NATURAL_LANG stringlengths 0 446 | SCHEMA stringlengths 27 2.21k | SQL stringlengths 18 453 | input_ids list | attention_mask list | labels list |
|---|---|---|---|---|---|
None of the communities listed has a percentage smaller than 8.6 in 2006. | CREATE TABLE table_11294 (
"Parties and voter communities" text,
"% 2006" real,
"Seats 2006" real,
"% 2001" real,
"Seats 2001" real
) | SELECT COUNT("Seats 2001") FROM table_11294 WHERE "% 2006" < '8.6' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2596,
357,
4240,
41,
96,
13725,
725,
11,
10018,
2597,
121,
1499,
6,
96,
1454,
3581,
121,
490,
6,
96,
134,
1544,
7,
3581,
121,
490,
6,
96,
1454,
4402,
121,
490,
6,
96,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
134,
1544,
7,
4402,
8512,
21680,
953,
834,
2596,
357,
4240,
549,
17444,
427,
96,
1454,
3581,
121,
3,
2,
3,
31,
927,
5,
948,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What Texas has Johnson from Nort Dakota? | CREATE TABLE table_name_92 (texas VARCHAR, north_dakota VARCHAR) | SELECT texas FROM table_name_92 WHERE north_dakota = "johnson" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4508,
41,
10354,
9,
7,
584,
4280,
28027,
6,
3457,
834,
26,
9,
15414,
9,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
2514,
65,
5891,
45,
7005,
17,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
10354,
9,
7,
21680,
953,
834,
4350,
834,
4508,
549,
17444,
427,
3457,
834,
26,
9,
15414,
9,
3274,
96,
27341,
739,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the smallest crowd size for away team st kilda? | CREATE TABLE table_name_25 (
crowd INTEGER,
away_team VARCHAR
) | SELECT MIN(crowd) FROM table_name_25 WHERE away_team = "st kilda" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1828,
41,
4374,
3,
21342,
17966,
6,
550,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
3,
17924,
4374,
812,
21,
550,
372,
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,
3,
17684,
599,
75,
3623,
26,
61,
21680,
953,
834,
4350,
834,
1828,
549,
17444,
427,
550,
834,
11650,
3274,
96,
7,
17,
3,
157,
173,
26,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the number in total of silver with a gold smaller than 0? | CREATE TABLE table_5495 (
"Rank" text,
"Nation" text,
"Gold" real,
"Silver" real,
"Bronze" real,
"Total" real
) | SELECT COUNT("Silver") FROM table_5495 WHERE "Gold" < '0' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5062,
3301,
41,
96,
22557,
121,
1499,
6,
96,
567,
257,
121,
1499,
6,
96,
23576,
121,
490,
6,
96,
134,
173,
624,
121,
490,
6,
96,
22780,
29,
776,
121,
490,
6,
96,
3696,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
134,
173,
624,
8512,
21680,
953,
834,
5062,
3301,
549,
17444,
427,
96,
23576,
121,
3,
2,
3,
31,
632,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What Date was the Country of japan, and a Label of sony? | CREATE TABLE table_43267 (
"Date" text,
"Label" text,
"Format" text,
"Country" text,
"Catalog" text
) | SELECT "Date" FROM table_43267 WHERE "Country" = 'japan' AND "Label" = 'sony' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
2668,
3708,
41,
96,
308,
342,
121,
1499,
6,
96,
434,
10333,
121,
1499,
6,
96,
3809,
3357,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
18610,
9,
2152,
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,
308,
342,
121,
21680,
953,
834,
591,
2668,
3708,
549,
17444,
427,
96,
10628,
651,
121,
3274,
3,
31,
1191,
2837,
31,
3430,
96,
434,
10333,
121,
3274,
3,
31,
739,
63,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees whose salary is in the range of 8000 and 12000 and commission is not null or department number does not equal to 40, visualize a bar chart about the distribution of job_id and the sum of department_id , and group by attribute job_id, and could you sort sum department id in descending order? | CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE departments (
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 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 jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
) | SELECT JOB_ID, SUM(DEPARTMENT_ID) FROM employees WHERE SALARY BETWEEN 8000 AND 12000 AND COMMISSION_PCT <> "null" OR DEPARTMENT_ID <> 40 GROUP BY JOB_ID ORDER BY SUM(DEPARTMENT_ID) DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
6266,
41,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
11116,
632,
201,
4083,
517,
9215,
834,
567,
17683,
3,
4331,
4059,
599,
1828,
61,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
446,
10539,
834,
4309,
6,
180,
6122,
599,
5596,
19846,
11810,
834,
4309,
61,
21680,
1652,
549,
17444,
427,
180,
4090,
24721,
272,
7969,
518,
23394,
3,
25129,
3430,
586,
2313,
3430,
3,
6657,
329,
16994,
9215,
834,
4051... |
Which model(s) has AGP graphics and 400 FSB (MHz)? | CREATE TABLE table_name_44 (model VARCHAR, graphics VARCHAR, fsb__mhz_ VARCHAR) | SELECT model FROM table_name_44 WHERE graphics = "agp" AND fsb__mhz_ = "400" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3628,
41,
21770,
584,
4280,
28027,
6,
6484,
584,
4280,
28027,
6,
3,
89,
7,
115,
834,
834,
51,
107,
172,
834,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0... | [
3,
23143,
14196,
825,
21680,
953,
834,
4350,
834,
3628,
549,
17444,
427,
6484,
3274,
96,
9,
122,
102,
121,
3430,
3,
89,
7,
115,
834,
834,
51,
107,
172,
834,
3274,
96,
5548,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is Time, when Composer(s) is 'Kyriakos Papadopoulos'? | CREATE TABLE table_60619 (
"English translation" text,
"Original album" text,
"Lyricist(s)" text,
"Composer(s)" text,
"Time" text
) | SELECT "Time" FROM table_60619 WHERE "Composer(s)" = 'kyriakos papadopoulos' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3328,
948,
2294,
41,
96,
26749,
7314,
121,
1499,
6,
96,
667,
3380,
10270,
2306,
121,
1499,
6,
96,
434,
63,
2234,
343,
599,
7,
61,
121,
1499,
6,
96,
5890,
2748,
49,
599,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
13368,
121,
21680,
953,
834,
3328,
948,
2294,
549,
17444,
427,
96,
5890,
2748,
49,
599,
7,
61,
121,
3274,
3,
31,
3781,
52,
23,
9,
9692,
22250,
26,
32,
102,
1063,
2298,
31,
1,
-100,
-100,
-100,
-100,
-100,
-1... |
What is the highest amount of money a player with a score of 69-71-71-73=284 has? | CREATE TABLE table_46476 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text,
"Money ( $ )" real
) | SELECT MAX("Money ( $ )") FROM table_46476 WHERE "Score" = '69-71-71-73=284' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
591,
4389,
3959,
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,
4800,
4,
599,
121,
9168,
15,
63,
41,
1514,
3,
61,
8512,
21680,
953,
834,
591,
4389,
3959,
549,
17444,
427,
96,
134,
9022,
121,
3274,
3,
31,
3951,
18,
4450,
18,
4450,
18,
4552,
2423,
357,
4608,
31,
1,
-100,
-100,... |
How many Goals have Years at club of 1961–1966, and a Debut year larger than 1961? | CREATE TABLE table_name_9 (goals VARCHAR, years_at_club VARCHAR, debut_year VARCHAR) | SELECT COUNT(goals) FROM table_name_9 WHERE years_at_club = "1961–1966" AND debut_year > 1961 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1298,
41,
839,
5405,
584,
4280,
28027,
6,
203,
834,
144,
834,
13442,
584,
4280,
28027,
6,
5695,
834,
1201,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
839,
5405,
61,
21680,
953,
834,
4350,
834,
1298,
549,
17444,
427,
203,
834,
144,
834,
13442,
3274,
96,
2294,
4241,
104,
2294,
3539,
121,
3430,
5695,
834,
1201,
2490,
21018,
1,
-100,
-100,
-100,
-100,... |
Which website is in english and has the frequency of an online newspaper ? | CREATE TABLE table_name_77 (
website VARCHAR,
language VARCHAR,
frequency VARCHAR
) | SELECT website FROM table_name_77 WHERE language = "english" AND frequency = "online newspaper" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4013,
41,
475,
584,
4280,
28027,
6,
1612,
584,
4280,
28027,
6,
7321,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
475,
19,
16,
22269,
11,
65,
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,
475,
21680,
953,
834,
4350,
834,
4013,
549,
17444,
427,
1612,
3274,
96,
4606,
40,
1273,
121,
3430,
7321,
3274,
96,
15846,
8468,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the date for the UTC time of 03:15:46? | CREATE TABLE table_26950408_1 (
date__yyyy_mm_dd_ VARCHAR,
time___utc__ VARCHAR
) | SELECT date__yyyy_mm_dd_ FROM table_26950408_1 WHERE time___utc__ = "03:15:46" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
3301,
6348,
4018,
834,
536,
41,
833,
834,
834,
63,
63,
63,
63,
834,
635,
834,
26,
26,
834,
584,
4280,
28027,
6,
97,
834,
834,
834,
76,
17,
75,
834,
834,
584,
4280... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
833,
834,
834,
63,
63,
63,
63,
834,
635,
834,
26,
26,
834,
21680,
953,
834,
2688,
3301,
6348,
4018,
834,
536,
549,
17444,
427,
97,
834,
834,
834,
76,
17,
75,
834,
834,
3274,
96,
4928,
10,
1808,
10,
4448,
121,
... |
What Player is from Connecticut? | CREATE TABLE table_name_39 (player VARCHAR, college_country_team VARCHAR) | SELECT player FROM table_name_39 WHERE college_country_team = "connecticut" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3288,
41,
20846,
584,
4280,
28027,
6,
1900,
834,
