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 |
|---|---|---|---|---|---|---|
Visualize a bar chart about the distribution of meter_600 and ID , and order by the bars in asc. | CREATE TABLE record (
ID int,
Result text,
Swimmer_ID int,
Event_ID int
)
CREATE TABLE stadium (
ID int,
name text,
Capacity int,
City text,
Country text,
Opening_year int
)
CREATE TABLE event (
ID int,
Name text,
Stadium_ID int,
Year text
)
CREATE TABLE swimme... | SELECT meter_600, ID FROM swimmer ORDER BY meter_600 | 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,
... |
indicate the monthly minimum amount of arterial bp [systolic] for patient 25814 since 61 days ago. | CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
... | SELECT MIN(chartevents.valuenum) FROM chartevents WHERE chartevents.icustay_id IN (SELECT icustays.icustay_id FROM icustays WHERE icustays.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 25814)) AND chartevents.itemid IN (SELECT d_items.itemid FROM d_items WHERE d_items.label = 'arte... | 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,
... |
Find the number of students living in each city with a bar chart, and display by the Y-axis from high to low please. | CREATE TABLE Dorm_amenity (
amenid INTEGER,
amenity_name VARCHAR(25)
)
CREATE TABLE Student (
StuID INTEGER,
LName VARCHAR(12),
Fname VARCHAR(12),
Age INTEGER,
Sex VARCHAR(1),
Major INTEGER,
Advisor INTEGER,
city_code VARCHAR(3)
)
CREATE TABLE Lives_in (
stuid INTEGER,
... | SELECT city_code, COUNT(*) FROM Student GROUP BY city_code ORDER BY COUNT(*) 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,
... |
Show the transaction type descriptions and dates if the share count is smaller than 10. | CREATE TABLE Ref_Transaction_Types (
transaction_type_description VARCHAR,
transaction_type_code VARCHAR
)
CREATE TABLE TRANSACTIONS (
date_of_transaction VARCHAR,
transaction_type_code VARCHAR,
share_count INTEGER
) | SELECT T1.transaction_type_description, T2.date_of_transaction FROM Ref_Transaction_Types AS T1 JOIN TRANSACTIONS AS T2 ON T1.transaction_type_code = T2.transaction_type_code WHERE T2.share_count < 10 | 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's the 2nd leg result in the round where Panionios is team #2? | CREATE TABLE table_22824 (
"Team #1" text,
"Agg. score" text,
"Team #2" text,
"1st leg" text,
"2nd leg" text
) | SELECT "2nd leg" FROM table_22824 WHERE "Team #2" = 'Panionios' | 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 drug type and drug route of drug code soln2? | 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 prescriptions.drug_type, prescriptions.route FROM prescriptions WHERE prescriptions.formulary_drug_cd = "SOLN2" | 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 location when the designer is glen peloso and the restaurant is joe boo's cookoos? | CREATE TABLE table_63664 (
"Restaurant Name" text,
"Original Name" text,
"Location" text,
"Chef" text,
"Designer" text,
"Still Open?" text
) | SELECT "Location" FROM table_63664 WHERE "Designer" = 'glen peloso' AND "Restaurant Name" = 'joe boo''s cookoos' | 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 number of rooms for each bed type Visualize by bar chart, and I want to show in descending by the y axis. | CREATE TABLE Reservations (
Code INTEGER,
Room TEXT,
CheckIn TEXT,
CheckOut TEXT,
Rate REAL,
LastName TEXT,
FirstName TEXT,
Adults INTEGER,
Kids INTEGER
)
CREATE TABLE Rooms (
RoomId TEXT,
roomName TEXT,
beds INTEGER,
bedType TEXT,
maxOccupancy INTEGER,
baseP... | SELECT bedType, COUNT(*) FROM Rooms GROUP BY bedType ORDER BY COUNT(*) 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,
... |
Which entrant scored less than 8 points and used a Maserati chassis? | CREATE TABLE table_70593 (
"Year" real,
"Entrant" text,
"Chassis" text,
"Engine" text,
"Points" real
) | SELECT "Entrant" FROM table_70593 WHERE "Points" < '8' AND "Chassis" = 'maserati' | 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 average zone for waddon railway station and has more than 2 platforms | CREATE TABLE table_name_54 (
zone INTEGER,
stations VARCHAR,
platforms VARCHAR
) | SELECT AVG(zone) FROM table_name_54 WHERE stations = "waddon railway station" AND platforms > 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 average age of patients whose insurance is government and days of hospital stay is 1? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
... | SELECT AVG(demographic.age) FROM demographic WHERE demographic.insurance = "Government" AND demographic.days_stay = "1" | 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 Location when the time was 11:55? | CREATE TABLE table_name_22 (
