WHERE "nation" IN ('italy', 'spain') ORDER BY "silver" DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
519,
4581,
41,
3,
23,
26,
381,
6,
96,
6254,
121,
381,
6,
96,
29,
257,
121,
1499,
6,
96,
14910,
121,
381,
6,
96,
7,
173,
624,
121,
381,
6,
96,
13711,
776,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
29,
257,
121,
21680,
953,
834,
23330,
834,
519,
4581,
549,
17444,
427,
96,
29,
257,
121,
3388,
41,
31,
9538,
63,
31,
6,
3,
31,
14147,
77,
31,
61,
4674,
11300,
272,
476,
96,
7,
173,
624,
121,
309,
25067,
87... |
What is the total amount of allied-unrelated where the component is human capital? | CREATE TABLE table_11944282_1 (
allied_unrelated VARCHAR,
component VARCHAR
) | SELECT COUNT(allied_unrelated) FROM table_11944282_1 WHERE component = "Human Capital" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19993,
3628,
2577,
357,
834,
536,
41,
3,
26655,
834,
202,
3897,
584,
4280,
28027,
6,
3876,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
792,
866,
13,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
26655,
834,
202,
3897,
61,
21680,
953,
834,
19993,
3628,
2577,
357,
834,
536,
549,
17444,
427,
3876,
3274,
96,
13284,
348,
5826,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
For those employees who do not work in departments with managers that have ids between 100 and 200, show me about the distribution of first_name and salary in a bar chart, list in desc by the Y. | CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
) | SELECT FIRST_NAME, SALARY FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY SALARY DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1440,
41,
2847,
17161,
11824,
834,
4309,
3,
4331,
4059,
16426,
6,
2847,
17161,
11824,
834,
567,
17683,
3,
4331,
4059,
599,
2445,
201,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
1714,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
30085,
834,
567,
17683,
6,
180,
4090,
24721,
21680,
1652,
549,
17444,
427,
4486,
3396,
19846,
11810,
834,
4309,
3388,
41,
23143,
14196,
3396,
19846,
11810,
834,
4309,
21680,
10521,
549,
17444,
427,
283,
15610,
17966,
834,... |
What is the sum of the value Top-10 that has a Cuts value of 2 and a Wins value smaller than 0? | CREATE TABLE table_15568 (
"Tournament" text,
"Wins" real,
"Top-5" real,
"Top-10" real,
"Top-25" real,
"Events" real,
"Cuts made" real
) | SELECT SUM("Top-10") FROM table_15568 WHERE "Cuts made" = '2' AND "Wins" < '0' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
20896,
3651,
41,
96,
382,
1211,
20205,
17,
121,
1499,
6,
96,
18455,
7,
121,
490,
6,
96,
22481,
18,
17395,
490,
6,
96,
22481,
4536,
121,
490,
6,
96,
22481,
14855,
121,
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,
180,
6122,
599,
121,
22481,
4536,
8512,
21680,
953,
834,
20896,
3651,
549,
17444,
427,
96,
15784,
17,
7,
263,
121,
3274,
3,
31,
357,
31,
3430,
96,
18455,
7,
121,
3,
2,
3,
31,
632,
31,
1,
-100,
-100,
-100,
-100,
... |
Which Player has a School/Club Team of Illinois? | CREATE TABLE table_name_5 (
player VARCHAR,
school_club_team VARCHAR
) | SELECT player FROM table_name_5 WHERE school_club_team = "illinois" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
755,
41,
1959,
584,
4280,
28027,
6,
496,
834,
13442,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
12387,
65,
3,
9,
1121,
87,
254,
11... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1959,
21680,
953,
834,
4350,
834,
755,
549,
17444,
427,
496,
834,
13442,
834,
11650,
3274,
96,
1092,
77,
32,
159,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Which Away team score has a Venue of princes park? | CREATE TABLE table_52121 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT "Away team score" FROM table_52121 WHERE "Venue" = 'princes park' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5373,
22011,
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,
2604,
121,
21680,
953,
834,
5373,
22011,
549,
17444,
427,
96,
553,
35,
76,
15,
121,
3274,
3,
31,
12298,
2319,
2447,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What player has money of ( ) 159,500, and france is the country? | CREATE TABLE table_34820 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text,
"Money ( \u00a3 )" text
) | SELECT "Player" FROM table_34820 WHERE "Money ( \u00a3 )" = '159,500' AND "Country" = 'france' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
519,
3707,
1755,
41,
96,
345,
11706,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
3696,
260,
121,
1499,
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,
15800,
49,
121,
21680,
953,
834,
519,
3707,
1755,
549,
17444,
427,
96,
9168,
15,
63,
41,
3,
2,
76,
1206,
9,
519,
3,
61,
121,
3274,
3,
31,
27904,
6,
2560,
31,
3430,
96,
10628,
651,
121,
3274,
3,
31,
89,
5... |
Name the position for british columbia | CREATE TABLE table_28059992_2 (
position VARCHAR,
college VARCHAR
) | SELECT position FROM table_28059992_2 WHERE college = "British Columbia" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2577,
3076,
19446,
357,
834,
357,
41,
1102,
584,
4280,
28027,
6,
1900,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
1102,
21,
3,
2160,
17,
1273,
7632,
5... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1102,
21680,
953,
834,
2577,
3076,
19446,
357,
834,
357,
549,
17444,
427,
1900,
3274,
96,
279,
13224,
7,
107,
8183,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What was the score of the game 57 after February 23? | CREATE TABLE table_name_19 (
score VARCHAR,
february VARCHAR,
game VARCHAR
) | SELECT score FROM table_name_19 WHERE february > 23 AND game = 57 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2294,
41,
2604,
584,
4280,
28027,
6,
29976,
76,
1208,
584,
4280,
28027,
6,
467,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2604,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
21680,
953,
834,
4350,
834,
2294,
549,
17444,
427,
29976,
76,
1208,
2490,
1902,
3430,
467,
3274,
3,
3436,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
When 0.6 1.4 is the b r (t) what is the h ci (ka/m)? | CREATE TABLE table_2282444_1 (
h_ci__ka_m_ VARCHAR,
b_r__t_ VARCHAR
) | SELECT h_ci__ka_m_ FROM table_2282444_1 WHERE b_r__t_ = "0.6–1.4" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
2577,
2266,
3628,
834,
536,
41,
3,
107,
834,
75,
23,
834,
834,
1258,
834,
51,
834,
584,
4280,
28027,
6,
3,
115,
834,
52,
834,
834,
17,
834,
584,
4280,
28027,
3,
61... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
107,
834,
75,
23,
834,
834,
1258,
834,
51,
834,
21680,
953,
834,
357,
2577,
2266,
3628,
834,
536,
549,
17444,
427,
3,
115,
834,
52,
834,
834,
17,
834,
3274,
96,
22787,
104,
14912,
121,
1,
-100,
-100,
-100,
-1... |
What is the number of platforms for each location? Show the comparison with a bar chart, and show from low to high by the X. | CREATE TABLE train (
Train_ID int,
Name text,
Time text,
Service text
)
CREATE TABLE station (
Station_ID int,
Name text,
Annual_entry_exit real,
Annual_interchanges real,
Total_Passengers real,
Location text,
Main_Services text,
Number_of_Platforms int
)
CREATE TABLE train_station (
Train_ID int,
Station_ID int
) | SELECT Location, SUM(Number_of_Platforms) FROM station GROUP BY Location ORDER BY Location | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2412,
41,
15059,
834,
4309,
16,
17,
6,
5570,
1499,
6,
2900,
1499,
6,
1387,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
2478,
41,
5939,
834,
4309,
16,
17,
6,
5... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
10450,
6,
180,
6122,
599,
567,
5937,
49,
834,
858,
834,
10146,
2032,
7,
61,
21680,
2478,
350,
4630,
6880,
272,
476,
10450,
4674,
11300,
272,
476,
10450,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the marital status and gender of Sheila Riley? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT demographic.marital_status, demographic.gender FROM demographic WHERE demographic.name = "Sheila Riley" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