17529,
834,
11650,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
12387,
19,
45,
15505,
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,
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,
3288,
549,
17444,
427,
1900,
834,
17529,
834,
11650,
3274,
96,
19532,
23,
3044,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What location entered service in 1999 and had a customer of Anadarko? | CREATE TABLE table_37195 (
"Name" text,
"Type" text,
"Entered service" text,
"Water depth" text,
"Location" text,
"Customer" text
) | SELECT "Location" FROM table_37195 WHERE "Entered service" = '1999' AND "Customer" = 'anadarko' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4118,
22464,
41,
96,
23954,
121,
1499,
6,
96,
25160,
121,
1499,
6,
96,
16924,
3737,
313,
121,
1499,
6,
96,
28632,
4963,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
434,
32,
75,
257,
121,
21680,
953,
834,
4118,
22464,
549,
17444,
427,
96,
16924,
3737,
313,
121,
3274,
3,
31,
2294,
3264,
31,
3430,
96,
30067,
49,
121,
3274,
3,
31,
152,
9,
26,
6604,
32,
31,
1,
-100,
-100,
... |
What Score has a Tournament of tanjung selor, indonesia? | CREATE TABLE table_name_76 (
score VARCHAR,
tournament VARCHAR
) | SELECT score FROM table_name_76 WHERE tournament = "tanjung selor, indonesia" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3959,
41,
2604,
584,
4280,
28027,
6,
5892,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
17763,
65,
3,
9,
20502,
13,
3,
17,
152,
22498,
3,
7,
12... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
2604,
21680,
953,
834,
4350,
834,
3959,
549,
17444,
427,
5892,
3274,
96,
17,
152,
22498,
3,
7,
1209,
6,
16,
2029,
15,
7,
23,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Name the years in orlando for forward | CREATE TABLE table_15621965_10 (years_in_orlando VARCHAR, position VARCHAR) | SELECT years_in_orlando FROM table_15621965_10 WHERE position = "Forward" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1808,
4056,
2294,
4122,
834,
1714,
41,
1201,
7,
834,
77,
834,
32,
7721,
32,
584,
4280,
28027,
6,
1102,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
203,
16... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
203,
834,
77,
834,
32,
7721,
32,
21680,
953,
834,
1808,
4056,
2294,
4122,
834,
1714,
549,
17444,
427,
1102,
3274,
96,
3809,
2239,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many patients have been diagnosed with unspecified pseudomonas infection? | 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 diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE diagnoses.short_title = "Pseudomonas infect NOS" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14798,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
564,
1499,
6,
2774,
1947,
834,
8547,
302,
1499,
6,
1246,
1499,
6,
103,
115,
1499,
6,
7285,
1499,
6,
1612,
14... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
What is the district of Paraswada with none reserved? | CREATE TABLE table_64781 (
"Constituency number" text,
"Name" text,
"Reserved for ( SC / ST /None)" text,
"District" text,
"Number of electorates (2009)" real
) | SELECT "District" FROM table_64781 WHERE "Reserved for ( SC / ST /None)" = 'none' AND "Name" = 'paraswada' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4389,
3940,
536,
41,
96,
4302,
2248,
17,
76,
4392,
381,
121,
1499,
6,
96,
23954,
121,
1499,
6,
96,
1649,
3473,
15,
26,
21,
41,
6508,
3,
87,
5097,
3,
87,
567,
782,
61,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
308,
23,
20066,
121,
21680,
953,
834,
4389,
3940,
536,
549,
17444,
427,
96,
1649,
3473,
15,
26,
21,
41,
6508,
3,
87,
5097,
3,
87,
567,
782,
61,
121,
3274,
3,
31,
29,
782,
31,
3430,
96,
23954,
121,
3274,
3,... |
What team has more than 32 games and 311 rebounds? | CREATE TABLE table_name_27 (team VARCHAR, games VARCHAR, rebounds VARCHAR) | SELECT team FROM table_name_27 WHERE games > 32 AND rebounds = 311 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2555,
41,
11650,
584,
4280,
28027,
6,
1031,
584,
4280,
28027,
6,
3,
23768,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
372,
65,
72,
145,
3538,
1031,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
372,
21680,
953,
834,
4350,
834,
2555,
549,
17444,
427,
1031,
2490,
3538,
3430,
3,
23768,
3274,
220,
2596,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which Score in the final has an Outcome of winner, and a Surface of hard (i)? | CREATE TABLE table_name_12 (
score_in_the_final VARCHAR,
outcome VARCHAR,
surface VARCHAR
) | SELECT score_in_the_final FROM table_name_12 WHERE outcome = "winner" AND surface = "hard (i)" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2122,
41,
2604,
834,
77,
834,
532,
834,
12406,
584,
4280,
28027,
6,
6138,
584,
4280,
28027,
6,
1774,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2604,
834,
77,
834,
532,
834,
12406,
21680,
953,
834,
4350,
834,
2122,
549,
17444,
427,
6138,
3274,
96,
3757,
687,
121,
3430,
1774,
3274,
96,
5651,
41,
23,
61,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Name the language that has number of 14 | CREATE TABLE table_name_69 (language VARCHAR, number VARCHAR) | SELECT language FROM table_name_69 WHERE number = "14" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3951,
41,
24925,
584,
4280,
28027,
6,
381,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
1612,
24,
65,
381,
13,
968,
1,
0,
0,
0,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
1612,
21680,
953,
834,
4350,
834,
3951,
549,
17444,
427,
381,
3274,
96,
2534,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which sail is in the America 3 Foundation syndicate on the America 3 yacht? | CREATE TABLE table_name_96 (sail VARCHAR, syndicate VARCHAR, yacht VARCHAR) | SELECT sail FROM table_name_96 WHERE syndicate = "america 3 foundation" AND yacht = "america 3" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4314,
41,
7,
9,
173,
584,
4280,
28027,
6,
23608,
15,
584,
4280,
28027,
6,
18082,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
14725,
19,
16,
8,
137... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
14725,
21680,
953,
834,
4350,
834,
4314,
549,
17444,
427,
23608,
15,
3274,
96,
23064,
220,
3361,
121,
3430,
18082,
3274,
96,
23064,
220,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the seat percentage when vote percentage is 2.4% (-8.3)? | CREATE TABLE table_78628 (
"Party" text,
"Party-list votes" real,
"Vote percentage" text,
"Total seats" text,
"Seat percentage" text
) | SELECT "Seat percentage" FROM table_78628 WHERE "Vote percentage" = '2.4% (-8.3)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
940,
3840,
2577,
41,
96,
13725,
63,
121,
1499,
6,
96,
13725,
63,
18,
3350,
11839,
121,
490,
6,
96,
553,
32,
17,
15,
5294,
121,
1499,
6,
96,
3696,
1947,
6116,
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,
134,
1544,
5294,
121,
21680,
953,
834,
940,
3840,
2577,
549,
17444,
427,
96,
553,
32,
17,
15,
5294,
121,
3274,
3,
31,
4416,
5988,
41,
6039,
5,
5268,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What was the Outcome of the match with Partner Kateryna Bondarenko? | CREATE TABLE table_name_84 (outcome VARCHAR, partner VARCHAR) | SELECT outcome FROM table_name_84 WHERE partner = "kateryna bondarenko" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4608,
41,
670,
287,
15,
584,
4280,
28027,
6,
2397,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
3387,
287,
15,
13,
8,
1588,
28,
5793,
11845,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
6138,
21680,
953,
834,
4350,
834,
4608,
549,
17444,
427,
2397,
3274,
96,
8682,
4203,
29,
9,
6235,
291,
18994,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
give me the number of patients whose gender is f and diagnoses long title is benzodiazepine-based tranquilizers causing adverse effects in therapeutic use? | 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 procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id 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 diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.gender = "F" AND diagnoses.long_title = "Benzodiazepine-based tranquilizers causing adverse effects in therapeutic use" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
List the season above 241.0 that was handled by brad tanenbaum. | CREATE TABLE table_29518 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text,
"U.S. viewers (millions)" text
) | SELECT "No. in season" FROM table_29518 WHERE "Directed by" = 'Brad Tanenbaum' AND "No. in series" > '241.0' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3301,
2606,
41,
96,
4168,
5,
16,
939,
121,
490,
6,
96,
4168,
5,
16,
774,
121,
490,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
15,
26,
57,
121,
1499,
6,
96,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
4168,
5,
16,
774,
121,
21680,
953,
834,
357,
3301,
2606,
549,
17444,
427,
96,
23620,
15,
26,
57,
121,
3274,
3,
31,
18304,
26,
8331,
35,
18088,
31,
3430,
96,
4168,
5,
16,
939,
121,
2490,
3,
31,
2266,
12734,
... |