location VARCHAR,
time VARCHAR
) | SELECT location FROM table_name_22 WHERE time = "11:55" | 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 rebounds did Tammy Sutton-Brown have? | CREATE TABLE table_25353861_5 (
rebounds VARCHAR,
player VARCHAR
) | SELECT rebounds FROM table_25353861_5 WHERE player = "Tammy Sutton-Brown" | 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 the name and number of employees for the departments managed by heads whose temporary acting value is 'Yes'? | CREATE TABLE department (
name VARCHAR,
num_employees VARCHAR,
department_id VARCHAR
)
CREATE TABLE management (
department_id VARCHAR,
temporary_acting VARCHAR
) | SELECT T1.name, T1.num_employees FROM department AS T1 JOIN management AS T2 ON T1.department_id = T2.department_id WHERE T2.temporary_acting = 'Yes' | 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 admission location and diagnosis short title of Dominga Garvin? | 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 demographic.admission_location, diagnoses.short_title FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Dominga Garvin" | 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 all the songs that do not have a lead vocal. | CREATE TABLE vocals (
songid VARCHAR
)
CREATE TABLE songs (
title VARCHAR,
songid VARCHAR
) | SELECT DISTINCT title FROM vocals AS t1 JOIN songs AS t2 ON t1.songid = t2.songid EXCEPT SELECT t2.title FROM vocals AS t1 JOIN songs AS t2 ON t1.songid = t2.songid WHERE TYPE = "lead" | 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 2010/ 11 has a 2011/ 12 of former non-ranking tournaments? | CREATE TABLE table_62376 (
"1999/ 00" text,
"2000/ 01" text,
"2001/ 02" text,
"2002/ 03" text,
"2003/ 04" text,
"2004/ 05" text,
"2005/ 06" text,
"2006/ 07" text,
"2007/ 08" text,
"2008/ 09" text,
"2009/ 10" text,
"2010/ 11" text,
"2011/ 12" text,
"2012/ 13" text
... | SELECT "2010/ 11" FROM table_62376 WHERE "2011/ 12" = 'former non-ranking tournaments' | 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 virtue is acedia(Latin)? | CREATE TABLE table_36358 (
"Virtue" text,
"Latin" text,
"Gloss" text,
"(Vice)" text,
"(Latin)" text
) | SELECT "Virtue" FROM table_36358 WHERE "(Latin)" = 'acedia' | 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 was the home team's score at Corio Oval? | CREATE TABLE table_name_20 (
home_team VARCHAR,
venue VARCHAR
) | SELECT home_team AS score FROM table_name_20 WHERE venue = "corio oval" | 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 Grid has a Driver of cristiano da matta, and Points smaller than 33? | CREATE TABLE table_5157 (
"Driver" text,
"Team" text,
"Laps" real,
"Time/Retired" text,
"Grid" real,
"Points" real
) | SELECT SUM("Grid") FROM table_5157 WHERE "Driver" = 'cristiano da matta' AND "Points" < '33' | 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 married patients have left internal jugular vein thrombosis left arm edema as their primary disease? | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.marital_status = "MARRIED" AND demographic.diagnosis = "LEFT INTERNAL JUGULAR VEIN THROMBOSIS;LEFT ARM EDEMA" | 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,
... |
Emacs users in Frederick, MD. | CREATE TABLE PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE SuggestedEdits (
Id number,
PostId number,
CreationDate time,
ApprovalDa... | SELECT * FROM Users WHERE Location LIKE '%Frederick, MD%' ORDER BY Reputation DESC | 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 match total for a score over 299 and under 412 innings? | CREATE TABLE table_71853 (
"Matches" real,
"Innings" real,
"Not Out" real,
"High Score" text,
"Runs" real,
"Average" real
) | SELECT SUM("Matches") FROM table_71853 WHERE "High Score" = '299' AND "Innings" < '412' | 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 two destinations were available for less than one year ? | CREATE TABLE table_203_323 (
id number,
"city" text,
"country" text,
"airport" text,
"begin" number,
"end" number
) | SELECT "city" FROM table_203_323 WHERE "end" - "begin" < 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 1st party with Charles Isaac Elton as the 2nd member? | CREATE TABLE table_71438 (
"Election" text,
"1st Member" text,
"1st Party" text,
"2nd Member" text,
"2nd Party" text
) | SELECT "1st Party" FROM table_71438 WHERE "2nd Member" = 'charles isaac elton' | 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 year is the event in athens, greece? | CREATE TABLE table_11121 (