18730,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
14798,
5,
1635,
9538,
834,
8547,
302,
6,
14798,
5,
122,
3868,
21680,
14798,
549,
17444,
427,
14798,
5,
4350,
3274,
96,
12736,
173,
9,
26766,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the exercise when the equipment is heart rate monitor, water and towel? | CREATE TABLE table_27512025_1 (
exercise VARCHAR,
equipment VARCHAR
) | SELECT exercise FROM table_27512025_1 WHERE equipment = "Heart rate monitor, water and towel" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25988,
15518,
1828,
834,
536,
41,
2510,
584,
4280,
28027,
6,
1277,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2510,
116,
8,
1277,
19,
842,
1080,
33... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2510,
21680,
953,
834,
25988,
15518,
1828,
834,
536,
549,
17444,
427,
1277,
3274,
96,
3845,
1408,
1080,
3393,
6,
387,
11,
15580,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Which 2009 tournament had Grand Slams? | CREATE TABLE table_name_58 (tournament VARCHAR) | SELECT tournament FROM table_name_58 WHERE 2009 = "grand slams" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3449,
41,
17,
1211,
20205,
17,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
2464,
5892,
141,
2698,
29291,
7,
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,
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,
5892,
21680,
953,
834,
4350,
834,
3449,
549,
17444,
427,
2464,
3274,
96,
15448,
3,
7,
40,
265,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Give me the comparison about Team_ID over the All_Home , and group by attribute ACC_Home, I want to list by the Team_ID in descending please. | CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
) | SELECT All_Home, Team_ID FROM basketball_match GROUP BY ACC_Home, All_Home ORDER BY Team_ID DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
8498,
834,
19515,
41,
2271,
834,
4309,
16,
17,
6,
1121,
834,
4309,
16,
17,
6,
2271,
834,
23954,
1499,
6,
3,
14775,
834,
17748,
4885,
834,
134,
15,
9,
739,
1499,
6,
3,
14775,
834,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
432,
834,
19040,
6,
2271,
834,
4309,
21680,
8498,
834,
19515,
350,
4630,
6880,
272,
476,
3,
14775,
834,
19040,
6,
432,
834,
19040,
4674,
11300,
272,
476,
2271,
834,
4309,
309,
25067,
1,
-100,
-100,
-100,
-100,
-100,
... |
In what round did he play against Sergiy Stakhovsky? | CREATE TABLE table_2993 (
"Edition" text,
"Round" text,
"Date" text,
"Against" text,
"Surface" text,
"Opponent" text,
"Win/Lose" text,
"Result" text
) | SELECT "Round" FROM table_2993 WHERE "Opponent" = 'Sergiy Stakhovsky' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
4271,
41,
96,
427,
10569,
121,
1499,
6,
96,
448,
32,
1106,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
20749,
121,
1499,
6,
96,
134,
450,
4861,
121,
1499,
6,
96... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
448,
32,
1106,
121,
21680,
953,
834,
3166,
4271,
549,
17444,
427,
96,
667,
102,
9977,
121,
3274,
3,
31,
134,
49,
122,
23,
63,
472,
1639,
23304,
5352,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
When the tie no was 1, what was the score? | CREATE TABLE table_name_44 (
score VARCHAR,
tie_no VARCHAR
) | SELECT score FROM table_name_44 WHERE tie_no = "1" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3628,
41,
2604,
584,
4280,
28027,
6,
6177,
834,
29,
32,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
8,
6177,
150,
47,
1914,
125,
47,
8,
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,
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,
3628,
549,
17444,
427,
6177,
834,
29,
32,
3274,
96,
536,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the Home team with an Away team that is wrexham? | CREATE TABLE table_name_90 (home_team VARCHAR, away_team VARCHAR) | SELECT home_team FROM table_name_90 WHERE away_team = "wrexham" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2394,
41,
5515,
834,
11650,
584,
4280,
28027,
6,
550,
834,
11650,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1210,
372,
28,
46,
71,
1343,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
234,
834,
11650,
21680,
953,
834,
4350,
834,
2394,
549,
17444,
427,
550,
834,
11650,
3274,
96,
210,
60,
226,
1483,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
When santiago del estero is the hometown who is the contestant? | CREATE TABLE table_18626383_2 (
contestant VARCHAR,
hometown VARCHAR
) | SELECT contestant FROM table_18626383_2 WHERE hometown = "Santiago del Estero" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2606,
4056,
3891,
4591,
834,
357,
41,
4233,
288,
584,
4280,
28027,
6,
22295,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
366,
3,
7,
5965,
9,
839,
20,
40,
249,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4233,
288,
21680,
953,
834,
2606,
4056,
3891,
4591,
834,
357,
549,
17444,
427,
22295,
3274,
96,
134,
5965,
9,
839,
20,
40,
2972,
52,
32,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Which is the smallest First year when the population is 32,645? | CREATE TABLE table_name_33 (first_year INTEGER, population VARCHAR) | SELECT MIN(first_year) FROM table_name_33 WHERE population = 32 OFFSET 645 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4201,
41,
14672,
834,
1201,
3,
21342,
17966,
6,
2074,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
19,
8,
3,
17924,
1485,
215,
116,
8,
2074,
19,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
14672,
834,
1201,
61,
21680,
953,
834,
4350,
834,
4201,
549,
17444,
427,
2074,
3274,
3538,
3,
15316,
20788,
431,
2128,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the title of the episode with the original air date October 21, 1998? | CREATE TABLE table_2618152_1 (
title VARCHAR,
original_air_date VARCHAR
) | SELECT title FROM table_2618152_1 WHERE original_air_date = "October 21, 1998" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
2606,
26320,
834,
536,
41,
2233,
584,
4280,
28027,
6,
926,
834,
2256,
834,
5522,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2233,
13,
8,
5640... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2233,
21680,
953,
834,
2688,
2606,
26320,
834,
536,
549,
17444,
427,
926,
834,
2256,
834,
5522,
3274,
96,
28680,
12026,
6260,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the latest year of a gratitude type mission with 99 in the entourage? | CREATE TABLE table_name_60 (
year INTEGER,
number_in_entourage VARCHAR,
mission_type VARCHAR
) | SELECT MAX(year) FROM table_name_60 WHERE number_in_entourage = "99" AND mission_type = "gratitude" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3328,
41,
215,
3,
21342,
17966,
6,
381,
834,
77,
834,
295,
1211,
545,
584,
4280,
28027,
6,
2253,
834,
6137,
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,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
1201,
61,
21680,
953,
834,
4350,
834,
3328,
549,
17444,
427,
381,
834,
77,
834,
295,
1211,
545,
3274,
96,
3264,
121,
3430,
2253,
834,
6137,
3274,
96,
3484,
6592,
121,
1,
-100,
-100,
-100,
-100,
-100,
... |
What was the highest points when the second was 4? | CREATE TABLE table_name_12 (points INTEGER, second VARCHAR) | SELECT MAX(points) FROM table_name_12 WHERE second = "4" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2122,
41,
2700,
7,
3,
21342,
17966,
6,
511,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
2030,
979,
116,
8,
511,
47,
314,
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,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
2700,
7,
61,
21680,
953,
834,
4350,
834,
2122,
549,
17444,
427,
511,
3274,
96,
20364,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
get me both the short title and long title of diagnoses for patient roxanna weaver. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT diagnoses.short_title, diagnoses.long_title FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Roxanna Weaver" | [
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,
18730,
7,
5,
7,
14184,
834,
