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 |
|---|---|---|---|---|---|---|
Digital channel of 32 belongs to what analog channel? | CREATE TABLE table_name_3 (
analog_channel VARCHAR,
digital_channel VARCHAR
) | SELECT analog_channel FROM table_name_3 WHERE digital_channel = "32" | 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 inputs that patient 010-8740 has received on the first icu visit? | CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime t... | SELECT SUM(intakeoutput.cellvaluenumeric) FROM intakeoutput WHERE intakeoutput.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '010-8740') AND NOT patient.unitdischargetime IS ... | 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 won stage 18? | CREATE TABLE table_14395920_2 (
winner VARCHAR,
stage VARCHAR
) | SELECT winner FROM table_14395920_2 WHERE stage = 18 | 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,
... |
give me the procedure icd9 code and drug type of subject id 18480. | CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
... | SELECT procedures.icd9_code, prescriptions.drug_type FROM procedures INNER JOIN prescriptions ON procedures.hadm_id = prescriptions.hadm_id WHERE procedures.subject_id = "18480" | 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 Round with a Opponent with blackburn? | CREATE TABLE table_77997 (
"Round" text,
"Date" text,
"Opponent" text,
"Venue" text,
"Result" text
) | SELECT "Round" FROM table_77997 WHERE "Opponent" = 'blackburn' | 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,
... |
history of head trauma with prolonged loss of consciousness ( > 10 minutes ) or any neurological condition including stroke or seizure ( excluding childhood febrile seizure ) or history of migraine headache. | CREATE TABLE table_train_126 (
"id" int,
"childhood_febrile_seizure" bool,
"neurodegenerative_disease" bool,
"cns_disease" bool,
"head_injury" bool,
"stroke" bool,
"renal_disease" bool,
"cerebrovascular_disease" bool,
"hepatic_disease" bool,
"headache" bool,
"cardiovascular_d... | SELECT * FROM table_train_126 WHERE head_injury = 1 OR (neurological_disease = 1 OR stroke = 1 OR (seizure_disorder = 1 AND childhood_febrile_seizure = 0) OR headache = 1) | criteria2sql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
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 patients whose admission type is elective that had a procedure named umbilical vein catheterization. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob te... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.admission_type = "ELECTIVE" AND procedures.long_title = "Umbilical vein catheterization" | 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,
... |
how many teams won at least 85 games ? | CREATE TABLE table_204_905 (
id number,
"team" text,
"wins" number,
"losses" number,
"win %" number,
"gb" number
) | SELECT COUNT("team") FROM table_204_905 WHERE "wins" >= 85 | 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,
... |
Which school is in Riverside, CA? | CREATE TABLE table_77982 (
"Player" text,
"Height" text,
"School" text,
"Hometown" text,
"College" text,
"NBA Draft" text
) | SELECT "School" FROM table_77982 WHERE "Hometown" = 'riverside, ca' | 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 area has Years of 1 8, and a Name of broomfield school? | CREATE TABLE table_name_9 (
area VARCHAR,
years VARCHAR,
name VARCHAR
) | SELECT area FROM table_name_9 WHERE years = "1–8" AND name = "broomfield school" | 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 names of aircrafts and the number of times it won matches Plot them as bar chart, and order by the X-axis in descending. | CREATE TABLE aircraft (
Aircraft_ID int(11),
Aircraft varchar(50),
Description varchar(50),
Max_Gross_Weight varchar(50),
Total_disk_area varchar(50),
Max_disk_Loading varchar(50)
)
CREATE TABLE pilot (
Pilot_Id int(11),
Name varchar(50),
Age int(11)
)
CREATE TABLE airport_aircraft... | SELECT Aircraft, COUNT(*) FROM aircraft AS T1 JOIN match AS T2 ON T1.Aircraft_ID = T2.Winning_Aircraft GROUP BY T2.Winning_Aircraft ORDER BY Aircraft 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 was the game site week 15? | CREATE TABLE table_name_79 (
game_site VARCHAR,
week VARCHAR
) | SELECT game_site FROM table_name_79 WHERE week = 15 | 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 Team has a Score of 89-123? | CREATE TABLE table_name_40 (
team VARCHAR,
score VARCHAR
) | SELECT team FROM table_name_40 WHERE score = "89-123" | 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,
... |
