instruction
stringlengths 151
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CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- this year what was the four most commonly ordered specimen test?
|
SELECT t1.spec_type_desc FROM (SELECT microbiologyevents.spec_type_desc, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM microbiologyevents WHERE DATETIME(microbiologyevents.charttime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-0 year') GROUP BY microbiologyevents.spec_type_desc) AS t1 WHERE t1.c1 <= 4
|
mimic_iii
|
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the number of patients whose discharge location is disc-tran cancer/chldrn h and procedure long title is incision of vessel, abdominal arteries?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.discharge_location = "DISC-TRAN CANCER/CHLDRN H" AND procedures.long_title = "Incision of vessel, abdominal arteries"
|
mimicsql_data
|
CREATE TABLE table_name_77 (
losses INTEGER,
club VARCHAR,
against VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Cobden has more than 1487 against and what average of losses?
|
SELECT AVG(losses) FROM table_name_77 WHERE club = "cobden" AND against > 1487
|
sql_create_context
|
CREATE TABLE table_name_58 (
start_term INTEGER,
end_term VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the average Start term with a 1912 end term?
|
SELECT AVG(start_term) FROM table_name_58 WHERE end_term = 1912
|
sql_create_context
|
CREATE TABLE table_name_79 (
director VARCHAR,
title VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who directed the movie The Star Packer?
|
SELECT director FROM table_name_79 WHERE title = "the star packer"
|
sql_create_context
|
CREATE TABLE t_kc21 (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SERVANT_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc21_t_kc22 (
MED_CLINIC_ID text,
MED_EXP_DET_ID number
)
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 医院6176731一共诊治过多少住院病人，在09-12-18到11-08-05这期间
|
SELECT COUNT(*) FROM t_kc21 WHERE t_kc21.MED_SER_ORG_NO = '6176731' AND t_kc21.IN_HOSP_DATE BETWEEN '2009-12-18' AND '2011-08-05' AND t_kc21.CLINIC_TYPE = '住院'
|
css
|
CREATE TABLE book (
Book_ID int,
Title text,
Issues real,
Writer text
)
CREATE TABLE publication (
Publication_ID int,
Book_ID int,
Publisher text,
Publication_Date text,
Price real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Bar chart x axis publication date y axis how many publication date, could you order by the x-axis in ascending?
|
SELECT Publication_Date, COUNT(Publication_Date) FROM publication GROUP BY Publication_Date ORDER BY Publication_Date
|
nvbench
|
CREATE TABLE table_7605 (
"Tie no" text,
"Home team" text,
"Score" text,
"Away team" text,
"Date" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Tie has a Score of 5 1?
|
SELECT "Tie no" FROM table_7605 WHERE "Score" = '5–1'
|
wikisql
|
CREATE TABLE table_25716399_1 (
written_by VARCHAR,
original_air_date VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who wrote the episode where the original air date is july20,2007?
|
SELECT written_by FROM table_25716399_1 WHERE original_air_date = "July20,2007"
|
sql_create_context
|
CREATE TABLE table_name_41 (
byes VARCHAR,
losses VARCHAR,
wins VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the total number of byes that has 13 losses and wins less than 5?
|
SELECT COUNT(byes) FROM table_name_41 WHERE losses = 13 AND wins < 5
|
sql_create_context
|
CREATE TABLE jybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH text,
BGJGDM text,
BGJGMC text,
BGRGH text,
BGRQ time,
BGRXM text,
BGSJ time,
CJRQ time,
JSBBRQSJ time,
JSBBSJ time,
JYBBH text,
JYJGMC text,
JYJSGH text,
JYJSQM text,
JYKSBM text,
JYKSMC text,
JYLX number,
JYRQ time,
JYSQJGMC text,
JYXMDM text,
JYXMMC text,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM text,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text
)
CREATE TABLE hz_info (
KH text,
KLX number,
RYBH text,
YLJGDM text
)
CREATE TABLE txmzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH number,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TZ number,
WDBZ number,
XL number,
YLJGDM number,
ZSEBZ number,
ZZBZ number,
ZZYSGH text
)
CREATE TABLE zyjzjlb (
CYBQDM text,
CYBQMC text,
CYCWH text,
CYKSDM text,
CYKSMC text,
CYSJ time,
CYZTDM number,
HZXM text,
JZKSDM text,
JZKSMC text,
JZLSH text,
KH text,
KLX number,
MZBMLX number,
MZJZLSH text,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYCWH text,
RYDJSJ time,
RYSJ time,
RYTJDM number,
RYTJMC text,
RZBQDM text,
RZBQMC text,
WDBZ number,
YLJGDM text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text
)
CREATE TABLE ftxmzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH number,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TZ number,
WDBZ number,
XL number,
YLJGDM number,
ZSEBZ number,
ZZBZ number,
ZZYSGH text
)
CREATE TABLE jyjgzbb (
BGDH text,
BGRQ time,
CKZFWDX text,
CKZFWSX number,
CKZFWXX number,
JCFF text,
JCRGH text,
JCRXM text,
JCXMMC text,
JCZBDM text,
JCZBJGDL number,
JCZBJGDW text,
JCZBJGDX text,
JCZBMC text,
JLDW text,
JYRQ time,
JYZBLSH text,
SBBM text,
SHRGH text,
SHRXM text,
YLJGDM text,
YQBH text,
YQMC text
)
CREATE TABLE person_info (
CSD text,
CSRQ time,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
MZDM text,
MZMC text,
RYBH text,
XBDM number,
XBMC text,
XLDM text,
XLMC text,
XM text,
ZYLBDM text,
ZYMC text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 病患去门诊诊断为器质性精神综合征时的同型半胱氨酸数据的平均值以及最值分别是多少？
|
SELECT AVG(jyjgzbb.JCZBJGDL), MIN(jyjgzbb.JCZBJGDL), MAX(jyjgzbb.JCZBJGDL) FROM txmzjzjlb JOIN jybgb JOIN jyjgzbb ON txmzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND txmzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH WHERE txmzjzjlb.JZZDSM = '器质性精神综合征' AND jyjgzbb.JCZBMC = '同型半胱氨酸' UNION SELECT AVG(jyjgzbb.JCZBJGDL), MIN(jyjgzbb.JCZBJGDL), MAX(jyjgzbb.JCZBJGDL) FROM ftxmzjzjlb JOIN jybgb JOIN jyjgzbb ON ftxmzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND ftxmzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH WHERE ftxmzjzjlb.JZZDSM = '器质性精神综合征' AND jyjgzbb.JCZBMC = '同型半胱氨酸'
|
css
|
CREATE TABLE table_name_12 (
position INTEGER,
name VARCHAR,
drawn VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the lowest position when the name is esv t rkheim, and Drawn more than 0?
|
SELECT MIN(position) FROM table_name_12 WHERE name = "esv türkheim" AND drawn > 0
|
sql_create_context
|
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_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those employees whose salary is in the range of 8000 and 12000 and commission is not null or department number does not equal to 40, visualize a scatter chart about the correlation between commission_pct and manager_id .
|
SELECT COMMISSION_PCT, MANAGER_ID FROM employees WHERE SALARY BETWEEN 8000 AND 12000 AND COMMISSION_PCT <> "null" OR DEPARTMENT_ID <> 40
|
nvbench
|
CREATE TABLE table_name_56 (
week INTEGER,
result VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the average week for result of l 28 17
|
SELECT AVG(week) FROM table_name_56 WHERE result = "l 28–17"
|
sql_create_context
|
CREATE TABLE table_25474825_1 (
description VARCHAR,
software VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the description of the intact software?
|
SELECT description FROM table_25474825_1 WHERE software = "IntAct"
|
sql_create_context
|
CREATE TABLE table_name_77 (
surface VARCHAR,
outcome VARCHAR,
date VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the Surface when Todd Woodbridge was the runner-up, and a Date of 24 february 1997?
|
SELECT surface FROM table_name_77 WHERE outcome = "runner-up" AND date = "24 february 1997"
|
sql_create_context
|
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- count the number of patients for whom lorazepam 2 mg/1 ml 1 ml inj was prescribed within 2 months after having been diagnosed with primary lung cancer - small cell ca since 2105.