21869,
6,
18730,
7,
5,
2961,
834,
21869,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
549,
174... |
Name the attendance with record of 34-51 | CREATE TABLE table_name_61 (
attendance VARCHAR,
record VARCHAR
) | SELECT attendance FROM table_name_61 WHERE record = "34-51" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4241,
41,
11364,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
11364,
28,
1368,
13,
6154,
18,
5553,
1,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
11364,
21680,
953,
834,
4350,
834,
4241,
549,
17444,
427,
1368,
3274,
96,
3710,
18,
5553,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the Nationality when the club team is Peterborough Petes (OHL)? | CREATE TABLE table_17206 (
"Round" real,
"Overall" text,
"Player" text,
"Position" text,
"Nationality" text,
"Club team" text
) | SELECT "Nationality" FROM table_17206 WHERE "Club team" = 'Peterborough Petes (OHL)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
24643,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
23847,
1748,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
24732,
485,
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,
24732,
485,
121,
21680,
953,
834,
2517,
24643,
549,
17444,
427,
96,
254,
11158,
372,
121,
3274,
3,
31,
345,
15,
449,
12823,
19786,
7,
41,
9195,
434,
61,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the record for Big Ten Team #4 Purdue? | CREATE TABLE table_25646 (
"ACC Team" text,
"Big Ten Team" text,
"Location" text,
"Attendance" real,
"Winner" text,
"Challenge Leader" text
) | SELECT "Winner" FROM table_25646 WHERE "Big Ten Team" = '#4 Purdue' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19337,
4448,
41,
96,
14775,
2271,
121,
1499,
6,
96,
23805,
4738,
2271,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
188,
17,
324,
26,
663,
121,
490,
6,
96,
184... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
18455,
687,
121,
21680,
953,
834,
19337,
4448,
549,
17444,
427,
96,
23805,
4738,
2271,
121,
3274,
3,
31,
4663,
591,
7333,
1259,
15,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
who is the the mens doubles with mixed doubles being jimm aalto nina sarnesto | CREATE TABLE table_19028 (
"Year" real,
"Mens singles" text,
"Womens singles" text,
"Mens doubles" text,
"Womens doubles" text,
"Mixed doubles" text
) | SELECT "Mens doubles" FROM table_19028 WHERE "Mixed doubles" = 'Jimm Aalto Nina Sarnesto' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
11776,
2577,
41,
96,
476,
2741,
121,
490,
6,
96,
329,
35,
7,
712,
7,
121,
1499,
6,
96,
518,
32,
904,
7,
712,
7,
121,
1499,
6,
96,
329,
35,
7,
1486,
7,
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,
329,
35,
7,
1486,
7,
121,
21680,
953,
834,
11776,
2577,
549,
17444,
427,
96,
329,
2407,
15,
26,
1486,
7,
121,
3274,
3,
31,
683,
23,
635,
71,
138,
235,
12776,
9,
9422,
1496,
235,
31,
1,
-100,
-100,
-100,
-1... |
Which player has United States as the country, more money ($) than 535,000, t10 as the place, with 73-68-73-74=288 as the score? | CREATE TABLE table_47421 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text,
"Money ($)" real
) | SELECT "Player" FROM table_47421 WHERE "Country" = 'united states' AND "Money ($)" > '535,000' AND "Place" = 't10' AND "Score" = '73-68-73-74=288' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4177,
591,
2658,
41,
96,
345,
11706,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
3696,
260,
121,
1499,
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,
15800,
49,
121,
21680,
953,
834,
4177,
591,
2658,
549,
17444,
427,
96,
10628,
651,
121,
3274,
3,
31,
15129,
15,
26,
2315,
31,
3430,
96,
9168,
15,
63,
8785,
61,
121,
2490,
3,
31,
4867,
5898,
31,
3430,
96,
345... |
What kind of North Marquesan has a Takuu of /ɾani/? | CREATE TABLE table_name_2 (north_marquesan VARCHAR, takuu VARCHAR) | SELECT north_marquesan FROM table_name_2 WHERE takuu = "/ɾani/" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
357,
41,
29,
127,
189,
834,
1635,
7771,
152,
584,
4280,
28027,
6,
3,
17,
16296,
76,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
773,
13,
1117,
1571... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3457,
834,
1635,
7771,
152,
21680,
953,
834,
4350,
834,
357,
549,
17444,
427,
3,
17,
16296,
76,
3274,
96,
87,
2,
2738,
87,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
In the tournament that has 15 events, and less than 6 top-25's, how many top-5's did he have? | CREATE TABLE table_name_76 (top_5 INTEGER, events VARCHAR, top_25 VARCHAR) | SELECT SUM(top_5) FROM table_name_76 WHERE events = 15 AND top_25 < 6 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3959,
41,
2916,
834,
755,
3,
21342,
17966,
6,
984,
584,
4280,
28027,
6,
420,
834,
1828,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
86,
8,
5892,
24,
65,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2916,
834,
9120,
21680,
953,
834,
4350,
834,
3959,
549,
17444,
427,
984,
3274,
627,
3430,
420,
834,
1828,
3,
2,
431,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which player was selected in rounds under 3? | CREATE TABLE table_name_33 (player VARCHAR, round INTEGER) | SELECT player FROM table_name_33 WHERE round < 3 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4201,
41,
20846,
584,
4280,
28027,
6,
1751,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
4073,
1959,
47,
2639,
16,
14419,
365,
220,
58,
1,
0,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1959,
21680,
953,
834,
4350,
834,
4201,
549,
17444,
427,
1751,
3,
2,
220,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Which patients had a triglyceride lab test? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE lab.label = "Triglycer" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
18730,
7,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
7690,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7690,
5,
8399,
51,
834,
23,
26,
549,
17444,... |
What is the combined of the 14 Super G? | CREATE TABLE table_7145 (
"Season" real,
"Overall" real,
"Slalom" text,
"Super G" real,
"Downhill" text,
"Combined" text
) | SELECT "Combined" FROM table_7145 WHERE "Super G" = '14' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4450,
2128,
41,
96,
134,
15,
9,
739,
121,
490,
6,
96,
23847,
1748,
121,
490,
6,
96,
134,
40,
138,
32,
51,
121,
1499,
6,
96,
23290,
350,
121,
490,
6,
96,
308,
9197,
63... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
28257,
121,
21680,
953,
834,
4450,
2128,
549,
17444,
427,
96,
23290,
350,
121,
3274,
3,
31,
2534,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the Attendance in the game against the New Orleans Saints? | CREATE TABLE table_45983 (
"Week" real,
"Date" text,
"Opponent" text,
"Result" text,
"Attendance" real
) | SELECT COUNT("Attendance") FROM table_45983 WHERE "Opponent" = 'new orleans saints' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2128,
3916,
519,
41,
96,
518,
10266,
121,
490,
6,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
20119,
121,
1499,
6,
96,
188,
17,
324,
26,
663,
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,
2847,
17161,
599,
121,
188,
17,
324,
26,
663,
8512,
21680,
953,
834,
2128,
3916,
519,
549,
17444,
427,
96,
667,
102,
9977,
121,
3274,
3,
31,
5534,
42,
109,
3247,
15528,
7,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the dma of branding is big oldies 107.3 with the station warv-fm? | CREATE TABLE table_19131921_1 (
dma VARCHAR,
branding VARCHAR,
station VARCHAR
) | SELECT dma FROM table_19131921_1 WHERE branding = "Big Oldies 107.3" AND station = "WARV-FM" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2294,
2368,
2294,
2658,
834,
536,
41,
3,
26,
51,
9,
584,
4280,
28027,
6,
14282,
584,
4280,
28027,
6,
2478,
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,
26,
51,
9,
21680,
953,
834,
2294,
2368,
2294,
2658,
834,
536,
549,
17444,
427,
14282,
3274,
96,
23805,
3525,
725,
335,
27914,
121,
3430,
2478,
3274,
96,
518,
4280,
553,
18,
14908,
121,
1,