count how many hospital visits patient 015-66570 has in this year. | CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number... | SELECT COUNT(DISTINCT patient.patienthealthsystemstayid) FROM patient WHERE patient.uniquepid = '015-66570' AND DATETIME(patient.hospitaladmittime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-0 year') | 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,
... |
Are there classes in the morning that are RELIGION 347 ? | CREATE TABLE gsi (
course_offering_id int,
student_id int
)
CREATE TABLE semester (
semester_id int,
semester varchar,
year int
)
CREATE TABLE instructor (
instructor_id int,
name varchar,
uniqname varchar
)
CREATE TABLE program_requirement (
program_id int,
category varchar,
... | SELECT COUNT(*) > 0 FROM course, course_offering, semester WHERE course_offering.start_time < '12:00:00' AND course_offering.start_time >= '08:00:00' AND course.course_id = course_offering.course_id AND course.department = 'RELIGION' AND course.number = 347 AND semester.semester = 'WN' AND semester.semester_id = course... | 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,
... |
For those employees who was hired before 2002-06-21, show me about the distribution of hire_date and the average of manager_id bin hire_date by time in a bar chart, could you list from low to high by the the average of manager id 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 HIRE_DATE, AVG(MANAGER_ID) FROM employees WHERE HIRE_DATE < '2002-06-21' ORDER BY AVG(MANAGER_ID) | nvbench | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who is the rider with 22 laps and a +19.435 time/retired? | CREATE TABLE table_48797 (
"Rider" text,
"Manufacturer" text,
"Laps" text,
"Time/Retired" text,
"Grid" text
) | SELECT "Rider" FROM table_48797 WHERE "Laps" = '22' AND "Time/Retired" = '+19.435' | 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 Opponent has a Score of 92 93? | CREATE TABLE table_12534 (
"Game" real,
"Date" text,
"Opponent" text,
"Score" text,
"Location/Attendance" text,
"Record" text,
"Streak" text
) | SELECT "Opponent" FROM table_12534 WHERE "Score" = '92–93' | 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 st kilda played as the away team, what date was that? | CREATE TABLE table_54830 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
) | SELECT "Date" FROM table_54830 WHERE "Away team" = 'st kilda' | 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 all episode air dates whose audition venues were Nego Quirido Sambadrome? | CREATE TABLE table_29666 (
"Episode Air Date" text,
"Audition City" text,
"Audition Date" text,
"Audition Venue" text,
"Guest Fourth Judge" text
) | SELECT "Episode Air Date" FROM table_29666 WHERE "Audition Venue" = 'Nego Quirido Sambadrome' | 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 is the venue nikos goumas stadium and the score is 2 2 4 4 a.e.t. 6 5 pso? | CREATE TABLE table_name_44 (
year VARCHAR,
venue VARCHAR,
score VARCHAR
) | SELECT year FROM table_name_44 WHERE venue = "nikos goumas stadium" AND score = "2–2 4–4 a.e.t. 6–5 pso" | 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 2005 when 2003 is A, 2007 is 2r and 2012 is 3r? | CREATE TABLE table_name_49 (
Id VARCHAR
) | SELECT 2005 FROM table_name_49 WHERE 2003 = "a" AND 2007 = "2r" AND 2012 = "3r" | 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,
... |
has there been any swab microbiology test since 2105 for patient 63676? | CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE admissions (
row_id numb... | SELECT COUNT(*) > 0 FROM microbiologyevents WHERE microbiologyevents.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 63676) AND microbiologyevents.spec_type_desc = 'swab' AND STRFTIME('%y', microbiologyevents.charttime) >= '2105' | mimic_iii | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is a procedure patient 74392 received for the first time until 2102? | CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime t... | SELECT d_icd_procedures.short_title FROM d_icd_procedures WHERE d_icd_procedures.icd9_code IN (SELECT procedures_icd.icd9_code FROM procedures_icd WHERE procedures_icd.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 74392) AND STRFTIME('%y', procedures_icd.charttime) <= '2102' ORDER ... | mimic_iii | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the place number for the player with a To Par score of 'E'? | CREATE TABLE table_name_85 (
place VARCHAR,
to_par VARCHAR
) | SELECT place FROM table_name_85 WHERE to_par = "e" | 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 long for the player with 26 carries? | CREATE TABLE table_53198 (
