instruction stringlengths 0 1.06k | input stringlengths 33 7.14k | response stringlengths 2 4.44k | source stringclasses 25
values | prompt listlengths 1 1 | input_ids listlengths 1 1 | label_ids listlengths 1 1 |
|---|---|---|---|---|---|---|
Which Home team score has a AEDT Time of 11:00 pm? | CREATE TABLE table_name_78 (
home_team VARCHAR,
aedt_time VARCHAR
) | SELECT home_team AS score FROM table_name_78 WHERE aedt_time = "11:00 pm" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the name for the forward in the 2009-2010 season? | CREATE TABLE table_6811 (
"Name" text,
"Position" text,
"Number" text,
"School/Club Team" text,
"Season" text,
"Acquisition via" text
) | SELECT "Name" FROM table_6811 WHERE "Position" = 'forward' AND "Season" = '2009-2010' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What's the smallest pick number of a player playing in Minnesota North Stars? | CREATE TABLE table_1965650_4 (
pick__number INTEGER,
nhl_team VARCHAR
) | SELECT MIN(pick__number) FROM table_1965650_4 WHERE nhl_team = "Minnesota North Stars" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the 20 questions for 8-04 | CREATE TABLE table_1566852_5 (
date VARCHAR
) | SELECT 20 AS _questions FROM table_1566852_5 WHERE date = "8-04" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What was Eduardo Romero's score? | CREATE TABLE table_62192 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text
) | SELECT "Score" FROM table_62192 WHERE "Player" = 'eduardo romero' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
How did the jab tak hai jaan movie gross worldwide? | CREATE TABLE table_58225 (
"Rank" real,
"Movie" text,
"Year" real,
"Worldwide Gross" text,
"Director" text,
"Verdict" text
) | SELECT "Worldwide Gross" FROM table_58225 WHERE "Movie" = 'jab tak hai jaan' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which team had Christoph John as an outgoing manager? | CREATE TABLE table_9272 (
"Team" text,
"Outgoing manager" text,
"Date of vacancy" text,
"Replaced by" text,
"Date of appointment" text
) | SELECT "Team" FROM table_9272 WHERE "Outgoing manager" = 'christoph john' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what 's the cheapest fare for a round trip from INDIANAPOLIS to ORLANDO on 12 27 | CREATE TABLE class_of_service (
booking_class varchar,
rank int,
class_description text
)
CREATE TABLE fare (
fare_id int,
from_airport varchar,
to_airport varchar,
fare_basis_code text,
fare_airline text,
restriction_code text,
one_direction_cost int,
round_trip_cost int,
... | SELECT DISTINCT fare.fare_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, date_day AS DATE_DAY_0, date_day AS DATE_DAY_1, days AS DAYS_0, days AS DAYS_1, fare, fare_basis, flight, flight_fare WHERE ((CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND C... | atis | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what is the number of patients whose gender is f and procedure icd9 code is 8968? | 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,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.gender = "F" AND procedures.icd9_code = "8968" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which goverment had a party of yisrael beiteinu? | CREATE TABLE table_61584 (
"Minister" text,
"Party" text,
"Governments" text,
"Term start" text,
"Term end" text
) | SELECT "Governments" FROM table_61584 WHERE "Party" = 'yisrael beiteinu' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what are the top four most common diagnosis until 2102? | CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wa... | SELECT t1.diagnosisname FROM (SELECT diagnosis.diagnosisname, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM diagnosis WHERE STRFTIME('%y', diagnosis.diagnosistime) <= '2102' GROUP BY diagnosis.diagnosisname) AS t1 WHERE t1.c1 <= 4 | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which Surface has an Opponent of oleksandra kravets? | CREATE TABLE table_name_99 (
surface VARCHAR,
opponent VARCHAR
) | SELECT surface FROM table_name_99 WHERE opponent = "oleksandra kravets" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Most viseted post for each user. | CREATE TABLE PostsWithDeleted (
Id number,
PostTypeId number,
AcceptedAnswerId number,
ParentId number,
CreationDate time,
DeletionDate time,
Score number,
ViewCount number,
Body text,
OwnerUserId number,
OwnerDisplayName text,
LastEditorUserId number,