|
SELECT COUNT(DISTINCT t1.uniquepid) FROM (SELECT patient.uniquepid, diagnosis.diagnosistime FROM diagnosis JOIN patient ON diagnosis.patientunitstayid = patient.patientunitstayid WHERE diagnosis.diagnosisname = 'primary lung cancer - small cell ca' AND STRFTIME('%y', diagnosis.diagnosistime) >= '2105') AS t1 JOIN (SELECT patient.uniquepid, medication.drugstarttime FROM medication JOIN patient ON medication.patientunitstayid = patient.patientunitstayid WHERE medication.drugname = 'lorazepam 2 mg/1 ml 1 ml inj' AND STRFTIME('%y', medication.drugstarttime) >= '2105') AS t2 WHERE t1.diagnosistime < t2.drugstarttime AND DATETIME(t2.drugstarttime) BETWEEN DATETIME(t1.diagnosistime) AND DATETIME(t1.diagnosistime, '+2 month')
|
eicu
|
CREATE TABLE table_name_56 (
streak VARCHAR,
game INTEGER
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Streak has a Game larger than 49?
|
SELECT streak FROM table_name_56 WHERE game > 49
|
sql_create_context
|
CREATE TABLE table_name_34 (
ubigeo INTEGER,
province VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Chep n's average UBIGEO?
|
SELECT AVG(ubigeo) FROM table_name_34 WHERE province = "chepén"
|
sql_create_context
|
CREATE TABLE table_name_81 (
played VARCHAR,
tries_against VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Played, when Tries Against is '63'?
|
SELECT played FROM table_name_81 WHERE tries_against = "63"
|
sql_create_context
|
CREATE TABLE table_21021796_1 (
torque VARCHAR,
stroke VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- List the torque possible when the stroke is 88.4mm?
|
SELECT torque FROM table_21021796_1 WHERE stroke = "88.4mm"
|
sql_create_context
|
CREATE TABLE table_62469 (
"Parish (Prestegjeld)" text,
"Sub-Parish (Sokn)" text,
"Church Name" text,
"Year Built" text,
"Location of the Church" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Parish (Prestegjeld) was built in 1907?
|
SELECT "Parish (Prestegjeld)" FROM table_62469 WHERE "Year Built" = '1907'
|
wikisql
|
CREATE TABLE table_name_90 (
builder VARCHAR,
works_number VARCHAR,
date VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the builder for 4/1906 and works number more than 199
|
SELECT builder FROM table_name_90 WHERE works_number > 199 AND date = "4/1906"
|
sql_create_context
|
CREATE TABLE policies (
policy_type_code VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the number of records of each policy type and its type code.
|
SELECT policy_type_code, COUNT(*) FROM policies GROUP BY policy_type_code
|
sql_create_context
|
CREATE TABLE table_72226 (
"Member" text,
"Week Arrived On Main Island" text,
"Week Sent To Third Island" text,
"Original Tribe" text,
"Tribe They Chose To Win" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many members arrived on the main island in week 4?
|
SELECT COUNT("Member") FROM table_72226 WHERE "Week Arrived On Main Island" = '4'
|
wikisql
|
CREATE TABLE musical (
Musical_ID int,
Name text,
Year int,
Award text,
Category text,
Nominee text,
Result text
)
CREATE TABLE actor (
Actor_ID int,
Name text,
Musical_ID int,
Character text,
Duration text,
age int
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Return a bar chart on how many musicals has each nominee been nominated for?
|
SELECT Nominee, COUNT(*) FROM musical GROUP BY Nominee
|
nvbench
|
CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
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 diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is patient 15257's last careunit when they visited the hospital first time?
|
SELECT transfers.careunit FROM transfers WHERE transfers.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 15257 AND NOT admissions.dischtime IS NULL ORDER BY admissions.admittime LIMIT 1) AND NOT transfers.careunit IS NULL ORDER BY transfers.intime DESC LIMIT 1
|
mimic_iii
|
CREATE TABLE table_64847 (
"Date" text,
"Course" text,
"Distance" text,
"Type" text,
"Winner" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who was the winner at Milan Circuit Race?
|
SELECT "Winner" FROM table_64847 WHERE "Course" = 'milan circuit race'
|
wikisql
|
CREATE TABLE table_12119 (
"Mininera DFL" text,
"Wins" real,
"Byes" real,
"Losses" real,
"Draws" real,
"Against" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- WHAT IS THE HIGHEST WINS WITH AGAINST SMALLER THAN 924, LOSSES SMALLER THAN 2?
|
SELECT MAX("Wins") FROM table_12119 WHERE "Against" < '924' AND "Losses" < '2'
|
wikisql
|
CREATE TABLE ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
CREATE TABLE SuggestedEditVotes (
Id number,
SuggestedEditId number,
UserId number,
VoteTypeId number,
CreationDate time,
TargetUserId number,
TargetRepChange number
)
CREATE TABLE CloseAsOffTopicReasonTypes (
Id number,
IsUniversal boolean,
InputTitle text,
MarkdownInputGuidance text,
MarkdownPostOwnerGuidance text,
MarkdownPrivilegedUserGuidance text,
MarkdownConcensusDescription text,
CreationDate time,
CreationModeratorId number,
ApprovalDate time,
ApprovalModeratorId number,
DeactivationDate time,
DeactivationModeratorId number
)
CREATE TABLE VoteTypes (
Id number,
Name text
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE PendingFlags (
Id number,
FlagTypeId number,
PostId number,
CreationDate time,
CloseReasonTypeId number,
CloseAsOffTopicReasonTypeId number,
DuplicateOfQuestionId number,
BelongsOnBaseHostAddress text
)
CREATE TABLE PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
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,
LastEditDate time,
LastActivityDate time,
Title text,
Tags text,
AnswerCount number,
CommentCount number,
FavoriteCount number,
ClosedDate time,
CommunityOwnedDate time,
ContentLicense text
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE ReviewTaskResultTypes (
Id number,
Name text,
Description text
)
CREATE TABLE TagSynonyms (
Id number,
SourceTagName text,
TargetTagName text,
CreationDate time,
OwnerUserId number,
AutoRenameCount number,
LastAutoRename time,
Score number,
ApprovedByUserId number,
ApprovalDate time
)
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
CREATE TABLE SuggestedEdits (
Id number,
PostId number,
CreationDate time,
ApprovalDate time,
RejectionDate time,
OwnerUserId number,
Comment text,
Text text,
Title text,
Tags text,
RevisionGUID other
)
CREATE TABLE PostHistory (
Id number,
PostHistoryTypeId number,
PostId number,
RevisionGUID other,
CreationDate time,
UserId number,
UserDisplayName text,
Comment text,
Text text,
ContentLicense text
)
CREATE TABLE PostFeedback (
Id number,
PostId number,
IsAnonymous boolean,
VoteTypeId number,
CreationDate time
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
CREATE TABLE Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE Users (
Id number,
Reputation number,
CreationDate time,
DisplayName text,
LastAccessDate time,
WebsiteUrl text,
Location text,
AboutMe text,
Views number,
UpVotes number,
DownVotes number,
ProfileImageUrl text,
EmailHash text,
AccountId number
)
CREATE TABLE PostTypes (
Id number,
Name text
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostsWithDeleted (
Id number,
PostTypeId number,
AcceptedAnswerId number,
ParentId number,
CreationDate time,
DeletionDate time,
Score number,
ViewCount number,
Body text,
OwnerUserId number,
OwnerDisplayName text,
LastEditorUserId number,
LastEditorDisplayName text,
LastEditDate time,
LastActivityDate time,
Title text,
Tags text,
AnswerCount number,
CommentCount number,
FavoriteCount number,
ClosedDate time,
CommunityOwnedDate time,
ContentLicense text
)
CREATE TABLE Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Users by number of famous question badges.
|
SELECT DisplayName, COUNT(*) AS number FROM Posts INNER JOIN Users ON Posts.OwnerUserId = Users.Id GROUP BY DisplayName ORDER BY number DESC
|
sede
|
CREATE TABLE table_203_305 (
id number,
"round" number,
"#" number,
"player" text,
"nationality" text,
"college/junior/club team (league)" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- list each player drafted from canada .
|
SELECT "player" FROM table_203_305 WHERE "nationality" = 'canada'
|
squall
|
CREATE TABLE table_42156 (
"Season" real,
"Series" text,
"Team" text,
"Races" real,
"Wins" real,
"Points" text,
"Position" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the Series in 2009?