-100,
-100,
-100,
-100,
... |
Who was the home team for the 2013 season and the result was 0 0? | CREATE TABLE table_24949975_1 (
home_team VARCHAR,
season VARCHAR,
result VARCHAR
) | SELECT home_team FROM table_24949975_1 WHERE season = "2013" AND result = "0–0" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2266,
4240,
3264,
3072,
834,
536,
41,
234,
834,
11650,
584,
4280,
28027,
6,
774,
584,
4280,
28027,
6,
741,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
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,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
234,
834,
11650,
21680,
953,
834,
2266,
4240,
3264,
3072,
834,
536,
549,
17444,
427,
774,
3274,
96,
11138,
121,
3430,
741,
3274,
96,
632,
104,
632,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is Ateneo de Manila's PBA Team? | CREATE TABLE table_name_96 (
pba_team VARCHAR,
college VARCHAR
) | SELECT pba_team FROM table_name_96 WHERE college = "ateneo de manila" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4314,
41,
3,
102,
115,
9,
834,
11650,
584,
4280,
28027,
6,
1900,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
486,
35,
15,
32,
20,
25432,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
102,
115,
9,
834,
11650,
21680,
953,
834,
4350,
834,
4314,
549,
17444,
427,
1900,
3274,
96,
9,
324,
15,
32,
20,
388,
173,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
In what year was Wisconsin the runner-up? | CREATE TABLE table_64553 (
"Year" real,
"Champion" text,
"Score" text,
"Runner-up" text,
"City" text,
"Arena" text
) | SELECT "Year" FROM table_64553 WHERE "Runner-up" = 'wisconsin' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
3769,
519,
41,
96,
476,
2741,
121,
490,
6,
96,
254,
1483,
12364,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
23572,
18,
413,
121,
1499,
6,
96,
254,
485,
121,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
476,
2741,
121,
21680,
953,
834,
4389,
3769,
519,
549,
17444,
427,
96,
23572,
18,
413,
121,
3274,
3,
31,
210,
159,
8056,
77,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Name the number of viewers for series number 50 | CREATE TABLE table_20704243_5 (
us_viewers__in_millions_ VARCHAR,
series__number VARCHAR
) | SELECT us_viewers__in_millions_ FROM table_20704243_5 WHERE series__number = 50 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26426,
6348,
27730,
834,
755,
41,
178,
834,
4576,
277,
834,
834,
77,
834,
17030,
7,
834,
584,
4280,
28027,
6,
939,
834,
834,
5525,
1152,
584,
4280,
28027,
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,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
178,
834,
4576,
277,
834,
834,
77,
834,
17030,
7,
834,
21680,
953,
834,
26426,
6348,
27730,
834,
755,
549,
17444,
427,
939,
834,
834,
5525,
1152,
3274,
943,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What Location Attendance has a Game of 4? | CREATE TABLE table_60158 (
"Game" text,
"Date" text,
"Opponent" text,
"Score" text,
"Location Attendance" text,
"Record" text
) | SELECT "Location Attendance" FROM table_60158 WHERE "Game" = '4' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3328,
26556,
41,
96,
23055,
121,
1499,
6,
96,
308,
342,
121,
1499,
6,
96,
667,
102,
9977,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
434,
32,
75,
257,
22497,
663,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
434,
32,
75,
257,
22497,
663,
121,
21680,
953,
834,
3328,
26556,
549,
17444,
427,
96,
23055,
121,
3274,
3,
31,
591,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Before 2008, if the Manufacturer is dodge and the start is under 9, what's the highest finish time? | CREATE TABLE table_name_17 (
finish INTEGER,
year VARCHAR,
manufacturer VARCHAR,
start VARCHAR
) | SELECT MAX(finish) FROM table_name_17 WHERE manufacturer = "dodge" AND start < 9 AND year < 2008 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2517,
41,
1992,
3,
21342,
17966,
6,
215,
584,
4280,
28027,
6,
4818,
584,
4280,
28027,
6,
456,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
3103,
2628,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
25535,
61,
21680,
953,
834,
4350,
834,
2517,
549,
17444,
427,
4818,
3274,
96,
26,
32,
26,
397,
121,
3430,
456,
3,
2,
668,
3430,
215,
3,
2,
2628,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
List document id of documents status is done and document type is Paper and the document is shipped by shipping agent named USPS. | CREATE TABLE Ref_Shipping_Agents (
document_id VARCHAR,
document_status_code VARCHAR,
document_type_code VARCHAR
)
CREATE TABLE Documents (
document_id VARCHAR,
document_status_code VARCHAR,
document_type_code VARCHAR
) | SELECT document_id FROM Documents WHERE document_status_code = "done" AND document_type_code = "Paper" INTERSECT SELECT document_id FROM Documents JOIN Ref_Shipping_Agents ON Documents.shipping_agent_code = Ref_Shipping_Agents.shipping_agent_code WHERE Ref_Shipping_Agents.shipping_agent_name = "USPS" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
419,
89,
834,
10499,
23,
5341,
834,
188,
5560,
7,
41,
1708,
834,
23,
26,
584,
4280,
28027,
6,
1708,
834,
8547,
302,
834,
4978,
584,
4280,
28027,
6,
1708,
834,
6137,
834,
4978,
584,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
1708,
834,
23,
26,
21680,
11167,
7,
549,
17444,
427,
1708,
834,
8547,
302,
834,
4978,
3274,
96,
2029,
15,
121,
3430,
1708,
834,
6137,
834,
4978,
3274,
96,
15182,
49,
121,
3,
21342,
5249,
14196,
3,
23143,
14196,
1708... |
Which Grand Prix had 9 rounds? | CREATE TABLE table_54998 (
"Round" real,
"Race Title" text,
"Grand Prix" text,
"Circuit" text,
"Date" text
) | SELECT "Grand Prix" FROM table_54998 WHERE "Round" = '9' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3647,
3916,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
448,
3302,
11029,
121,
1499,
6,
96,
4744,
727,
12942,
121,
1499,
6,
96,
254,
23,
52,
21560,
121,
1499,
6,
96,
3... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0... | [
3,
23143,
14196,
96,
4744,
727,
12942,
121,
21680,
953,
834,
755,
3647,
3916,
549,
17444,
427,
96,
448,
32,
1106,
121,
3274,
3,
31,
1298,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
If Arthur Albert is the director, what is the maximum series number? | CREATE TABLE table_17356106_1 (
series__number INTEGER,
directed_by VARCHAR
) | SELECT MAX(series__number) FROM table_17356106_1 WHERE directed_by = "Arthur Albert" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
2469,
948,
16431,
834,
536,
41,
939,
834,
834,
5525,
1152,
3,
21342,
17966,
6,
6640,
834,
969,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
156,
13962,
11375... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4800,
4,
599,
10833,
7,
834,
834,
5525,
1152,
61,
21680,
953,
834,
2517,
2469,
948,
16431,
834,
536,
549,
17444,
427,
6640,
834,
969,
3274,
96,
7754,
10666,
11375,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the name of the building that was the tallest from 1990–1997 in Frankfurt? | CREATE TABLE table_name_78 (name VARCHAR, city VARCHAR, years_as_tallest VARCHAR) | SELECT name FROM table_name_78 WHERE city = "frankfurt" AND years_as_tallest = "1990–1997" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3940,
41,
4350,
584,
4280,
28027,
6,
690,
584,
4280,
28027,
6,
203,
834,
9,
7,
834,
17,
1748,
222,
584,
4280,
28027,
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,
0,
0... | [
3,
23143,
14196,
564,
21680,
953,
834,
4350,
834,
3940,
549,
17444,
427,
690,
3274,
96,
89,
6254,
9827,
17,
121,
3430,
203,
834,
9,
7,
834,
17,
1748,
222,
3274,
96,
2294,
2394,
104,
2294,
4327,
121,
1,
-100,
-100,
-100,
-100,
-100... |
What game did they lose by 6 - 5? | CREATE TABLE table_name_67 (loss VARCHAR, score VARCHAR) | SELECT loss FROM table_name_67 WHERE score = "6 - 5" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3708,
41,
2298,
7,
584,
4280,
28027,
6,
2604,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
467,
410,
79,
2615,
57,
431,
3,
18,
305,
58,