"Player" text,
"Car." real,
"Yards" text,
"Avg." text,
"TD's" real,
"Long" text
) | SELECT "Long" FROM table_53198 WHERE "Car." = '26' | 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 OWGR pts has Dates of may 10-13? | CREATE TABLE table_name_37 (
owgr_pts INTEGER,
dates VARCHAR
) | SELECT SUM(owgr_pts) FROM table_name_37 WHERE dates = "may 10-13" | 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 1:50? | CREATE TABLE table_name_79 (
opponent VARCHAR,
time VARCHAR
) | SELECT opponent FROM table_name_79 WHERE time = "1:50" | 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 average for swimsuits smaller than 9.62 in Colorado? | CREATE TABLE table_58555 (
"Country" text,
"Interview" real,
"Swimsuit" real,
"Evening Gown" real,
"Average" real
) | SELECT SUM("Average") FROM table_58555 WHERE "Swimsuit" < '9.62' AND "Country" = 'colorado' | 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 Users in Tag (in UK). | CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE Users (
Id number,
Reputation number,
CreationDate time,
DisplayName text,
LastAccessDate time,
WebsiteUrl text,
Location text,
... | SELECT Users.DisplayName, Users.Location, SUM(Posts.Score) AS TotalScore, 'https://stackoverflow.com/users/' + CAST(Users.Id AS TEXT) AS Profile FROM Posts INNER JOIN Users ON Posts.OwnerUserId = Users.Id INNER JOIN PostTags ON Posts.Id = PostTags.PostId INNER JOIN Tags ON PostTags.TagId = Tags.Id WHERE TagName = '##ta... | 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 are McCain's Percent when Obama has 36.47%? | CREATE TABLE table_20688030_1 (
mccain_percentage VARCHAR,
obama_percentage VARCHAR
) | SELECT mccain_percentage FROM table_20688030_1 WHERE obama_percentage = "36.47%" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What was the amount of deaths that had a natural growth smaller than 3.4, and a total fertility rate of 1.63? | CREATE TABLE table_66704 (
"Year" text,
"Births (000s)" real,
"Deaths" real,
"Natural Growth" real,
"Total Fertility Rate" text
) | SELECT "Deaths" FROM table_66704 WHERE "Natural Growth" < '3.4' AND "Total Fertility Rate" = '1.63' | 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 winning score has in-kyung kim as the runner(s)-up? | CREATE TABLE table_62004 (
"Date" text,
"Tournament" text,
"Winning score" text,
"To par" text,
"Margin of victory" text,
"Runner(s)-up" text,
"Winner's share ( $ )" real
) | SELECT "Winning score" FROM table_62004 WHERE "Runner(s)-up" = 'in-kyung kim' | 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,
... |
Give me the comparison about Team_ID over the All_Road by a bar chart, I want to list by the X-axis in ascending please. | CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
)
CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Per... | SELECT All_Road, Team_ID FROM basketball_match ORDER BY All_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,
... |
What is total number of show times per dat for each cinema? | CREATE TABLE film (
film_id number,
rank_in_series number,
number_in_season number,
title text,
directed_by text,
original_air_date text,
production_code text
)
CREATE TABLE schedule (
cinema_id number,
film_id number,
date text,
show_times_per_day number,
price number
)... | SELECT T2.name, SUM(T1.show_times_per_day) FROM schedule AS T1 JOIN cinema AS T2 ON T1.cinema_id = T2.cinema_id GROUP BY T1.cinema_id | 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,
... |
what is the number of patients whose days of hospital stay is greater than 20 and drug code is ipra2h? | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.days_stay > "20" AND prescriptions.formulary_drug_cd = "IPRA2H" | 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 SOCIAL SOFTWARE WITH NO DISCUSSION, NO TIME TRACKING, AND NO CHARTING? | CREATE TABLE table_name_18 (
social_software VARCHAR,
charting VARCHAR,
discussion VARCHAR,
time_tracking VARCHAR
) | SELECT social_software FROM table_name_18 WHERE discussion = "no" AND time_tracking = "no" AND charting = "no" | 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 number of patients whose year of birth is less than 2121 and lab test fluid is cerebrospinal fluid (csf)? | CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location t... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.dob_year < "2121" AND lab.fluid = "Cerebrospinal Fluid (CSF)" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Questions by Time of Day and Day of Week. Designed to consider whether 'night' questions have more visibility than 'day' questions | CREATE TABLE Posts (