LastEditorDispl... | SELECT Users.DisplayName, Posts.Title, Posts.ViewCount FROM Users INNER JOIN Posts ON Posts.OwnerUserId = Users.Id WHERE Posts.ViewCount = (SELECT MAX(p.ViewCount) FROM Posts AS p WHERE p.OwnerUserId = Users.Id GROUP BY p.OwnerUserId) ORDER BY ViewCount | sede | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the number of end dates for incidents with incident type code 'NOISE'? Bin by weekday and return a bar chart. | CREATE TABLE Ref_Address_Types (
address_type_code VARCHAR(15),
address_type_description VARCHAR(80)
)
CREATE TABLE Student_Addresses (
student_id INTEGER,
address_id INTEGER,
date_address_from DATETIME,
date_address_to DATETIME,
monthly_rental DECIMAL(19,4),
other_details VARCHAR(255)
... | SELECT date_incident_start, COUNT(date_incident_start) FROM Behavior_Incident WHERE incident_type_code = "NOISE" | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
give me the number of patients whose gender is m and diagnoses short title is emphysema nec? | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.gender = "M" AND diagnoses.short_title = "Emphysema NEC" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Explain to me all the requirements of the CS-LSA degree . | CREATE TABLE student_record (
student_id int,
course_id int,
semester int,
grade varchar,
how varchar,
transfer_source varchar,
earn_credit varchar,
repeat_term varchar,
test_id varchar
)
CREATE TABLE gsi (
course_offering_id int,
student_id int
)
CREATE TABLE semester (
... | SELECT DISTINCT program_requirement.additional_req, program_requirement.category, program_requirement.min_credit, program.name FROM program, program_requirement WHERE program.name LIKE '%CS-LSA%' AND program.program_id = program_requirement.program_id | advising | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What shows as the Diameter (km) when the Diameter (mi) is 5mi? | CREATE TABLE table_name_5 (
diameter__km_ VARCHAR,
diameter__mi_ VARCHAR
) | SELECT diameter__km_ FROM table_name_5 WHERE diameter__mi_ = "5mi" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What was the method of resolution when Katsuhisa Fujii's record was 0-1? | CREATE TABLE table_name_31 (
method VARCHAR,
record VARCHAR
) | SELECT method FROM table_name_31 WHERE record = "0-1" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
When 22 is the tries for what is the lost? | CREATE TABLE table_17941032_1 (
lost VARCHAR,
tries_for VARCHAR
) | SELECT lost FROM table_17941032_1 WHERE tries_for = "22" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what number of patients under procedure icd9 code 4439 had medicare insurance? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.insurance = "Medicare" AND procedures.icd9_code = "4439" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
give me the number of patients whose procedure long title is continuous invasive mechanical ventilation for less than 96 consecutive hours and lab test category is chemistry? | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
C... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE procedures.long_title = "Continuous invasive mechanical ventilation for less than 96 consecutive hours" AND lab."CATEGORY" = "Chemist... | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
get the number of patients with lab test item id 51379 who were admitted in hospital before the year 2178. | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.admityear < "2178" AND lab.itemid = "51379" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Who is the golfer that golfs for Northern Ireland? | CREATE TABLE table_name_54 (
player VARCHAR,
country VARCHAR
) | SELECT player FROM table_name_54 WHERE country = "northern ireland" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how many patients whose death status is 0 and procedure icd9 code is 8872? | 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... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.expire_flag = "0" AND procedures.icd9_code = "8872" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Find the number of the name of the project for which a scientist whose name contains Smith is assigned to. | CREATE TABLE Projects (
Code Char(4),
Name Char(50),
Hours int
)
CREATE TABLE AssignedTo (
Scientist int,
Project char(4)
)
CREATE TABLE Scientists (
SSN int,
Name Char(30)
) | SELECT T2.Name, COUNT(T2.Name) FROM AssignedTo AS T1 JOIN Projects AS T2 ON T1.Project = T2.Code JOIN Scientists AS T3 ON T1.Scientist = T3.SSN WHERE T3.Name LIKE '%Smith%' GROUP BY T2.Name | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the first elected for new york 1 | CREATE TABLE table_1341472_34 (