|
SELECT "Series" FROM table_42156 WHERE "Season" = '2009'
|
wikisql
|
CREATE TABLE table_name_50 (
date VARCHAR,
away_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the date when the away team was carlisle united?
|
SELECT date FROM table_name_50 WHERE away_team = "carlisle united"
|
sql_create_context
|
CREATE TABLE table_30578 (
"Pick #" real,
"Player" text,
"Position" text,
"Nationality" text,
"NHL team" text,
"College/junior/club team" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What nationality is listed when the college/junior/club team is oshawa generals (ohl)?
|
SELECT "Nationality" FROM table_30578 WHERE "College/junior/club team" = 'Oshawa Generals (OHL)'
|
wikisql
|
CREATE TABLE table_name_18 (
away_team VARCHAR,
home_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the score of the away team that played home team Geelong?
|
SELECT away_team AS score FROM table_name_18 WHERE home_team = "geelong"
|
sql_create_context
|
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- count the amount of hospital visits for patient 029-27704 during this year.
|
SELECT COUNT(DISTINCT patient.patienthealthsystemstayid) FROM patient WHERE patient.uniquepid = '029-27704' AND DATETIME(patient.hospitaladmittime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-0 year')
|
eicu
|
CREATE TABLE table_name_20 (
country VARCHAR,
airport VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which country has the Narita International Airport?
|
SELECT country FROM table_name_20 WHERE airport = "narita international airport"
|
sql_create_context
|
CREATE TABLE table_14655 (
"City" text,
"Province/Region" text,
"Country" text,
"IATA" text,
"ICAO" text,
"Airport" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which city has an IATA of tsa?
|
SELECT "City" FROM table_14655 WHERE "IATA" = 'tsa'
|
wikisql
|
CREATE TABLE table_name_89 (
played INTEGER,
lost VARCHAR,
goal_difference VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the highest number played when there were less than 13 losses and a goal difference of +46?
|
SELECT MAX(played) FROM table_name_89 WHERE lost < 13 AND goal_difference = "+46"
|
sql_create_context
|
CREATE TABLE dependent (
Dependent_name VARCHAR,
relationship VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- find all dependent names who have a spouse relation with some employee.
|
SELECT Dependent_name FROM dependent WHERE relationship = 'Spouse'
|
sql_create_context
|
CREATE TABLE table_name_52 (
constructor VARCHAR,
engine_† VARCHAR,
driver VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What constructor has an engine of cosworth cr-2 and a driver of luciano burti?
|
SELECT constructor FROM table_name_52 WHERE engine_† = "cosworth cr-2" AND driver = "luciano burti"
|
sql_create_context
|
CREATE TABLE table_204_886 (
id number,
"rank" number,
"swimmer" text,
"country" text,
"time" text,
"note" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many competitors from venezuela qualified for the final ?
|
SELECT COUNT("swimmer") FROM table_204_886 WHERE "country" = 'venezuela'
|
squall
|
CREATE TABLE Reservations (
Code INTEGER,
Room TEXT,
CheckIn TEXT,
CheckOut TEXT,
Rate REAL,
LastName TEXT,
FirstName TEXT,
Adults INTEGER,
Kids INTEGER
)
CREATE TABLE Rooms (
RoomId TEXT,
roomName TEXT,
beds INTEGER,
bedType TEXT,
maxOccupancy INTEGER,
basePrice INTEGER,
decor TEXT
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Draw a bar chart for what is the average base price of rooms, for each bed type?, display x axis in asc order.
|
SELECT bedType, AVG(basePrice) FROM Rooms GROUP BY bedType ORDER BY bedType
|
nvbench
|
CREATE TABLE table_29005 (
"Pick #" real,
"Player" text,
"Position" text,
"Nationality" text,
"NHL team" text,
"College/junior/club team" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the nhl team for the player john maclean?
|
SELECT "NHL team" FROM table_29005 WHERE "Player" = 'John MacLean'
|
wikisql
|
CREATE TABLE table_name_42 (
original_name VARCHAR,
singer_s_ VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the original name for the song performed by Brad Kavanagh?
|
SELECT original_name FROM table_name_42 WHERE singer_s_ = "brad kavanagh"
|
sql_create_context
|
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
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,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- the first time patient 011-55939 was diagnosed during the last year with hyperglycemia - stress related?
|
SELECT diagnosis.diagnosistime FROM diagnosis WHERE diagnosis.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '011-55939')) AND diagnosis.diagnosisname = 'hyperglycemia - stress related' AND DATETIME(diagnosis.diagnosistime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-1 year') ORDER BY diagnosis.diagnosistime LIMIT 1
|
eicu
|
CREATE TABLE table_name_73 (
mountain_peak VARCHAR,
location VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the mountain peak when the location is 37.5775 n 105.4856 w?
|
SELECT mountain_peak FROM table_name_73 WHERE location = "37.5775°n 105.4856°w"
|
sql_create_context
|
CREATE TABLE table_46332 (
"Round" real,
"Pick #" real,
"Player" text,
"Position" text,
"College" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which the highest Round has a Player of mike williams, and a Pick # larger than 4?
|
SELECT MAX("Round") FROM table_46332 WHERE "Player" = 'mike williams' AND "Pick #" > '4'
|
wikisql
|
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE ReviewTaskResultTypes (
Id number,
Name text,
Description text
)
CREATE TABLE Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE PendingFlags (
Id number,
FlagTypeId number,
PostId number,
CreationDate time,
CloseReasonTypeId number,
CloseAsOffTopicReasonTypeId number,
DuplicateOfQuestionId number,
BelongsOnBaseHostAddress text
)
CREATE TABLE PostFeedback (
Id number,
PostId number,
IsAnonymous boolean,
VoteTypeId number,
CreationDate time
)
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,
LastEditDate time,
LastActivityDate time,
Title text,
Tags text,
AnswerCount number,
CommentCount number,
FavoriteCount number,
ClosedDate time,
CommunityOwnedDate time,
ContentLicense text
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostTypes (
Id number,
Name text
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE SuggestedEditVotes (
Id number,
SuggestedEditId number,
UserId number,
VoteTypeId number,
CreationDate time,
TargetUserId number,
TargetRepChange number
)
CREATE TABLE VoteTypes (
Id number,
Name text
)
CREATE TABLE PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
CREATE TABLE Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE PostsWithDeleted (
Id number,
PostTypeId number,
AcceptedAnswerId number,
ParentId number,
CreationDate time,
DeletionDate time,
Score number,
ViewCount number,
Body text,
OwnerUserId number,
OwnerDisplayName text,
LastEditorUserId number,
LastEditorDisplayName text,
LastEditDate time,
LastActivityDate time,
Title text,
Tags text,
AnswerCount number,
CommentCount number,
FavoriteCount number,
ClosedDate time,
CommunityOwnedDate time,
ContentLicense text
)
CREATE TABLE CloseAsOffTopicReasonTypes (
Id number,
IsUniversal boolean,
InputTitle text,
MarkdownInputGuidance text,
MarkdownPostOwnerGuidance text,
MarkdownPrivilegedUserGuidance text,
MarkdownConcensusDescription text,
CreationDate time,
CreationModeratorId number,
ApprovalDate time,
ApprovalModeratorId number,
DeactivationDate time,
DeactivationModeratorId number
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE Users (
Id number,
Reputation number,
CreationDate time,
DisplayName text,
LastAccessDate time,
WebsiteUrl text,
Location text,
AboutMe text,
Views number,
UpVotes number,
DownVotes number,
ProfileImageUrl text,
EmailHash text,
AccountId number
)
CREATE TABLE SuggestedEdits (
Id number,
PostId number,
CreationDate time,
ApprovalDate time,
RejectionDate time,
OwnerUserId number,
Comment text,
Text text,
Title text,
Tags text,
RevisionGUID other
)
CREATE TABLE TagSynonyms (
Id number,
SourceTagName text,
TargetTagName text,
CreationDate time,
OwnerUserId number,
AutoRenameCount number,
LastAutoRename time,
Score number,
ApprovedByUserId number,
ApprovalDate time
)
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostHistory (
Id number,
PostHistoryTypeId number,
PostId number,
RevisionGUID other,
CreationDate time,
UserId number,
UserDisplayName text,
Comment text,
Text text,
ContentLicense text
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Top 50 users from France.
