instruction
stringlengths 151
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| output
stringlengths 2
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| source
stringclasses 26
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|---|---|---|
CREATE TABLE table_3744 (
"Version" text,
"Codename" text,
"Edition" text,
"Code Base" text,
"Compatible repository" text,
"Default desktop environment" text,
"Release date" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the the codename when the code base is ubuntu 8.04 and the edition is fluxbox ce?
|
SELECT "Codename" FROM table_3744 WHERE "Code Base" = 'Ubuntu 8.04' AND "Edition" = 'Fluxbox CE'
|
wikisql
|
CREATE TABLE table_340 (
"Dep." text,
"Chief town" text,
"Arrondissement" text,
"Population (1999)" text,
"Area (Square km)" real,
"Pop density" real,
"Cantons" real,
"Communes" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many communes when the arrondissement is cosne-cours-sur-loire?
|
SELECT MIN("Communes") FROM table_340 WHERE "Arrondissement" = 'Cosne-Cours-sur-Loire'
|
wikisql
|
CREATE TABLE Sales (
sales_transaction_id INTEGER,
sales_details VARCHAR(255)
)
CREATE TABLE Lots (
lot_id INTEGER,
investor_id INTEGER,
lot_details VARCHAR(255)
)
CREATE TABLE Investors (
investor_id INTEGER,
Investor_details VARCHAR(255)
)
CREATE TABLE Transactions (
transaction_id INTEGER,
investor_id INTEGER,
transaction_type_code VARCHAR(10),
date_of_transaction DATETIME,
amount_of_transaction DECIMAL(19,4),
share_count VARCHAR(40),
other_details VARCHAR(255)
)
CREATE TABLE Ref_Transaction_Types (
transaction_type_code VARCHAR(10),
transaction_type_description VARCHAR(80)
)
CREATE TABLE Purchases (
purchase_transaction_id INTEGER,
purchase_details VARCHAR(255)
)
CREATE TABLE Transactions_Lots (
transaction_id INTEGER,
lot_id INTEGER
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Bin all date of transactions into the YEAR interval, and sum the share count of each bin Return the result using a line chart, sort by the X from low to high.
|
SELECT date_of_transaction, SUM(share_count) FROM Transactions ORDER BY date_of_transaction
|
nvbench
|
CREATE TABLE takes (
ID varchar(5),
course_id varchar(8),
sec_id varchar(8),
semester varchar(6),
year numeric(4,0),
grade varchar(2)
)
CREATE TABLE instructor (
ID varchar(5),
name varchar(20),
dept_name varchar(20),
salary numeric(8,2)
)
CREATE TABLE course (
course_id varchar(8),
title varchar(50),
dept_name varchar(20),
credits numeric(2,0)
)
CREATE TABLE section (
course_id varchar(8),
sec_id varchar(8),
semester varchar(6),
year numeric(4,0),
building varchar(15),
room_number varchar(7),
time_slot_id varchar(4)
)
CREATE TABLE teaches (
ID varchar(5),
course_id varchar(8),
sec_id varchar(8),
semester varchar(6),
year numeric(4,0)
)
CREATE TABLE student (
ID varchar(5),
name varchar(20),
dept_name varchar(20),
tot_cred numeric(3,0)
)
CREATE TABLE advisor (
s_ID varchar(5),
i_ID varchar(5)
)
CREATE TABLE classroom (
building varchar(15),
room_number varchar(7),
capacity numeric(4,0)
)
CREATE TABLE department (
dept_name varchar(20),
building varchar(15),
budget numeric(12,2)
)
CREATE TABLE prereq (
course_id varchar(8),
prereq_id varchar(8)
)
CREATE TABLE time_slot (
time_slot_id varchar(4),
day varchar(1),
start_hr numeric(2),
start_min numeric(2),
end_hr numeric(2),
end_min numeric(2)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the sum of credit value of courses with more than one prerequisite for each title? Return a bar chart, rank in asc by the x-axis.
|
SELECT title, SUM(credits) FROM course AS T1 JOIN prereq AS T2 ON T1.course_id = T2.course_id GROUP BY title ORDER BY title
|
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 lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the number of patients whose days of hospital stay is greater than 6 and procedure long title is cardiopulmonary resuscitation, not otherwise specified?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.days_stay > "6" AND procedures.long_title = "Cardiopulmonary resuscitation, not otherwise specified"
|
mimicsql_data
|
CREATE TABLE table_54872 (
"Party" text,
"Results 2004" text,
"Ifop 11/12/08" text,
"Ifop 1/9/09" text,
"Ipsos 3/14/09" text,
"CSA 4/16/09" text,
"OpinionWay 4/17/09" text,
"Ifop 4/24/09" text,
"Ipsos 5/2/09" text,
"Ifop 5/11/09" text,
"OpinionWay 5/11/09" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the csa 4/16/09 for opinionway being 4/17/09 of 12%
|
SELECT "CSA 4/16/09" FROM table_54872 WHERE "OpinionWay 4/17/09" = '12%'
|
wikisql
|
CREATE TABLE table_name_5 (
year_s__won VARCHAR,
to_par VARCHAR,
finish VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What year (s) won was +2 the To par, and t22 the finish?
|
SELECT year_s__won FROM table_name_5 WHERE to_par = "+2" AND finish = "t22"
|
sql_create_context
|
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 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 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.
-- what is the number of patients whose drug name is 5% dextrose?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE prescriptions.drug = "5% Dextrose"
|
mimicsql_data
|
CREATE TABLE t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_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_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 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_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.
-- 对于患者48319787高于3818.79元的医疗费总额的医疗记录,列出出院诊断疾病编码和名称有哪些?
|
SELECT t_kc21.OUT_DIAG_DIS_CD, t_kc21.OUT_DIAG_DIS_NM FROM t_kc21 WHERE t_kc21.PERSON_ID = '48319787' AND t_kc21.MED_CLINIC_ID IN (SELECT t_kc21_t_kc24.MED_CLINIC_ID FROM t_kc24 WHERE t_kc24.MED_AMOUT > 3818.79)
|
css
|
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 lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many male patients are prescribed chlorothiazide medication?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.gender = "M" AND prescriptions.drug = "Chlorothiazide"
|
mimicsql_data
|
CREATE TABLE writes (
aid int,
pid int
)
CREATE TABLE keyword (
keyword varchar,
kid int
)
CREATE TABLE domain_journal (
did int,
jid int
)
CREATE TABLE cite (
cited int,
citing int
)
CREATE TABLE domain_conference (
cid int,
did int
)
CREATE TABLE domain (
did int,
name varchar
)
CREATE TABLE publication_keyword (
kid int,
pid int
)
CREATE TABLE publication (
abstract varchar,
cid int,
citation_num int,
jid int,
pid int,
reference_num int,
title varchar,
year int
)
CREATE TABLE domain_keyword (
did int,
kid int
)
CREATE TABLE organization (
continent varchar,
homepage varchar,
name varchar,
oid int
)
CREATE TABLE conference (
cid int,
homepage varchar,
name varchar
)
CREATE TABLE domain_author (
aid int,
did int
)
CREATE TABLE domain_publication (
did int,
pid int
)
CREATE TABLE author (
aid int,
homepage varchar,
name varchar,
oid int
)
CREATE TABLE journal (
homepage varchar,
jid int,
name varchar
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- return me the number of papers published in the VLDB conference in each year .