first_elected VARCHAR,
district VARCHAR
) | SELECT COUNT(first_elected) FROM table_1341472_34 WHERE district = "New York 1" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what are the five most common microbiology tests that patients had within 2 months after receiving colonoscopy the previous year? | CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_ty... | SELECT t3.spec_type_desc FROM (SELECT t2.spec_type_desc, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM (SELECT admissions.subject_id, procedures_icd.charttime FROM procedures_icd JOIN admissions ON procedures_icd.hadm_id = admissions.hadm_id WHERE procedures_icd.icd9_code = (SELECT d_icd_procedures.icd9_code FR... | mimic_iii | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What school did player number 6 come from? | CREATE TABLE table_10015132_1 (
school_club_team VARCHAR,
no VARCHAR
) | SELECT school_club_team FROM table_10015132_1 WHERE no = "6" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
How many points total for san lorenzo? | CREATE TABLE table_19357 (
"Team" text,
"Average" text,
"Points" real,
"Played" real,
"1987-88" text,
"1988-89" text,
"1989-90" real
) | SELECT COUNT("Points") FROM table_19357 WHERE "Team" = 'San Lorenzo' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
How many figures are named for security forces in 1998? | CREATE TABLE table_24520 (
"Period" real,
"Civilians" text,
"Security forces" text,
"Insurgents" text,
"Total per period" real
) | SELECT COUNT("Security forces") FROM table_24520 WHERE "Period" = '1998' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the diameter in km of the feature named Colette Patera? | CREATE TABLE table_16799784_8 (
diameter__km_ VARCHAR,
name VARCHAR
) | SELECT diameter__km_ FROM table_16799784_8 WHERE name = "Colette Patera" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What was the crowd size at the match that had an away team score of 6.8 (44)? | CREATE TABLE table_4802 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT SUM("Crowd") FROM table_4802 WHERE "Away team score" = '6.8 (44)' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the 2008 for 2012 of sf | CREATE TABLE table_37807 (
"Tournament" text,
"2006" text,
"2008" text,
"2009" text,
"2010" text,
"2011" text,
"2012" text,
"2013" text
) | SELECT "2008" FROM table_37807 WHERE "2012" = 'sf' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which report had a circuit of Cagliari? | CREATE TABLE table_12344 (
"Name" text,
"Circuit" text,
"Date" text,
"Winning driver" text,
"Winning constructor" text,
"Report" text
) | SELECT "Report" FROM table_12344 WHERE "Circuit" = 'cagliari' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What's the track for 1982? | CREATE TABLE table_name_18 (
track VARCHAR,
year VARCHAR
) | SELECT track FROM table_name_18 WHERE year = 1982 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is every reference for the example of AF117? | CREATE TABLE table_31424 (
"Prefix class" text,
"Type and usage" text,
"Example" text,
"Equivalent" text,
"Reference" text
) | SELECT "Reference" FROM table_31424 WHERE "Example" = 'AF117' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the original title for the winner and nominees 'Secrets & Lies'? | CREATE TABLE table_54797 (
"Year" text,
"Winner and nominees" text,
"Original title" text,
"Country" text,
"Director" text
) | SELECT "Original title" FROM table_54797 WHERE "Winner and nominees" = 'secrets & lies' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the pick# for the California Golden Seals? | CREATE TABLE table_name_92 (
pick__number VARCHAR,
nhl_team VARCHAR
) | SELECT pick__number FROM table_name_92 WHERE nhl_team = "california golden seals" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is recorded as the lowest Round for the Player Jim Thompson? | CREATE TABLE table_name_26 (
round INTEGER,
player VARCHAR
) | SELECT MIN(round) FROM table_name_26 WHERE player = "jim thompson" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the highest Pick that is wide receiver with overall of 29? | CREATE TABLE table_name_60 (
pick__number INTEGER,
position VARCHAR,
overall VARCHAR
) | SELECT MAX(pick__number) FROM table_name_60 WHERE position = "wide receiver" AND overall = 29 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Find the names of customers who never ordered product Latte. | 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,