what number of black/cape verdean patients had the drug 0.45%sodium chloride? | 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 prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.ethnicity = "BLACK/CAPE VERDEAN" AND prescriptions.drug = "0.45% Sodium Chloride" | [
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,
7744,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
7744,
7,
5,
8399,
51,
834,
23,
26,
549... |
Which district was the race between john i. nolan (r) 87% thomas f. feeley (s) 13%? | CREATE TABLE table_1346118_5 (
district VARCHAR,
candidates VARCHAR
) | SELECT district FROM table_1346118_5 WHERE candidates = "John I. Nolan (R) 87% Thomas F. Feeley (S) 13%" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2368,
4448,
20056,
834,
755,
41,
3939,
584,
4280,
28027,
6,
4341,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
3939,
47,
8,
1964,
344,
3,
27341,
3,
23,
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,
3939,
21680,
953,
834,
2368,
4448,
20056,
834,
755,
549,
17444,
427,
4341,
3274,
96,
18300,
27,
5,
465,
1618,
41,
448,
61,
505,
6170,
3576,
377,
5,
8495,
1306,
41,
134,
61,
209,
5170,
121,
1,
-100,
-100,
-100,
-10... |
In what season did Bob Pratt play? | CREATE TABLE table_name_86 (
season VARCHAR,
player VARCHAR
) | SELECT season FROM table_name_86 WHERE player = "bob pratt" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3840,
41,
774,
584,
4280,
28027,
6,
1959,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
86,
125,
774,
410,
5762,
6110,
17,
17,
577,
58,
1,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
774,
21680,
953,
834,
4350,
834,
3840,
549,
17444,
427,
1959,
3274,
96,
17396,
3,
5319,
17,
17,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is To par, when Place is 'T5', and when Score is '70-68=138'? | CREATE TABLE table_60731 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text
) | SELECT "To par" FROM table_60731 WHERE "Place" = 't5' AND "Score" = '70-68=138' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3328,
4552,
536,
41,
96,
345,
11706,
121,
1499,
6,
96,
15800,
49,
121,
1499,
6,
96,
10628,
651,
121,
1499,
6,
96,
134,
9022,
121,
1499,
6,
96,
3696,
260,
121,
1499,
3,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3328,
4552,
536,
549,
17444,
427,
96,
345,
11706,
121,
3274,
3,
31,
17,
755,
31,
3430,
96,
134,
9022,
121,
3274,
3,
31,
2518,
18,
3651,
2423,
22744,
31,
1,
-100,
-100,
-100,
... |
What tournament took place before 1972 with an extra of 200 m? | CREATE TABLE table_name_14 (
tournament VARCHAR,
extra VARCHAR,
year VARCHAR
) | SELECT tournament FROM table_name_14 WHERE extra = "200 m" AND year < 1972 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2534,
41,
5892,
584,
4280,
28027,
6,
996,
584,
4280,
28027,
6,
215,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
5892,
808,
286,
274,
16583,
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,
5892,
21680,
953,
834,
4350,
834,
2534,
549,
17444,
427,
996,
3274,
96,
3632,
3,
51,
121,
3430,
215,
3,
2,
16583,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
What was the crowd size when the away team scored 10.9 (69)? | CREATE TABLE table_33117 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT COUNT("Crowd") FROM table_33117 WHERE "Away team score" = '10.9 (69)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4201,
20275,
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,
2847,
17161,
599,
121,
254,
3623,
26,
8512,
21680,
953,
834,
4201,
20275,
549,
17444,
427,
96,
188,
1343,
372,
2604,
121,
3274,
3,
31,
10415,
1298,
41,
3951,
61,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
How many institutions are located in wilmore, kentucky and private | CREATE TABLE table_10581768_2 (founded INTEGER, type VARCHAR, location VARCHAR) | SELECT MAX(founded) FROM table_10581768_2 WHERE type = "Private" AND location = "Wilmore, Kentucky" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1714,
3449,
2517,
3651,
834,
357,
41,
23329,
3,
21342,
17966,
6,
686,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
4222,
33,
1069... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
4800,
4,
599,
23329,
61,
21680,
953,
834,
1714,
3449,
2517,
3651,
834,
357,
549,
17444,
427,
686,
3274,
96,
7855,
208,
342,
121,
3430,
1128,
3274,
96,
518,
173,
3706,
6,
13401,
121,
1,
-100,
-100,
-100,
-100,
-100,
... |
Find the dates on which more than one revisions were made. | CREATE TABLE attribute_definitions (
attribute_id number,
attribute_name text,
attribute_data_type text
)
CREATE TABLE catalog_contents_additional_attributes (
catalog_entry_id number,
catalog_level_number number,
attribute_id number,
attribute_value text
)
CREATE TABLE catalog_structure (
catalog_level_number number,
catalog_id number,
catalog_level_name text
)
CREATE TABLE catalogs (
catalog_id number,
catalog_name text,
catalog_publisher text,
date_of_publication time,
date_of_latest_revision time
)
CREATE TABLE catalog_contents (
catalog_entry_id number,
catalog_level_number number,
parent_entry_id number,
previous_entry_id number,
next_entry_id number,
catalog_entry_name text,
product_stock_number text,
price_in_dollars number,
price_in_euros number,
price_in_pounds number,
capacity text,
length text,
height text,
width text
) | SELECT date_of_latest_revision FROM catalogs GROUP BY date_of_latest_revision HAVING COUNT(*) > 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
15816,
834,
221,
5582,
10872,
41,
15816,
834,
23,
26,
381,
6,
15816,
834,
4350,
1499,
6,
15816,
834,
6757,
834,
6137,
1499,
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,
833,
834,
858,
834,
521,
4377,
834,
60,
6610,
21680,
10173,
7,
350,
4630,
6880,
272,
476,
833,
834,
858,
834,
521,
4377,
834,
60,
6610,
454,
6968,
2365,
2847,
17161,
599,
1935,
61,
2490,
209,
1,
-100,
-100,
-100,
... |
What is the country of the player with a t6 place? | CREATE TABLE table_name_33 (country VARCHAR, place VARCHAR) | SELECT country FROM table_name_33 WHERE place = "t6" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4201,
41,
17529,
584,
4280,
28027,
6,
286,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
684,
13,
8,
1959,
28,
3,
9,
3,
17,
948,
286,
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,
4201,
549,
17444,
427,
286,
3274,
96,
17,
948,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the result of the week 1 game? | CREATE TABLE table_15629 (
"Week" real,
"Date" text,
"Opponent" text,
"Result" text,
"Attendance" real
) | SELECT "Result" FROM table_15629 WHERE "Week" = '1' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
25463,
3166,
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,
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,
0... | [
3,
23143,
14196,
96,
20119,
121,
21680,
953,
834,
25463,
3166,
549,
17444,
427,
96,
518,
10266,
121,
3274,
3,
31,
536,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
which player with the most saves | CREATE TABLE table_204_147 (
id number,
"#" number,
"date" text,
"opponent" text,
"score" text,
"win" text,
"loss" text,
"save" text,
"attendance" number,
"record" text
) | SELECT "save" FROM table_204_147 GROUP BY "save" ORDER BY COUNT(*) DESC LIMIT 1 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26363,
834,
24719,
41,
3,
23,
26,
381,
6,
96,
4663,
121,
381,
6,
96,
5522,
121,
1499,
6,
96,
32,
102,
9977,
121,
1499,
6,
96,
7,
9022,
121,
1499,
6,
96,
3757,
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,
7,
9,
162,
121,
21680,
953,
834,
26363,
834,
24719,
350,
4630,
6880,
272,
476,
96,
7,
9,
162,
121,
4674,
11300,
272,
476,
2847,
17161,
599,
1935,
61,
309,
25067,
8729,
12604,
209,
1,
-100,
-100,
-100,
-100,
-1... |
What date did Passion Pictures receive an award? | CREATE TABLE table_name_42 (date VARCHAR, recipient VARCHAR) | SELECT date FROM table_name_42 WHERE recipient = "passion pictures" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4165,
41,
5522,
584,
4280,
28027,
6,
11095,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
833,
410,
21924,
16571,
911,
46,
2760,
58,
1,
0,
0,
0,
0,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
833,
21680,
953,
834,
4350,
834,
4165,
549,
17444,
427,
11095,
3274,
96,
26249,
1933,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What is the high average that has a Finale larger than 35, a HK viewers of 2.12 million, and a Peak larger than 40? | CREATE TABLE table_54631 (
"Rank" real,
"English title" text,
"Chinese title" text,
"Average" real,
"Peak" real,
"Premiere" real,
"Finale" real,
"HK viewers" text
) | SELECT MAX("Average") FROM table_54631 WHERE "Finale" > '35' AND "HK viewers" = '2.12 million' AND "Peak" > '40' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
5062,
3891,
536,
41,
96,
22557,
121,
490,
6,
96,
26749,
2233,
121,
1499,
6,
96,
3541,
4477,
15,
2233,
121,
1499,
6,
96,
188,
624,
545,
121,
490,
6,
96,
345,
15,
1639,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
624,
545,
8512,
21680,
953,
834,
5062,
3891,
536,
549,
17444,
427,
96,
371,
10270,
15,
121,
2490,
3,
31,
2469,
31,
3430,
96,
20240,
13569,
121,
3274,
3,
31,
14489,
357,
770,
31,
3430,
96,
... |
What Score has a Date of 11 september 2010? | CREATE TABLE table_name_25 (
score VARCHAR,
date VARCHAR