|
SELECT ROW_NUMBER() OVER (ORDER BY Reputation DESC) AS "#", Id AS "user_link", Reputation, Location FROM Users WHERE LOWER(Location) LIKE '%france%' OR UPPER(Location) LIKE '%france' ORDER BY Reputation DESC LIMIT 2500
|
sede
|
CREATE TABLE gwyjzb (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID number,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_CLINIC_ID text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE fgwyjzb (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID number,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 在09年2月17到日2015年11月4日内这段时间，医疗机构3153321的统筹金额消耗最多的29个科室都有哪些？
|
SELECT gwyjzb.MED_ORG_DEPT_CD, gwyjzb.MED_ORG_DEPT_NM FROM gwyjzb JOIN t_kc24 ON gwyjzb.MED_CLINIC_ID = t_kc24.MED_CLINIC_ID WHERE gwyjzb.MED_SER_ORG_NO = '3153321' AND t_kc24.CLINIC_SLT_DATE BETWEEN '2009-02-17' AND '2015-11-04' GROUP BY gwyjzb.MED_ORG_DEPT_CD ORDER BY SUM(t_kc24.OVE_PAY) DESC LIMIT 29 UNION SELECT fgwyjzb.MED_ORG_DEPT_CD, fgwyjzb.MED_ORG_DEPT_NM FROM fgwyjzb JOIN t_kc24 ON fgwyjzb.MED_CLINIC_ID = t_kc24.MED_CLINIC_ID WHERE fgwyjzb.MED_SER_ORG_NO = '3153321' AND t_kc24.CLINIC_SLT_DATE BETWEEN '2009-02-17' AND '2015-11-04' GROUP BY fgwyjzb.MED_ORG_DEPT_CD ORDER BY SUM(t_kc24.OVE_PAY) DESC LIMIT 29
|
css
|
CREATE TABLE ref_colors (
color_code text,
color_description text
)
CREATE TABLE characteristics (
characteristic_id number,
characteristic_type_code text,
characteristic_data_type text,
characteristic_name text,
other_characteristic_details text
)
CREATE TABLE ref_characteristic_types (
characteristic_type_code text,
characteristic_type_description text
)
CREATE TABLE product_characteristics (
product_id number,
characteristic_id number,
product_characteristic_value text
)
CREATE TABLE products (
product_id number,
color_code text,
product_category_code text,
product_name text,
typical_buying_price text,
typical_selling_price text,
product_description text,
other_product_details text
)
CREATE TABLE ref_product_categories (
product_category_code text,
product_category_description text,
unit_of_measure text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What are characteristic names used at least twice across all products?
|
SELECT t3.characteristic_name FROM products AS t1 JOIN product_characteristics AS t2 ON t1.product_id = t2.product_id JOIN characteristics AS t3 ON t2.characteristic_id = t3.characteristic_id GROUP BY t3.characteristic_name HAVING COUNT(*) >= 2
|
spider
|
CREATE TABLE table_80283 (
"Player" text,
"Height" real,
"Position" text,
"Year born" real,
"Current Club" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What position does Mario Kasun play?
|
SELECT "Position" FROM table_80283 WHERE "Player" = 'mario kasun'
|
wikisql
|
CREATE TABLE program (
program_id int,
name varchar,
college varchar,
introduction varchar
)
CREATE TABLE program_requirement (
program_id int,
category varchar,
min_credit int,
additional_req varchar
)
CREATE TABLE student_record (
student_id int,
course_id int,
semester int,
grade varchar,
how varchar,
transfer_source varchar,
earn_credit varchar,
repeat_term varchar,
test_id varchar
)
CREATE TABLE offering_instructor (
offering_instructor_id int,
offering_id int,
instructor_id int
)
CREATE TABLE course_prerequisite (
pre_course_id int,
course_id int
)
CREATE TABLE ta (
campus_job_id int,
student_id int,
location varchar
)
CREATE TABLE instructor (
instructor_id int,
name varchar,
uniqname varchar
)
CREATE TABLE course_offering (
offering_id int,
course_id int,
semester int,
section_number int,
start_time time,
end_time time,
monday varchar,
tuesday varchar,
wednesday varchar,
thursday varchar,
friday varchar,
saturday varchar,
sunday varchar,
has_final_project varchar,
has_final_exam varchar,
textbook varchar,
class_address varchar,
allow_audit varchar
)
CREATE TABLE comment_instructor (
instructor_id int,
student_id int,
score int,
comment_text varchar
)
CREATE TABLE jobs (
job_id int,
job_title varchar,
description varchar,
requirement varchar,
city varchar,
state varchar,
country varchar,
zip int
)
CREATE TABLE course (
course_id int,
name varchar,
department varchar,
number varchar,
credits varchar,
advisory_requirement varchar,
enforced_requirement varchar,
description varchar,
num_semesters int,
num_enrolled int,
has_discussion varchar,
has_lab varchar,
has_projects varchar,
has_exams varchar,
num_reviews int,
clarity_score int,
easiness_score int,
helpfulness_score int
)
CREATE TABLE program_course (
program_id int,
course_id int,
workload int,
category varchar
)
CREATE TABLE area (
course_id int,
area varchar
)
CREATE TABLE semester (
semester_id int,
semester varchar,
year int
)
CREATE TABLE requirement (
requirement_id int,
requirement varchar,
college varchar
)
CREATE TABLE course_tags_count (
course_id int,
clear_grading int,
pop_quiz int,
group_projects int,
inspirational int,
long_lectures int,
extra_credit int,
few_tests int,
good_feedback int,
tough_tests int,
heavy_papers int,
cares_for_students int,
heavy_assignments int,
respected int,
participation int,
heavy_reading int,
tough_grader int,
hilarious int,
would_take_again int,
good_lecture int,
no_skip int
)
CREATE TABLE gsi (
course_offering_id int,
student_id int
)
CREATE TABLE student (
student_id int,
lastname varchar,
firstname varchar,
program_id int,
declare_major varchar,
total_credit int,
total_gpa float,
entered_as varchar,
admit_term int,
predicted_graduation_semester int,
degree varchar,
minor varchar,
internship varchar
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What Other classes will be offered over the Winter ?