activ... | SELECT customer_name FROM customers EXCEPT SELECT t1.customer_name FROM customers AS t1 JOIN customer_orders AS t2 ON t1.customer_id = t2.customer_id JOIN order_items AS t3 ON t2.order_id = t3.order_id JOIN products AS t4 ON t3.product_id = t4.product_id WHERE t4.product_details = 'Latte' | spider | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
How many innings for the player with an average of 30.03? | CREATE TABLE table_30115 (
"Player" text,
"Matches" real,
"Innings" real,
"Wickets" real,
"Average" text,
"BBI" text,
"BBM" text,
"5wi" real
) | SELECT MIN("Innings") FROM table_30115 WHERE "Average" = '30.03' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the courses required for PORTUG 232 ? | CREATE TABLE program (
program_id int,
name varchar,
college varchar,
introduction varchar
)
CREATE TABLE program_requirement (
program_id int,
category varchar,
min_credit int,
additional_req varchar
)
CREATE TABLE student_record (
student_id int,
course_id int,
semester i... | SELECT DISTINCT COURSE_1.department, COURSE_1.name, COURSE_1.number FROM course AS COURSE_0 INNER JOIN course_prerequisite ON COURSE_0.course_id = course_prerequisite.course_id INNER JOIN course AS COURSE_1 ON COURSE_1.course_id = course_prerequisite.pre_course_id WHERE COURSE_0.department = 'PORTUG' AND COURSE_0.numbe... | advising | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Who is the rider for Honda with a grid of 25? | CREATE TABLE table_name_72 (
rider VARCHAR,
manufacturer VARCHAR,
grid VARCHAR
) | SELECT rider FROM table_name_72 WHERE manufacturer = "honda" AND grid = "25" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
How many goals have a Lokomotiv Plovdiv club and goals against larger than 58? | CREATE TABLE table_33104 (
"Position" real,
"Club" text,
"Played" real,
"Wins" real,
"Draws" real,
"Losses" real,
"Goals for" real,
"Goals against" real,
"Points" real,
"Goal Difference" real
) | SELECT COUNT("Goals for") FROM table_33104 WHERE "Club" = 'lokomotiv plovdiv' AND "Goals against" > '58' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
count the number of patients whose discharge location is short term hospital and procedure long title is other endoscopy of small intestine. | 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 (... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.discharge_location = "SHORT TERM HOSPITAL" AND procedures.long_title = "Other endoscopy of small intestine" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which frequency belongs to the cihr-fm call sign? | CREATE TABLE table_7984 (
"Frequency" text,
"Call sign" text,
"Branding" text,
"Format" text,
"Owner" text
) | SELECT "Frequency" FROM table_7984 WHERE "Call sign" = 'cihr-fm' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
When 6th, south division 2 is the mens 1st xi what is the mens 2nd xi? | CREATE TABLE table_21576644_2 (
mens_2nd_xi VARCHAR,
mens_1st_xi VARCHAR
) | SELECT mens_2nd_xi FROM table_21576644_2 WHERE mens_1st_xi = "6th, South Division 2" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Visualize the general trend of the number of planned delivery date over the planned delivery date. | CREATE TABLE Bookings_Services (
Order_ID INTEGER,
Product_ID INTEGER
)
CREATE TABLE Invoices (
Invoice_ID INTEGER,
Order_ID INTEGER,
payment_method_code CHAR(15),
Product_ID INTEGER,
Order_Quantity VARCHAR(288),
Other_Item_Details VARCHAR(255),
Order_Item_ID INTEGER
)
CREATE TABLE... | SELECT Planned_Delivery_Date, COUNT(Planned_Delivery_Date) FROM Bookings | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what television title did she perform in directly after loose women ? | CREATE TABLE table_203_224 (
id number,
"title" text,
"year" number,
"channel" text,
"role" text,
"notes" text
) | SELECT "title" FROM table_203_224 WHERE id = (SELECT id FROM table_203_224 WHERE "title" = 'loose women') + 1 | squall | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what is the part number that has a turbo of low power? | CREATE TABLE table_name_85 (
part_number_s_ VARCHAR,
turbo VARCHAR
) | SELECT part_number_s_ FROM table_name_85 WHERE turbo = "low power" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which Label has a Format of cd, a Country of Japan and a Catalog of vjcp-68403? | CREATE TABLE table_9407 (
"Country" text,
"Date" text,
"Label" text,