) | SELECT score FROM table_name_25 WHERE date = "11 september 2010" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1828,
41,
2604,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
17763,
65,
3,
9,
7678,
13,
850,
16022,
18247,
2735,
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,
2604,
21680,
953,
834,
4350,
834,
1828,
549,
17444,
427,
833,
3274,
96,
2596,
16022,
18247,
2735,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Which game number includes a record of 1-2? | CREATE TABLE table_name_31 (
game VARCHAR,
record VARCHAR
) | SELECT game FROM table_name_31 WHERE record = "1-2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3341,
41,
467,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
467,
381,
963,
3,
9,
1368,
13,
3,
9596,
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,
467,
21680,
953,
834,
4350,
834,
3341,
549,
17444,
427,
1368,
3274,
96,
9596,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the lowest altitude of the flight with a mach bigger than 0.905 and a duration of 00:06:17? | CREATE TABLE table_name_80 (altitude__ft_ INTEGER, mach VARCHAR, duration VARCHAR) | SELECT MIN(altitude__ft_) FROM table_name_80 WHERE mach > 0.905 AND duration = "00:06:17" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2079,
41,
138,
6592,
834,
834,
89,
17,
834,
3,
21342,
17966,
6,
3,
8276,
584,
4280,
28027,
6,
8659,
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,
1,
1... | [
3,
23143,
14196,
3,
17684,
599,
138,
6592,
834,
834,
89,
17,
834,
61,
21680,
953,
834,
4350,
834,
2079,
549,
17444,
427,
3,
8276,
2490,
3,
23758,
3076,
3430,
8659,
3274,
96,
1206,
10,
5176,
10,
2517,
121,
1,
-100,
-100,
-100,
-100... |
What is the nationality of the HMS Cheshire? | CREATE TABLE table_name_32 (nationality VARCHAR, name VARCHAR) | SELECT nationality FROM table_name_32 WHERE name = "hms cheshire" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2668,
41,
16557,
485,
584,
4280,
28027,
6,
564,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
1157,
485,
13,
8,
454,
4211,
2556,
5718,
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,
1157,
485,
21680,
953,
834,
4350,
834,
2668,
549,
17444,
427,
564,
3274,
96,
107,
51,
7,
3,
1033,
5718,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which chassis had an entrant of John Mecom? | CREATE TABLE table_name_37 (chassis VARCHAR, entrant VARCHAR) | SELECT chassis FROM table_name_37 WHERE entrant = "john mecom" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4118,
41,
524,
6500,
7,
584,
4280,
28027,
6,
3,
295,
3569,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
22836,
141,
46,
3,
295,
3569,
13,
1079,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
22836,
21680,
953,
834,
4350,
834,
4118,
549,
17444,
427,
3,
295,
3569,
3274,
96,
27341,
140,
287,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Which Word wrap support has a Format of mobipocket? | CREATE TABLE table_name_65 (word_wrap_support VARCHAR, format VARCHAR) | SELECT word_wrap_support FROM table_name_65 WHERE format = "mobipocket" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4122,
41,
6051,
834,
210,
5846,
834,
20390,
584,
4280,
28027,
6,
1910,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
4467,
6215,
380,
65,
3,
9,
12439,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1448,
834,
210,
5846,
834,
20390,
21680,
953,
834,
4350,
834,
4122,
549,
17444,
427,
1910,
3274,
96,
51,
6690,
10496,
8044,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which Player has a height of 6-10, and went to College at LSU? | CREATE TABLE table_56870 (
"Player" text,
"Height" text,
"School" text,
"Hometown" text,
"College" text,
"NBA Draft" text
) | SELECT "Player" FROM table_56870 WHERE "Height" = '6-10' AND "College" = 'lsu' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3651,
2518,
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,
15800,
49,
121,
21680,
953,
834,
755,
3651,
2518,
549,
17444,
427,
96,
3845,
2632,
121,
3274,
3,
31,
948,
4536,
31,
3430,
96,
9939,
7883,
121,
3274,
3,
31,
40,
7,
76,
31,
1,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the name of episode 43 in the series? | CREATE TABLE table_30750 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text,
"Production code" text,
"U.S. viewers (million)" text
) | SELECT "Title" FROM table_30750 WHERE "No. in series" = '43' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1458,
9979,
41,
96,
4168,
5,
16,
939,
121,
490,
6,
96,
4168,
5,
16,
774,
121,
490,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
15,
26,
57,
121,
1499,
6,
96,
24965,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
96,
382,
155,
109,
121,
21680,
953,
834,
1458,
9979,
549,
17444,
427,
96,
4168,
5,
16,
939,
121,
3274,
3,
31,
4906,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the total number of races in the 2006 season with 0 poles and more than 0 podiums? | CREATE TABLE table_name_54 (races VARCHAR, podiums VARCHAR, poles VARCHAR, season VARCHAR) | SELECT COUNT(races) FROM table_name_54 WHERE poles = 0 AND season = "2006" AND podiums > 0 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
5062,
41,
12614,
7,
584,
4280,
28027,
6,
22828,
7,
584,
4280,
28027,
6,
11148,
7,
584,
4280,
28027,
6,
774,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
12614,
7,
61,
21680,
953,
834,
4350,
834,
5062,
549,
17444,
427,
11148,
7,
3274,
3,
632,
3430,
774,
3274,
96,
21196,
121,
3430,
22828,
7,
2490,
3,
632,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who won the men's double when Chou Tien-Chen won the men's single? | CREATE TABLE table_17592 (
"Year" real,
"Mens singles" text,
"Womens singles" text,
"Mens doubles" text,
"Womens doubles" text,
"Mixed doubles" text
) | SELECT "Mens doubles" FROM table_17592 WHERE "Mens singles" = 'Chou Tien-chen' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2517,
3390,
357,
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... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2517,
3390,
357,
549,
17444,
427,
96,
329,
35,
7,
712,
7,
121,
3274,
3,
31,
254,
9492,
2262,
35,
18,
1559,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Show the location codes with at least 3 documents. | CREATE TABLE ref_locations (
location_code text,
location_name text,
location_description text
)
CREATE TABLE employees (
employee_id number,
role_code text,
employee_name text,
gender_mfu text,
date_of_birth time,
other_details text
)
CREATE TABLE documents_to_be_destroyed (
document_id number,
destruction_authorised_by_employee_id number,
destroyed_by_employee_id number,
planned_destruction_date time,
actual_destruction_date time,
other_details text
)
CREATE TABLE ref_document_types (
document_type_code text,
document_type_name text,
document_type_description text
)
CREATE TABLE document_locations (
document_id number,
location_code text,
date_in_location_from time,
date_in_locaton_to time
)
CREATE TABLE all_documents (
document_id number,
date_stored time,
document_type_code text,
document_name text,
document_description text,
other_details text
)
CREATE TABLE roles (
role_code text,
role_name text,
role_description text
)
CREATE TABLE ref_calendar (
calendar_date time,
day_number number
) | SELECT location_code FROM document_locations GROUP BY location_code HAVING COUNT(*) >= 3 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
6273,
834,
14836,
7,
41,
1128,
834,
4978,
1499,
6,
1128,
834,
4350,
1499,
6,
1128,
834,
221,
11830,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
1652,
41,
3490,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
1128,
834,
4978,
21680,
1708,
834,
14836,
7,
350,
4630,
6880,
272,
476,
1128,
834,
4978,
454,
6968,
2365,
2847,
17161,
599,
1935,
61,
2490,
2423,
220,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What's the largest pick number for corrie d'alessio with a rd number over 6? | CREATE TABLE table_56028 (
"Rd #" real,
"Pick #" real,
"Player" text,
"Team (League)" text,
"Reg GP" real,
"Pl GP" real
) | SELECT MAX("Pick #") FROM table_56028 WHERE "Player" = 'corrie d''alessio' AND "Rd #" > '6' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
755,
3328,
2577,
41,
96,
448,
26,
1713,
121,
490,
6,
96,
345,
3142,
1713,
121,
490,
6,
96,
15800,
49,
121,
1499,
6,
96,
18699,
41,
2796,
9,
5398,
61,
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,
4800,
4,
599,
121,
345,
3142,
1713,
8512,
21680,
953,
834,
755,
3328,
2577,
549,
17444,
427,
96,
15800,
49,
121,
3274,
3,
31,
5715,
1753,
3,
26,
31,
31,
9,
924,
23,
32,
31,
3430,
96,
448,
26,
1713,
121,
2490,
... |
Which country had a total of 295? | CREATE TABLE table_name_46 (
country VARCHAR,
total VARCHAR
) | SELECT country FROM table_name_46 WHERE total = 295 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4448,
41,
684,
584,
4280,
28027,
6,
792,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
684,
141,
3,
9,
792,
13,
204,
3301,
58,
1,
0,
0,
0,
0,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
684,
21680,
953,
834,
4350,
834,
4448,
549,
17444,
427,
792,
3274,
204,