|
SELECT DISTINCT course.department, course.name, course.number FROM course INNER JOIN course_offering ON course.course_id = course_offering.course_id INNER JOIN semester ON semester.semester_id = course_offering.semester INNER JOIN program_course ON program_course.course_id = course_offering.course_id WHERE program_course.category LIKE '%Other%' AND semester.semester = 'Winter' AND semester.year = 2017
|
advising
|
CREATE TABLE mzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH text,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TXBZ number,
TZ number,
WDBZ number,
XL number,
ZSEBZ number,
ZZBZ number,
ZZYSGH text,
mzjzjlb_id number
)
CREATE TABLE jyjgzbb (
BGDH text,
BGRQ time,
CKZFWDX text,
CKZFWSX number,
CKZFWXX number,
JCFF text,
JCRGH text,
JCRXM text,
JCXMMC text,
JCZBDM text,
JCZBJGDL number,
JCZBJGDW text,
JCZBJGDX text,
JCZBMC text,
JLDW text,
JYRQ time,
JYZBLSH text,
SBBM text,
SHRGH text,
SHRXM text,
YLJGDM text,
YQBH text,
YQMC text
)
CREATE TABLE zyjzjlb (
CYBQDM text,
CYBQMC text,
CYCWH text,
CYKSDM text,
CYKSMC text,
CYSJ time,
CYZTDM number,
HZXM text,
JZKSDM text,
JZKSMC text,
JZLSH text,
KH text,
KLX number,
MZBMLX number,
MZJZLSH text,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYCWH text,
RYDJSJ time,
RYSJ time,
RYTJDM number,
RYTJMC text,
RZBQDM text,
RZBQMC text,
WDBZ number,
YLJGDM text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text
)
CREATE TABLE hz_info (
KH text,
KLX number,
RYBH text,
YLJGDM text
)
CREATE TABLE jybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH text,
BGJGDM text,
BGJGMC text,
BGRGH text,
BGRQ time,
BGRXM text,
BGSJ time,
CJRQ time,
JSBBRQSJ time,
JSBBSJ time,
JYBBH text,
JYJGMC text,
JYJSGH text,
JYJSQM text,
JYKSBM text,
JYKSMC text,
JYLX number,
JYRQ time,
JYSQJGMC text,
JYXMDM text,
JYXMMC text,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM text,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text
)
CREATE TABLE person_info (
CSD text,
CSRQ time,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
MZDM text,
MZMC text,
RYBH text,
XBDM number,
XBMC text,
XLDM text,
XLMC text,
XM text,
ZYLBDM text,
ZYMC text
)
CREATE TABLE hz_info_mzjzjlb (
JZLSH number,
YLJGDM number,
mzjzjlb_id number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 列出在2015年5月8日到17年10月15日内病号葛承泽所有检验结果指标记录中的仪器编号以及名称都是啥？
|
SELECT jyjgzbb.YQBH, jyjgzbb.YQMC FROM person_info JOIN hz_info JOIN mzjzjlb JOIN jybgb JOIN jyjgzbb JOIN hz_info_mzjzjlb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = hz_info_mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND hz_info_mzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH AND hz_info_mzjzjlb.JZLSH = mzjzjlb.JZLSH AND hz_info_mzjzjlb.YLJGDM = hz_info_mzjzjlb.YLJGDM AND hz_info_mzjzjlb.JZLSH = mzjzjlb.JZLSH AND hz_info_mzjzjlb.mzjzjlb_id = mzjzjlb.mzjzjlb_id WHERE person_info.XM = '葛承泽' AND jyjgzbb.JYRQ BETWEEN '2015-05-08' AND '2017-10-15' UNION SELECT jyjgzbb.YQBH, jyjgzbb.YQMC FROM person_info JOIN hz_info JOIN zyjzjlb JOIN jybgb JOIN jyjgzbb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = zyjzjlb.YLJGDM AND hz_info.KH = zyjzjlb.KH AND hz_info.KLX = zyjzjlb.KLX AND zyjzjlb.YLJGDM = jybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = jybgb.JZLSH_ZYJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH WHERE person_info.XM = '葛承泽' AND jyjgzbb.JYRQ BETWEEN '2015-05-08' AND '2017-10-15'
|
css
|
CREATE TABLE table_45684 (
"Wicket" text,
"Runs" text,
"Batting partners" text,
"Batting team" text,
"Fielding team" text,
"Venue" text,
"Season" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who was the batting team in the 2006 season?
|
SELECT "Batting team" FROM table_45684 WHERE "Season" = '2006'
|
wikisql
|
CREATE TABLE table_35054 (
"Round" real,
"Player" text,
"Position" text,
"Nationality" text,
"College/Junior/Club Team" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which round was Robert Deciantis taken in?
|
SELECT "Round" FROM table_35054 WHERE "Player" = 'robert deciantis'
|
wikisql
|
CREATE TABLE artist (
artist_name varchar2(50),
country varchar2(20),
gender varchar2(20),
preferred_genre varchar2(50)
)
CREATE TABLE song (
song_name varchar2(50),
artist_name varchar2(50),
country varchar2(20),
f_id number(10),
genre_is varchar2(20),
rating number(10),
languages varchar2(20),
releasedate Date,
resolution number(10)
)
CREATE TABLE files (
f_id number(10),
artist_name varchar2(50),
file_size varchar2(20),
duration varchar2(20),
formats varchar2(20)
)
CREATE TABLE genre (
g_name varchar2(20),
rating varchar2(10),
most_popular_in varchar2(50)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Show the shortest duration and lowest rating of songs grouped by genre using a bar chart.
|
SELECT MIN(T1.duration), MIN(T2.rating) FROM files AS T1 JOIN song AS T2 ON T1.f_id = T2.f_id GROUP BY MIN(T1.duration)
|
nvbench
|
CREATE TABLE jybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH text,
BGJGDM text,
BGJGMC text,
BGRGH text,
BGRQ time,
BGRXM text,
BGSJ time,
CJRQ time,
JSBBRQSJ time,
JSBBSJ time,
JYBBH text,
JYJGMC text,
JYJSGH text,
JYJSQM text,
JYKSBM text,
JYKSMC text,
JYLX number,
JYRQ time,
JYSQJGMC text,
JYXMDM text,
JYXMMC text,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM text,
YLJGDM_ZYJZJLB text
)
CREATE TABLE mzjzjlb_jybgb (
YLJGDM_MZJZJLB text,
BGDH number,
YLJGDM number
)
CREATE TABLE mzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH text,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TXBZ number,
TZ number,
WDBZ number,
XL number,
YLJGDM text,
ZSEBZ number,
ZZBZ number,
ZZYSGH text
)
CREATE TABLE zyjzjlb (
CYBQDM text,
CYBQMC text,
CYCWH text,
CYKSDM text,
CYKSMC text,
CYSJ time,
CYZTDM number,
HZXM text,
JZKSDM text,
JZKSMC text,
JZLSH text,
KH text,
KLX number,
MZBMLX number,
MZJZLSH text,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYCWH text,
RYDJSJ time,
RYSJ time,
RYTJDM number,
RYTJMC text,
RZBQDM text,
RZBQMC text,
WDBZ number,
YLJGDM text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text
)
CREATE TABLE person_info (
CSD text,
CSRQ time,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
MZDM text,
MZMC text,
RYBH text,
XBDM number,
XBMC text,
XLDM text,
XLMC text,
XM text,
ZYLBDM text,
ZYMC text
)
CREATE TABLE hz_info (
KH text,
KLX number,
RYBH text,
YLJGDM text
)
CREATE TABLE jyjgzbb (
BGDH text,
BGRQ time,
CKZFWDX text,
CKZFWSX number,
CKZFWXX number,
JCFF text,
JCRGH text,
JCRXM text,
JCXMMC text,
JCZBDM text,
JCZBJGDL number,
JCZBJGDW text,
JCZBJGDX text,
JCZBMC text,
JLDW text,
JYRQ time,
JYZBLSH text,
SBBM text,
SHRGH text,
SHRXM text,
YLJGDM text,
YQBH text,
YQMC text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 看看病患33309508颅部各项指标的检验结果怎么样
|
SELECT * FROM hz_info JOIN mzjzjlb JOIN jybgb JOIN jyjgzbb JOIN mzjzjlb_jybgb ON hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = mzjzjlb_jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH AND mzjzjlb_jybgb.YLJGDM = jybgb.YLJGDM AND mzjzjlb_jybgb.BGDH = jybgb.BGDH AND mzjzjlb_jybgb.YLJGDM = jybgb.YLJGDM AND mzjzjlb_jybgb.BGDH = jybgb.BGDH WHERE hz_info.RYBH = '33309508' AND jybgb.BBCJBW = '颅部' UNION SELECT * FROM hz_info JOIN zyjzjlb JOIN jybgb JOIN jyjgzbb ON hz_info.YLJGDM = zyjzjlb.YLJGDM AND hz_info.KH = zyjzjlb.KH AND hz_info.KLX = zyjzjlb.KLX AND zyjzjlb.YLJGDM = jybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = jybgb.JZLSH_ZYJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH WHERE hz_info.RYBH = '33309508' AND jybgb.BBCJBW = '颅部'
|
css
|
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the number of patients whose language is span and year of birth is less than 2074?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.language = "SPAN" AND demographic.dob_year < "2074"
|
mimicsql_data
|
CREATE TABLE student (
stuid number,
lname text,
fname text,
age number,
sex text,
major number,
advisor number,
city_code text
)
CREATE TABLE plays_games (
stuid number,
gameid number,
hours_played number
)
CREATE TABLE video_games (
gameid number,
gname text,
gtype text
)
CREATE TABLE sportsinfo (
stuid number,
sportname text,
hoursperweek number,
gamesplayed number,
onscholarship text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Show all video game types.
|
SELECT DISTINCT gtype FROM video_games
|
spider
|
CREATE TABLE College (
cName VARCHAR,
enr VARCHAR,
state VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the names of either colleges in LA with greater than 15000 size or in state AZ with less than 13000 enrollment.
|
SELECT cName FROM College WHERE enr < 13000 AND state = "AZ" UNION SELECT cName FROM College WHERE enr > 15000 AND state = "LA"
|
sql_create_context
|
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
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 labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what were the five most common medications prescribed to male patients in the 30s during the same hospital visit after they had been diagnosed with hyperlipidemia nec/nos in 2105?