"Format" text,
"Catalog" text
) | SELECT "Label" FROM table_9407 WHERE "Format" = 'cd' AND "Country" = 'japan' AND "Catalog" = 'vjcp-68403' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what's the minimum total cost of the hospital that involves a procedure called hormonal therapy (for varices) - vasopressin during this year? | 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,
a... | SELECT MIN(t1.c1) FROM (SELECT SUM(cost.cost) AS c1 FROM cost WHERE cost.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.patientunitstayid IN (SELECT treatment.patientunitstayid FROM treatment WHERE treatment.treatmentname = 'hormonal therapy (for varices) - vasopressin... | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how many patients whose procedure long title is annuloplasty and lab test fluid is cerebrospinal fluid (csf)? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE procedures.long_title = "Annuloplasty" AND lab.fluid = "Cerebrospinal Fluid (CSF)" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what is the record that had a score of 5-3? | CREATE TABLE table_27539272_5 (
record VARCHAR,
score VARCHAR
) | SELECT record FROM table_27539272_5 WHERE score = "5-3" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Of the years that had exactly 17096 departures, what is the greatest number of aircraft kilometers flown? | CREATE TABLE table_105344_2 (
aircraft_kilometers INTEGER,
departures VARCHAR
) | SELECT MAX(aircraft_kilometers) FROM table_105344_2 WHERE departures = 17096 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What are the last names of faculty who are part of the computer science department? | CREATE TABLE gradeconversion (
lettergrade text,
gradepoint number
)
CREATE TABLE student (
stuid number,
lname text,
fname text,
age number,
sex text,
major number,
advisor number,
city_code text
)
CREATE TABLE minor_in (
stuid number,
dno number
)
CREATE TABLE facult... | SELECT T2.lname FROM department AS T1 JOIN faculty AS T2 ON T1.dno = T3.dno JOIN member_of AS T3 ON T2.facid = T3.facid WHERE T1.dname = "Computer Science" | spider | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how much patient 005-66412 has changed in pt last measured on the last hospital visit compared to the first value measured on the last hospital visit? | CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugsto... | SELECT (SELECT lab.labresult FROM lab WHERE lab.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '005-66412' AND NOT patient.hospitaldischargetime IS NULL ORDER BY patient.hospi... | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Is there such a thing as an NEUROSCI 4 -credit course ? | CREATE TABLE course_prerequisite (
pre_course_id int,
course_id int
)
CREATE TABLE area (
course_id int,
area varchar
)
CREATE TABLE semester (
semester_id int,
semester varchar,
year int
)
CREATE TABLE offering_instructor (
offering_instructor_id int,
offering_id int,
instruc... | SELECT DISTINCT name, number FROM course WHERE department = 'NEUROSCI' AND credits = 4 | advising | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how many patients whose diagnoses short title is abn react-procedure nos and lab test fluid is cerebrospinal fluid (csf)? | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE diagnoses.short_title = "Abn react-procedure NOS" AND lab.fluid = "Cerebrospinal Fluid (CSF)" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
when was the first time that patient 15119 had a minimum po2 in 03/2105? | CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
... | SELECT labevents.charttime FROM labevents WHERE labevents.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 15119) AND labevents.itemid IN (SELECT d_labitems.itemid FROM d_labitems WHERE d_labitems.label = 'po2') AND STRFTIME('%y-%m', labevents.charttime) = '2105-03' ORDER BY labevents... | mimic_iii | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
give me the number of patients less than 41 years who are categorized under chemistry lab test. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.age < "41" AND lab."CATEGORY" = "Chemistry" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is re-elected Incumbent Jerry Costello's First elected date? | CREATE TABLE table_name_36 (
first_elected INTEGER,
results VARCHAR,
incumbent VARCHAR
) | SELECT MIN(first_elected) FROM table_name_36 WHERE results = "re-elected" AND incumbent = "jerry costello" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the least week for september 25, 1983 | CREATE TABLE table_14940519_1 (