|
SELECT COUNT(DISTINCT (publication.title)), publication.year FROM conference, publication WHERE conference.name = 'VLDB' AND publication.cid = conference.cid GROUP BY publication.year
|
academic
|
CREATE TABLE table_42961 (
"Year" real,
"Result" real,
"World Rank" text,
"Location" text,
"Date" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What's the lowest Year with a World Rank of 5th, with a Result greater than 20.31?
|
SELECT MIN("Year") FROM table_42961 WHERE "World Rank" = '5th' AND "Result" > '20.31'
|
wikisql
|
CREATE TABLE table_49208 (
"Game" real,
"Date" text,
"Team" text,
"Score" text,
"High points" text,
"High rebounds" text,
"High assists" text,
"Location Attendance" text,
"Series" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is High Points, when Game is '3'?
|
SELECT "High points" FROM table_49208 WHERE "Game" = '3'
|
wikisql
|
CREATE TABLE table_name_70 (
date VARCHAR,
year VARCHAR,
location VARCHAR,
winner VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Date, when Location is Polo Grounds, when Winner is Philadelphia Eagles, and when Year is 1948?
|
SELECT date FROM table_name_70 WHERE location = "polo grounds" AND winner = "philadelphia eagles" AND year = 1948
|
sql_create_context
|
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 treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
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 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 lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- the heartrate of patient 010-9767 has been ever greater than 116.0 on 03/01/2105?
|
SELECT COUNT(*) > 0 FROM vitalperiodic WHERE vitalperiodic.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '010-9767')) AND vitalperiodic.heartrate > 116.0 AND NOT vitalperiodic.heartrate IS NULL AND STRFTIME('%y-%m-%d', vitalperiodic.observationtime) = '2105-03-01'
|
eicu
|
CREATE TABLE table_19856 (
"Stage" real,
"Winner" text,
"General classification" text,
"Points classification" text,
"Mountains classification" text,
"Combination classification" text,
"Team classification" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- In how many stages did Jose Vicente Garcia Acosta won?
|
SELECT COUNT("Stage") FROM table_19856 WHERE "Winner" = 'Jose Vicente Garcia Acosta'
|
wikisql
|
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 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 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.
-- count the number of patients diagnosed with hypotension of hemodialysis who had long term care hospital discharge.
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.discharge_location = "LONG TERM CARE HOSPITAL" AND diagnoses.long_title = "Hypotension of hemodialysis"
|
mimicsql_data
|
CREATE TABLE table_name_91 (
country VARCHAR,
place VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the country that placed 4?
|
SELECT country FROM table_name_91 WHERE place = "4"
|
sql_create_context
|
CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
)
CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Visualize a bar chart about the distribution of All_Neutral and Team_ID , I want to display by the Y-axis from high to low please.
|
SELECT All_Neutral, Team_ID FROM basketball_match ORDER BY Team_ID DESC
|
nvbench
|
CREATE TABLE table_17131 (
"Series #" real,
"Season #" real,
"Title" text,
"Director(s)" text,
"Writer(s)" text,
"Original airdate" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many series has the title 'interior loft'?
|
SELECT COUNT("Series #") FROM table_17131 WHERE "Title" = 'Interior Loft'
|
wikisql
|
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many patients whose admission year is less than 2198 and drug name is risperidone oral solution?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.admityear < "2198" AND prescriptions.drug = "Risperidone Oral Solution"
|
mimicsql_data
|
CREATE TABLE table_20140132_1 (
head_coach VARCHAR,
venue VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who is the head coach of the team who's venue is Lokomotiv?
|
SELECT head_coach FROM table_20140132_1 WHERE venue = "Lokomotiv"
|
sql_create_context
|
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 zyjzjlb_jybgb (
YLJGDM_ZYJZJLB text,
BGDH number,
YLJGDM 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 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
)
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 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 医疗机构5099708的胸部肿瘤外科的记录里,在09年1月5日到20年10月20日期间内,共有多少住院的患者
|
SELECT COUNT(*) FROM zyjzjlb WHERE zyjzjlb.YLJGDM = '5099708' AND zyjzjlb.JZKSMC = '胸部肿瘤科' AND zyjzjlb.RYDJSJ BETWEEN '2009-01-05' AND '2020-10-20'
|
css
|
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_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_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.
-- 医疗机构6226694在2011年7月25日到2019年11月30日内险种类型为儿童的医疗就诊记录数量有多少?
|
SELECT COUNT(*) FROM t_kc21 WHERE t_kc21.MED_SER_ORG_NO = '6226694' AND t_kc21.IN_HOSP_DATE BETWEEN '2011-07-25' AND '2019-11-30' AND t_kc21.INSU_TYPE = '儿童'
|
css
|
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 t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_ID 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
)
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_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2008-09-21到2015-12-28的这段时间,医疗机构7987100的总金额和统筹总金额分别是多少
|
SELECT SUM(t_kc24.MED_AMOUT), SUM(t_kc24.OVE_PAY) FROM t_kc21 JOIN t_kc24 JOIN t_kc21_t_kc24 ON t_kc21.MED_CLINIC_ID = t_kc21_t_kc24.MED_CLINIC_ID AND t_kc21_t_kc24.MED_SAFE_PAY_ID = t_kc24.MED_SAFE_PAY_ID WHERE t_kc21.MED_SER_ORG_NO = '7987100' AND t_kc24.CLINIC_SLT_DATE BETWEEN '2008-09-21' AND '2015-12-28'
|
css
|
CREATE TABLE t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_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_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 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_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.
-- 范清宁这位患者自18.9.12起,到19.7.1止,看病从医保的个人账户总共支付了多少金额
|
SELECT SUM(t_kc24.PER_ACC_PAY) FROM t_kc21 JOIN t_kc24 JOIN t_kc21_t_kc24 ON t_kc21.MED_CLINIC_ID = t_kc21_t_kc24.MED_CLINIC_ID AND t_kc21_t_kc24.MED_SAFE_PAY_ID = t_kc24.MED_SAFE_PAY_ID WHERE t_kc21.PERSON_NM = '范清宁' AND t_kc24.CLINIC_SLT_DATE BETWEEN '2018-09-12' AND '2019-07-01'
|
css
|
CREATE TABLE checking (
balance INTEGER
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the average checking balance.
|
SELECT AVG(balance) FROM checking
|
sql_create_context
|
CREATE TABLE table_name_2 (
took_office INTEGER,
district VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the earliest date of taking office for district 22?
|
SELECT MIN(took_office) FROM table_name_2 WHERE district = 22
|
sql_create_context
|
CREATE TABLE table_name_26 (
english VARCHAR,
german VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which English has German of leben?
|
SELECT english FROM table_name_26 WHERE german = "leben"
|
sql_create_context
|
CREATE TABLE table_name_25 (
december INTEGER,
record VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the average day in December of the game with a 8-2-3 record?