Id number,
PostTypeId number,
AcceptedAnswerId number,
ParentId number,
CreationDate time,
DeletionDate time,
Score number,
ViewCount number,
Body text,
OwnerUserId number,
OwnerDisplayName text,
LastEditorUserId number,
LastEditorDisplayName text... | SELECT ((TIME_TO_STR(Posts.CreationDate, '%W')) + (TIME_TO_STR(Posts.CreationDate, '%h')) / 24.0) AS HourOfWeek, COUNT(Posts.Id) AS Questions FROM Posts WHERE PostTypeId = 1 GROUP BY TIME_TO_STR(Posts.CreationDate, '%W'), TIME_TO_STR(Posts.CreationDate, '%h') ORDER BY HourOfWeek | 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,
... |
how much is the total medical bill of patient 73423 until 4 years ago during their stay? | CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE inputevents_cv (
row_id nu... | SELECT SUM(cost.cost) FROM cost WHERE cost.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 73423) AND DATETIME(cost.chargetime) <= DATETIME(CURRENT_TIME(), '-4 year') | 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,
... |
who is the incumbent where the district is florida 9? | CREATE TABLE table_724 (
"District" text,
"Incumbent" text,
"Party" text,
"First elected" real,
"Result" text,
"Candidates" text
) | SELECT "Incumbent" FROM table_724 WHERE "District" = 'Florida 9' | 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,
... |
mean answer score as function of response time. | CREATE TABLE VoteTypes (
Id number,
Name text
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
O... | WITH a AS (SELECT pa.Score, pq.CreationDate AS question_date, pa.CreationDate AS answer_date, DATEDIFF(day, pq.CreationDate, CreationDate) AS daydiff FROM Posts AS pa JOIN Posts AS pq ON pa.ParentId = pq.Id) SELECT daydiff, AVG(1.00 * Score) AS quality FROM a WHERE daydiff >= 0 AND daydiff <= 300 GROUP BY daydiff ORDER... | 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 Player is from Connecticut? | CREATE TABLE table_46647 (
"Pick" real,
"Player" text,
"Nationality" text,
"New WNBA Team" text,
"Former WNBA Team" text,
"College/Country/Team" text
) | SELECT "Player" FROM table_46647 WHERE "College/Country/Team" = 'connecticut' | 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 1406 komppa of asteroid which 1391 carelia is 1460 haltia | CREATE TABLE table_21566 (
"1391 Carelia" text,
"1398 Donnera" text,
"1405 Sibelius" text,
"1406 Komppa" text,
"1407 Lindel\u00f6f" text
) | SELECT "1406 Komppa" FROM table_21566 WHERE "1391 Carelia" = '1460 Haltia' | 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,
... |
at most part , how many emission standards are equal to or less than 1.1 ? | CREATE TABLE table_204_909 (
id number,
"pollutant" text,
"units" text,
"emission standard" number,
"coal-fired" text,
"petroleum coke-fired" text
) | SELECT COUNT("emission standard") FROM table_204_909 WHERE "emission standard" = '≤ 1.1' | 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,
... |
Which team has a match played of 10 4? | CREATE TABLE table_73343 (
"Team" text,
"Stadium" text,
"Match played" text,
"Highest" real,
"Lowest" real,
"Average" real
) | SELECT "Team" FROM table_73343 WHERE "Match played" = '10 4' | 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,
... |
Users receiving multiple bounties from the same person. | CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE Posts (
Id number,
PostTypeId number,
AcceptedAnswerId number,
ParentId number,
CreationDate time,
DeletionDate time,
Score number,
... | SELECT CAST(N'2016-03-08T08:00:00' AS DATETIME) | 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 average Episode Number, when Original Airdate is March 21, 2010, and when Season is less than 3? | CREATE TABLE table_46367 (
"Year" real,
"Show" text,
"Season" real,
"Episode" text,
"Episode number" real,
"Original airdate" text
) | SELECT AVG("Episode number") FROM table_46367 WHERE "Original airdate" = 'march 21, 2010' AND "Season" < '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,
... |
Which Venue has a Round of gs, and a Result of 0 3? | CREATE TABLE table_name_2 (
venue VARCHAR,
round VARCHAR,
result VARCHAR
) | SELECT venue FROM table_name_2 WHERE round = "gs" AND result = "0–3" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which producer worked for Animus Films LTD? | CREATE TABLE table_name_42 (
producer_s_ VARCHAR,
recipient VARCHAR
) | SELECT producer_s_ FROM table_name_42 WHERE recipient = "animus films ltd" | 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 studios of each film and the number of films produced by that studio Show bar chart, could you list by the X from low to high? | CREATE TABLE film (