"Year" real,
"Tournament" text,
"Venue" text,
"Result" text,
"Extra" text
) | SELECT MAX("Year") FROM table_11121 WHERE "Venue" = 'athens, greece' | 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 seats for 2001 is greater than 15 and % 2001 is greater than 100, what is the % 2006? | CREATE TABLE table_70957 (
"Parties and voter communities" text,
"% 2006" real,
"seats 2006" real,
"% 2001" real,
"seats 2001" real
) | SELECT AVG("% 2006") FROM table_70957 WHERE "seats 2001" > '15' AND "% 2001" > '100' | 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 Round, when Tournament is 'Paris'? | CREATE TABLE table_name_61 (
round VARCHAR,
tournament VARCHAR
) | SELECT round FROM table_name_61 WHERE tournament = "paris" | 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 Answers My Questions? (Tutorial). | CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE SuggestedEdits (
Id number,
... | SELECT a.Id AS "post_link", a.Score, au.Id AS "user_link" FROM Posts AS p JOIN Posts AS a ON p.Id = a.ParentId JOIN Users AS au ON a.OwnerUserId = au.Id WHERE p.PostTypeId = 1 AND p.OwnerUserId = '##UserId##' ORDER BY a.Score DESC | 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,
... |
For all employees who have the letters D or S in their first name, draw a bar chart about the distribution of job_id and the sum of employee_id , and group by attribute job_id, and order total number from low to high order please. | CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
CO... | SELECT JOB_ID, SUM(EMPLOYEE_ID) FROM employees WHERE FIRST_NAME LIKE '%D%' OR FIRST_NAME LIKE '%S%' GROUP BY JOB_ID ORDER BY SUM(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,
... |
What number does the player from Ohio play with? | CREATE TABLE table_11545282_10 (
no VARCHAR,
school_club_team VARCHAR
) | SELECT no FROM table_11545282_10 WHERE school_club_team = "Ohio" | 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 for the tournament jou -l s-tours? | CREATE TABLE table_13951 (
"Date" text,
"Tournament" text,
"Surface" text,
"Opponent in the final" text,
"Score" text
) | SELECT "Date" FROM table_13951 WHERE "Tournament" = 'joué-lès-tours' | 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 intelligence os the one that has s , 'thought'? | CREATE TABLE table_2150 (
"Shekhina:" text,
"Reason" text,
"Mind" text,
"Intelligence" text,
"Thought" text,
"Understanding" text
) | SELECT "Intelligence" FROM table_2150 WHERE "Thought" = '思 sī, "thought' | 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,
... |
If the goals scored were below 6, 11 games were played, and there were 7 assists, what's the sum of points with games meeting these criteria? | CREATE TABLE table_name_78 (
points INTEGER,
goals VARCHAR,
assists VARCHAR,
games VARCHAR
) | SELECT SUM(points) FROM table_name_78 WHERE assists = 7 AND games = 11 AND goals < 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,
... |
What Rider had a Speed of 108.347mph and Time of 1:02.40.93? | CREATE TABLE table_name_12 (
rider VARCHAR,
speed VARCHAR,
time VARCHAR
) | SELECT rider FROM table_name_12 WHERE speed = "108.347mph" AND time = "1:02.40.93" | 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,
... |
For all employees who have the letters D or S in their first name, give me the comparison about the sum of salary over the hire_date bin hire_date by weekday. | CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
... | SELECT HIRE_DATE, SUM(SALARY) FROM employees WHERE FIRST_NAME LIKE '%D%' OR FIRST_NAME LIKE '%S%' | 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,
... |
when's the first time patient 1902's heart rate was measured or taken today? | CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE ... | SELECT chartevents.charttime FROM chartevents WHERE chartevents.icustay_id IN (SELECT icustays.icustay_id FROM icustays WHERE icustays.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 1902)) AND chartevents.itemid IN (SELECT d_items.itemid FROM d_items WHERE d_items.label = 'heart rat... | 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,
... |
For those employees who did not have any job in the past, draw a bar chart about the distribution of hire_date and the sum of salary bin hire_date by time, order from low to high by the Y. | CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE... | SELECT HIRE_DATE, SUM(SALARY) FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) ORDER BY SUM(SALARY) | 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 locomotive built after 1895 has the highest SLM number? | CREATE TABLE table_name_26 (