|
SELECT t3.drug FROM (SELECT t2.drug, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM (SELECT admissions.subject_id, diagnoses_icd.charttime, admissions.hadm_id FROM diagnoses_icd JOIN admissions ON diagnoses_icd.hadm_id = admissions.hadm_id WHERE diagnoses_icd.icd9_code = (SELECT d_icd_diagnoses.icd9_code FROM d_icd_diagnoses WHERE d_icd_diagnoses.short_title = 'hyperlipidemia nec/nos') AND STRFTIME('%y', diagnoses_icd.charttime) = '2105') AS t1 JOIN (SELECT admissions.subject_id, prescriptions.drug, prescriptions.startdate, admissions.hadm_id FROM prescriptions JOIN admissions ON prescriptions.hadm_id = admissions.hadm_id WHERE admissions.subject_id IN (SELECT patients.subject_id FROM patients WHERE patients.gender = 'm') AND admissions.age BETWEEN 30 AND 39 AND STRFTIME('%y', prescriptions.startdate) = '2105') AS t2 ON t1.subject_id = t2.subject_id WHERE t1.charttime < t2.startdate AND t1.hadm_id = t2.hadm_id GROUP BY t2.drug) AS t3 WHERE t3.c1 <= 5
|
mimic_iii
|
CREATE TABLE Apartment_Buildings (
building_id INTEGER,
building_short_name CHAR(15),
building_full_name VARCHAR(80),
building_description VARCHAR(255),
building_address VARCHAR(255),
building_manager VARCHAR(50),
building_phone VARCHAR(80)
)
CREATE TABLE Apartments (
apt_id INTEGER,
building_id INTEGER,
apt_type_code CHAR(15),
apt_number CHAR(10),
bathroom_count INTEGER,
bedroom_count INTEGER,
room_count CHAR(5)
)
CREATE TABLE View_Unit_Status (
apt_id INTEGER,
apt_booking_id INTEGER,
status_date DATETIME,
available_yn BIT
)
CREATE TABLE Apartment_Bookings (
apt_booking_id INTEGER,
apt_id INTEGER,
guest_id INTEGER,
booking_status_code CHAR(15),
booking_start_date DATETIME,
booking_end_date DATETIME
)
CREATE TABLE Apartment_Facilities (
apt_id INTEGER,
facility_code CHAR(15)
)
CREATE TABLE Guests (
guest_id INTEGER,
gender_code CHAR(1),
guest_first_name VARCHAR(80),
guest_last_name VARCHAR(80),
date_of_birth DATETIME
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Plot how many booking start date by grouped by booking start date as a bar graph, order Y in ascending order.
|
SELECT booking_start_date, COUNT(booking_start_date) FROM Apartment_Bookings ORDER BY COUNT(booking_start_date)
|
nvbench
|
CREATE TABLE table_23292220_13 (
scores VARCHAR,
seans_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the score on the episode that had Russell Kane and Louise Redknapp on Sean's team?
|
SELECT scores FROM table_23292220_13 WHERE seans_team = "Russell Kane and Louise Redknapp"
|
sql_create_context
|
CREATE TABLE table_2208838_4 (
team VARCHAR,
average VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which team had an average of 20.4?
|
SELECT team FROM table_2208838_4 WHERE average = "20.4"
|
sql_create_context
|
CREATE TABLE table_24329520_4 (
fate_in_1832 VARCHAR,
county VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the fate in 1832 for pembrokeshire
|
SELECT fate_in_1832 FROM table_24329520_4 WHERE county = "Pembrokeshire"
|
sql_create_context
|
CREATE TABLE basketball_match (
team_id number,
school_id number,
team_name text,
acc_regular_season text,
acc_percent text,
acc_home text,
acc_road text,
all_games text,
all_games_percent number,
all_home text,
all_road text,
all_neutral text
)
CREATE TABLE university (
school_id number,
school text,
location text,
founded number,
affiliation text,
enrollment number,
nickname text,
primary_conference text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Return the name of the team and the acc during the regular season for the school that was founded the earliest.
|
SELECT t2.team_name, t2.acc_regular_season FROM university AS t1 JOIN basketball_match AS t2 ON t1.school_id = t2.school_id ORDER BY t1.founded LIMIT 1
|
spider
|
CREATE TABLE t_kc22 (
MED_EXP_DET_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
MED_CLINIC_ID text,
MED_EXP_BILL_ID text,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
DIRE_TYPE number,
CHA_ITEM_LEV number,
MED_INV_ITEM_TYPE text,
MED_DIRE_CD text,
MED_DIRE_NM text,
VAL_UNIT text,
DOSE_UNIT text,
DOSE_FORM text,
SPEC text,
USE_FRE text,
EACH_DOSAGE text,
QTY number,
UNIVALENT number,
AMOUNT number,
SELF_PAY_PRO number,
RER_SOL number,
SELF_PAY_AMO number,
UP_LIMIT_AMO number,
OVE_SELF_AMO number,
EXP_OCC_DATE time,
RECIPE_BILL_ID text,
FLX_MED_ORG_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
REF_STA_FLG number,
DATA_ID text,
SYNC_TIME time,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
TRADE_TYPE number,
STA_FLG number,
STA_DATE time,
REIMBURS_TYPE number,
FXBZ number,
REMOTE_SETTLE_FLG text
)
CREATE TABLE t_kc21 (
MED_CLINIC_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
COMP_ID text,
PERSON_ID text,
PERSON_NM text,
IDENTITY_CARD text,
SOC_SRT_CARD text,
PERSON_SEX number,
PERSON_AGE number,
IN_HOSP_DATE time,
OUT_HOSP_DATE time,
DIFF_PLACE_FLG number,
FLX_MED_ORG_ID text,
MED_SER_ORG_NO text,
CLINIC_TYPE text,
MED_TYPE number,
CLINIC_ID text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
INPT_AREA_BED text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
MAIN_COND_DES text,
INSU_TYPE text,
IN_HOSP_DAYS number,
MED_AMOUT number,
FERTILITY_STS number,
DATA_ID text,
SYNC_TIME time,
REIMBURSEMENT_FLG number,
HOSP_LEV number,
HOSP_STS number,
INSURED_IDENTITY number,
SERVANT_FLG text,
TRADE_TYPE number,
INSURED_STS text,
REMOTE_SETTLE_FLG text
)
CREATE TABLE t_kc24 (
MED_SAFE_PAY_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
MED_CLINIC_ID text,
REF_SLT_FLG number,
CLINIC_SLT_DATE time,
COMP_ID text,
PERSON_ID text,
FLX_MED_ORG_ID text,
INSU_TYPE text,
MED_AMOUT number,
PER_ACC_PAY number,
OVE_PAY number,
ILL_PAY number,
CIVIL_SUBSIDY number,
PER_SOL number,
PER_EXP number,
DATA_ID text,
SYNC_TIME time,
OUT_HOSP_DATE time,
CLINIC_ID text,
MED_TYPE number,
INSURED_STS text,
INSURED_IDENTITY number,
TRADE_TYPE number,
RECIPE_BILL_ID text,
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
RECEIVER_DEAL_ID text,
SENDER_REVOKE_ID text,
RECEIVER_REVOKE_ID text,
SENDER_OFFSET_ID text,
RECEIVER_OFFSET_ID text,
LAS_OVE_PAY number,
OVE_ADD_PAY number,
SUP_ADD_PAY number,
CKC102 number,
CASH_PAY number,
COM_ACC_PAY number,
ENT_ACC_PAY number,
ENT_PAY number,
COM_PAY number,
OLDC_FUND_PAY number,
SPE_FUND_PAY number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 孙文心病患在一三年八月十二日到一八年六月十一日内期间主要看哪位医生？
|
SELECT OUT_DIAG_DOC_CD, OUT_DIAG_DOC_NM FROM t_kc21 WHERE PERSON_NM = '孙文心' AND IN_HOSP_DATE BETWEEN '2013-08-12' AND '2018-06-11' GROUP BY OUT_DIAG_DOC_CD ORDER BY COUNT(*) DESC LIMIT 1
|
css
|
CREATE TABLE table_name_80 (
build_date VARCHAR,
prr_class VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the build date for PRR Class gf30a?