Film_ID int,
Title text,
Studio text,
Director text,
Gross_in_dollar int
)
CREATE TABLE film_market_estimation (
Estimation_ID int,
Low_Estimate real,
High_Estimate real,
Film_ID int,
Type text,
Market_ID int,
Year int
)
CREATE TABLE market (
Mar... | SELECT Studio, COUNT(*) FROM film GROUP BY Studio ORDER BY Studio | 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,
... |
how many millions of north american viewers had the episode whose director was Michael Lembeck? | CREATE TABLE table_29792 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text,
"Production code(s)" real,
"U.S. viewers (millions)" text
) | SELECT "U.S. viewers (millions)" FROM table_29792 WHERE "Directed by" = 'Michael Lembeck' | 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,
... |
With 37 tries against, what is the try bonus? | CREATE TABLE table_name_82 (
try_bonus VARCHAR,
tries_against VARCHAR
) | SELECT try_bonus FROM table_name_82 WHERE tries_against = "37" | 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 last representative to take office ? | CREATE TABLE table_203_345 (
id number,
"name" text,
"party" text,
"took office" number,
"left office" number
) | SELECT "name" FROM table_203_345 ORDER BY "took office" DESC LIMIT 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,
... |
Return a bar chart on what is the number of professors for different school?, and sort from high to low by the the total number . | CREATE TABLE COURSE (
CRS_CODE varchar(10),
DEPT_CODE varchar(10),
CRS_DESCRIPTION varchar(35),
CRS_CREDIT float(8)
)
CREATE TABLE PROFESSOR (
EMP_NUM int,
DEPT_CODE varchar(10),
PROF_OFFICE varchar(50),
PROF_EXTENSION varchar(4),
PROF_HIGH_DEGREE varchar(5)
)
CREATE TABLE STUDENT ... | SELECT SCHOOL_CODE, COUNT(*) FROM DEPARTMENT AS T1 JOIN PROFESSOR AS T2 ON T1.DEPT_CODE = T2.DEPT_CODE GROUP BY T1.SCHOOL_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,
... |
What is the total number of Matches, when Clubs is 588 406? | CREATE TABLE table_name_16 (
matches VARCHAR,
clubs VARCHAR
) | SELECT COUNT(matches) FROM table_name_16 WHERE clubs = "588 → 406" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Find meter_400 and ID , and visualize them by a bar chart, and list by the Y from high to low please. | CREATE TABLE event (
ID int,
Name text,
Stadium_ID int,
Year text
)
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 swimme... | SELECT meter_400, ID FROM swimmer ORDER BY ID 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,
... |
For those employees who do not work in departments with managers that have ids between 100 and 200, give me the comparison about employee_id over the last_name , show by the Y-axis in ascending. | CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
... | SELECT LAST_NAME, EMPLOYEE_ID FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY 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 is the Week of the game with an Attendance of 64,900 and a Result of L 34-13? | CREATE TABLE table_name_83 (
week INTEGER,
attendance VARCHAR,
result VARCHAR
) | SELECT MAX(week) FROM table_name_83 WHERE attendance = "64,900" AND result = "l 34-13" | 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 To par has the presence of Vijay Singh? | CREATE TABLE table_70730 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text,
"Hole" text
) | SELECT "To par" FROM table_70730 WHERE "Player" = 'vijay singh' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the names of everybody who has exactly one friend? | CREATE TABLE personfriend (
name text,
friend text,
year number
)
CREATE TABLE person (
name text,
age number,
city text,
gender text,
job text
) | SELECT name FROM personfriend GROUP BY name HAVING COUNT(*) = 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,
... |
How many Antonov An-2 Colt aircraft are in service? | CREATE TABLE table_name_37 (
in_service INTEGER,
aircraft VARCHAR
) | SELECT AVG(in_service) FROM table_name_37 WHERE aircraft = "antonov an-2 colt" | 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,
... |
i want to fly from MIAMI to CHICAGO on AA and arrive at around 5 o'clock in the afternoon show me all flights | CREATE TABLE city (
city_code varchar,
city_name varchar,
state_code varchar,
country_name varchar,
time_zone_code varchar
)
CREATE TABLE aircraft (
aircraft_code varchar,
aircraft_description varchar,
manufacturer varchar,
basic_type varchar,
engines int,
propulsion varchar... | 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 (((flight.arrival_time <= 1730 AND flight.arrival_time >= 1630) AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'CHICAGO' AND flight.to... | 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,