SLM INTEGER,
built INTEGER
) | SELECT MAX(SLM) AS number FROM table_name_26 WHERE built > 1895 | 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 round when the match was against sergis kyratzis? | CREATE TABLE table_name_21 (
round VARCHAR,
opponent VARCHAR
) | SELECT round FROM table_name_21 WHERE opponent = "sergis kyratzis" | 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,
... |
Draw a bar chart about the distribution of ACC_Road and the sum of School_ID , and group by attribute ACC_Road, show from low to high by the bar please. | CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
CREATE TABLE university (
Scho... | SELECT ACC_Road, SUM(School_ID) FROM basketball_match GROUP BY ACC_Road ORDER BY ACC_Road | 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 Time of broadcast has a Picture format of 4:3, and Hours of 20:30, and Days of the week of monday, wednesday, friday? | CREATE TABLE table_name_23 (
time_of_broadcast VARCHAR,
days_of_the_week VARCHAR,
picture_format VARCHAR,
hours VARCHAR
) | SELECT time_of_broadcast FROM table_name_23 WHERE picture_format = "4:3" AND hours = "20:30" AND days_of_the_week = "monday, wednesday, friday" | 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,
... |
a FIRST class flight on AA to SAN FRANCISCO on tuesday in the next week | CREATE TABLE aircraft (
aircraft_code varchar,
aircraft_description varchar,
manufacturer varchar,
basic_type varchar,
engines int,
propulsion varchar,
wide_body varchar,
wing_span int,
length int,
weight int,
capacity int,
pay_load int,
cruising_speed int,
range_... | SELECT DISTINCT flight.flight_id FROM airport_service, city, date_day AS DATE_DAY_0, date_day AS DATE_DAY_1, days AS DAYS_0, days AS DAYS_1, fare, fare_basis AS FARE_BASIS_0, fare_basis AS FARE_BASIS_1, flight, flight_fare WHERE ((DATE_DAY_0.day_number = 22 AND DATE_DAY_0.month_number = 3 AND DATE_DAY_0.year = 1991 AND... | 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,
... |
how many total international races did german silva place in the top 3 spots ? | CREATE TABLE table_203_245 (
id number,
"year" number,
"competition" text,
"venue" text,
"position" text,
"event" text,
"notes" text
) | SELECT COUNT("competition") FROM table_203_245 WHERE "position" <= 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,
... |
Vote comments on user posts. | 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 *, 'http://stackoverflow.com/questions/' + QuestionId + '/#comment' + CommentId + '_' + QuestionId AS Url FROM (SELECT COALESCE(Q.Title, Posts.Title) AS Question, Comments.UserDisplayName AS Commenter, Text AS Comment, Posts.OwnerDisplayName AS Poster, PostTypes.Name AS "post_type", Posts.CreationDate, CAST(Comm... | 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,
... |
Which Rank by average is the lowest one that has a Total of 425, and a Place larger than 1? | CREATE TABLE table_name_54 (
rank_by_average INTEGER,
total VARCHAR,
place VARCHAR
) | SELECT MIN(rank_by_average) FROM table_name_54 WHERE total = 425 AND place > 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 termini does the route with a population Area of aguilares have? | CREATE TABLE table_name_40 (
termini VARCHAR,
population_area VARCHAR
) | SELECT termini FROM table_name_40 WHERE population_area = "aguilares" | 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 total number of bronze medals won by france ? | CREATE TABLE table_204_311 (
id number,
"rank" number,
"nation" text,
"gold" number,
"silver" number,
"bronze" number,
"total" number
) | SELECT "bronze" FROM table_204_311 WHERE "nation" = 'france' | 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,
... |
Regarding players before 2000, what is the USC player's position? | CREATE TABLE table_55461 (
"Year" real,
"Player" text,
"Position" text,
"College/Country" text,
"WNBA Team" text
) | SELECT "Position" FROM table_55461 WHERE "Year" < '2000' AND "College/Country" = 'usc' | 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 stadiums have a capacity between 6000 and 8000 ? | CREATE TABLE table_203_420 (
id number,
"#" number,
"stadium" text,
"capacity" number,
"city" text,
"home team" text
) | SELECT COUNT("stadium") FROM table_203_420 WHERE "capacity" >= 6000 AND "capacity" <= 8000 | 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,
... |
i need to fly from NASHVILLE to TACOMA first thing in the morning what is there | CREATE TABLE days (