3301,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How much Gold has a Silver smaller than 14, and a Rank larger than 8, and a Bronze of 3? | CREATE TABLE table_name_80 (gold VARCHAR, bronze VARCHAR, silver VARCHAR, rank VARCHAR) | SELECT COUNT(gold) FROM table_name_80 WHERE silver < 14 AND rank > 8 AND bronze = 3 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2079,
41,
14910,
584,
4280,
28027,
6,
13467,
584,
4280,
28027,
6,
4294,
584,
4280,
28027,
6,
11003,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
231,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
14910,
61,
21680,
953,
834,
4350,
834,
2079,
549,
17444,
427,
4294,
3,
2,
968,
3430,
11003,
2490,
505,
3430,
13467,
3274,
220,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the number of Goals For for Games Played more than 8? | CREATE TABLE table_name_44 (goals_for INTEGER, games_played INTEGER) | SELECT SUM(goals_for) FROM table_name_44 WHERE games_played > 8 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3628,
41,
839,
5405,
834,
1161,
3,
21342,
17966,
6,
1031,
834,
4895,
15,
26,
3,
21342,
17966,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
381,
13,
17916,
7,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
180,
6122,
599,
839,
5405,
834,
1161,
61,
21680,
953,
834,
4350,
834,
3628,
549,
17444,
427,
1031,
834,
4895,
15,
26,
2490,
505,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what are the specimen tests top five most frequently ordered during this year? | CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
) | SELECT t1.culturesite FROM (SELECT microlab.culturesite, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM microlab WHERE DATETIME(microlab.culturetakentime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-0 year') GROUP BY microlab.culturesite) AS t1 WHERE t1.c1 <= 5 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
3362,
4267,
32,
4370,
41,
3362,
4267,
32,
26,
1294,
26,
381,
6,
1868,
15129,
21545,
23,
26,
381,
6,
2912,
381,
6,
3,
7,
9,
32,
357,
381,
6,
842,
2206,
381,
6,
14114,
257,
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,
3,
17,
5411,
10547,
3585,
21680,
41,
23143,
14196,
2179,
9339,
5,
10547,
3585,
6,
3,
22284,
4132,
834,
16375,
439,
9960,
3,
23288,
41,
2990,
11300,
272,
476,
2847,
17161,
599,
1935,
61,
309,
25067,
61,
6157,
3,
75,
... |
What was the last episode featuring Rob Estes? | CREATE TABLE table_name_93 (final_episode VARCHAR, actor VARCHAR) | SELECT final_episode FROM table_name_93 WHERE actor = "rob estes" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4271,
41,
12406,
834,
15,
102,
159,
32,
221,
584,
4280,
28027,
6,
7556,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
336,
5640,
4767,
5376,
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,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
804,
834,
15,
102,
159,
32,
221,
21680,
953,
834,
4350,
834,
4271,
549,
17444,
427,
7556,
3274,
96,
5840,
249,
7,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the Date that chicago black hawks has a Record of 2 2? | CREATE TABLE table_name_5 (
date VARCHAR,
visitor VARCHAR,
record VARCHAR
) | SELECT date FROM table_name_5 WHERE visitor = "chicago black hawks" AND record = "2–2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
755,
41,
833,
584,
4280,
28027,
6,
7019,
584,
4280,
28027,
6,
1368,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
7678,
24,
8780,
9,
839,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
833,
21680,
953,
834,
4350,
834,
755,
549,
17444,
427,
7019,
3274,
96,
1436,
658,
839,
1001,
3,
14400,
7,
121,
3430,
1368,
3274,
96,
357,
104,
357,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
What are the maximum and minimum age of students with major 600? | CREATE TABLE student (
stuid number,
lname text,
fname text,
age number,
sex text,
major number,
advisor number,
city_code text
)
CREATE TABLE voting_record (
stuid number,
registration_date text,
election_cycle text,
president_vote number,
vice_president_vote number,
secretary_vote number,
treasurer_vote number,
class_president_vote number,
class_senator_vote number
) | SELECT MAX(age), MIN(age) FROM student WHERE major = 600 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1236,
41,
21341,
23,
26,
381,
6,
3,
40,
4350,
1499,
6,
3,
89,
4350,
1499,
6,
1246,
381,
6,
3,
7,
994,
1499,
6,
779,
381,
6,
8815,
381,
6,
690,
834,
4978,
1499,
3,
61,
3,
3210... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
545,
201,
3,
17684,
599,
545,
61,
21680,
1236,
549,
17444,
427,
779,
3274,
7366,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Show the number of games for each away team in a bar chart, and I want to sort by the X in asc please. | CREATE TABLE game (
stadium_id int,
id int,
Season int,
Date text,
Home_team text,
Away_team text,
Score text,
Competition text
)
CREATE TABLE injury_accident (
game_id int,
id int,
Player text,
Injury text,
Number_of_matches text,
Source text
)
CREATE TABLE stadium (
id int,
name text,
Home_Games int,
Average_Attendance real,
Total_Attendance real,
Capacity_Percentage real
) | SELECT Away_team, COUNT(Away_team) FROM game GROUP BY Away_team ORDER BY Away_team | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
467,
41,
14939,
834,
23,
26,
16,
17,
6,
3,
23,
26,
16,
17,
6,
7960,
16,
17,
6,
7678,
1499,
6,
1210,
834,
11650,
1499,
6,
71,
1343,
834,
11650,
1499,
6,
17763,
1499,
6,
15571,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1343,
834,
11650,
6,
2847,
17161,
599,
188,
1343,
834,
11650,
61,
21680,
467,
350,
4630,
6880,
272,
476,
71,
1343,
834,
11650,
4674,
11300,
272,
476,
71,
1343,
834,
11650,
1,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Where is the University of North Carolina at Greensboro located? | CREATE TABLE table_27726 (
"Institution" text,
"Location" text,
"Nickname" text,
"Founded" real,
"Type" text,
"Enrollment" real,
"Joined" real,
"Left" real,
"Current Conference" text
) | SELECT "Location" FROM table_27726 WHERE "Institution" = 'University of North Carolina at Greensboro' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
4013,
2688,
41,
96,
1570,
17448,
121,
1499,
6,
96,
434,
32,
75,
257,
121,
1499,
6,
96,
567,
3142,
4350,
121,
1499,
6,
96,
20100,
121,
490,
6,
96,
25160,
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,
434,
32,
75,
257,
121,
21680,
953,
834,
357,
4013,
2688,
549,
17444,
427,
96,
1570,
17448,
121,
3274,
3,
31,
8313,
485,
13,
1117,
5089,
44,
1862,
7,
14901,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
What is the event with a result of 3-2? | CREATE TABLE table_name_40 (
competition VARCHAR,
result VARCHAR
) | SELECT competition FROM table_name_40 WHERE result = "3-2" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2445,
41,
2259,
584,
4280,
28027,
6,
741,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
605,
28,
3,
9,
741,
13,
3,
21160,
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,
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,
2259,
21680,
953,
834,
4350,
834,
2445,
549,
17444,
427,
741,
3274,
96,
21160,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
which year was the original title გაღმა ნაპირი | CREATE TABLE table_18069789_1 (year_ VARCHAR, e_ VARCHAR, original_title VARCHAR) | SELECT year_[e_] AS __ceremony_ FROM table_18069789_1 WHERE original_title = "გაღმა ნაპირი" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2606,
5176,
4327,
3914,
834,
536,
41,
1201,
834,
584,
4280,
28027,
6,
3,
15,
834,
584,
4280,
28027,
6,
926,
834,
21869,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
215,
834,
6306,
15,
834,
908,
6157,
3,
834,
834,
2110,
15,
21208,
834,
21680,
953,
834,
2606,
5176,
4327,
3914,
834,
536,
549,
17444,
427,
926,
834,
21869,
3274,
96,
2,
3,
2,
121,
1,
-100,
-100,
-100,
-100,
-100,
... |
What location had 25/25 fatalities? | CREATE TABLE table_name_15 (
location VARCHAR,
fatalities VARCHAR
) | SELECT location FROM table_name_15 WHERE fatalities = "25/25" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
1808,
41,
1128,
584,
4280,
28027,
6,
12699,
2197,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
1128,
141,
944,
87,
1828,
12699,
2197,
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,
1128,
21680,
953,
834,
4350,
834,
1808,
549,
17444,
427,
12699,
2197,
3274,
96,
1828,
13311,
17395,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
How many insurgents are there when the total per period is 156? | CREATE TABLE table_21636599_2 (insurgents VARCHAR, total_per_period VARCHAR) | SELECT insurgents FROM table_21636599_2 WHERE total_per_period = 156 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
27184,
10402,
3264,
834,
357,
41,
77,
3042,
5560,
7,
584,
4280,
28027,
6,
792,
834,
883,
834,
4267,
32,
26,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
571,
186,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
16,
3042,
5560,
7,
21680,
953,
834,
27184,
10402,
3264,
834,
357,
549,
17444,
427,
792,
834,
883,
834,
4267,
32,
26,
3274,
3,
25463,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Who picked a player from Weber State? | CREATE TABLE table_16575609_1 (cfl_team VARCHAR, college VARCHAR) | SELECT cfl_team FROM table_16575609_1 WHERE college = "Weber State" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