... |
Who is the opponent in the Tournament of Lahore final? | CREATE TABLE table_57816 (
"Date" text,
"Tournament" text,
"Surface" text,
"Opponent in the final" text,
"Score" text
) | SELECT "Opponent in the final" FROM table_57816 WHERE "Tournament" = 'lahore' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees who do not work in departments with managers that have ids between 100 and 200, a bar chart shows the distribution of hire_date and the average of manager_id bin hire_date by time. | CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varc... | SELECT HIRE_DATE, AVG(MANAGER_ID) FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) | 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,
... |
papers about crowdsourcing in acl 2015 | CREATE TABLE paperfield (
fieldid int,
paperid int
)
CREATE TABLE author (
authorid int,
authorname varchar
)
CREATE TABLE paperkeyphrase (
paperid int,
keyphraseid int
)
CREATE TABLE paperdataset (
paperid int,
datasetid int
)
CREATE TABLE field (
fieldid int
)
CREATE TABLE key... | SELECT DISTINCT paper.paperid FROM keyphrase, paper, paperkeyphrase, venue WHERE keyphrase.keyphrasename = 'crowdsourcing' AND paperkeyphrase.keyphraseid = keyphrase.keyphraseid AND paper.paperid = paperkeyphrase.paperid AND paper.year = 2015 AND venue.venueid = paper.venueid AND venue.venuename = 'acl' | scholar | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
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 Years in competition that had a Premiership of 1982, 1984, 1999, 2002-03, 2008-09-10? | CREATE TABLE table_34195 (
"Club" text,
"Nickname" text,
"Years in Competition" text,
"No. of Premierships" real,
"Premiership Years" text
) | SELECT "Years in Competition" FROM table_34195 WHERE "Premiership Years" = '1982, 1984, 1999, 2002-03, 2008-09-10' | 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,
... |
what is the change in the hemoglobin of patient 88191's value second measured on the first hospital visit compared to the value first measured on the first hospital visit? | CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE d_labitems (
row_id ... | SELECT (SELECT labevents.valuenum FROM labevents WHERE labevents.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 88191 AND NOT admissions.dischtime IS NULL ORDER BY admissions.admittime LIMIT 1) AND labevents.itemid IN (SELECT d_labitems.itemid FROM d_labitems WHERE d_labitems.label ... | 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,
... |
when the key tower was built in 1991 , what was the previous tallest building constructed ? | CREATE TABLE table_204_649 (
id number,
"rank" number,
"name" text,
"image" number,
"height\nft (m)" text,
"floors" number,
"year" number,
"notes" text
) | SELECT "name" FROM table_204_649 WHERE "year" < 1991 ORDER BY "height\nft (m)" DESC LIMIT 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,
... |
when did patient 015-59871 receive procedures for the first time during their last hospital visit? | CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE vitalperiodic (
vitalp... | SELECT treatment.treatmenttime FROM treatment WHERE treatment.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '015-59871' AND NOT patient.hospitaldischargetime IS NULL ORDER BY... | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what was the total amount of output amt-jackson pratt drain patient 021-250695 produced on 11/18/last year? | CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE cost (
costid number,
... | SELECT SUM(intakeoutput.cellvaluenumeric) FROM intakeoutput WHERE intakeoutput.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '021-250695')) AND intakeoutput.celllabel = 'outp... | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What scored is recorded on April 24? | CREATE TABLE table_name_92 (
score VARCHAR,
date VARCHAR
) | SELECT score FROM table_name_92 WHERE date = "april 24" | 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,
... |
I want the total number of matches for draw less than 7 and lost point of 16 with lose more than 4 | CREATE TABLE table_name_14 (
matches VARCHAR,
lose VARCHAR,
draw VARCHAR,
lost_point VARCHAR
) | SELECT COUNT(matches) FROM table_name_14 WHERE draw < 7 AND lost_point = 16 AND lose > 4 | 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 Slovene word for Thursday? | CREATE TABLE table_17780 (
"Day (see Irregularities )" text,
"Monday First Day" text,
"Tuesday Second Day" text,