days_code varchar,
day_name varchar
)
CREATE TABLE fare_basis (
fare_basis_code text,
booking_class text,
class_type text,
premium text,
economy text,
discounted text,
night text,
season text,
basis_days text
)
CREATE TABLE equipment_sequence (
aircr... | 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, flight WHERE ((CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'NASHVILLE' AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'TA... | 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,
... |
when was the episode on which barbara windsor and heston blumenthal guest starred broadcasted | CREATE TABLE table_29135051_3 (
broadcast_date VARCHAR,
guest_s_ VARCHAR
) | SELECT broadcast_date FROM table_29135051_3 WHERE guest_s_ = "Barbara Windsor and Heston Blumenthal" | 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 year with a kurtis kraft 500a chassis? | CREATE TABLE table_71618 (
"Year" real,
"Entrant" text,
"Chassis" text,
"Engine" text,
"Points" real
) | SELECT SUM("Year") FROM table_71618 WHERE "Chassis" = 'kurtis kraft 500a' | 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 series occurred when the 7800 was 5040.00? | CREATE TABLE table_2544694_3 (
indonesia_super_series_2008 VARCHAR
) | SELECT indonesia_super_series_2008 FROM table_2544694_3 WHERE 780000 = "5040.00" | 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 Thermodynamics and Kinetics courses are worth 9 credits ? | CREATE TABLE ta (
campus_job_id int,
student_id int,
location varchar
)
CREATE TABLE course_prerequisite (
pre_course_id int,
course_id int
)
CREATE TABLE jobs (
job_id int,
job_title varchar,
description varchar,
requirement varchar,
city varchar,
state varchar,
countr... | SELECT DISTINCT department, name, number FROM course WHERE (description LIKE '%Thermodynamics and Kinetics%' OR name LIKE '%Thermodynamics and Kinetics%') AND credits = 9 | 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 is the tally when the opposition is Derry, and total is 14? | CREATE TABLE table_name_12 (
tally VARCHAR,
opposition VARCHAR,
total VARCHAR
) | SELECT tally FROM table_name_12 WHERE opposition = "derry" AND total = 14 | 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 opponent has a Time of 1:34? | CREATE TABLE table_71198 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" real,
"Time" text,
"Location" text
) | SELECT "Opponent" FROM table_71198 WHERE "Time" = '1:34' | 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,
... |
TOP 50 users from Michigan. Lists the top 50 users (ranked by reputation) that are located in Calicut/Kozhikode, Kerala, India according to their profile information.
Thanks to http://data.stackexchange.com/stackoverflow/qe/1157/top-100-users-from-greece | 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 Id, DisplayName, Reputation, WebsiteUrl, Location FROM Users WHERE Location LIKE '%Michigan%' ORDER BY Reputation DESC LIMIT 150 | 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,
... |
give me the number of patients who had endoscopic excision or destruction of lesion or tissue of stomach and were hospitalized for more than 13 days. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.days_stay > "13" AND procedures.short_title = "Endosc destr stomach les" | 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 race caller when jim mckay and al michaels were s hosts in the year 1987? | CREATE TABLE table_25080 (
"Year" real,
"Network" text,
"Race caller" text,
"s Host" text,
"s Analyst" text,
"Reporters" text,
"Trophy presentation" text
) | SELECT "Race caller" FROM table_25080 WHERE "s Host" = 'Jim McKay and Al Michaels' AND "Year" = '1987' | 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,
... |
list names of all departments ordered by their names. | CREATE TABLE department (
dept_name VARCHAR
) | SELECT dept_name FROM department ORDER BY dept_name | 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 grid when the time/retired is +27.112? | CREATE TABLE table_name_79 (
grid VARCHAR,
time_retired VARCHAR
) | SELECT grid FROM table_name_79 WHERE time_retired = "+27.112" | 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,
... |
among the patients of age 40s a year before, what was the top three most frequent procedure? | CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE intakeoutput (
intakeoutputid numb... | SELECT t1.treatmentname FROM (SELECT treatment.treatmentname, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM treatment WHERE treatment.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.age BETWEEN 40 AND 49) AND DATETIME(treatment.treatmenttime, 'start of year') = DATETIME(CURRENT... | 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,