1,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1453,
21680,
953,
834,
4350,
834,
3708,
549,
17444,
427,
2604,
3274,
96,
948,
3,
18,
3,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
For those employees who did not have any job in the past, give me the comparison about the sum of employee_id over the hire_date bin hire_date by time, and list by the y axis in descending. | CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
) | SELECT HIRE_DATE, SUM(EMPLOYEE_ID) FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) ORDER BY SUM(EMPLOYEE_ID) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1440,
41,
2847,
17161,
11824,
834,
4309,
3,
4331,
4059,
16426,
6,
2847,
17161,
11824,
834,
567,
17683,
3,
4331,
4059,
599,
2445,
201,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
1714,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
454,
14132,
834,
308,
6048,
6,
180,
6122,
599,
6037,
345,
5017,
476,
5080,
834,
4309,
61,
21680,
1652,
549,
17444,
427,
4486,
262,
5244,
5017,
476,
5080,
834,
4309,
3388,
41,
23143,
14196,
262,
5244,
5017,
476,
5080,
... |
How many different constructors had Paul Thiel as a winning driver? | CREATE TABLE table_1140114_5 (
constructor VARCHAR,
winning_driver VARCHAR
) | SELECT COUNT(constructor) FROM table_1140114_5 WHERE winning_driver = "Paul Thiel" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2596,
2445,
18959,
834,
755,
41,
6774,
127,
584,
4280,
28027,
6,
3447,
834,
13739,
52,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
315,
6774,
127,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
15982,
5317,
61,
21680,
953,
834,
2596,
2445,
18959,
834,
755,
549,
17444,
427,
3447,
834,
13739,
52,
3274,
96,
23183,
332,
16219,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What club had a points difference of -24? | CREATE TABLE table_8599 (
"Club" text,
"Played" text,
"Drawn" text,
"Lost" text,
"Points for" text,
"Points against" text,
"Points difference" text,
"Points" text
) | SELECT "Club" FROM table_8599 WHERE "Points difference" = '-24' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4433,
3264,
41,
96,
254,
11158,
121,
1499,
6,
96,
15800,
15,
26,
121,
1499,
6,
96,
308,
10936,
29,
121,
1499,
6,
96,
434,
3481,
121,
1499,
6,
96,
22512,
7,
21,
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,
254,
11158,
121,
21680,
953,
834,
4433,
3264,
549,
17444,
427,
96,
22512,
7,
1750,
121,
3274,
3,
31,
14962,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the number of opponents that play at 4pm ? | CREATE TABLE table_204_718 (
id number,
"date" text,
"opponent" text,
"time" text,
"score" text,
"record" text
) | SELECT COUNT("opponent") FROM table_204_718 WHERE "time" = '4 p.m' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
940,
2606,
41,
3,
23,
26,
381,
6,
96,
5522,
121,
1499,
6,
96,
32,
102,
9977,
121,
1499,
6,
96,
715,
121,
1499,
6,
96,
7,
9022,
121,
1499,
6,
96,
60,
7621,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
32,
102,
9977,
8512,
21680,
953,
834,
26363,
834,
940,
2606,
549,
17444,
427,
96,
715,
121,
3274,
3,
31,
591,
3,
102,
5,
51,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the lowest crowd number at the venue MCG? | CREATE TABLE table_name_73 (crowd INTEGER, venue VARCHAR) | SELECT MIN(crowd) FROM table_name_73 WHERE venue = "mcg" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4552,
41,
75,
3623,
26,
3,
21342,
17966,
6,
5669,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
7402,
4374,
381,
44,
8,
5669,
283,
12150,
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,
3,
17684,
599,
75,
3623,
26,
61,
21680,
953,
834,
4350,
834,
4552,
549,
17444,
427,
5669,
3274,
96,
51,
75,
122,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the Round when there is an overall of 246? | CREATE TABLE table_39999 (
"Round" real,
"Overall" real,
"Player" text,
"Position" text,
"College" text
) | SELECT "Round" FROM table_39999 WHERE "Overall" = '246' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3288,
19446,
41,
96,
448,
32,
1106,
121,
490,
6,
96,
23847,
1748,
121,
490,
6,
96,
15800,
49,
121,
1499,
6,
96,
345,
32,
7,
4749,
121,
1499,
6,
96,
9939,
7883,
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,
448,
32,
1106,
121,
21680,
953,
834,
3288,
19446,
549,
17444,
427,
96,
23847,
1748,
121,
3274,
3,
31,
357,
4448,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
A scatter chart shows the correlation between People_ID and Clean_Jerk . | CREATE TABLE people (
People_ID int,
Name text,
Height real,
Weight real,
Birth_Date text,
Birth_Place text
)
CREATE TABLE body_builder (
Body_Builder_ID int,
People_ID int,
Snatch real,
Clean_Jerk real,
Total real
) | SELECT People_ID, Clean_Jerk FROM body_builder | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
151,
41,
2449,
834,
4309,
16,
17,
6,
5570,
1499,
6,
24231,
490,
6,
14230,
490,
6,
26337,
834,
308,
342,
1499,
6,
26337,
834,
345,
11706,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2449,
834,
4309,
6,
7433,
834,
683,
49,
157,
21680,
643,
834,
16422,
49,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
how many more adherents does constantinople have compared to jerusalem ? | CREATE TABLE table_204_284 (
id number,
"jurisdiction" text,
"adherents" number,
"bishops" number,
"priests" number,
"monastics" number,
"monasteries" number,
"parishes" number
) | SELECT (SELECT "adherents" FROM table_204_284 WHERE "jurisdiction" = 'constantinople') - (SELECT "adherents" FROM table_204_284 WHERE "jurisdiction" = 'jerusalem') | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
357,
4608,
41,
3,
23,
26,
381,
6,
96,
20868,
7,
12472,
121,
1499,
6,
96,
9,
26,
760,
295,
7,
121,
381,
6,
96,
11514,
10776,
7,
121,
381,
6,
96,
2246,
222,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
41,
23143,
14196,
96,
9,
26,
760,
295,
7,
121,
21680,
953,
834,
26363,
834,
357,
4608,
549,
17444,
427,
96,
20868,
7,
12472,
121,
3274,
3,
31,
1018,
2427,
28436,
4788,
31,
61,
3,
18,
41,
23143,
14196,
96,
9,
26,... |
Find the name and capacity of the dorm with least number of amenities. | CREATE TABLE has_amenity (
dormid VARCHAR,
amenid VARCHAR
)
CREATE TABLE dorm_amenity (
amenid VARCHAR
)
CREATE TABLE dorm (
dorm_name VARCHAR,
student_capacity VARCHAR,
dormid VARCHAR
) | SELECT T1.dorm_name, T1.student_capacity FROM dorm AS T1 JOIN has_amenity AS T2 ON T1.dormid = T2.dormid JOIN dorm_amenity AS T3 ON T2.amenid = T3.amenid GROUP BY T2.dormid ORDER BY COUNT(*) LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
65,
834,
9,
904,
485,
41,
103,
52,
6983,
584,
4280,
28027,
6,
183,
35,
23,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
103,
52,
51,
834,
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,
332,
5411,
26,
127,
51,
834,
4350,
6,
332,
5411,
8637,
295,
834,
4010,
9,
6726,
21680,
103,
52,
51,
6157,
332,
536,
3,
15355,
3162,
65,
834,
9,
904,
485,
6157,
332,
357,
9191,
332,
5411,
26,
127,
6983,
3274,
332... |
what is the smallest number of laps imre toth has? | CREATE TABLE table_70550 (
"Rider" text,
"Manufacturer" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
) | SELECT MIN("Laps") FROM table_70550 WHERE "Rider" = 'imre toth' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2518,
17147,
41,
96,
448,
23,
588,
121,
1499,
6,
96,
7296,
76,
8717,
450,
49,
121,
1499,
6,
96,
3612,
102,
7,
121,
490,
6,
96,
13368,
87,
1649,
11809,
26,
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,
3,
17684,
599,
121,
3612,
102,
7,
8512,
21680,
953,
834,
2518,
17147,
549,
17444,
427,
96,
448,
23,
588,
121,
3274,
3,
31,
603,
60,
12,
189,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is To par, when Player is 'Greg Turner'? | CREATE TABLE table_79093 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text,
"Money ( \u00a3 )" real
) | SELECT "To par" FROM table_79093 WHERE "Player" = 'greg turner' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4440,
4198,
519,
41,
96,
345,
11706,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