|
SELECT AVG(december) FROM table_name_25 WHERE record = "8-2-3"
|
sql_create_context
|
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE 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 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 labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime 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 patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE d_icd_diagnoses (
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_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime 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_items (
row_id number,
itemid number,
label text,
linksto 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- tell me the first value of reticulocyte count, automated in patient 13806 in the last hospital visit?
|
SELECT labevents.valuenum FROM labevents WHERE labevents.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 13806 AND NOT admissions.dischtime IS NULL ORDER BY admissions.admittime DESC LIMIT 1) AND labevents.itemid IN (SELECT d_labitems.itemid FROM d_labitems WHERE d_labitems.label = 'reticulocyte count, automated') ORDER BY labevents.charttime LIMIT 1
|
mimic_iii
|
CREATE TABLE table_31402 (
"Rank" real,
"Country/Territory" text,
"Miss International" real,
"1st Runner-up" real,
"2nd Runner-up" real,
"3rd Runner-up" real,
"4th Runner-up" real,
"Semifinalists" real,
"Total" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the smallest quantity displayed under the title 'first runner-up'?
|
SELECT MIN("1st Runner-up") FROM table_31402
|
wikisql
|
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
)
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 d_icd_procedures (
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 d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto 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_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime 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
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- the last time during the first hospital visit patient 56635 received a rt/left heart card cath treatment?
|
SELECT procedures_icd.charttime FROM procedures_icd WHERE procedures_icd.icd9_code = (SELECT d_icd_procedures.icd9_code FROM d_icd_procedures WHERE d_icd_procedures.short_title = 'rt/left heart card cath') AND procedures_icd.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 56635 AND NOT admissions.dischtime IS NULL ORDER BY admissions.admittime LIMIT 1) ORDER BY procedures_icd.charttime DESC LIMIT 1
|
mimic_iii
|
CREATE TABLE table_26541 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text,
"Production code" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who directed 'Torn Between Two Lovers'?
|
SELECT "Directed by" FROM table_26541 WHERE "Title" = 'Torn Between Two Lovers'
|
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 diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE 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 elective hospital admissions who had clinic referral/premature as their admission location.
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.admission_type = "ELECTIVE" AND demographic.admission_location = "CLINIC REFERRAL/PREMATURE"
|
mimicsql_data
|
CREATE TABLE table_name_86 (
ethernet_ports VARCHAR,
name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the ethernet ports of the u150 appliance?
|
SELECT ethernet_ports FROM table_name_86 WHERE name = "u150"
|
sql_create_context
|
CREATE TABLE table_204_918 (
id number,
"week" number,
"date" text,
"opponent" text,
"result" text,
"record" text,
"attendance" number,
"bye" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the difference in attendance between the first game in september and the last game in january ?
|
SELECT ABS((SELECT "attendance" FROM table_204_918 WHERE "date" = 9 ORDER BY "date" LIMIT 1) - (SELECT "attendance" FROM table_204_918 WHERE "date" = 1 ORDER BY "date" DESC LIMIT 1))
|
squall
|
CREATE TABLE table_24600706_1 (
released INTEGER,
song VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the most released for right here, right now
|
SELECT MAX(released) FROM table_24600706_1 WHERE song = "Right Here, Right Now"
|
sql_create_context
|
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_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_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 t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_ID 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.
-- 在04年4月10日到2021年8月16日之间患者15314573买西药的次数共是多少?
|
SELECT COUNT(*) FROM t_kc21 JOIN t_kc22 ON t_kc21.MED_CLINIC_ID = t_kc22.MED_CLINIC_ID WHERE t_kc21.PERSON_ID = '15314573' AND t_kc22.STA_DATE BETWEEN '2004-04-10' AND '2021-08-16' AND t_kc22.MED_INV_ITEM_TYPE = '西药费'
|
css
|
CREATE TABLE table_76168 (
"Year" text,
"Winner" text,
"Points" real,
"Playoff result" text,
"Win #" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Playoff Result, when Winner is 'Alaska Aces', when Win # is greater than 1, when Points is less than 106, and when Year is '2011-12'?
|
SELECT "Playoff result" FROM table_76168 WHERE "Winner" = 'alaska aces' AND "Win #" > '1' AND "Points" < '106' AND "Year" = '2011-12'
|
wikisql
|
CREATE TABLE table_name_79 (
touchdowns INTEGER,
receptions VARCHAR,
games_started VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- With games started smaller than 16 plus receptions of 51, what is the smallest amount of touchdowns listed?
|
SELECT MIN(touchdowns) FROM table_name_79 WHERE receptions = 51 AND games_started < 16
|
sql_create_context
|
CREATE TABLE table_name_80 (
result VARCHAR,
score VARCHAR,
couple VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the result for Steve & Anna when the score was 21 (7, 7, 7)?
|
SELECT result FROM table_name_80 WHERE score = "21 (7, 7, 7)" AND couple = "steve & anna"
|
sql_create_context
|
CREATE TABLE table_name_37 (
bronze INTEGER,
total VARCHAR,
silver VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many bronzes were held by those with a total of 4 and less than 3 silvers.
|
SELECT SUM(bronze) FROM table_name_37 WHERE total = 4 AND silver < 3
|
sql_create_context
|
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
)
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 person_info_hz_info (
RYBH text,
KH number,
KLX number,
YLJGDM 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 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,
YLJGDM text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 潘乐山这位患者的补体C3在2003年5月12日到2009年10月10日期间的情况
|
SELECT * FROM person_info JOIN hz_info JOIN mzjzjlb JOIN jybgb JOIN jyjgzbb JOIN person_info_hz_info ON person_info.RYBH = person_info_hz_info.RYBH AND hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX WHERE person_info.XM = '潘乐山' AND jyjgzbb.JYRQ BETWEEN '2003-05-12' AND '2009-10-10' AND jyjgzbb.JCZBMC = '补体C3' UNION SELECT * FROM person_info JOIN hz_info JOIN zyjzjlb JOIN jybgb JOIN jyjgzbb JOIN person_info_hz_info ON person_info.RYBH = person_info_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 AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX WHERE person_info.XM = '潘乐山' AND jyjgzbb.JYRQ BETWEEN '2003-05-12' AND '2009-10-10' AND jyjgzbb.JCZBMC = '补体C3'
|
css
|
CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
)
CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those records from the products and each product's manufacturer, a bar chart shows the distribution of headquarter and the average of price , and group by attribute headquarter.
|
SELECT Headquarter, AVG(Price) FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY Headquarter
|
nvbench
|
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 mzjybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH number,
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,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM number,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB 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 zyjybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH number,
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,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM number,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text
)
CREATE TABLE hz_info (
KH text,
KLX number,
RYBH text,
YLJGDM text
)
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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 为韩飞双这个患者在05年4月12日到12年6月12日内检测过尿素的医务人员工号及姓名分别是什么?