week INTEGER,
date VARCHAR
) | SELECT MAX(week) FROM table_14940519_1 WHERE date = "September 25, 1983" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
during the last hospital visit how old was patient 86404? | CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE d_items (
row_id number,
... | SELECT admissions.age FROM admissions WHERE admissions.subject_id = 86404 AND NOT admissions.dischtime IS NULL ORDER BY admissions.admittime DESC LIMIT 1 | mimic_iii | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the province with a contestant of tatiana vargas rosales? | CREATE TABLE table_name_43 (
province VARCHAR,
_community VARCHAR,
contestant VARCHAR
) | SELECT province, _community FROM table_name_43 WHERE contestant = "tatiana vargas rosales" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is Date, when Round is '2'? | CREATE TABLE table_name_38 (
date VARCHAR,
round VARCHAR
) | SELECT date FROM table_name_38 WHERE round = 2 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the result of the song 'ride'? | CREATE TABLE table_61560 (
"Draw" real,
"Artist" text,
"Song" text,
"Results" text,
"Place" text
) | SELECT "Results" FROM table_61560 WHERE "Song" = 'ride' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
When did grid 8 finish? | CREATE TABLE table_8491 (
"Name" text,
"Team" text,
"Laps" real,
"Time/Retired" text,
"Grid" real,
"Points" real
) | SELECT "Time/Retired" FROM table_8491 WHERE "Grid" = '8' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the average attendance for the New York Jets? | CREATE TABLE table_40657 (
"Week" real,
"Date" text,
"Opponent" text,
"Result" text,
"Attendance" real
) | SELECT AVG("Attendance") FROM table_40657 WHERE "Opponent" = 'new york jets' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what club is after the sevilla fc ? | CREATE TABLE table_204_256 (
id number,
"position" number,
"club" text,
"played" number,
"points" number,
"wins" number,
"draws" number,
"losses" number,
"goals for" number,
"goals against" number,
"goal difference" number
) | SELECT "club" FROM table_204_256 WHERE "position" = (SELECT "position" FROM table_204_256 WHERE "club" = 'sevilla fc') + 1 | squall | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the most number of leitrim | CREATE TABLE table_1705429_1 (
no INTEGER,
constituency VARCHAR
) | SELECT MAX(no) FROM table_1705429_1 WHERE constituency = "Leitrim" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
which party had only one leader and only a three year office term ? | CREATE TABLE table_201_25 (
id number,
"party" text,
"leader" text,
"from" text,
"to" text
) | SELECT "party" FROM table_201_25 GROUP BY "party" HAVING COUNT("leader") = 1 AND "to" - "from" = 3 | squall | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What kind of decor has the least number of reservations? | CREATE TABLE Rooms (
decor VARCHAR,
RoomId VARCHAR
)
CREATE TABLE Reservations (
Room VARCHAR
) | SELECT T2.decor FROM Reservations AS T1 JOIN Rooms AS T2 ON T1.Room = T2.RoomId GROUP BY T2.decor ORDER BY COUNT(T2.decor) LIMIT 1 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what is the date of vacancy when the date of appointment is 1 january 2009? | CREATE TABLE table_name_54 (
date_of_vacancy VARCHAR,
date_of_appointment VARCHAR
) | SELECT date_of_vacancy FROM table_name_54 WHERE date_of_appointment = "1 january 2009" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the average game that has December 17 as the date? | CREATE TABLE table_name_32 (
game INTEGER,
date VARCHAR
) | SELECT AVG(game) FROM table_name_32 WHERE date = "december 17" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Show all customer ids and the number of accounts for each customer. Show the correlation. | CREATE TABLE Customers (
customer_id INTEGER,
customer_first_name VARCHAR(20),
customer_last_name VARCHAR(20),
customer_address VARCHAR(255),
customer_phone VARCHAR(255),
customer_email VARCHAR(255),
other_customer_details VARCHAR(255)
)
CREATE TABLE Customers_Cards (
card_id INTEGER,
... | SELECT customer_id, COUNT(*) FROM Accounts GROUP BY customer_id | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
provide the number of patients whose age is less than 51 and diagnoses short title is preterm nec 2500+g? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.age < "51" AND diagnoses.short_title = "Preterm NEC 2500+g" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Who is week 3 if week 2 is Nikki Fiction? | CREATE TABLE table_61291 (