... |
Who was the visitor at the pittsburgh penguins at 7:00 pm that had a record of 0-2-2? | CREATE TABLE table_39669 (
"Date" text,
"Time" text,
"Visitor" text,
"Score" text,
"Home" text,
"Location/Attendance" text,
"Record" text
) | SELECT "Visitor" FROM table_39669 WHERE "Home" = 'pittsburgh penguins' AND "Time" = '7:00 pm' AND "Record" = '0-2-2' | 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 was the score of the game on November 22? | CREATE TABLE table_name_8 (
result VARCHAR,
date VARCHAR
) | SELECT result FROM table_name_8 WHERE date = "november 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,
... |
who was the lead vocalist in sweat it out ? | CREATE TABLE table_203_629 (
id number,
"year" number,
"title" text,
"lead vocalist" text,
"aria chart position" number,
"album" text
) | SELECT "lead vocalist" FROM table_203_629 WHERE "title" = '"sweat it out"' | 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,
... |
Who was the partner that played against Serena Williams Venus Williams? | CREATE TABLE table_name_94 (
partner VARCHAR,
opponents_in_the_final VARCHAR
) | SELECT partner FROM table_name_94 WHERE opponents_in_the_final = "serena williams venus williams" | 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 one is easier EECS 532 or EECS 481 ? | CREATE TABLE course_offering (
offering_id int,
course_id int,
semester int,
section_number int,
start_time time,
end_time time,
monday varchar,
tuesday varchar,
wednesday varchar,
thursday varchar,
friday varchar,
saturday varchar,
sunday varchar,
has_final_proje... | SELECT DISTINCT course.number FROM course INNER JOIN program_course ON program_course.course_id = course.course_id WHERE (course.number = 532 OR course.number = 481) AND program_course.workload = (SELECT MIN(PROGRAM_COURSEalias1.workload) FROM program_course AS PROGRAM_COURSEalias1 INNER JOIN course AS COURSEalias1 ON ... | 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 was the title of the episode with a production code of 1gowo04? | CREATE TABLE table_name_3 (
episode_title VARCHAR,
prod_code VARCHAR
) | SELECT episode_title FROM table_name_3 WHERE prod_code = "1gowo04" | 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's the opening when white is Anand with fewer than 61 moves for a result of ? | CREATE TABLE table_name_83 (
opening VARCHAR,
result VARCHAR,
white VARCHAR,
moves VARCHAR
) | SELECT opening FROM table_name_83 WHERE white = "anand" AND moves < 61 AND result = "½–½" | 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,
... |
List the number of items by the details of the organization that owns it using a bar chart, rank in ascending by the organization_details. | CREATE TABLE Residents_Services (
resident_id INTEGER,
service_id INTEGER,
date_moved_in DATETIME,
property_id INTEGER,
date_requested DATETIME,
date_provided DATETIME,
other_details VARCHAR(255)
)
CREATE TABLE Timed_Locations_of_Things (
thing_id INTEGER,
Date_and_Time DATETIME,
... | SELECT organization_details, COUNT(organization_details) FROM Things AS T1 JOIN Organizations AS T2 ON T1.organization_id = T2.organization_id GROUP BY organization_details ORDER BY organization_details | 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 is the name of the shop that has the most different kinds of devices in stock? | CREATE TABLE stock (
shop_id number,
device_id number,
quantity number
)
CREATE TABLE device (
device_id number,
device text,
carrier text,
package_version text,
applications text,
software_platform text
)
CREATE TABLE shop (
shop_id number,
shop_name text,
location tex... | SELECT T2.shop_name FROM stock AS T1 JOIN shop AS T2 ON T1.shop_id = T2.shop_id GROUP BY T1.shop_id ORDER BY COUNT(*) DESC LIMIT 1 | 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,
... |
Who did he fight in Rumble of the Kings 6? | CREATE TABLE table_4985 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" real,
"Time" text,
"Location" text
) | SELECT "Opponent" FROM table_4985 WHERE "Event" = 'rumble of the kings 6' | 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,
... |
get me the number of patients born before 2107 who have coronary artery primary disease. | 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 WHERE demographic.diagnosis = "CORONARY ARTERY DISEASE" AND demographic.dob_year < "2107" | 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 film title used for nomination with the original title sedamdeset i dva dana? | CREATE TABLE table_name_65 (