3436,
4834,
4198,
834,
536,
41,
75,
89,
40,
834,
11650,
584,
4280,
28027,
6,
1900,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
2645,
4758,
3,
9,
1959,
45,
16... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
75,
89,
40,
834,
11650,
21680,
953,
834,
2938,
3436,
4834,
4198,
834,
536,
549,
17444,
427,
1900,
3274,
96,
15805,
49,
1015,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Which political party is involved where John J. Delaney is the sitting Representative? | CREATE TABLE table_18605 (
"District" text,
"Incumbent" text,
"Party" text,
"First elected" real,
"Result" text,
"Candidates" text
) | SELECT "Party" FROM table_18605 WHERE "Incumbent" = 'John J. Delaney' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
24700,
755,
41,
96,
308,
23,
20066,
121,
1499,
6,
96,
1570,
75,
5937,
295,
121,
1499,
6,
96,
13725,
63,
121,
1499,
6,
96,
25171,
8160,
121,
490,
6,
96,
20119,
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,
13725,
63,
121,
21680,
953,
834,
24700,
755,
549,
17444,
427,
96,
1570,
75,
5937,
295,
121,
3274,
3,
31,
18300,
446,
5,
6236,
9,
3186,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
What is the Away Team Score of the Hawthorn Home Team? | CREATE TABLE table_name_6 (
away_team VARCHAR,
home_team VARCHAR
) | SELECT away_team AS score FROM table_name_6 WHERE home_team = "hawthorn" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
948,
41,
550,
834,
11650,
584,
4280,
28027,
6,
234,
834,
11650,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
71,
1343,
2271,
17763,
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,
550,
834,
11650,
6157,
2604,
21680,
953,
834,
4350,
834,
948,
549,
17444,
427,
234,
834,
11650,
3274,
96,
1024,
210,
17,
6293,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
Who is the team captain for the team with sparkasse (d sseldorf) as the shirt sponsor? | CREATE TABLE table_8201 (
"Team" text,
"Head coach" text,
"Team captain" text,
"Kitmaker" text,
"Shirt sponsor" text
) | SELECT "Team captain" FROM table_8201 WHERE "Shirt sponsor" = 'sparkasse (düsseldorf)' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4613,
4542,
41,
96,
18699,
121,
1499,
6,
96,
3845,
9,
26,
3763,
121,
1499,
6,
96,
18699,
14268,
121,
1499,
6,
96,
439,
155,
8337,
121,
1499,
6,
96,
16671,
9037,
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,
18699,
14268,
121,
21680,
953,
834,
4613,
4542,
549,
17444,
427,
96,
16671,
9037,
121,
3274,
3,
31,
7,
6334,
3974,
41,
26,
12079,
40,
8716,
61,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
The location (transmitter site) San Fernando, Pampanga ** has what Power kW (ERP)? | CREATE TABLE table_2610582_2 (power_kw__erp_ VARCHAR, location__transmitter_site_ VARCHAR) | SELECT power_kw__erp_ FROM table_2610582_2 WHERE location__transmitter_site_ = "San Fernando, Pampanga **" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2688,
12869,
4613,
834,
357,
41,
6740,
834,
157,
210,
834,
834,
49,
102,
834,
584,
4280,
28027,
6,
1128,
834,
834,
7031,
1538,
449,
834,
3585,
834,
584,
4280,
28027,
61,
3,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
579,
834,
157,
210,
834,
834,
49,
102,
834,
21680,
953,
834,
2688,
12869,
4613,
834,
357,
549,
17444,
427,
1128,
834,
834,
7031,
1538,
449,
834,
3585,
834,
3274,
96,
134,
152,
28989,
6,
276,
4624,
1468,
9,
14011,
... |
Name the category for nominated at the british comedy awards | CREATE TABLE table_name_26 (category VARCHAR, result VARCHAR, award VARCHAR) | SELECT category FROM table_name_26 WHERE result = "nominated" AND award = "british comedy awards" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2688,
41,
8367,
839,
651,
584,
4280,
28027,
6,
741,
584,
4280,
28027,
6,
2760,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
5570,
8,
3295,
21,
150,
1109,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
3295,
21680,
953,
834,
4350,
834,
2688,
549,
17444,
427,
741,
3274,
96,
3114,
77,
920,
121,
3430,
2760,
3274,
96,
2160,
17,
1273,
12373,
6120,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What were the scores when Jamie and Johns guest was Phillips Idowu? | CREATE TABLE table_29141354_2 (scores VARCHAR, jamie_and_johns_guest VARCHAR) | SELECT scores FROM table_29141354_2 WHERE jamie_and_johns_guest = "Phillips Idowu" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3166,
2534,
2368,
5062,
834,
357,
41,
7,
9022,
7,
584,
4280,
28027,
6,
2662,
2720,
834,
232,
834,
27341,
7,
834,
15991,
17,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0... | [
3,
23143,
14196,
7586,
21680,
953,
834,
3166,
2534,
2368,
5062,
834,
357,
549,
17444,
427,
2662,
2720,
834,
232,
834,
27341,
7,
834,
15991,
17,
3274,
96,
23305,
7446,
7,
27,
15198,
76,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the team name when 243 is the total? | CREATE TABLE table_22014431_3 (
team_name VARCHAR,
total VARCHAR
) | SELECT team_name FROM table_22014431_3 WHERE total = "243" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
10218,
591,
3341,
834,
519,
41,
372,
834,
4350,
584,
4280,
28027,
6,
792,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
372,
564,
116,
3,
27730,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
372,
834,
4350,
21680,
953,
834,
357,
10218,
591,
3341,
834,
519,
549,
17444,
427,
792,
3274,
96,
27730,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-1... |
Pick # of 203 went to which college? | CREATE TABLE table_name_16 (
college VARCHAR,
pick__number VARCHAR
) | SELECT college FROM table_name_16 WHERE pick__number = 203 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2938,
41,
1900,
584,
4280,
28027,
6,
1432,
834,
834,
5525,
1152,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
8356,
1713,
13,
3,
23330,
877,
12,
84,
1... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
1900,
21680,
953,
834,
4350,
834,
2938,
549,
17444,
427,
1432,
834,
834,
5525,
1152,
3274,
3,
23330,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many companies are there? | CREATE TABLE office_locations (
building_id number,
company_id number,
move_in_year number
)
CREATE TABLE buildings (
id number,
name text,
city text,
height number,
stories number,
status text
)
CREATE TABLE companies (
id number,
name text,
headquarters text,
industry text,
sales_billion number,
profits_billion number,
assets_billion number,
market_value_billion text
) | SELECT COUNT(*) FROM companies | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
828,
834,
14836,
7,
41,
740,
834,
23,
26,
381,
6,
349,
834,
23,
26,
381,
6,
888,
834,
77,
834,
1201,
381,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
3950,
41,
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,
2847,
17161,
599,
1935,
61,
21680,
688,
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,
-100,
-1... |
Find the contact channel code that was used by the customer named 'Tillman Ernser'. | CREATE TABLE customers (
customer_id number,
payment_method text,
customer_name text,
date_became_customer time,
other_customer_details text
)
CREATE TABLE products (
product_id number,
product_details text
)
CREATE TABLE order_items (
order_id number,
product_id number,
order_quantity text
)
CREATE TABLE customer_addresses (
customer_id number,
address_id number,
date_address_from time,
address_type text,
date_address_to time
)
CREATE TABLE addresses (
address_id number,
address_content text,
city text,
zip_postcode text,
state_province_county text,
country text,
other_address_details text
)
CREATE TABLE customer_contact_channels (
customer_id number,
channel_code text,
active_from_date time,
active_to_date time,
contact_number text
)
CREATE TABLE customer_orders (
order_id number,
customer_id number,
order_status text,
order_date time,
order_details text
) | SELECT DISTINCT channel_code FROM customers AS t1 JOIN customer_contact_channels AS t2 ON t1.customer_id = t2.customer_id WHERE t1.customer_name = "Tillman Ernser" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
722,
41,
884,
834,
23,
26,
381,
6,
1942,
834,
23152,
1499,
6,
884,
834,
4350,
1499,
6,
833,
834,
346,
6527,
15,
834,
25697,
49,
97,
6,
119,
834,
25697,
49,
834,
221,
5756,
7,
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,
3,
15438,
25424,
6227,
4245,
834,
4978,
21680,
722,
6157,
3,
17,
536,
3,
15355,
3162,
884,
834,
27608,
834,
19778,
7,
6157,
3,
17,
357,
9191,
3,
17,
5411,
25697,
49,
834,
23,
26,
3274,
3,
17,
4416,
25697,
49,
83... |
How many different provinces is Baghaberd the center of? | CREATE TABLE table_26377 (
"Province (ashkharh)" text,
"Armenian name" text,
"Area (km\u00b2)" real,
"Number of cantons (gavars)" real,
"Center" text
) | SELECT COUNT("Province (ashkharh)") FROM table_26377 WHERE "Center" = 'Baghaberd' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3891,
4013,
41,
96,
3174,
2494,
565,
41,
3198,
157,
3272,
107,
61,
121,
1499,
6,
96,
23823,
15,
15710,
564,
121,
1499,
6,
96,
188,
864,
41,
5848,
2,
76,
1206,
115,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
121,
3174,
2494,
565,
41,
3198,
157,
3272,
107,
61,
8512,
21680,
953,
834,
357,
3891,
4013,