|
SELECT jyjgzbb.JCRGH, jyjgzbb.JCRXM FROM person_info JOIN hz_info JOIN mzjzjlb JOIN zyjybgb JOIN jyjgzbb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = zyjybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = zyjybgb.JZLSH_MZJZJLB AND zyjybgb.YLJGDM = jyjgzbb.YLJGDM AND zyjybgb.BGDH = jyjgzbb.BGDH WHERE jyjgzbb.JYRQ BETWEEN '2005-04-12' AND '2012-06-12' AND person_info.XM = '韩飞双' AND jyjgzbb.JCZBMC = '尿素' UNION SELECT jyjgzbb.JCRGH, jyjgzbb.JCRXM FROM person_info JOIN hz_info JOIN mzjzjlb JOIN mzjybgb JOIN jyjgzbb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = mzjybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = mzjybgb.JZLSH_MZJZJLB AND mzjybgb.YLJGDM = jyjgzbb.YLJGDM AND mzjybgb.BGDH = jyjgzbb.BGDH WHERE jyjgzbb.JYRQ BETWEEN '2005-04-12' AND '2012-06-12' AND person_info.XM = '韩飞双' AND jyjgzbb.JCZBMC = '尿素' UNION SELECT jyjgzbb.JCRGH, jyjgzbb.JCRXM FROM person_info JOIN hz_info JOIN zyjzjlb JOIN zyjybgb 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 = zyjybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = zyjybgb.JZLSH_ZYJZJLB AND zyjybgb.YLJGDM = jyjgzbb.YLJGDM AND zyjybgb.BGDH = jyjgzbb.BGDH WHERE jyjgzbb.JYRQ BETWEEN '2005-04-12' AND '2012-06-12' AND person_info.XM = '韩飞双' AND jyjgzbb.JCZBMC = '尿素' UNION SELECT jyjgzbb.JCRGH, jyjgzbb.JCRXM FROM person_info JOIN hz_info JOIN zyjzjlb JOIN mzjybgb 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 = mzjybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = mzjybgb.JZLSH_ZYJZJLB AND mzjybgb.YLJGDM = jyjgzbb.YLJGDM AND mzjybgb.BGDH = jyjgzbb.BGDH WHERE jyjgzbb.JYRQ BETWEEN '2005-04-12' AND '2012-06-12' AND person_info.XM = '韩飞双' AND jyjgzbb.JCZBMC = '尿素'
|
css
|
CREATE TABLE table_40042 (
"Chapter" real,
"Chinese" text,
"Pinyin" text,
"English Translation" text,
"Articles" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Can you tell me the lowest Chapter that has the Pinyin of dehua, and the Articles smaller than 16?
|
SELECT MIN("Chapter") FROM table_40042 WHERE "Pinyin" = 'dehua' AND "Articles" < '16'
|
wikisql
|
CREATE TABLE table_21436373_12 (
stadium VARCHAR,
type_of_record VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- where was the total attendance-regular season record made
|
SELECT stadium FROM table_21436373_12 WHERE type_of_record = "Total attendance-Regular season"
|
sql_create_context
|
CREATE TABLE table_73333 (
"Administrative division" text,
"Area (km\u00b2) 2005" text,
"Population 2010 Census" real,
"Population 2011 SIAK Database" text,
"Population density (/km\u00b2 2010)" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the population density of bandung regency?
|
SELECT "Population density (/km\u00b2 2010)" FROM table_73333 WHERE "Administrative division" = 'Bandung Regency'
|
wikisql
|
CREATE TABLE airport_service (
city_code varchar,
airport_code varchar,
miles_distant int,
direction varchar,
minutes_distant int
)
CREATE TABLE days (
days_code varchar,
day_name varchar
)
CREATE TABLE airline (
airline_code varchar,
airline_name text,
note text
)
CREATE TABLE equipment_sequence (
aircraft_code_sequence varchar,
aircraft_code varchar
)
CREATE TABLE dual_carrier (
main_airline varchar,
low_flight_number int,
high_flight_number int,
dual_airline varchar,
service_name text
)
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 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 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 code_description (
code varchar,
description text
)
CREATE TABLE flight_leg (
flight_id int,
leg_number int,
leg_flight int
)
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 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 month (
month_number int,
month_name text
)
CREATE TABLE state (
state_code text,
state_name text,
country_name text
)
CREATE TABLE ground_service (
city_code text,
airport_code text,
transport_type text,
ground_fare int
)
CREATE TABLE time_interval (
period text,
begin_time int,
end_time int
)
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 food_service (
meal_code text,
meal_number int,
compartment text,
meal_description varchar
)
CREATE TABLE date_day (
month_number int,
day_number int,
year int,
day_name varchar
)
CREATE TABLE flight_fare (
flight_id int,
fare_id int
)
CREATE TABLE class_of_service (
booking_class varchar,
rank int,
class_description text
)
CREATE TABLE compartment_class (
compartment varchar,
class_type varchar
)
CREATE TABLE time_zone (
time_zone_code text,
time_zone_name text,
hours_from_gmt int
)
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 city (
city_code varchar,
city_name varchar,
state_code varchar,
country_name varchar,
time_zone_code varchar
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- i'd like a UA flight on wednesday from SAN FRANCISCO to BOSTON
|
SELECT DISTINCT flight.flight_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, date_day, days, flight WHERE ((CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'BOSTON' AND date_day.day_number = 23 AND date_day.month_number = 4 AND date_day.year = 1991 AND days.day_name = date_day.day_name AND flight.flight_days = days.days_code AND flight.to_airport = AIRPORT_SERVICE_1.airport_code) AND CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'SAN FRANCISCO' AND flight.from_airport = AIRPORT_SERVICE_0.airport_code) AND flight.airline_code = 'UA'
|
atis
|
CREATE TABLE hz_info (
KH text,
KLX number,
YLJGDM text,
RYBH text
)
CREATE TABLE jybgb (
YLJGDM text,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text,
BGDH text,
BGRQ time,
JYLX number,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SQRGH text,
SQRXM text,
BGRGH text,
BGRXM text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
JYKSBM text,
JYKSMC text,
BGJGDM text,
BGJGMC text,
SQRQ time,
CJRQ time,
JYRQ time,
BGSJ time,
BBDM text,
BBMC text,
JYBBH text,
BBZT number,
BBCJBW text,
JSBBSJ time,
JYXMMC text,
JYXMDM text,
JYSQJGMC text,
JYJGMC text,
JSBBRQSJ time,
JYJSQM text,
JYJSGH text
)
CREATE TABLE person_info (
RYBH text,
XBDM number,
XBMC text,
XM text,
CSRQ time,
CSD text,
MZDM text,
MZMC text,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
XLDM text,
XLMC text,
ZYLBDM text,
ZYMC text
)
CREATE TABLE mzjzjlb (
YLJGDM text,
JZLSH text,
KH text,
KLX number,
MJZH text,
HZXM text,
NLS number,
NLY number,
ZSEBZ number,
JZZTDM number,
JZZTMC text,
JZJSSJ time,
TXBZ number,
ZZBZ number,
WDBZ number,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
ZZYSGH text,
QTJZYSGH text,
JZZDBM text,
JZZDSM text,
MZZYZDZZBM text,
MZZYZDZZMC text,
SG number,
TZ number,
TW number,
SSY number,
SZY number,
XL number,
HXPLC number,
ML number,
JLSJ time
)
CREATE TABLE jyjgzbb (
JYZBLSH text,
YLJGDM text,
BGDH text,
BGRQ time,
JYRQ time,
JCRGH text,
JCRXM text,
SHRGH text,
SHRXM text,
JCXMMC text,
JCZBDM text,
JCFF text,
JCZBMC text,
JCZBJGDX text,
JCZBJGDL number,
JCZBJGDW text,
SBBM text,
YQBH text,
YQMC text,
CKZFWDX text,
CKZFWXX number,
CKZFWSX number,
JLDW text
)
CREATE TABLE zyjzjlb (
YLJGDM text,
JZLSH text,
MZJZLSH text,
KH text,
KLX number,
HZXM text,
WDBZ number,
RYDJSJ time,
RYTJDM number,
RYTJMC text,
JZKSDM text,
JZKSMC text,
RZBQDM text,
RZBQMC text,
RYCWH text,
CYKSDM text,
CYKSMC text,
CYBQDM text,
CYBQMC text,
CYCWH text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text,
MZBMLX number,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYSJ time,
CYSJ time,
CYZTDM number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 患者66129206在二零一六年七月三十一日往后的住院就诊的检验报告单有哪些?查询住院就诊流水号
|
SELECT zyjzjlb.JZLSH FROM hz_info JOIN zyjzjlb ON hz_info.YLJGDM = zyjzjlb.YLJGDM AND hz_info.KH = zyjzjlb.KH AND hz_info.KLX = zyjzjlb.KLX WHERE hz_info.RYBH = '66129206' AND NOT zyjzjlb.JZLSH IN (SELECT JZLSH FROM jybgb WHERE BGRQ <= '2016-07-31')
|
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 lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
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.