"Week 1" text,
"Week 2" text,
"Week 3" text,
"Week 4" text,
"Week 5" text
) | SELECT "Week 3" FROM table_61291 WHERE "Week 2" = 'nikki fiction' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
find the total checkins in Moroccan restaurant in ' Los Angeles | CREATE TABLE user (
uid int,
user_id varchar,
name varchar
)
CREATE TABLE tip (
tip_id int,
business_id varchar,
text longtext,
user_id varchar,
likes int,
year int,
month varchar
)
CREATE TABLE business (
bid int,
business_id varchar,
name varchar,
full_address... | SELECT SUM(checkin.count) FROM business, category AS CATEGORY_0, category AS CATEGORY_1, checkin WHERE business.city = 'Los Angeles' AND CATEGORY_0.business_id = business.business_id AND CATEGORY_0.category_name = 'restaurant' AND CATEGORY_1.business_id = business.business_id AND CATEGORY_1.category_name = 'Moroccan' A... | yelp | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which chassis scored 52 points? | CREATE TABLE table_name_55 (
chassis VARCHAR,
points VARCHAR
) | SELECT chassis FROM table_name_55 WHERE points = 52 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the Romanji title for around40 on TBS? | CREATE TABLE table_66108 (
"Japanese Title" text,
"Romaji Title" text,
"TV Station" text,
"Episodes" real,
"Average Ratings" text
) | SELECT "Romaji Title" FROM table_66108 WHERE "TV Station" = 'tbs' AND "Japanese Title" = 'around40〜注文の多いオンナたち〜' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Name the tournament for 2012 grand slam tournaments | CREATE TABLE table_name_32 (
tournament VARCHAR
) | SELECT tournament FROM table_name_32 WHERE 2012 = "grand slam tournaments" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Who's leading in the general classification in stage 1a? | CREATE TABLE table_12261714_2 (
general_classification VARCHAR,
stage VARCHAR
) | SELECT general_classification FROM table_12261714_2 WHERE stage = "1a" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how many patients have been discharged from the hospital in just since 2100? | CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TA... | SELECT COUNT(DISTINCT patient.uniquepid) FROM patient WHERE NOT patient.hospitaldischargetime IS NULL AND STRFTIME('%y', patient.hospitaldischargetime) >= '2100' | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
show me the flights on friday from NEWARK to TAMPA | CREATE TABLE time_interval (
period text,
begin_time int,
end_time int
)
CREATE TABLE restriction (
restriction_code text,
advance_purchase int,
stopovers text,
saturday_stay_required text,
minimum_stay int,
maximum_stay int,
application text,
no_discounts text
)
CREATE TAB... | SELECT DISTINCT flight.flight_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, date_day, days, flight WHERE (CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'TAMPA' AND date_day.day_number = 25 AND date_day.month_number = 6 AND dat... | atis | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
provide the number of private health insurance patients who have had single internal mammary-coronary artery bypass. | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.insurance = "Private" AND procedures.long_title = "Single internal mammary-coronary artery bypass" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Total number of registered users over time. Shows the total number of registered users for every month since site inception. | CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
CREATE TABLE Posts (
Id number,
PostTypeId number,
AcceptedAnswer... | WITH c AS (SELECT TIME_TO_STR(CreationDate, '%Y') AS Year, TIME_TO_STR(CreationDate, '%m') AS Month, TIME_TO_STR(CreationDate, '%d') AS Day FROM Users), d AS (SELECT Year, Month, Day, COUNT(*) OVER (PARTITION BY Year, Month, Day) AS Count FROM c), e AS (SELECT Year, Month, Day, Count FROM d GROUP BY Year, Month, Day, C... | sede | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
In how many different games did Roy Hibbert (16) did the most high rebounds? | CREATE TABLE table_27756164_2 (
game VARCHAR,
high_rebounds VARCHAR
) | SELECT COUNT(game) FROM table_27756164_2 WHERE high_rebounds = "Roy Hibbert (16)" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What is the smallest round with a time of 1:12? | CREATE TABLE table_44953 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" real,