549,
17444,
427,
96,
24382,
121,
3274,
3,
31,
279,
18583,
9,
1152,
26,
31,
1,
-100,
-100,
-100,
-100,
-... |
On July 17, 2008, what was the total number of lead maragin? | CREATE TABLE table_16751596_13 (
lead_maragin VARCHAR,
dates_administered VARCHAR
) | SELECT COUNT(lead_maragin) FROM table_16751596_13 WHERE dates_administered = "July 17, 2008" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2938,
3072,
1808,
4314,
834,
2368,
41,
991,
834,
1635,
6623,
29,
584,
4280,
28027,
6,
5128,
834,
9,
26,
17791,
15,
26,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
3210... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0... | [
3,
23143,
14196,
2847,
17161,
599,
109,
9,
26,
834,
1635,
6623,
29,
61,
21680,
953,
834,
2938,
3072,
1808,
4314,
834,
2368,
549,
17444,
427,
5128,
834,
9,
26,
17791,
15,
26,
3274,
96,
683,
83,
63,
12864,
2628,
121,
1,
-100,
-100,
... |
Which away team goes against the home team Mauritius? | CREATE TABLE table_name_94 (away_team VARCHAR, home_team VARCHAR) | SELECT away_team FROM table_name_94 WHERE home_team = "mauritius" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4240,
41,
8006,
834,
11650,
584,
4280,
28027,
6,
234,
834,
11650,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
4073,
550,
372,
1550,
581,
8,
234,
372,
7758... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
550,
834,
11650,
21680,
953,
834,
4350,
834,
4240,
549,
17444,
427,
234,
834,
11650,
3274,
96,
51,
402,
13224,
302,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
what is teh ihsaa class/football/soccer when the location is alexandria? | CREATE TABLE table_name_43 (
ihsaa_class___football___soccer VARCHAR,
location VARCHAR
) | SELECT ihsaa_class___football___soccer FROM table_name_43 WHERE location = "alexandria" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4906,
41,
3,
23,
107,
7,
9,
9,
834,
4057,
834,
834,
834,
6259,
3184,
834,
834,
834,
7,
13377,
49,
584,
4280,
28027,
6,
1128,
584,
4280,
28027,
3,
61,
3,
3210... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
23,
107,
7,
9,
9,
834,
4057,
834,
834,
834,
6259,
3184,
834,
834,
834,
7,
13377,
49,
21680,
953,
834,
4350,
834,
4906,
549,
17444,
427,
1128,
3274,
96,
138,
994,
232,
52,
23,
9,
121,
1,
-100,
-100,
-100,
-1... |
What is the title from 302 bc? | CREATE TABLE table_7195 (
"State" text,
"Type" text,
"Name" text,
"Title" text,
"Royal house" text,
"From" text
) | SELECT "Title" FROM table_7195 WHERE "From" = '302 bc' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4450,
3301,
41,
96,
134,
4748,
121,
1499,
6,
96,
25160,
121,
1499,
6,
96,
23954,
121,
1499,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
448,
32,
63,
138,
629,
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,
382,
155,
109,
121,
21680,
953,
834,
4450,
3301,
549,
17444,
427,
96,
22674,
121,
3274,
3,
31,
1458,
357,
3,
115,
75,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the first year that South Korea won gold and Malaysia won bronze? | CREATE TABLE table_name_74 (year INTEGER, gold VARCHAR, bronze VARCHAR) | SELECT MIN(year) FROM table_name_74 WHERE gold = "south korea" AND bronze = "malaysia" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4581,
41,
1201,
3,
21342,
17966,
6,
2045,
584,
4280,
28027,
6,
13467,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
8,
166,
215,
24,
1013,
7054,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
17684,
599,
1201,
61,
21680,
953,
834,
4350,
834,
4581,
549,
17444,
427,
2045,
3274,
96,
7,
670,
107,
3,
5543,
15,
9,
121,
3430,
13467,
3274,
96,
51,
9,
20244,
23,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-10... |
Which Game has a Score of 3 4? | CREATE TABLE table_name_76 (
game INTEGER,
score VARCHAR
) | SELECT MIN(game) FROM table_name_76 WHERE score = "3–4" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3959,
41,
467,
3,
21342,
17966,
6,
2604,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
4435,
65,
3,
9,
17763,
13,
220,
314,
58,
1,
0,
0,
0,
0... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
17684,
599,
7261,
61,
21680,
953,
834,
4350,
834,
3959,
549,
17444,
427,
2604,
3274,
96,
519,
104,
20364,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-10... |
What is the IHSAA class when the county was 83 vermillion? | CREATE TABLE table_name_40 (ihsaa_class VARCHAR, county VARCHAR) | SELECT ihsaa_class FROM table_name_40 WHERE county = "83 vermillion" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
2445,
41,
23,
107,
7,
9,
9,
834,
4057,
584,
4280,
28027,
6,
5435,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
19,
8,
27,
4950,
5498,
853,
116,
8,... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
3,
23,
107,
7,
9,
9,
834,
4057,
21680,
953,
834,
4350,
834,
2445,
549,
17444,
427,
5435,
3274,
96,
4591,
548,
17030,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What number episode was written by kurt sutter & jack logiudice? | CREATE TABLE table_23854 (
"No. in series" real,
"Title" text,
"Directedby" text,
"Writtenby" text,
"Originalairdate" text,
"Production code" text
) | SELECT MAX("No. in series") FROM table_23854 WHERE "Writtenby" = 'Kurt Sutter & Jack LoGiudice' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3747,
5062,
41,
96,
4168,
5,
16,
939,
121,
490,
6,
96,
382,
155,
109,
121,
1499,
6,
96,
23620,
15,
26,
969,
121,
1499,
6,
96,
24965,
324,
969,
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,
4800,
4,
599,
121,
4168,
5,
16,
939,
8512,
21680,
953,
834,
357,
3747,
5062,
549,
17444,
427,
96,
24965,
324,
969,
121,
3274,
3,
31,
439,
450,
17,
180,
5108,
3,
184,
4496,
1815,
517,
23,
5291,
565,
31,
1,
-100,
... |
who is the reference when romaji title is heartbreak sniper? | CREATE TABLE table_16413 (
"Romaji title" text,
"Japanese title" text,
"Release date" text,
"Reference" text,
"Oricon" real
) | SELECT "Reference" FROM table_16413 WHERE "Romaji title" = 'Heartbreak Sniper' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
26987,
2368,
41,
96,
448,
32,
16547,
23,
2233,
121,
1499,
6,
96,
683,
9750,
1496,
15,
2233,
121,
1499,
6,
96,
1649,
40,
14608,
833,
121,
1499,
6,
96,
1649,
11788,
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,
1649,
11788,
121,
21680,
953,
834,
26987,
2368,
549,
17444,
427,
96,
448,
32,
16547,
23,
2233,
121,
3274,
3,
31,
3845,
1408,
14577,
180,
29,
23,
883,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
How many points against did the club with a losing bonus of 3 and 84 tries have? | CREATE TABLE table_name_68 (
points_against VARCHAR,
losing_bonus VARCHAR,
tries_for VARCHAR
) | SELECT points_against FROM table_name_68 WHERE losing_bonus = "3" AND tries_for = "84" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
979,
834,
9,
16720,
7,
17,
584,
4280,
28027,
6,
5489,
834,
5407,
302,
584,
4280,
28027,
6,
3,
9000,
834,
1161,
584,
4280,
28027,
3,
61,
3,
32102,
321... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
979,
834,
9,
16720,
7,
17,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
5489,
834,
5407,
302,
3274,
96,
519,
121,
3430,
3,
9000,
834,
1161,
3274,
96,
4608,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
Show the number of the dates of transactions if the share count is bigger than 100 or the amount is bigger than 1000, and list by the date_of_transaction in desc. | CREATE TABLE Lots (
lot_id INTEGER,
investor_id INTEGER,
lot_details VARCHAR(255)
)
CREATE TABLE Purchases (
purchase_transaction_id INTEGER,
purchase_details VARCHAR(255)
)
CREATE TABLE Sales (
sales_transaction_id INTEGER,
sales_details VARCHAR(255)
)
CREATE TABLE Ref_Transaction_Types (
transaction_type_code VARCHAR(10),
transaction_type_description VARCHAR(80)
)
CREATE TABLE Investors (
investor_id INTEGER,
Investor_details VARCHAR(255)
)
CREATE TABLE Transactions (
transaction_id INTEGER,
investor_id INTEGER,
transaction_type_code VARCHAR(10),
date_of_transaction DATETIME,
amount_of_transaction DECIMAL(19,4),
share_count VARCHAR(40),
other_details VARCHAR(255)
)
CREATE TABLE Transactions_Lots (
transaction_id INTEGER,
lot_id INTEGER
) | SELECT date_of_transaction, COUNT(date_of_transaction) FROM Transactions WHERE share_count > 100 OR amount_of_transaction > 1000 ORDER BY date_of_transaction DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
14868,
41,
418,
834,
23,
26,
3,
21342,
17966,
6,
12024,
834,
23,
26,
3,
21342,
17966,
6,
418,
834,
221,
5756,
7,
584,
4280,
28027,
599,
25502,
61,
3,
61,
3,
32102,
32103,
32102,
20... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
833,
834,
858,
834,
7031,
4787,
6,
2847,
17161,
599,
5522,
834,
858,
834,
7031,
4787,
61,
21680,
21469,
7,
549,
17444,
427,
698,
834,
13362,
2490,
910,
4674,
866,
834,
858,
834,
7031,
4787,
2490,
5580,
4674,
11300,
... |
Please give me a bar chart to compare the stars by directors, list by the y-axis in desc. | CREATE TABLE Reviewer (
rID int,
name text
)
CREATE TABLE Movie (
mID int,
title text,
year int,
director text
)
CREATE TABLE Rating (
rID int,
mID int,
stars int,
ratingDate date
) | SELECT director, stars FROM Rating AS T1 JOIN Movie AS T2 ON T1.mID = T2.mID ORDER BY stars DESC | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4543,