-- how many patients whose gender is f and procedure icd9 code is 3799?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.gender = "F" AND procedures.icd9_code = "3799"
|
mimicsql_data
|
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
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 medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime 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.
-- what number of patients were prescribed docusate in the same month after having been diagnosed with acute renal failure since 3 years ago?
|
SELECT COUNT(DISTINCT t1.uniquepid) FROM (SELECT patient.uniquepid, diagnosis.diagnosistime FROM diagnosis JOIN patient ON diagnosis.patientunitstayid = patient.patientunitstayid WHERE diagnosis.diagnosisname = 'acute renal failure' AND DATETIME(diagnosis.diagnosistime) >= DATETIME(CURRENT_TIME(), '-3 year')) AS t1 JOIN (SELECT patient.uniquepid, medication.drugstarttime FROM medication JOIN patient ON medication.patientunitstayid = patient.patientunitstayid WHERE medication.drugname = 'docusate' AND DATETIME(medication.drugstarttime) >= DATETIME(CURRENT_TIME(), '-3 year')) AS t2 WHERE t1.diagnosistime < t2.drugstarttime AND DATETIME(t1.diagnosistime, 'start of month') = DATETIME(t2.drugstarttime, 'start of month')
|
eicu
|
CREATE TABLE table_203_817 (
id number,
"state" text,
"incumbent" text,
"party" text,
"result" text,
"candidates" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many states were listed as democratic ?
|
SELECT COUNT("state") FROM table_203_817 WHERE "party" = 'democratic'
|
squall
|
CREATE TABLE program (
program_id int,
name varchar,
college varchar,
introduction 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 course_prerequisite (
pre_course_id int,
course_id int
)
CREATE TABLE program_requirement (
program_id int,
category varchar,
min_credit int,
additional_req 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 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 offering_instructor (
offering_instructor_id int,
offering_id int,
instructor_id int
)
CREATE TABLE jobs (
job_id int,
job_title varchar,
description varchar,
requirement varchar,
city varchar,
state varchar,
country varchar,
zip int
)
CREATE TABLE instructor (
instructor_id int,
name varchar,
uniqname varchar
)
CREATE TABLE comment_instructor (
instructor_id int,
student_id int,
score int,
comment_text varchar
)
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
)
CREATE TABLE area (
course_id int,
area varchar
)
CREATE TABLE gsi (
course_offering_id int,
student_id int
)
CREATE TABLE requirement (
requirement_id int,
requirement varchar,
college varchar
)
CREATE TABLE semester (
semester_id int,
semester varchar,
year int
)
CREATE TABLE ta (
campus_job_id int,
student_id int,
location varchar
)
CREATE TABLE program_course (
program_id int,
course_id int,
workload int,
category varchar
)
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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- In the Fall or Winter term are there 400 -level classes available to take ?
|
SELECT DISTINCT COURSEalias0.department, COURSEalias0.name, COURSEalias0.number, SEMESTERalias0.semester FROM (SELECT course_id FROM student_record WHERE earn_credit = 'Y' AND student_id = 1) AS DERIVED_TABLEalias0, course AS COURSEalias0, course_offering AS COURSE_OFFERINGalias0, semester AS SEMESTERalias0 WHERE ((SEMESTERalias0.semester = 'FA' AND SEMESTERalias0.year = 2016) OR (SEMESTERalias0.semester = 'WN' AND SEMESTERalias0.year = 2017)) AND COURSEalias0.course_id = COURSE_OFFERINGalias0.course_id AND NOT COURSEalias0.course_id IN (DERIVED_TABLEalias0.course_id) AND NOT COURSEalias0.course_id IN (SELECT DISTINCT COURSE_PREREQUISITEalias0.course_id FROM course_prerequisite AS COURSE_PREREQUISITEalias0 WHERE NOT COURSE_PREREQUISITEalias0.pre_course_id IN (DERIVED_TABLEalias0.course_id)) AND COURSEalias0.department = 'EECS' AND COURSEalias0.number BETWEEN 400 AND 400 + 100 AND SEMESTERalias0.semester_id = COURSE_OFFERINGalias0.semester
|
advising
|
CREATE TABLE candidate (
Candidate_ID int,
People_ID int,
Poll_Source text,
Date text,
Support_rate real,
Consider_rate real,
Oppose_rate real,
Unsure_rate real
)
CREATE TABLE people (
People_ID int,
Sex text,
Name text,
Date_of_Birth text,
Height real,
Weight real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Visualize a bar chart about the distribution of Sex and the sum of Height , and group by attribute Sex.
|
SELECT Sex, SUM(Height) FROM people GROUP BY Sex
|
nvbench
|
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
)
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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what number of patients who were given the drug lidocain have died in or before the year 2180?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.dod_year <= "2180.0" AND prescriptions.drug = "Lidocaine"
|
mimicsql_data
|
CREATE TABLE Aircraft (
aid VARCHAR,
name VARCHAR
)
CREATE TABLE Flight (
flno VARCHAR,
aid VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Show all flight numbers with aircraft Airbus A340-300.