"Time" text,
"Location" text
) | SELECT MIN("Round") FROM table_44953 WHERE "Time" = '1:12' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Which positions were in Toronto in 2004? | CREATE TABLE table_15876 (
"Player" text,
"No." text,
"Nationality" text,
"Position" text,
"Years in Toronto" text,
"School/Club Team" text
) | SELECT "Position" FROM table_15876 WHERE "Years in Toronto" = '2004' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-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, give me the comparison about the average of employee_id over the hire_date bin hire_date by weekday by a bar chart, could you sort by the y axis from low to high please? | 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 departments (
DEPARTMENT_ID decimal... | SELECT HIRE_DATE, AVG(EMPLOYEE_ID) FROM employees WHERE SALARY BETWEEN 8000 AND 12000 AND COMMISSION_PCT <> "null" OR DEPARTMENT_ID <> 40 ORDER BY AVG(EMPLOYEE_ID) | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Who was the high rebound for the high assists of d. j. augustin (8)? | CREATE TABLE table_21196 (
"Game" real,
"Date" text,
"Team" text,
"Score" text,
"High points" text,
"High rebounds" text,
"High assists" text,
"Location Attendance" text,
"Record" text
) | SELECT "High rebounds" FROM table_21196 WHERE "High assists" = 'D. J. Augustin (8)' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Find the first name of the band mate that has performed in most songs. | CREATE TABLE Songs (
SongId VARCHAR
)
CREATE TABLE Band (
firstname VARCHAR,
id VARCHAR
)
CREATE TABLE Performance (
bandmate VARCHAR
) | SELECT t2.firstname FROM Performance AS t1 JOIN Band AS t2 ON t1.bandmate = t2.id JOIN Songs AS T3 ON T3.SongId = T1.SongId GROUP BY firstname ORDER BY COUNT(*) DESC LIMIT 1 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how many patients have received a phenobarbital test? | CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREAT... | SELECT COUNT(DISTINCT patient.uniquepid) FROM patient WHERE patient.patientunitstayid IN (SELECT lab.patientunitstayid FROM lab WHERE lab.labname = 'phenobarbital') | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what is the top five most frequent output events in this year? | CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
sy... | SELECT t1.celllabel FROM (SELECT intakeoutput.celllabel, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM intakeoutput WHERE intakeoutput.cellpath LIKE '%output%' AND DATETIME(intakeoutput.intakeoutputtime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-0 year') GROUP BY intakeoutput.celllabel) AS ... | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
how many bosnian in cook islands is macedonian | CREATE TABLE table_27112 (
"Afghan" text,
"Albanian" text,
"Arabic" text,
"Bangladeshi" text,
"Bosnian" text,
"Chinese" text,
"Colombian" text,
"Cook Islands" text
) | SELECT COUNT("Cook Islands") FROM table_27112 WHERE "Bosnian" = 'Macedonian' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Who had the high assist total when the team was 0-1? | CREATE TABLE table_27902171_4 (
high_assists VARCHAR,
record VARCHAR
) | SELECT high_assists FROM table_27902171_4 WHERE record = "0-1" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
What are the countries of perpetrators? Show each country and the corresponding number of perpetrators there Plot them as bar chart, and rank by the x-axis from high to low. | CREATE TABLE people (
People_ID int,
Name text,
Height real,
Weight real,
"Home Town" text
)
CREATE TABLE perpetrator (
Perpetrator_ID int,
People_ID int,
Date text,
Year real,
Location text,
Country text,
Killed int,
Injured int
) | SELECT Country, COUNT(*) FROM perpetrator GROUP BY Country ORDER BY Country DESC | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
what are the top four most frequent diagnoses among patients of age 20s until 4 years ago? | CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,... | SELECT d_icd_diagnoses.short_title FROM d_icd_diagnoses WHERE d_icd_diagnoses.icd9_code IN (SELECT t1.icd9_code FROM (SELECT diagnoses_icd.icd9_code, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM diagnoses_icd WHERE diagnoses_icd.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.age BETWEEN... | mimic_iii | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-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,
-100,
-100,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.