|
SELECT build_date FROM table_name_80 WHERE prr_class = "gf30a"
|
sql_create_context
|
CREATE TABLE table_2581397_4 (
distance VARCHAR,
race VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the distance in the Manikato Stakes race?
|
SELECT distance FROM table_2581397_4 WHERE race = "Manikato Stakes"
|
sql_create_context
|
CREATE TABLE table_31507 (
"Townland" text,
"Area( acres )" real,
"Barony" text,
"Civil parish" text,
"Poor law union" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many acres does the area of Lissagroom with Bandon as its poor law union cover?
|
SELECT "Area( acres )" FROM table_31507 WHERE "Poor law union" = 'Bandon' AND "Townland" = 'Lissagroom'
|
wikisql
|
CREATE TABLE Guests (
guest_first_name VARCHAR,
guest_last_name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Return the first names and last names of all guests
|
SELECT guest_first_name, guest_last_name FROM Guests
|
sql_create_context
|
CREATE TABLE table_178242_7 (
season VARCHAR,
the_mole VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which season is it when Milouska was the show's mole ?
|
SELECT season FROM table_178242_7 WHERE the_mole = "Milouska"
|
sql_create_context
|
CREATE TABLE table_train_248 (
"id" int,
"anemia" bool,
"prostate_specific_antigen_psa" float,
"hemoglobin_a1c_hba1c" float,
"body_weight" float,
"fasting_triglycerides" int,
"hyperlipidemia" bool,
"hgb" int,
"fasting_total_cholesterol" int,
"fasting_ldl_cholesterol" int,
"body_mass_index_bmi" float,
"NOUSE" float
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- anemia ( hgb < 11 )
|
SELECT * FROM table_train_248 WHERE anemia = 1 OR hgb < 11
|
criteria2sql
|
CREATE TABLE table_31537 (
"Place" real,
"Title" text,
"Platform" text,
"Publisher" text,
"Units sold" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Tell me the average units sold for square enix
|
SELECT AVG("Units sold") FROM table_31537 WHERE "Publisher" = 'square enix'
|
wikisql
|
CREATE TABLE t_kc21_t_kc22 (
MED_CLINIC_ID text,
MED_EXP_DET_ID number
)
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc21 (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SERVANT_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 根据出院诊断的不同以及科室的不同计算出0101657这家医院全部医疗就诊的记录里患者就诊的平均岁数是多少，把里面平均岁数超过23岁的记录留下来
|
SELECT t_kc21.MED_ORG_DEPT_NM, t_kc21.OUT_DIAG_DIS_NM, AVG(t_kc21.PERSON_AGE) FROM t_kc21 WHERE t_kc21.MED_SER_ORG_NO = '0101657' GROUP BY t_kc21.MED_ORG_DEPT_NM, t_kc21.OUT_DIAG_DIS_NM HAVING AVG(t_kc21.PERSON_AGE) > 23
|
css
|
CREATE TABLE table_23585197_3 (
position VARCHAR,
artist VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the position of the song thar genjor mcnell performed?
|
SELECT position FROM table_23585197_3 WHERE artist = "Genjor McNell"
|
sql_create_context
|
CREATE TABLE table_name_19 (
year VARCHAR,
country VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the year for the United Arab Emirates?
|
SELECT COUNT(year) FROM table_name_19 WHERE country = "united arab emirates"
|
sql_create_context
|
CREATE TABLE table_204_11 (
id number,
"year" number,
"fbs opponent" text,
"result" text,
"opponent's conference" text,
"opponent's head coach" text,
"charleston southern's head coach" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- who was the longest head coach ?
|
SELECT "charleston southern's head coach" FROM table_204_11 GROUP BY "charleston southern's head coach" ORDER BY COUNT(*) DESC LIMIT 1
|
squall
|
CREATE TABLE table_31075 (
"Train Number" real,
"Train Name" text,
"Departure Pune" text,
"Arrival Lonavla" text,
"Frequency" text,
"Origin" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what time does the train that arrives in lonavla at 22:22 depart pune
|
SELECT "Departure Pune" FROM table_31075 WHERE "Arrival Lonavla" = '22:22'
|
wikisql
|
CREATE TABLE table_3459 (
"Year" real,
"Starts" real,
"Wins" real,
"Top 5" real,
"Top 10" real,
"Poles" real,
"Avg. Start" text,
"Avg. Finish" text,
"Winnings" text,
"Position" text,
"Team(s)" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is every value for top 5 if average start is 21.9?
|
SELECT "Top 5" FROM table_3459 WHERE "Avg. Start" = '21.9'
|
wikisql
|
CREATE TABLE table_20527 (
"Institution" text,
"Location" text,
"Founded" real,
"Affiliation" text,
"Enrollment" real,
"Team Nickname" text,
"Primary conference" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What conference does Gonzaga University play in?
|
SELECT "Primary conference" FROM table_20527 WHERE "Institution" = 'Gonzaga University'
|
wikisql
|
CREATE TABLE table_67637 (
"Episode" text,
"First aired" text,
"Entrepreneur(s)" text,
"Company or product name" text,
"Money requested (\u00a3)" text,
"Investing Dragon(s)" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How much money did James Seddon request?
|
SELECT "Money requested (\u00a3)" FROM table_67637 WHERE "Entrepreneur(s)" = 'james seddon'
|
wikisql
|
CREATE TABLE table_39275 (
"Year" real,
"Class" text,
"Team" text,
"Points" real,
"Rank" text,
"Wins" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which rank has a team of Suzuki with under 16 points?
|
SELECT "Rank" FROM table_39275 WHERE "Team" = 'suzuki' AND "Points" < '16'
|
wikisql
|
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many patients whose procedure long title is other closed [endoscopic] biopsy of biliary duct or sphincter of oddi and lab test fluid is cerebrospinal fluid (csf)?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE procedures.long_title = "Other closed [endoscopic] biopsy of biliary duct or sphincter of Oddi" AND lab.fluid = "Cerebrospinal Fluid (CSF)"
|
mimicsql_data
|
CREATE TABLE zyjzjlb (
CYBQDM text,
CYBQMC text,
CYCWH text,
CYKSDM text,
CYKSMC text,
CYSJ time,
CYZTDM number,
HZXM text,
JZKSDM text,
JZKSMC text,
JZLSH text,
KH text,
KLX number,
MZBMLX number,
MZJZLSH text,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYCWH text,
RYDJSJ time,
RYSJ time,
RYTJDM number,
RYTJMC text,
RZBQDM text,
RZBQMC text,
WDBZ number,
YLJGDM text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text
)
CREATE TABLE hz_info (
KH text,
KLX number,
RYBH text,
YLJGDM text
)
CREATE TABLE hz_info_mzjzjlb (
JZLSH number,
YLJGDM number,
mzjzjlb_id number
)
CREATE TABLE mzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH text,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TXBZ number,
TZ number,
WDBZ number,
XL number,
ZSEBZ number,
ZZBZ number,
ZZYSGH text,
mzjzjlb_id number
)
CREATE TABLE person_info (
CSD text,
CSRQ time,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
MZDM text,
MZMC text,
RYBH text,
XBDM number,
XBMC text,
XLDM text,
XLMC text,
XM text,
ZYLBDM text,
ZYMC text
)
CREATE TABLE jyjgzbb (
BGDH text,
BGRQ time,
CKZFWDX text,
CKZFWSX number,
CKZFWXX number,
JCFF text,
JCRGH text,
JCRXM text,
JCXMMC text,
JCZBDM text,
JCZBJGDL number,
JCZBJGDW text,
JCZBJGDX text,
JCZBMC text,
JLDW text,
JYRQ time,
JYZBLSH text,
SBBM text,
SHRGH text,
SHRXM text,
YLJGDM text,
YQBH text,
YQMC text
)
CREATE TABLE jybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH text,
BGJGDM text,
BGJGMC text,
BGRGH text,
BGRQ time,
BGRXM text,
BGSJ time,
CJRQ time,
JSBBRQSJ time,
JSBBSJ time,
JYBBH text,
JYJGMC text,
JYJSGH text,
JYJSQM text,
JYKSBM text,
JYKSMC text,
JYLX number,
JYRQ time,
JYSQJGMC text,
JYXMDM text,
JYXMMC text,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM text,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 陶雅昶病患的身高和体重各是多少？
|
SELECT mzjzjlb.SG, mzjzjlb.TZ FROM person_info JOIN hz_info JOIN mzjzjlb JOIN hz_info_mzjzjlb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = hz_info_mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND hz_info_mzjzjlb.JZLSH = mzjzjlb.JZLSH AND hz_info_mzjzjlb.YLJGDM = hz_info_mzjzjlb.YLJGDM AND hz_info_mzjzjlb.JZLSH = mzjzjlb.JZLSH AND hz_info_mzjzjlb.mzjzjlb_id = mzjzjlb.mzjzjlb_id WHERE person_info.XM = '陶雅昶'
|
css
|
CREATE TABLE table_43987 (
"Name" text,
"Location" text,
"Country" text,
"Longest span" text,
"Pylons" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Where was the third bridge over panama canal?