"Wednesday Third Day" text,
"Thursday Fourth Day" text,
"Friday Fifth Day" text,
"Saturday Sixth Day" text,
"Sunday Seventh Day" text
) | SELECT "Thursday Fourth Day" FROM table_17780 WHERE "Day (see Irregularities )" = 'Slovene' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the average overall of John Ayres, who had a pick # greater than 4? | CREATE TABLE table_name_38 (
overall INTEGER,
name VARCHAR,
pick__number VARCHAR
) | SELECT AVG(overall) FROM table_name_38 WHERE name = "john ayres" AND pick__number > 4 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What is the date of the circuit gilles villeneuve? | CREATE TABLE table_1137707_2 (
date VARCHAR,
location VARCHAR
) | SELECT date FROM table_1137707_2 WHERE location = "Circuit Gilles Villeneuve" | 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 position for the years 1998-99 | CREATE TABLE table_11545282_11 (
position VARCHAR,
years_for_jazz VARCHAR
) | SELECT position FROM table_11545282_11 WHERE years_for_jazz = "1998-99" | 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 Theme of Christie Paquet after 2004 with an Issue Price of $34.95? | CREATE TABLE table_name_54 (
theme VARCHAR,
year VARCHAR,
artist VARCHAR,
issue_price VARCHAR
) | SELECT theme FROM table_name_54 WHERE artist = "christie paquet" AND issue_price = "$34.95" AND year > 2004 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
find the admission time of jerry deberry. | CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
C... | SELECT demographic.admittime FROM demographic WHERE demographic.name = "Jerry Deberry" | 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 sum of Against, when Wins is greater than 8, and when Losses is greater than 6? | CREATE TABLE table_12641 (
"South West DFL" text,
"Wins" real,
"Byes" real,
"Losses" real,
"Draws" real,
"Against" real
) | SELECT SUM("Against") FROM table_12641 WHERE "Wins" > '8' AND "Losses" > '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,
... |
Who is the owner operator who has license number PL 59? | CREATE TABLE table_59730 (
"Name (year commissioned)" text,
"Owner/operator" text,
"Length" text,
"Maximum diameter" text,
"From/to" text,
"Licence number" text
) | SELECT "Owner/operator" FROM table_59730 WHERE "Licence number" = 'pl 59' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
For those employees who do not work in departments with managers that have ids between 100 and 200, return a bar chart about the distribution of email and department_id , display from high to low by the DEPARTMENT_ID. | CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_... | SELECT EMAIL, DEPARTMENT_ID FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY DEPARTMENT_ID 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,
... |
List all institutions with a team name of the Cardinals. | CREATE TABLE table_18483171_1 (
institution VARCHAR,
team_nickname VARCHAR
) | SELECT institution FROM table_18483171_1 WHERE team_nickname = "Cardinals" | 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 US Acres episode following the Garfield episode titled Robodie II? | CREATE TABLE table_22390 (
"Episode" text,
"Garfield Episode 1" text,
"U.S. Acres Episode" text,
"Garfield Episode 2" text,
"Original Airdate" text
) | SELECT "U.S. Acres Episode" FROM table_22390 WHERE "Garfield Episode 1" = 'Robodie II' | 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 patients whose diagnoses icd9 code is 59080 and drug route is neb? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE diagnoses.icd9_code = "59080" AND prescriptions.route = "NEB" | mimicsql_data | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Which school/club team has a player named Mark Sanford? | CREATE TABLE table_15463188_17 (
school_club_team VARCHAR,
name VARCHAR
) | SELECT school_club_team FROM table_15463188_17 WHERE name = "Mark Sanford" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
What are the prizes when 1 is the number of winning tickets? | CREATE TABLE table_20195922_3 (
prize__eur_ VARCHAR,
number_of_winning_tickets VARCHAR
) | SELECT prize__eur_ FROM table_20195922_3 WHERE number_of_winning_tickets = 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 long-term gain for collectibles coincides with ordinary income rate 15%? | CREATE TABLE table_55789 (
"Ordinary income rate" text,
"Long-term capital gain rate" text,
"Short-term capital gain rate" text,
"Long-term gain on commercial buildings*" text,
"Long-term gain on collectibles" text
) | SELECT "Long-term gain on collectibles" FROM table_55789 WHERE "Ordinary income rate" = '15%' | wikisql | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