|
SELECT T1.flno FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T2.name = "Airbus A340-300"
|
sql_create_context
|
CREATE TABLE table_32127 (
"Tournament" text,
"Wins" real,
"Top-5" real,
"Top-25" real,
"Events" real,
"Cuts made" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the smallest value for Wins when the number of cuts is greater than 4 and the Top-5 value is less than 1?
|
SELECT MIN("Wins") FROM table_32127 WHERE "Cuts made" > '4' AND "Top-5" < '1'
|
wikisql
|
CREATE TABLE table_42758 (
"Sport" text,
"Record" text,
"Nation - athlete(s)" text,
"Date" text,
"Time (seconds)" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the Date, when the Sport is luge - men's doubles, and when the Record is, 'start'?
|
SELECT "Date" FROM table_42758 WHERE "Sport" = 'luge - men''s doubles' AND "Record" = 'start'
|
wikisql
|
CREATE TABLE table_204_158 (
id number,
"official name" text,
"designation" text,
"area km2" number,
"population" number,
"parish" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- the only rural community on the list
|
SELECT "official name" FROM table_204_158 WHERE "designation" = 'rural community'
|
squall
|
CREATE TABLE table_12711 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text,
"Money ( \u00a3 )" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- In what place is the golfer with a score of 68-69-73-70=280?
|
SELECT "Place" FROM table_12711 WHERE "Score" = '68-69-73-70=280'
|
wikisql
|
CREATE TABLE table_38760 (
"The Kennel Club (UK) Toy Group" text,
"Canadian Kennel Club Toy Dogs Group" text,
"American Kennel Club Toy Group" text,
"Australian National Kennel Council Toy Dogs Group" text,
"New Zealand Kennel Club Toy Group" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the Australian National Kennel Council Toy Dogs Group with papillon as the Kennel Club breed?
|
SELECT "Australian National Kennel Council Toy Dogs Group" FROM table_38760 WHERE "The Kennel Club (UK) Toy Group" = 'papillon'
|
wikisql
|
CREATE TABLE table_55439 (
"Year" real,
"Nominated work" text,
"Event" text,
"Award" text,
"Result" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What year was Herself nominated at the MTV Movie Awards?
|
SELECT MAX("Year") FROM table_55439 WHERE "Nominated work" = 'herself' AND "Event" = 'mtv movie awards'
|
wikisql
|
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 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 ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId 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 PendingFlags (
Id number,
FlagTypeId number,
PostId number,
CreationDate time,
CloseReasonTypeId number,
CloseAsOffTopicReasonTypeId number,
DuplicateOfQuestionId number,
BelongsOnBaseHostAddress text
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
CREATE TABLE PostTypes (
Id number,
Name text
)
CREATE TABLE SuggestedEditVotes (
Id number,
SuggestedEditId number,
UserId number,
VoteTypeId number,
CreationDate time,
TargetUserId number,
TargetRepChange number
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE PostFeedback (
Id number,
PostId number,
IsAnonymous boolean,
VoteTypeId number,
CreationDate time
)
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId 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 Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
CREATE TABLE ReviewTaskResultTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewTaskStates (
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 Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId 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 PostHistory (
Id number,
PostHistoryTypeId number,
PostId number,
RevisionGUID other,
CreationDate time,
UserId number,
UserDisplayName text,
Comment text,
Text text,
ContentLicense text
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Average time to first answer, by tag. Rewrite of http://data.stackexchange.com/codereview/query/211467/average-time-to-in-seconds-to-answer-a-question-by-language-tag in response to http://codereview.stackexchange.com/questions/58668/average-time-to-first-answer. See http://codereview.stackexchange.com/a/58679/9357 for an explanation.
|
SELECT COUNT(*) AS QuestionCount, t.TagId FROM Posts AS p JOIN PostTags AS t ON p.Id = t.PostId WHERE t.TagId = 1589 AND p.PostTypeId = 1 GROUP BY t.TagId
|
sede
|
CREATE TABLE schedule (
Cinema_ID int,
Film_ID int,
Date text,
Show_times_per_day int,
Price float
)
CREATE TABLE film (
Film_ID int,
Rank_in_series int,
Number_in_season int,
Title text,
Directed_by text,
Original_air_date text,
Production_code text
)
CREATE TABLE cinema (
Cinema_ID int,
Name text,
Openning_year int,
Capacity int,
Location text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- A bar chart about what are the title and maximum price of each film?, display by the price from low to high.
|
SELECT Title, MAX(T1.Price) FROM schedule AS T1 JOIN film AS T2 ON T1.Film_ID = T2.Film_ID GROUP BY Title ORDER BY MAX(T1.Price)
|
nvbench
|
CREATE TABLE table_49498 (
"Issued" real,
"Type" text,
"Design" text,
"Serial format" text,
"Serials issued" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What type was issued in 1964?
|
SELECT "Type" FROM table_49498 WHERE "Issued" = '1964'
|
wikisql
|
CREATE TABLE schedule (
Cinema_ID int,
Film_ID int,
Date text,
Show_times_per_day int,
Price float
)
CREATE TABLE cinema (
Cinema_ID int,
Name text,
Openning_year int,
Capacity int,
Location text
)
CREATE TABLE film (
Film_ID int,
Rank_in_series int,
Number_in_season int,
Title text,
Directed_by text,
Original_air_date text,
Production_code text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For each film, return the number of cinemas showing that fim in a bar chart.
|
SELECT Title, COUNT(Title) FROM schedule AS T1 JOIN film AS T2 ON T1.Film_ID = T2.Film_ID JOIN cinema AS T3 ON T1.Cinema_ID = T3.Cinema_ID GROUP BY Title
|
nvbench
|
CREATE TABLE table_18066 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What's the title of the episode directed by David von Ancken, with a episode number bigger than 16.0?
|
SELECT "Title" FROM table_18066 WHERE "Directed by" = 'David Von Ancken' AND "No. in series" > '16.0'
|
wikisql
|
CREATE TABLE table_12161822_5 (
fastest_lap VARCHAR,
grand_prix VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- who is the the fastest lap with grand prix being european grand prix
|
SELECT fastest_lap FROM table_12161822_5 WHERE grand_prix = "European grand_prix"
|
sql_create_context
|
CREATE TABLE table_name_34 (
country VARCHAR,
winner VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What country was ole ellefs ter from?
|
SELECT country FROM table_name_34 WHERE winner = "ole ellefsæter"
|
sql_create_context
|
CREATE TABLE table_34560 (
"Year" text,
"Team" text,
"Progress" text,
"Score" text,
"Opponents" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Opponents have a Team of arsenal, and a Year of 1963 64?
|
SELECT "Opponents" FROM table_34560 WHERE "Team" = 'arsenal' AND "Year" = '1963–64'
|
wikisql
|
CREATE TABLE table_204_104 (
id number,
"title" text,
"genre" text,
"sub\u00addivisions" text,
"libretto" text,
"premiere date" text,
"place, theatre" text,
"notes" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many operas on this list has at least 3 acts ?
|
SELECT COUNT("title") FROM table_204_104 WHERE "sub\u00addivisions" >= 3
|
squall
|
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 procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the procedure and drug route of patient id 24425?