3696,
260,
121,
1499,
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,
3696,
260,
121,
21680,
953,
834,
4440,
4198,
519,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
18301,
919,
49,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
count the number of patients whose age is less than 43 and procedure long title is replacement of tube or enterostomy device of small intestine? | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
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 procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.age < "43" AND procedures.long_title = "Replacement of tube or enterostomy device of small intestine" | [
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,... |
For all employees in the same department as Clara excluding Clara, bin their hire date into the month interval, and count how many employees in each month for a bar chart, and could you list by the y axis in desc? | CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
) | SELECT HIRE_DATE, COUNT(HIRE_DATE) FROM employees WHERE DEPARTMENT_ID = (SELECT DEPARTMENT_ID FROM employees WHERE FIRST_NAME = "Clara") AND FIRST_NAME <> "Clara" ORDER BY COUNT(HIRE_DATE) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2476,
41,
446,
10539,
834,
4309,
3,
4331,
4059,
599,
16968,
6,
446,
10539,
834,
382,
3177,
3765,
3,
4331,
4059,
599,
2469,
201,
3,
17684,
834,
134,
4090,
24721,
7908,
1982,
599,
11071,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
454,
14132,
834,
308,
6048,
6,
2847,
17161,
599,
566,
14132,
834,
308,
6048,
61,
21680,
1652,
549,
17444,
427,
3396,
19846,
11810,
834,
4309,
3274,
41,
23143,
14196,
3396,
19846,
11810,
834,
4309,
21680,
1652,
549,
1744... |
what is the top speed ? | CREATE TABLE table_203_764 (
id number,
"name" text,
"date" number,
"nation" text,
"displacement" text,
"speed" text,
"number" number,
"notes" text
) | SELECT "speed" FROM table_203_764 ORDER BY "speed" DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
3959,
591,
41,
3,
23,
26,
381,
6,
96,
4350,
121,
1499,
6,
96,
5522,
121,
381,
6,
96,
29,
257,
121,
1499,
6,
96,
10475,
11706,
297,
121,
1499,
6,
96,
9993,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
9993,
121,
21680,
953,
834,
23330,
834,
3959,
591,
4674,
11300,
272,
476,
96,
9993,
121,
309,
25067,
8729,
12604,
209,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which track translates to Flemish Women? | CREATE TABLE table_name_96 (
track VARCHAR,
translation VARCHAR
) | SELECT track FROM table_name_96 WHERE translation = "flemish women" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4314,
41,
1463,
584,
4280,
28027,
6,
7314,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
1463,
3,
29213,
12,
5766,
12641,
107,
4047,
58,
1,
0,
0,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1463,
21680,
953,
834,
4350,
834,
4314,
549,
17444,
427,
7314,
3274,
96,
89,
109,
51,
1273,
887,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
How many points were scored against the club that drew 3 and scored 50 points? | CREATE TABLE table_69516 (
"Club" text,
"Played" 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 "Points against" FROM table_69516 WHERE "Drawn" = '3' AND "Points" = '50' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3951,
755,
2938,
41,
96,
254,
11158,
121,
1499,
6,
96,
15800,
15,
26,
121,
1499,
6,
96,
308,
10936,
29,
121,
1499,
6,
96,
434,
3481,
121,
1499,
6,
96,
22512,
7,
21,
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,
22512,
7,
581,
121,
21680,
953,
834,
3951,
755,
2938,
549,
17444,
427,
96,
308,
10936,
29,
121,
3274,
3,
31,
519,
31,
3430,
96,
22512,
7,
121,
3274,
3,
31,
1752,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the name of the series with the unknown host? | CREATE TABLE table_27487310_5 (name VARCHAR, host_s_ VARCHAR) | SELECT name FROM table_27487310_5 WHERE host_s_ = "unknown" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2555,
3707,
4552,
1714,
834,
755,
41,
4350,
584,
4280,
28027,
6,
2290,
834,
7,
834,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
564,
13,
8,
939,
28,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
564,
21680,
953,
834,
2555,
3707,
4552,
1714,
834,
755,
549,
17444,
427,
2290,
834,
7,
834,
3274,
96,
202,
5661,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who was eliminated a person at 18:48? | CREATE TABLE table_29692554_2 (
eliminated VARCHAR,
time VARCHAR
) | SELECT eliminated AS by FROM table_29692554_2 WHERE time = "18:48" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
3951,
1828,
5062,
834,
357,
41,
17809,
584,
4280,
28027,
6,
97,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
17809,
3,
9,
568,
44,
507,
10,
3707,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
17809,
6157,
57,
21680,
953,
834,
3166,
3951,
1828,
5062,
834,
357,
549,
17444,
427,
97,
3274,
96,
2606,
10,
3707,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the lowest Loss with Gain larger than 319 for derrick locke? | CREATE TABLE table_name_10 (loss INTEGER, name VARCHAR, gain VARCHAR) | SELECT MIN(loss) FROM table_name_10 WHERE name = "derrick locke" AND gain > 319 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1714,
41,
2298,
7,
3,
21342,
17966,
6,
564,
584,
4280,
28027,
6,
2485,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
7402,
3144,
7,
28,
22097,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3,
17684,
599,
2298,
7,
61,
21680,
953,
834,
4350,
834,
1714,
549,
17444,
427,
564,
3274,
96,
588,
5206,
6081,
15,
121,
3430,
2485,
2490,
220,
2294,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What country has todd hamilton as the player? | CREATE TABLE table_name_90 (
country VARCHAR,
player VARCHAR
) | SELECT country FROM table_name_90 WHERE player = "todd hamilton" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2394,
41,
684,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
684,
65,
12,
26,
26,
3,
1483,
23,
7377,
38,
8,
1959,
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... | [
3,
23143,
14196,
684,
21680,
953,
834,
4350,
834,
2394,
549,
17444,
427,
1959,
3274,
96,
235,
26,
26,
3,
1483,
23,
7377,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Payment has a Type of 2d, and a Release date of january 2003? | CREATE TABLE table_8707 (
"Developer(s)" text,
"Release date" text,
"Required OS" text,
"Payment" text,
"Type" text
) | SELECT "Payment" FROM table_8707 WHERE "Type" = '2d' AND "Release date" = 'january 2003' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4225,
4560,
41,
96,
2962,
162,
8745,
49,
599,
7,
61,
121,
1499,
6,
96,
1649,
40,
14608,
833,
121,
1499,
6,
96,
1649,
1169,
1271,
6328,
121,
1499,
6,
96,
19702,
297,
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,
19702,
297,
121,
21680,
953,
834,
4225,
4560,
549,
17444,
427,
96,
25160,
121,
3274,
3,
31,
357,
26,
31,
3430,
96,
1649,
40,
14608,
833,
121,
3274,
3,
31,
7066,
76,
1208,
3888,
31,
1,
-100,
-100,
-100,
-100,
... |
who is the away team when the home team is sydney spirit? | CREATE TABLE table_name_28 (
away_team VARCHAR,
home_team VARCHAR
) | SELECT away_team FROM table_name_28 WHERE home_team = "sydney spirit" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2577,
41,
550,
834,
11650,
584,
4280,
28027,
6,
234,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
113,
19,
8,
550,
372,
116,
8,
234,
372,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
550,
834,
11650,
21680,
953,
834,
4350,
834,
2577,
549,
17444,
427,
234,
834,
11650,
3274,
96,
7,
63,
26,
3186,
3564,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the lowest win% with an away score of 3-2 in 2011 season? | CREATE TABLE table_name_53 (win__percentage INTEGER, away VARCHAR, season VARCHAR) | SELECT MIN(win__percentage) FROM table_name_53 WHERE away = "3-2" AND season = "2011" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4867,
41,
3757,
834,
834,
883,
3728,
545,
3,
21342,
17966,
6,
550,
584,