film_title_used_in_nomination VARCHAR,
original_title VARCHAR
) | SELECT film_title_used_in_nomination FROM table_name_65 WHERE original_title = "sedamdeset i dva dana" | 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,
... |
Top 10 Users from. | CREATE TABLE CloseAsOffTopicReasonTypes (
Id number,
IsUniversal boolean,
InputTitle text,
MarkdownInputGuidance text,
MarkdownPostOwnerGuidance text,
MarkdownPrivilegedUserGuidance text,
MarkdownConcensusDescription text,
CreationDate time,
CreationModeratorId number,
ApprovalDa... | SELECT Id, DisplayName, Reputation FROM Users ORDER BY Reputation DESC LIMIT 10 | 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,
... |
Name the season for august 16, 2010 | CREATE TABLE table_2140071_10 (
season VARCHAR,
premier_date VARCHAR
) | SELECT season FROM table_2140071_10 WHERE premier_date = "August 16, 2010" | 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 Played has a Lost smaller than 3, and a Drawn smaller than 0? | CREATE TABLE table_name_13 (
played INTEGER,
lost VARCHAR,
drawn VARCHAR
) | SELECT AVG(played) FROM table_name_13 WHERE lost < 3 AND drawn < 0 | 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 First Pref Votes for the % FPv of 0.06? | CREATE TABLE table_9516 (
"Party" text,
"Leader" text,
"Seats" text,
"% of seats" text,
"First Pref votes" text,
"% FPv" text
) | SELECT "First Pref votes" FROM table_9516 WHERE "% FPv" = '0.06' | 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 was the value in 1989 with QF in 1997 and A in 1993? | CREATE TABLE table_77106 (
"Tournament" text,
"1989" text,
"1990" text,
"1991" text,
"1992" text,
"1993" text,
"1994" text,
"1995" text,
"1996" text,
"1997" text,
"1998" text,
"1999" text,
"2000" text,
"2001" text,
"2002" text,
"2003" text,
"Career SR"... | SELECT "1989" FROM table_77106 WHERE "1997" = 'qf' AND "1993" = 'a' | 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 difficult on average are the PreMajor classes ? | CREATE TABLE program_course (
program_id int,
course_id int,
workload int,
category varchar
)
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,
tes... | SELECT AVG(workload) FROM program_course WHERE category LIKE '%PreMajor%' | 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 orders in each day? Return a bar chart to show. | CREATE TABLE Customers (
customer_id INTEGER,
payment_method VARCHAR(15),
customer_name VARCHAR(80),
date_became_customer DATETIME,
other_customer_details VARCHAR(255)
)
CREATE TABLE Customer_Orders (
order_id INTEGER,
customer_id INTEGER,
order_status VARCHAR(15),
order_date DATETI... | SELECT order_date, COUNT(order_date) FROM Customers AS t1 JOIN Customer_Orders AS t2 ON t1.customer_id = t2.customer_id WHERE order_status = "Delivered" | 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 is the athlete muna lee lowest time? | CREATE TABLE table_name_45 (
time INTEGER,
athlete VARCHAR
) | SELECT MIN(time) FROM table_name_45 WHERE athlete = "muna lee" | 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 combined of 2 overalls and 5 slaloms? | CREATE TABLE table_name_93 (
combined VARCHAR,
overall VARCHAR,
slalom VARCHAR
) | SELECT combined FROM table_name_93 WHERE overall = "2" AND slalom = "5" | 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,
... |
For those employees who was hired before 2002-06-21, visualize a line chart about the change of department_id over hire_date , and could you list in descending by the X-axis? | 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 countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0... | SELECT HIRE_DATE, DEPARTMENT_ID FROM employees WHERE HIRE_DATE < '2002-06-21' ORDER BY HIRE_DATE 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 is the alternate title/translation of the series that premiered on December 12, 2006? | CREATE TABLE table_name_40 (
alternate_title_translation VARCHAR,
series_premiere VARCHAR
) | SELECT alternate_title_translation FROM table_name_40 WHERE series_premiere = "december 12, 2006" | 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 occurence has 0.925 listed as the matrix sim? | CREATE TABLE table_28964 (
"Detailed Family Information" text,
"From" real,
"To" real,
"Anchor" real,
"Orientation" text,
"Conserved in Mus Musculus" text,
"Matrix Sim" text,
"Sequence" text,
"Occurrence" real