|
SELECT procedures.long_title, prescriptions.route FROM procedures INNER JOIN prescriptions ON procedures.hadm_id = prescriptions.hadm_id WHERE procedures.subject_id = "24425"
|
mimicsql_data
|
CREATE TABLE table_33903 (
"Denomination" text,
"Metal" text,
"Weight" text,
"Shape" text,
"Size" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What metal has one rupee as the denomination?
|
SELECT "Metal" FROM table_33903 WHERE "Denomination" = 'one rupee'
|
wikisql
|
CREATE TABLE table_26842217_8 (
date VARCHAR,
site VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- If the site is sanford stadium athens, ga, what is the date?
|
SELECT date FROM table_26842217_8 WHERE site = "Sanford Stadium • Athens, GA"
|
sql_create_context
|
CREATE TABLE table_name_6 (
total INTEGER,
year_s__won VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Year(s) won of 1994 , 1997 has what average total?
|
SELECT AVG(total) FROM table_name_6 WHERE year_s__won = "1994 , 1997"
|
sql_create_context
|
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.
-- Calculate the total number of patients on elective admission before the year 2108
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.admission_type = "ELECTIVE" AND demographic.admityear < "2108"
|
mimicsql_data
|
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 jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
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 countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Give me a bar chart for employee_id of each last name, could you display X-axis from high to low order?
|
SELECT LAST_NAME, EMPLOYEE_ID FROM employees ORDER BY LAST_NAME DESC
|
nvbench
|
CREATE TABLE Elimination (
Elimination_ID text,
Wrestler_ID text,
Team text,
Eliminated_By text,
Elimination_Move text,
Time text
)
CREATE TABLE wrestler (
Wrestler_ID int,
Name text,
Reign text,
Days_held text,
Location text,
Event text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- A bar chart for what is the number of locations of the wrestlers, and show total number in ascending order.
|
SELECT Location, COUNT(Location) FROM wrestler GROUP BY Location ORDER BY COUNT(Location)
|
nvbench
|
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
)
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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many patients with black/cape verdean ethnicity were given the drug psyllium wafer?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.ethnicity = "BLACK/CAPE VERDEAN" AND prescriptions.drug = "Psyllium Wafer"
|
mimicsql_data
|
CREATE TABLE table_3089 (
"Name" text,
"Position" text,
"Period" text,
"Appearances\u00b9" real,
"Goals\u00b9" real,
"Nationality\u00b2" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the period total number if the name is Gerald o?
|
SELECT COUNT("Period") FROM table_3089 WHERE "Name" = 'Geraldão'
|
wikisql
|
CREATE TABLE dorm_amenity (
amenid number,
amenity_name text
)
CREATE TABLE student (
stuid number,
lname text,
fname text,
age number,
sex text,
major number,
advisor number,
city_code text
)
CREATE TABLE lives_in (
stuid number,
dormid number,
room_number number
)
CREATE TABLE dorm (
dormid number,
dorm_name text,
student_capacity number,
gender text
)
CREATE TABLE has_amenity (
dormid number,
amenid number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many female students (sex is F) whose age is below 25?
|
SELECT COUNT(*) FROM student WHERE sex = 'F' AND age < 25
|
spider
|
CREATE TABLE table_name_55 (
stadium VARCHAR,
final_score VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- At what stadium was the game with the final score of 9-23 played?
|
SELECT stadium FROM table_name_55 WHERE final_score = "9-23"
|
sql_create_context
|
CREATE TABLE Students (
personal_name VARCHAR
)
CREATE TABLE Student_Course_Enrolment (
student_id VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the personal names of students not enrolled in any course.
|
SELECT personal_name FROM Students EXCEPT SELECT T1.personal_name FROM Students AS T1 JOIN Student_Course_Enrolment AS T2 ON T1.student_id = T2.student_id
|
sql_create_context
|
CREATE TABLE table_78096 (
"Week" text,
"Date" text,
"Opponent" text,
"Result" text,
"Kickoff [a ]" text,
"Game site" text,
"Attendance" text,
"Record" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What week was it on November 19, 1995?
|
SELECT "Week" FROM table_78096 WHERE "Date" = 'november 19, 1995'
|
wikisql
|
CREATE TABLE table_70935 (
"Team" text,
"Manager 1" text,
"Captain" text,
"Kit manufacturer" text,
"Shirt sponsor" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- On which team was Robbie Earle the captain?
|
SELECT "Team" FROM table_70935 WHERE "Captain" = 'robbie earle'
|
wikisql
|
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 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,
t_kc21_CLINIC_ID text,
t_kc21_CLINIC_TYPE text,
t_kc21_COMP_ID text,
t_kc21_DATA_ID text,
t_kc21_DIFF_PLACE_FLG number,
t_kc21_FERTILITY_STS number,
t_kc21_FLX_MED_ORG_ID text,
t_kc21_HOSP_LEV number,
t_kc21_HOSP_STS number,
t_kc21_IDENTITY_CARD text,
t_kc21_INPT_AREA_BED text,
t_kc21_INSURED_IDENTITY number,
t_kc21_INSURED_STS text,
t_kc21_INSU_TYPE text,
t_kc21_IN_DIAG_DIS_CD text,
t_kc21_IN_DIAG_DIS_NM text,
t_kc21_IN_HOSP_DATE time,
t_kc21_IN_HOSP_DAYS number,
t_kc21_MAIN_COND_DES text,
t_kc21_MED_AMOUT number,
t_kc21_MED_ORG_DEPT_CD text,
t_kc21_MED_ORG_DEPT_NM text,
t_kc21_MED_SER_ORG_NO text,
t_kc21_MED_TYPE number,
t_kc21_OUT_DIAG_DIS_CD text,
t_kc21_OUT_DIAG_DIS_NM text,
t_kc21_OUT_DIAG_DOC_CD text,
t_kc21_OUT_DIAG_DOC_NM text,
t_kc21_OUT_HOSP_DATE time,
t_kc21_OVERALL_CD_ORG text,
t_kc21_OVERALL_CD_PERSON text,
t_kc21_PERSON_AGE number,
t_kc21_PERSON_ID text,
t_kc21_PERSON_NM text,
t_kc21_PERSON_SEX number,
t_kc21_REIMBURSEMENT_FLG number,
t_kc21_REMOTE_SETTLE_FLG text,
t_kc21_SERVANT_FLG text,
t_kc21_SOC_SRT_CARD text,
t_kc21_SYNC_TIME time,
t_kc21_TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 对于医疗费总额高于7064.81元的医疗记录属于患者62391480的,列出入院诊断疾病名称和编码是什么?
|
SELECT t_kc24.t_kc21_IN_DIAG_DIS_CD, t_kc24.t_kc21_IN_DIAG_DIS_NM FROM t_kc24 WHERE t_kc24.t_kc21_PERSON_ID = '62391480' AND t_kc24.MED_CLINIC_ID IN (SELECT t_kc24.MED_CLINIC_ID FROM t_kc24 WHERE t_kc24.MED_AMOUT > 7064.81)
|
css
|
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
)
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_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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 从一一年八月十九日开始一直9到一三年五月三十日截止,医院9399745的入院诊断疾病结果与出院诊断疾病结果不同的次数是多少?