4280,
28027,
6,
774,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
740... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
3757,
834,
834,
883,
3728,
545,
61,
21680,
953,
834,
4350,
834,
4867,
549,
17444,
427,
550,
3274,
96,
21160,
121,
3430,
774,
3274,
96,
13907,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the sum of the difference for 9 draws and over 18 played? | CREATE TABLE table_name_48 (
diff INTEGER,
drawn VARCHAR,
played VARCHAR
) | SELECT SUM(diff) FROM table_name_48 WHERE drawn = 9 AND played > 18 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3707,
41,
20624,
3,
21342,
17966,
6,
6796,
584,
4280,
28027,
6,
1944,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
4505,
13,
8,
1750,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
180,
6122,
599,
26,
5982,
61,
21680,
953,
834,
4350,
834,
3707,
549,
17444,
427,
6796,
3274,
668,
3430,
1944,
2490,
507,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
who is the home team when the away team is bolton wanderers? | CREATE TABLE table_8554 (
"Tie no" text,
"Home team" text,
"Score" text,
"Away team" text,
"Date" text
) | SELECT "Home team" FROM table_8554 WHERE "Away team" = 'bolton wanderers' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4433,
5062,
41,
96,
382,
23,
15,
150,
121,
1499,
6,
96,
19040,
372,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
188,
1343,
372,
121,
1499,
6,
96,
308,
342,
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,
19040,
372,
121,
21680,
953,
834,
4433,
5062,
549,
17444,
427,
96,
188,
1343,
372,
121,
3274,
3,
31,
4243,
17,
106,
10735,
277,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What internet explorer has 7.89% as the safari, and 8.22% as the chrome? | CREATE TABLE table_name_31 (
internet_explorer VARCHAR,
safari VARCHAR,
chrome VARCHAR
) | SELECT internet_explorer FROM table_name_31 WHERE safari = "7.89%" AND chrome = "8.22%" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3341,
41,
1396,
834,
20901,
584,
4280,
28027,
6,
24857,
584,
4280,
28027,
6,
17520,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
1396,
3,
20901,
65... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1396,
834,
20901,
21680,
953,
834,
4350,
834,
3341,
549,
17444,
427,
24857,
3274,
96,
940,
5,
3914,
1454,
121,
3430,
17520,
3274,
96,
927,
5,
357,
5406,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the highest number of losses with 23 points and 22 plays? | CREATE TABLE table_name_58 (lost INTEGER, points VARCHAR, played VARCHAR) | SELECT MAX(lost) FROM table_name_58 WHERE points = 23 AND played > 22 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3449,
41,
2298,
17,
3,
21342,
17966,
6,
979,
584,
4280,
28027,
6,
1944,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
2030,
381,
13,
8467,
28,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
4800,
4,
599,
2298,
17,
61,
21680,
953,
834,
4350,
834,
3449,
549,
17444,
427,
979,
3274,
1902,
3430,
1944,
2490,
1630,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the power at the cebu station? | CREATE TABLE table_19215259_1 (
power__kw_ VARCHAR,
location VARCHAR
) | SELECT power__kw_ FROM table_19215259_1 WHERE location = "Cebu" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
19978,
26320,
3390,
834,
536,
41,
579,
834,
834,
157,
210,
834,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
579,
44,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
579,
834,
834,
157,
210,
834,
21680,
953,
834,
19978,
26320,
3390,
834,
536,
549,
17444,
427,
1128,
3274,
96,
254,
15,
3007,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
If the Close ranged weapons are the knife (stone), knife (iron), what are the Long ranged weapons? | CREATE TABLE table_74162 (
"Warrior" text,
"Close ranged weapons" text,
"Mid ranged weapons" text,
"Long ranged weapons" text,
"Armor" text,
"Special weapon" text
) | SELECT "Long ranged weapons" FROM table_74162 WHERE "Close ranged weapons" = 'Knife (stone), Knife (iron)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4581,
2938,
357,
41,
96,
518,
10269,
127,
121,
1499,
6,
96,
254,
10227,
620,
26,
7749,
121,
1499,
6,
96,
329,
23,
26,
620,
26,
7749,
121,
1499,
6,
96,
434,
2444,
620,
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,
96,
434,
2444,
620,
26,
7749,
121,
21680,
953,
834,
4581,
2938,
357,
549,
17444,
427,
96,
254,
10227,
620,
26,
7749,
121,
3274,
3,
31,
439,
29,
99,
15,
41,
3009,
201,
16141,
89,
15,
41,
17773,
61,
31,
1,
-100,
... |
For those employees who was hired before 2002-06-21, show me about the distribution of job_id and the average of salary , and group by attribute job_id in a bar chart. | CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
) | SELECT JOB_ID, AVG(SALARY) FROM employees WHERE HIRE_DATE < '2002-06-21' GROUP BY JOB_ID | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1652,
41,
262,
5244,
5017,
476,
5080,
834,
4309,
7908,
1982,
599,
11071,
632,
201,
30085,
834,
567,
17683,
3,
4331,
4059,
599,
1755,
201,
301,
12510,
834,
567,
17683,
3,
4331,
4059,
59... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
446,
10539,
834,
4309,
6,
71,
17217,
599,
134,
4090,
24721,
61,
21680,
1652,
549,
17444,
427,
454,
14132,
834,
308,
6048,
3,
2,
3,
31,
24898,
18,
5176,
16539,
31,
350,
4630,
6880,
272,
476,
446,
10539,
834,
4309,
... |
How many people on average attended the game in week 14? | CREATE TABLE table_name_68 (attendance INTEGER, week VARCHAR) | SELECT AVG(attendance) FROM table_name_68 WHERE week = 14 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
15116,
663,
3,
21342,
17966,
6,
471,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
151,
30,
1348,
5526,
8,
467,
16,
471,
968,
58,
1,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
71,
17217,
599,
15116,
663,
61,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
471,
3274,
968,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
what is the difference between the population of ovada and the population of serravalle scrivia ? | CREATE TABLE table_203_413 (
id number,
"rank" text,
"city" text,
"population" number,
"area\n(km2)" number,
"density\n(inhabitants/km2)" number,
"altitude\n(mslm)" number
) | SELECT (SELECT "population" FROM table_203_413 WHERE "city" = 'ovada') - (SELECT "population" FROM table_203_413 WHERE "city" = 'serravalle scrivia') | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
23330,
834,
591,
2368,
41,
3,
23,
26,
381,
6,
96,
6254,
121,
1499,
6,
96,
6726,
121,
1499,
6,
96,
9791,
7830,
121,
381,
6,
96,
498,
2,
29,
599,
5848,
7318,
121,
381,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
41,
23143,
14196,
96,
9791,
7830,
121,
21680,
953,
834,
23330,
834,
591,
2368,
549,
17444,
427,
96,
6726,
121,
3274,
3,
31,
32,
16716,
31,
61,
3,
18,
41,
23143,
14196,
96,
9791,
7830,
121,
21680,
953,
834,
23330,
... |
How many leagues are there in England? | CREATE TABLE League (country_id VARCHAR); CREATE TABLE Country (id VARCHAR, name VARCHAR) | SELECT COUNT(*) FROM Country AS T1 JOIN League AS T2 ON T1.id = T2.country_id WHERE T1.name = "England" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3815,
41,
17529,
834,
23,
26,
584,
4280,
28027,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
6993,
41,
23,
26,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
61,
3,
32102,
3... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
1935,
61,
21680,
6993,
6157,
332,
536,
3,
15355,
3162,
3815,
6157,
332,
357,
9191,
332,
5411,
23,
26,
3274,
332,
4416,
17529,
834,
23,
26,
549,
17444,
427,
332,
5411,
4350,
3274,
96,
8532,
7002,
72... |
what amount of stations have station code is awy? | CREATE TABLE table_14688744_2 (station VARCHAR, station_code VARCHAR) | SELECT COUNT(station) FROM table_14688744_2 WHERE station_code = "AWY" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2534,
3651,
4225,
3628,
834,
357,
41,
6682,
584,
4280,
28027,
6,
2478,
834,
4978,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
125,