49,
41,
3,
52,
4309,
16,
17,
6,
564,
1499,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
10743,
41,
3,
51,
4309,
16,
17,
6,
2233,
1499,
6,
215,
16,
17,
6,
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,
2090,
6,
4811,
21680,
21662,
6157,
332,
536,
3,
15355,
3162,
10743,
6157,
332,
357,
9191,
332,
5411,
51,
4309,
3274,
332,
4416,
51,
4309,
4674,
11300,
272,
476,
4811,
309,
25067,
1,
-100,
-100,
-100,
-100,
-100,
-100,... |
Which tier has a division of LEB 2 and Cup Competitions of Copa LEB Plata runner-up? | CREATE TABLE table_name_91 (
tier VARCHAR,
division VARCHAR,
cup_competitions VARCHAR
) | SELECT tier FROM table_name_91 WHERE division = "leb 2" AND cup_competitions = "copa leb plata runner-up" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
4729,
41,
3,
3276,
584,
4280,
28027,
6,
4889,
584,
4280,
28027,
6,
4119,
834,
287,
19427,
2865,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
3,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
3,
3276,
21680,
953,
834,
4350,
834,
4729,
549,
17444,
427,
4889,
3274,
96,
109,
115,
204,
121,
3430,
4119,
834,
287,
19427,
2865,
3274,
96,
10845,
9,
90,
115,
16116,
3,
10806,
18,
413,
121,
1,
-100,
-100,
-100,
-... |
What was the number of viewers in millions for the broadcast from 2010? | CREATE TABLE table_24212608_1 (
viewers__millions_ VARCHAR,
broadcast_date VARCHAR
) | SELECT viewers__millions_ FROM table_24212608_1 WHERE broadcast_date = 2010 | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2266,
2658,
2688,
4018,
834,
536,
41,
13569,
834,
834,
17030,
7,
834,
584,
4280,
28027,
6,
6878,
834,
5522,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
363,
47,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0... | [
3,
23143,
14196,
13569,
834,
834,
17030,
7,
834,
21680,
953,
834,
2266,
2658,
2688,
4018,
834,
536,
549,
17444,
427,
6878,
834,
5522,
3274,
2735,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
How many division title teams were in the division championships 9 times? | CREATE TABLE table_2062 (
"Teams With Division Titles" text,
"Division Championships" real,
"Playoff Berths" real,
"AFC Titles" real,
"Super Bowl Wins" real
) | SELECT COUNT("Teams With Division Titles") FROM table_2062 WHERE "Division Championships" = '9' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
1755,
4056,
41,
96,
18699,
7,
438,
6022,
11029,
7,
121,
1499,
6,
96,
308,
23,
6610,
7666,
7,
121,
490,
6,
96,
15800,
1647,
5653,
189,
7,
121,
490,
6,
96,
188,
5390,
110... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
18699,
7,
438,
6022,
11029,
7,
8512,
21680,
953,
834,
1755,
4056,
549,
17444,
427,
96,
308,
23,
6610,
7666,
7,
121,
3274,
3,
31,
1298,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Bring me the list of patients less than 79 years old who are diagnosed wth human immunodeficiency virus disease. | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.age < "79" AND diagnoses.short_title = "Human immuno virus dis" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
3388,
18206,
3,
15355,
3162,
18730,
7,
9191,
14798,
5,
8399,
51,
834,
23,
26,
3274,
18730,
7,
5,
8399,
51,
834,
23,
26,
5... |
what is the name of the processor for model x33x0? | CREATE TABLE table_24101118_1 (processor VARCHAR, model__list_ VARCHAR) | SELECT processor FROM table_24101118_1 WHERE model__list_ = "X33x0" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
2266,
19621,
20056,
834,
536,
41,
15056,
127,
584,
4280,
28027,
6,
825,
834,
834,
3350,
834,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
125,
19,
8,
564,
13,
8,
75... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
7502,
21680,
953,
834,
2266,
19621,
20056,
834,
536,
549,
17444,
427,
825,
834,
834,
3350,
834,
3274,
96,
4,
4201,
226,
632,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which team's Head Coach is Steve Beever? | CREATE TABLE table_name_68 (
team VARCHAR,
head_coach VARCHAR
) | SELECT team FROM table_name_68 WHERE head_coach = "steve beever" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
3651,
41,
372,
584,
4280,
28027,
6,
819,
834,
509,
1836,
584,
4280,
28027,
3,
61,
3,
32102,
32103,
32101,
32103,
4073,
372,
31,
7,
3642,
9493,
19,
5659,
493,
325... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
372,
21680,
953,
834,
4350,
834,
3651,
549,
17444,
427,
819,
834,
509,
1836,
3274,
96,
849,
162,
36,
3258,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the dates of leaving office for politician from the province of Seville? | CREATE TABLE table_28609 (
"Election number" real,
"Election date" text,
"District" text,
"Province" text,
"Took office" text,
"Left office" text
) | SELECT "Left office" FROM table_28609 WHERE "Province" = 'Seville' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
357,
3840,
4198,
41,
96,
427,
12252,
381,
121,
490,
6,
96,
427,
12252,
833,
121,
1499,
6,
96,
308,
23,
20066,
121,
1499,
6,
96,
3174,
2494,
565,
121,
1499,
6,
96,
3696,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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,
2796,
89,
17,
828,
121,
21680,
953,
834,
357,
3840,
4198,
549,
17444,
427,
96,
3174,
2494,
565,
121,
3274,
3,
31,
134,
15,
1420,
31,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-... |
let me know the marital status and primary disease of patient james cepeda. | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
) | SELECT demographic.marital_status, demographic.diagnosis FROM demographic WHERE demographic.name = "James Cepeda" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4293,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
3,
447,
26,
1298,
834,
4978,
1499,
6,
710,
834,
21869,
1499,
6,
307,
834,
21869,
1499,
3,
61,
3,
32102,
32103... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
14798,
5,
1635,
9538,
834,
8547,
302,
6,
14798,
5,
25930,
4844,
159,
21680,
14798,
549,
17444,
427,
14798,
5,
4350,
3274,
96,
683,
9,
2687,
1064,
3138,
9,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100... |
how many patients are diagnosed with primary disease complete heart block? | CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
) | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "COMPLETE HEART BLOCK" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7690,
41,
1426,
834,
23,
26,
1499,
6,
141,
51,
834,
23,
26,
1499,
6,
2118,
23,
26,
1499,
6,
5059,
715,
1499,
6,
5692,
1499,
6,
701,
834,
15129,
1499,
6,
3783,
1499,
6,
5798,
1499... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
2847,
17161,
599,
15438,
25424,
6227,
14798,
5,
7304,
11827,
834,
23,
26,
61,
21680,
14798,
549,
17444,
427,
14798,
5,
25930,
4844,
159,
3274,
96,
6657,
27872,
3463,
3,
6021,
8241,
272,
5017,
10459,
121,
1,
-100,
-100... |
For those employees who did not have any job in the past, draw a bar chart about the distribution of hire_date and the amount of hire_date bin hire_date by time, and rank by the Y-axis in ascending please. | CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
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 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)
) | SELECT HIRE_DATE, COUNT(HIRE_DATE) FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) ORDER BY COUNT(HIRE_DATE) | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
6266,
41,
4083,
517,
9215,
834,
4309,
7908,
1982,
599,
11116,
632,
201,
4083,
517,
9215,
834,
567,
17683,
3,
4331,
4059,
599,
1828,
61,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
454,
14132,
834,
308,
6048,
6,
2847,
17161,
599,
566,
14132,
834,
308,
6048,
61,
21680,
1652,
549,
17444,
427,
4486,
262,
5244,
5017,
476,
5080,
834,
4309,
3388,
41,
23143,
14196,
262,
5244,
5017,
476,
5080,
834,
4309... |
What is the highest number listed under against when there were less than 3 wins and less than 15 losses? | CREATE TABLE table_75808 (
"Wins" real,
"Byes" real,
"Losses" real,
"Draws" real,
"Against" real
) | SELECT MAX("Against") FROM table_75808 WHERE "Wins" < '3' AND "Losses" < '15' | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
3072,
2079,
927,
41,
96,
18455,
7,
121,
490,
6,
96,
279,
10070,
121,
490,
6,
96,
434,
13526,
7,
121,
490,
6,
96,
308,
10936,
7,
121,
490,
6,
96,
20749,
121,
490,
3,
6... | [
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1... | [
3,
23143,
14196,
4800,
4,
599,
121,
20749,
8512,
21680,
953,
834,
3072,
2079,
927,
549,
17444,
427,
96,
18455,
7,
121,
3,
2,
3,
31,
519,
31,
3430,
96,
434,
13526,
7,
121,
3,
2,
3,
31,
1808,
31,
1,
-100,
-100,
-100,
-100,
-100,... |
What were the high points on May 12? | CREATE TABLE table_name_4 (high_points VARCHAR, date VARCHAR) | SELECT high_points FROM table_name_4 WHERE date = "may 12" | [
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
953,
834,
4350,
834,
591,
41,
6739,
834,
2700,
7,
584,
4280,
28027,
6,
833,
584,
4280,
28027,
61,
3,
32102,
32103,
32101,
32103,
363,
130,
8,
306,
979,
30,
932,
586,
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,
306,
834,
2700,
7,
21680,
953,
834,
4350,
834,
591,
549,
17444,
427,
833,
3274,
96,
13726,
586,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.