|
SELECT (SELECT COUNT(*) FROM t_kc21 WHERE MED_SER_ORG_NO = '9399745' AND IN_HOSP_DATE BETWEEN '2011-08-19' AND '2013-05-30') - (SELECT COUNT(*) FROM t_kc21 WHERE MED_SER_ORG_NO = '9399745' AND IN_HOSP_DATE BETWEEN '2011-08-19' AND '2013-05-30' AND IN_DIAG_DIS_CD = OUT_DIAG_DIS_CD)
|
css
|
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE 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 job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
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 regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For all employees who have the letters D or S in their first name, draw a bar chart about the distribution of hire_date and the sum of department_id bin hire_date by weekday, and sort by the sum department id in ascending please.
|
SELECT HIRE_DATE, SUM(DEPARTMENT_ID) FROM employees WHERE FIRST_NAME LIKE '%D%' OR FIRST_NAME LIKE '%S%' ORDER BY SUM(DEPARTMENT_ID)
|
nvbench
|
CREATE TABLE table_22879262_13 (
team VARCHAR,
date VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Where does the team play May 3?
|
SELECT team FROM table_22879262_13 WHERE date = "May 3"
|
sql_create_context
|
CREATE TABLE table_name_11 (
score VARCHAR,
decision VARCHAR,
record VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the score when the record was 18 14 4 with a toivonen decision?
|
SELECT score FROM table_name_11 WHERE decision = "toivonen" AND record = "18–14–4"
|
sql_create_context
|
CREATE TABLE zyb (
CLINIC_ID 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,
SERVANT_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 mzb (
CLINIC_ID 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,
SERVANT_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
)
CREATE TABLE qtb (
CLINIC_ID 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,
SERVANT_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE gyb (
CLINIC_ID 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,
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.
-- 病患编号41538489在医院7012713入院确诊的疾病名称里包括了未字的医疗就医记录都是多少编号?
|
SELECT qtb.MED_CLINIC_ID FROM qtb WHERE qtb.PERSON_ID = '41538489' AND qtb.MED_SER_ORG_NO = '7012713' AND qtb.IN_DIAG_DIS_NM LIKE '%未%' UNION SELECT gyb.MED_CLINIC_ID FROM gyb WHERE gyb.PERSON_ID = '41538489' AND gyb.MED_SER_ORG_NO = '7012713' AND gyb.IN_DIAG_DIS_NM LIKE '%未%' UNION SELECT zyb.MED_CLINIC_ID FROM zyb WHERE zyb.PERSON_ID = '41538489' AND zyb.MED_SER_ORG_NO = '7012713' AND zyb.IN_DIAG_DIS_NM LIKE '%未%' UNION SELECT mzb.MED_CLINIC_ID FROM mzb WHERE mzb.PERSON_ID = '41538489' AND mzb.MED_SER_ORG_NO = '7012713' AND mzb.IN_DIAG_DIS_NM LIKE '%未%'
|
css
|
CREATE TABLE table_39080 (
"Game" real,
"October" real,
"Opponent" text,
"Score" text,
"Record" text,
"Points" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Score has a Game larger than 7, and Points smaller than 14?
|
SELECT "Score" FROM table_39080 WHERE "Game" > '7' AND "Points" < '14'
|
wikisql
|
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 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 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 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 统计一下医疗记录中患者年龄低于28岁的平均医疗费总额都是多少?
|
SELECT AVG(t_kc24.MED_AMOUT) FROM t_kc24 WHERE t_kc24.MED_CLINIC_ID IN (SELECT gwyjzb.MED_CLINIC_ID FROM gwyjzb WHERE gwyjzb.PERSON_AGE < 28 UNION SELECT fgwyjzb.MED_CLINIC_ID FROM fgwyjzb WHERE fgwyjzb.PERSON_AGE < 28)
|
css
|
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
CREATE TABLE SuggestedEditVotes (
Id number,
SuggestedEditId number,
UserId number,
VoteTypeId number,
CreationDate time,
TargetUserId number,
TargetRepChange number
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE VoteTypes (
Id number,
Name text
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
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 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 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 PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
CREATE TABLE PostTypes (
Id number,
Name text
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewTaskResultTypes (
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 ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE PendingFlags (
Id number,
FlagTypeId number,
PostId number,
CreationDate time,
CloseReasonTypeId number,
CloseAsOffTopicReasonTypeId number,
DuplicateOfQuestionId number,
BelongsOnBaseHostAddress text
)
CREATE TABLE ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
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 PostFeedback (
Id number,
PostId number,
IsAnonymous boolean,
VoteTypeId number,
CreationDate time
)
CREATE TABLE Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
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 Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE ReviewTaskTypes (
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 SuggestedEdits (
Id number,
PostId number,
CreationDate time,
ApprovalDate time,
RejectionDate time,
OwnerUserId number,
Comment text,
Text text,
Title text,
Tags text,
RevisionGUID other
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Top 50 Users with the Most Communiy Wiki Answers.
|
SELECT u.Id AS "user_link", u.Reputation, COUNT(a.Score) AS TotalCount, SUM(a.Score) AS TotalScore FROM Users AS u INNER JOIN Posts AS a ON a.OwnerUserId = u.Id WHERE a.PostTypeId = 2 AND a.CommunityOwnedDate >= '20110101' GROUP BY u.Id, u.Reputation ORDER BY TotalCount DESC LIMIT 50
|
sede
|
CREATE TABLE table_name_94 (
score VARCHAR,
date VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the score on October 13?
|
SELECT score FROM table_name_94 WHERE date = "october 13"
|
sql_create_context
|
CREATE TABLE table_name_84 (
title VARCHAR,
published_in VARCHAR,
main_characters VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the title when the main characters are grant calthorpe, lee neilan and the published in of astounding stories
|
SELECT title FROM table_name_84 WHERE published_in = "astounding stories" AND main_characters = "grant calthorpe, lee neilan"
|
sql_create_context
|
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
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 PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
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 PostTags (
PostId number,
TagId number
)
CREATE TABLE SuggestedEditVotes (
Id number,
SuggestedEditId number,
UserId number,
VoteTypeId number,
CreationDate time,
TargetUserId number,
TargetRepChange number
)
CREATE TABLE ReviewTaskResultTypes (
Id number,
Name text,
Description text
)
CREATE TABLE VoteTypes (
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 ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
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 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 Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
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 PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
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 Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId 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 ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostTypes (
Id number,
Name 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 PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Comments with a score of 5 or more.
|
SELECT PostId AS "post_link", Score, Text FROM Comments WHERE UserId = @UserId AND Score >= 5 ORDER BY Score DESC
|
sede
|
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE 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 allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
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 medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- has patient 021-32860 had any surgery the previous year?
|
SELECT COUNT(*) > 0 FROM treatment WHERE treatment.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '021-32860')) AND DATETIME(treatment.treatmenttime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-1 year')
|
eicu
|
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