|
SELECT "Location" FROM table_43987 WHERE "Name" = 'third bridge over panama canal'
|
wikisql
|
CREATE TABLE table_37600 (
"Rank" real,
"Airport" text,
"Code (IATA/ICAO)" text,
"Total Cargo (Metric Tonnes)" real,
"% Change" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What's the average total cargo in metric tonnes that has an 11.8% Change?
|
SELECT AVG("Total Cargo (Metric Tonnes)") FROM table_37600 WHERE "% Change" = '11.8%'
|
wikisql
|
CREATE TABLE table_36964 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" real,
"Time" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Opponent has a Time of 2:31?
|
SELECT "Opponent" FROM table_36964 WHERE "Time" = '2:31'
|
wikisql
|
CREATE TABLE table_49351 (
"Average population (x 1000)" text,
"Live births 1" text,
"Deaths 1" text,
"Natural change 1" text,
"Crude birth rate (per 1000)" real,
"Crude death rate (per 1000)" real,
"Natural change (per 1000)" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the crude birth rate (per 1000) when the live births 1 is 356 013?
|
SELECT SUM("Crude birth rate (per 1000)") FROM table_49351 WHERE "Live births 1" = '356 013'
|
wikisql
|
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those employees who did not have any job in the past, find hire_date and the average of manager_id bin hire_date by weekday, and visualize them by a bar chart, show by the y-axis from high to low.
|
SELECT HIRE_DATE, AVG(MANAGER_ID) FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) ORDER BY AVG(MANAGER_ID) DESC
|
nvbench
|
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- provide the number of patients whose admission type is elective and lab test fluid is ascites?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.admission_type = "ELECTIVE" AND lab.fluid = "Ascites"
|
mimicsql_data
|
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
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 d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the total dose of sc 24 fe ng that patient 6170 received on the current intensive care unit visit?
|
SELECT SUM(inputevents_cv.amount) FROM inputevents_cv WHERE inputevents_cv.icustay_id IN (SELECT icustays.icustay_id FROM icustays WHERE icustays.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 6170) AND icustays.outtime IS NULL) AND inputevents_cv.itemid IN (SELECT d_items.itemid FROM d_items WHERE d_items.label = 'sc 24 fe ng' AND d_items.linksto = 'inputevents_cv')
|
mimic_iii
|
CREATE TABLE code_description (
code varchar,
description text
)
CREATE TABLE time_zone (
time_zone_code text,
time_zone_name text,
hours_from_gmt int
)
CREATE TABLE restriction (
restriction_code text,
advance_purchase int,
stopovers text,
saturday_stay_required text,
minimum_stay int,
maximum_stay int,
application text,
no_discounts text
)
CREATE TABLE airport (
airport_code varchar,
airport_name text,
airport_location text,
state_code varchar,
country_name varchar,
time_zone_code varchar,
minimum_connect_time int
)
CREATE TABLE time_interval (
period text,
begin_time int,
end_time int
)
CREATE TABLE days (
days_code varchar,
day_name varchar
)
CREATE TABLE dual_carrier (
main_airline varchar,
low_flight_number int,
high_flight_number int,
dual_airline varchar,
service_name text
)
CREATE TABLE ground_service (
city_code text,
airport_code text,
transport_type text,
ground_fare int
)
CREATE TABLE food_service (
meal_code text,
meal_number int,
compartment text,
meal_description varchar
)
CREATE TABLE airline (
airline_code varchar,
airline_name text,
note text
)
CREATE TABLE airport_service (
city_code varchar,
airport_code varchar,
miles_distant int,
direction varchar,
minutes_distant int
)
CREATE TABLE state (
state_code text,
state_name text,
country_name text
)
CREATE TABLE compartment_class (
compartment varchar,
class_type varchar
)
CREATE TABLE city (
city_code varchar,
city_name varchar,
state_code varchar,
country_name varchar,
time_zone_code varchar
)
CREATE TABLE flight_stop (
flight_id int,
stop_number int,
stop_days text,
stop_airport text,
arrival_time int,
arrival_airline text,
arrival_flight_number int,
departure_time int,
departure_airline text,
departure_flight_number int,
stop_time int
)
CREATE TABLE class_of_service (
booking_class varchar,
rank int,
class_description text
)
CREATE TABLE flight (
aircraft_code_sequence text,
airline_code varchar,
airline_flight text,
arrival_time int,
connections int,
departure_time int,
dual_carrier text,
flight_days text,
flight_id int,
flight_number int,
from_airport varchar,
meal_code text,
stops int,
time_elapsed int,
to_airport varchar
)
CREATE TABLE date_day (
month_number int,
day_number int,
year int,
day_name varchar
)
CREATE TABLE month (
month_number int,
month_name text
)
CREATE TABLE aircraft (
aircraft_code varchar,
aircraft_description varchar,
manufacturer varchar,
basic_type varchar,
engines int,
propulsion varchar,
wide_body varchar,
wing_span int,
length int,
weight int,
capacity int,
pay_load int,
cruising_speed int,
range_miles int,
pressurized varchar
)
CREATE TABLE fare (
fare_id int,
from_airport varchar,
to_airport varchar,
fare_basis_code text,
fare_airline text,
restriction_code text,
one_direction_cost int,
round_trip_cost int,
round_trip_required varchar
)
CREATE TABLE fare_basis (
fare_basis_code text,
booking_class text,
class_type text,
premium text,
economy text,
discounted text,
night text,
season text,
basis_days text
)
CREATE TABLE equipment_sequence (
aircraft_code_sequence varchar,
aircraft_code varchar
)
CREATE TABLE flight_fare (
flight_id int,
fare_id int
)
CREATE TABLE flight_leg (
flight_id int,
leg_number int,
leg_flight int
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what are the flights between PITTSBURGH and SAN FRANCISCO
|
SELECT DISTINCT flight.flight_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, flight WHERE CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'PITTSBURGH' AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'SAN FRANCISCO' AND flight.from_airport = AIRPORT_SERVICE_0.airport_code AND flight.to_airport = AIRPORT_SERVICE_1.airport_code
|
atis
|
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- provide the number of patients whose admission type is urgent and admission location is trsf within this facility?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.admission_type = "URGENT" AND demographic.admission_location = "TRSF WITHIN THIS FACILITY"
|
mimicsql_data
|
CREATE TABLE table_11677100_18 (
school VARCHAR,
hometown VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What school did the player attend who's hometown was Montvale, NJ?
|
SELECT school FROM table_11677100_18 WHERE hometown = "Montvale, NJ"
|
sql_create_context
|
CREATE TABLE table_name_72 (
player VARCHAR,
place VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which player placed t10?
|
SELECT player FROM table_name_72 WHERE place = "t10"
|
sql_create_context
|
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
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- count the number of patients whose insurance is medicare and diagnosis short title is hydronephrosis
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.insurance = "Medicare" AND diagnoses.short_title = "Hydronephrosis"
|
mimicsql_data
|
CREATE TABLE table_name_82 (
wins INTEGER,
points VARCHAR,
draws VARCHAR,
club VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the highest number of wins for club Cd Orense, with points greater than 36 and more than 4 draws?
|
SELECT MAX(wins) FROM table_name_82 WHERE draws > 4 AND club = "cd orense" AND points > 36
|
sql_create_context
|
CREATE TABLE table_22883210_7 (
score VARCHAR,
date VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the total score for january 18?
|
SELECT COUNT(score) FROM table_22883210_7 WHERE date = "January 18"
|
sql_create_context
|
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