) | SELECT MAX("Occurrence") FROM table_28964 WHERE "Matrix Sim" = '0.925' | 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 the nationality is united states, and the time is 58.06, and the heat is larger than 5 what is the lowest rank? | CREATE TABLE table_63273 (
"Rank" real,
"Heat" real,
"Lane" real,
"Name" text,
"Nationality" text,
"Time" text
) | SELECT MIN("Rank") FROM table_63273 WHERE "Nationality" = 'united states' AND "Time" = '58.06' AND "Heat" > '5' | 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 was the source of the poll that gave McAuliffe 30% on June 8? | CREATE TABLE table_21535453_1 (
source VARCHAR,
terry_mcauliffe VARCHAR,
dates_administered VARCHAR
) | SELECT source FROM table_21535453_1 WHERE terry_mcauliffe = "30%" AND dates_administered = "June 8" | 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 nationality is Steven Anthony? | CREATE TABLE table_54539 (
"Pick #" real,
"Player" text,
"Nationality" text,
"Position" text,
"League from" text
) | SELECT "Nationality" FROM table_54539 WHERE "Player" = 'steven anthony' | 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 enrollment ratio in preschool in the region where the enrollment ratio in primary is 93.10? | CREATE TABLE table_27316 (
"Region" text,
"Preschool (0\u20135 years)" text,
"Primary (6\u201313 years)" text,
"Secondary (14\u201317 years)" text,
"Tertiary (18\u201324 years)" text
) | SELECT "Preschool (0\u20135 years)" FROM table_27316 WHERE "Primary (6\u201313 years)" = '93.10' | 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,
... |
Are there any classes about Elementary African Languages ? | CREATE TABLE gsi (
course_offering_id int,
student_id int
)
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 requirement (... | SELECT DISTINCT department, name, number FROM course WHERE (description LIKE '%Elementary African Languages%' OR name LIKE '%Elementary African Languages%') AND department = 'EECS' | 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,
... |
Which year's crew is varsity 8+ when the record is 7-3? | CREATE TABLE table_38331 (
"Year" text,
"Coach" text,
"Crew" text,
"Record" text,
"Win %" real
) | SELECT "Year" FROM table_38331 WHERE "Crew" = 'varsity 8+' AND "Record" = '7-3' | 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 visitor has February 11 as the date? | CREATE TABLE table_name_37 (
visitor VARCHAR,
date VARCHAR
) | SELECT visitor FROM table_name_37 WHERE date = "february 11" | 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 total bill for patient 52898's hospital stay in their current hospital encounter? | CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
... | SELECT SUM(cost.cost) FROM cost WHERE cost.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 52898 AND admissions.dischtime IS NULL) | 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,
... |
How many products were not included in any order? | CREATE TABLE products (
product_id VARCHAR
)
CREATE TABLE Order_items (
product_id VARCHAR
) | SELECT COUNT(*) FROM products WHERE NOT product_id IN (SELECT product_id FROM Order_items) | 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 most laps with a grid of 20? | CREATE TABLE table_12062 (
"Driver" text,
"Constructor" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
) | SELECT MAX("Laps") FROM table_12062 WHERE "Grid" = '20' | 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 lowest fare UA charges between BOSTON and SAN FRANCISCO | CREATE TABLE days (
days_code varchar,
day_name varchar
)
CREATE TABLE flight_stop (
flight_id int,
stop_number int,
stop_days text,
stop_airport text,
arrival_time int,
arrival_airline text,
arrival_flight_number int,
departure_time int,
departure_airline text,
departur... | 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, fare, flight, flight_fare WHERE (CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'BOSTON' AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city... | 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 i/o bus for the brand name Core i3-21xx? | CREATE TABLE table_24538587_11 (
i_o_bus VARCHAR,
brand_name__list_ VARCHAR
) | SELECT i_o_bus FROM table_24538587_11 WHERE brand_name__list_ = "Core i3-21xx" | 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 of the building housing more than 101 floors, that was built after 2006? | CREATE TABLE table_54822 (
"Rank" text,
"Name" text,
"Height m (ft)" text,
"Floors" real,
"Year" real
) | SELECT "Name" FROM table_54822 WHERE "Year" > '2006' AND "Floors" > '101' | 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,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.