Who is the player with a t8 place? | CREATE TABLE table_name_67 (
player VARCHAR,
place VARCHAR
) | SELECT player FROM table_name_67 WHERE place = "t8" | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
When ellery and frankie are the couple what is the highest total? | CREATE TABLE table_23248 (
"Rank" real,
"Couple" text,
"Judges" real,
"Public" real,
"Total" real,
"Vote percentage" text,
"Result" text
) | SELECT MAX("Total") FROM table_23248 WHERE "Couple" = 'Ellery and Frankie' | 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 label in the region of Canada? | CREATE TABLE table_46824 (
"Region" text,
"Date" text,
"Label" text,
"Format" text,
"Catalog" text
) | SELECT "Label" FROM table_46824 WHERE "Region" = 'canada' | 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 Density per km is the lowest one that has a Number (map) smaller than 13, and an Area in km of 11.1? | CREATE TABLE table_name_21 (
density_per_km² INTEGER,
number__map_ VARCHAR,
area_in_km² VARCHAR
) | SELECT MIN(density_per_km²) FROM table_name_21 WHERE number__map_ < 13 AND area_in_km² = 11.1 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
what is the three year survival probability for the leukocytosis - leukemoid reaction patients diagnosed? | CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
... | SELECT SUM(CASE WHEN patient.hospitaldischargestatus = 'alive' THEN 1 WHEN STRFTIME('%j', patient.hospitaldischargetime) - STRFTIME('%j', t2.diagnosistime) > 3 * 365 THEN 1 ELSE 0 END) * 100 / COUNT(*) FROM (SELECT t1.uniquepid, t1.diagnosistime FROM (SELECT patient.uniquepid, diagnosis.diagnosistime FROM diagnosis JOI... | eicu | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many patients are below 50 years of age and diagnosed with coronary atherosclerosis of native coronary artery? | CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
... | SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.age < "50" AND diagnoses.long_title = "Coronary atherosclerosis of native coronary artery" | 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 track was next after all i got ? | CREATE TABLE table_203_701 (
id number,
"#" number,
"title" text,
"featured guest(s)" text,
"producer(s)" text,
"length" text
) | SELECT "title" FROM table_203_701 WHERE "#" = (SELECT "#" FROM table_203_701 WHERE "title" = '"all i got"') + 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 Score, when Visitor is 'Pittsburgh', and when Points is greater than 18? | CREATE TABLE table_47364 (
"Date" text,
"Visitor" text,
"Score" text,
"Home" text,
"Attendance" real,
"Record" text,
"Points" real
) | SELECT "Score" FROM table_47364 WHERE "Visitor" = 'pittsburgh' AND "Points" > '18' | 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 manager has Manchester City as the team? | CREATE TABLE table_name_14 (
manager VARCHAR,
team VARCHAR
) | SELECT manager FROM table_name_14 WHERE team = "manchester city" | 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 me minimal weight by sex in a histogram, I want to order names in ascending order please. | CREATE TABLE candidate (
Candidate_ID int,
People_ID int,
Poll_Source text,
Date text,
Support_rate real,
Consider_rate real,
Oppose_rate real,
Unsure_rate real
)
CREATE TABLE people (
People_ID int,
Sex text,
Name text,
Date_of_Birth text,
Height real,
Weight re... | SELECT Sex, MIN(Weight) FROM people GROUP BY Sex ORDER BY Sex | 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 lowest ends lost when the stolen ends for is less than 13, and stolten ends against is 6? | CREATE TABLE table_name_16 (
ends_lost INTEGER,
stolen_ends_for VARCHAR,
stolen_ends_against VARCHAR
) | SELECT MIN(ends_lost) FROM table_name_16 WHERE stolen_ends_for < 13 AND stolen_ends_against = 6 | sql_create_context | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
128000,
128006,
9125,
128007,
271,
38766,
1303,
33025,
2696,
25,
6790,
220,
2366,
18,
198,
15724,
2696,
25,
220,
1721,
4723,
220,
2366,
20,
271,
2675,
527,
264,
7941,
1887,
28175,
304,
... | [
[
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
... |
how many days has it been since patient 021-111547's admission to icu? | CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid num... | SELECT 1 * (STRFTIME('%j', CURRENT_TIME()) - STRFTIME('%j', patient.unitadmittime)) FROM patient WHERE patient.uniquepid = '021-111547' AND patient.unitdischargetime IS NULL | 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,
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.