866,
13,
6991,
43,
2478,
1081,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
6682,
61,
21680,
953,
834,
2534,
3651,
4225,
3628,
834,
357,
549,
17444,
427,
2478,
834,
4978,
3274,
96,
9851,
476,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
how many runners up were there on july 24 , 1967 ? | CREATE TABLE table_204_621 (
id number,
"no." number,
"date" text,
"tournament" text,
"winning score" text,
"margin\nof victory" text,
"runner(s)-up" text
) | SELECT "runner(s)-up" FROM table_204_621 WHERE "date" = 'jul 24, 1967' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
4056,
536,
41,
3,
23,
26,
381,
6,
96,
29,
32,
535,
381,
6,
96,
5522,
121,
1499,
6,
96,
17,
1211,
20205,
17,
121,
1499,
6,
96,
8163,
2604,
121,
1499,
6,
96... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
10806,
599,
7,
61,
18,
413,
121,
21680,
953,
834,
26363,
834,
4056,
536,
549,
17444,
427,
96,
5522,
121,
3274,
3,
31,
354,
83,
14320,
18148,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Year of 2006-07 had what studio host? | CREATE TABLE table_name_10 (
studio_host VARCHAR,
year VARCHAR
) | SELECT studio_host FROM table_name_10 WHERE year = "2006-07" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1714,
41,
3100,
834,
12675,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2929,
13,
3581,
18,
4560,
141,
125,
3100,
2290,
58,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3100,
834,
12675,
21680,
953,
834,
4350,
834,
1714,
549,
17444,
427,
215,
3274,
96,
21196,
18,
4560,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the average year for 0 points and ferrari v8? | CREATE TABLE table_66903 (
"Year" real,
"Entrant" text,
"Chassis" text,
"Engine" text,
"Points" real
) | SELECT AVG("Year") FROM table_66903 WHERE "Points" = '0' AND "Engine" = 'ferrari v8' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3539,
2394,
519,
41,
96,
476,
2741,
121,
490,
6,
96,
16924,
3569,
121,
1499,
6,
96,
3541,
6500,
7,
121,
1499,
6,
96,
31477,
121,
1499,
6,
96,
22512,
7,
121,
490,
3,
61,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
71,
17217,
599,
121,
476,
2741,
8512,
21680,
953,
834,
3539,
2394,
519,
549,
17444,
427,
96,
22512,
7,
121,
3274,
3,
31,
632,
31,
3430,
96,
31477,
121,
3274,
3,
31,
1010,
52,
1665,
3,
208,
927,
31,
1,
-100,
-100... |
I want the result for team of giants | CREATE TABLE table_name_63 (result VARCHAR, team VARCHAR) | SELECT result FROM table_name_63 WHERE team = "giants" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3891,
41,
60,
7,
83,
17,
584,
4280,
28027,
6,
372,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
27,
241,
8,
741,
21,
372,
13,
6079,
7,
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,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
741,
21680,
953,
834,
4350,
834,
3891,
549,
17444,
427,
372,
3274,
96,
22898,
17,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Who was South Melbourne's away opponents? | CREATE TABLE table_name_18 (
away_team VARCHAR,
home_team VARCHAR
) | SELECT away_team FROM table_name_18 WHERE home_team = "south melbourne" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2606,
41,
550,
834,
11650,
584,
4280,
28027,
6,
234,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
2645,
47,
1013,
9396,
31,
7,
550,
16383,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
550,
834,
11650,
21680,
953,
834,
4350,
834,
2606,
549,
17444,
427,
234,
834,
11650,
3274,
96,
7,
670,
107,
3,
2341,
26255,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
If the average start is 11.8, what was the team name? | CREATE TABLE table_2190919_3 (team_s_ VARCHAR, avg_start VARCHAR) | SELECT team_s_ FROM table_2190919_3 WHERE avg_start = "11.8" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
2294,
4198,
2294,
834,
519,
41,
11650,
834,
7,
834,
584,
4280,
28027,
6,
3,
9,
208,
122,
834,
10208,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
156,
8,
1348,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
372,
834,
7,
834,
21680,
953,
834,
357,
2294,
4198,
2294,
834,
519,
549,
17444,
427,
3,
9,
208,
122,
834,
10208,
3274,
96,
10032,
927,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the largest number in attendance when the record is 1-1-0? | CREATE TABLE table_71502 (
"Date" text,
"Visitor" text,
"Score" text,
"Home" text,
"Record" text,
"Attendance" real
) | SELECT MAX("Attendance") FROM table_71502 WHERE "Record" = '1-1-0' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4450,
1752,
357,
41,
96,
308,
342,
121,
1499,
6,
96,
553,
159,
155,
127,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
19040,
121,
1499,
6,
96,
1649,
7621,
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,
4800,
4,
599,
121,
188,
17,
324,
26,
663,
8512,
21680,
953,
834,
4450,
1752,
357,
549,
17444,
427,
96,
1649,
7621,
121,
3274,
3,
31,
536,
18,
18930,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the name of the school that has a player named Michael Dunigan? | CREATE TABLE table_55769 (
"Player" text,
"Height" text,
"School" text,
"Hometown" text,
"College" text,
"NBA Draft" text
) | SELECT "School" FROM table_55769 WHERE "Player" = 'michael dunigan' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3436,
3951,
41,
96,
15800,
49,
121,
1499,
6,
96,
3845,
2632,
121,
1499,
6,
96,
29364,
121,
1499,
6,
96,
19040,
3540,
121,
1499,
6,
96,
9939,
7883,
121,
1499,
6,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
29364,
121,
21680,
953,
834,
755,
3436,
3951,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
51,
362,
9,
15,
40,
146,
29,
12588,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the result on November 1, 1992? | CREATE TABLE table_name_53 (
result VARCHAR,
date VARCHAR
) | SELECT result FROM table_name_53 WHERE date = "november 1, 1992" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4867,
41,
741,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
741,
30,
1671,
1914,
9047,
58,
1,
0,
0,
0,
0,
0,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
741,
21680,
953,
834,
4350,
834,
4867,
549,
17444,
427,
833,
3274,
96,
5326,
18247,
1914,
9047,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Find the team of each player and sort them in ascending alphabetical order. | CREATE TABLE player (
player_id number,
player text,
team text,
age number,
position text,
school_id number
)
CREATE TABLE school (
school_id number,
school text,
location text,
enrollment number,
founded number,
denomination text,
boys_or_girls text,
day_or_boarding text,
year_entered_competition number,
school_colors text
)
CREATE TABLE school_performance (
school_id number,
school_year text,
class_a text,
class_aa text
)
CREATE TABLE school_details (
school_id number,
nickname text,
colors text,
league text,
class text,
division text
) | SELECT team FROM player ORDER BY team | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1959,
41,
1959,
834,
23,
26,
381,
6,
1959,
1499,
6,
372,
1499,
6,
1246,
381,
6,
1102,
1499,
6,
496,
834,
23,
26,
381,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
372,
21680,
1959,
4674,
11300,
272,
476,
372,
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,
-1... |
How many times was revenue in millions recorded when the spending per capita was $6,736? | CREATE TABLE table_14700336_1 (revenue__millions_ VARCHAR, spending_per_capita VARCHAR) | SELECT COUNT(revenue__millions_) FROM table_14700336_1 WHERE spending_per_capita = "$6,736" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2534,
9295,
519,
3420,
834,
536,
41,
60,
15098,
834,
834,
17030,
7,
834,
584,
4280,
28027,
6,
2887,
834,
883,
834,
4010,
155,
9,
584,
4280,
28027,
61,
3,
32102,
32103,
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,
2847,
17161,
599,
60,
15098,
834,
834,
17030,
7,
834,
61,
21680,
953,
834,
2534,
9295,
519,
3420,
834,
536,
549,
17444,
427,
2887,
834,
883,
834,
4010,
155,
9,
3274,
96,
3229,
11071,
940,
3420,
121,
1,
-100,
-100,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.