instruction
stringlengths 151
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CREATE TABLE order_items (
order_item_id number,
product_id number,
order_id number,
order_item_status text,
order_item_details text
)
CREATE TABLE shipment_items (
shipment_id number,
order_item_id number
)
CREATE TABLE shipments (
shipment_id number,
order_id number,
invoice_number number,
shipment_tracking_number text,
shipment_date time,
other_shipment_details text
)
CREATE TABLE customers (
customer_id number,
customer_name text,
customer_details text
)
CREATE TABLE orders (
order_id number,
customer_id number,
order_status text,
date_order_placed time,
order_details text
)
CREATE TABLE invoices (
invoice_number number,
invoice_date time,
invoice_details text
)
CREATE TABLE products (
product_id number,
product_name text,
product_details text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- List the names of all distinct products in alphabetical order.
|
SELECT DISTINCT product_name FROM products ORDER BY product_name
|
spider
|
CREATE TABLE city (
city_id SMALLINT UNSIGNED,
city VARCHAR(50),
country_id SMALLINT UNSIGNED,
last_update TIMESTAMP
)
CREATE TABLE rental (
rental_id INT,
rental_date DATETIME,
inventory_id MEDIUMINT UNSIGNED,
customer_id SMALLINT UNSIGNED,
return_date DATETIME,
staff_id TINYINT UNSIGNED,
last_update TIMESTAMP
)
CREATE TABLE country (
country_id SMALLINT UNSIGNED,
country VARCHAR(50),
last_update TIMESTAMP
)
CREATE TABLE film (
film_id SMALLINT UNSIGNED,
title VARCHAR(255),
description TEXT,
release_year YEAR,
language_id TINYINT UNSIGNED,
original_language_id TINYINT UNSIGNED,
rental_duration TINYINT UNSIGNED,
rental_rate DECIMAL(4,2),
length SMALLINT UNSIGNED,
replacement_cost DECIMAL(5,2),
rating any,
special_features any,
last_update TIMESTAMP
)
CREATE TABLE film_category (
film_id SMALLINT UNSIGNED,
category_id TINYINT UNSIGNED,
last_update TIMESTAMP
)
CREATE TABLE actor (
actor_id SMALLINT UNSIGNED,
first_name VARCHAR(45),
last_name VARCHAR(45),
last_update TIMESTAMP
)
CREATE TABLE film_text (
film_id SMALLINT,
title VARCHAR(255),
description TEXT
)
CREATE TABLE address (
address_id SMALLINT UNSIGNED,
address VARCHAR(50),
address2 VARCHAR(50),
district VARCHAR(20),
city_id SMALLINT UNSIGNED,
postal_code VARCHAR(10),
phone VARCHAR(20),
last_update TIMESTAMP
)
CREATE TABLE payment (
payment_id SMALLINT UNSIGNED,
customer_id SMALLINT UNSIGNED,
staff_id TINYINT UNSIGNED,
rental_id INT,
amount DECIMAL(5,2),
payment_date DATETIME,
last_update TIMESTAMP
)
CREATE TABLE category (
category_id TINYINT UNSIGNED,
name VARCHAR(25),
last_update TIMESTAMP
)
CREATE TABLE staff (
staff_id TINYINT UNSIGNED,
first_name VARCHAR(45),
last_name VARCHAR(45),
address_id SMALLINT UNSIGNED,
picture BLOB,
email VARCHAR(50),
store_id TINYINT UNSIGNED,
active BOOLEAN,
username VARCHAR(16),
password VARCHAR(40),
last_update TIMESTAMP
)
CREATE TABLE customer (
customer_id SMALLINT UNSIGNED,
store_id TINYINT UNSIGNED,
first_name VARCHAR(45),
last_name VARCHAR(45),
email VARCHAR(50),
address_id SMALLINT UNSIGNED,
active BOOLEAN,
create_date DATETIME,
last_update TIMESTAMP
)
CREATE TABLE film_actor (
actor_id SMALLINT UNSIGNED,
film_id SMALLINT UNSIGNED,
last_update TIMESTAMP
)
CREATE TABLE inventory (
inventory_id MEDIUMINT UNSIGNED,
film_id SMALLINT UNSIGNED,
store_id TINYINT UNSIGNED,
last_update TIMESTAMP
)
CREATE TABLE language (
language_id TINYINT UNSIGNED,
name CHAR(20),
last_update TIMESTAMP
)
CREATE TABLE store (
store_id TINYINT UNSIGNED,
manager_staff_id TINYINT UNSIGNED,
address_id SMALLINT UNSIGNED,
last_update TIMESTAMP
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What are the names of the different categories, and how many films are in each? Show me the bar graph, could you rank X-axis in asc order please?
|
SELECT name, COUNT(*) FROM film_category AS T1 JOIN category AS T2 ON T1.category_id = T2.category_id GROUP BY T1.category_id ORDER BY name
|
nvbench
|
CREATE TABLE table_name_83 (
city___state VARCHAR,
circuit VARCHAR,
winner VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is City / State, when Circuit is Eastern Creek Raceway, and when Winner is Michael Donaher?
|
SELECT city___state FROM table_name_83 WHERE circuit = "eastern creek raceway" AND winner = "michael donaher"
|
sql_create_context
|
CREATE TABLE regular_order_products (
regular_order_id number,
product_id number
)
CREATE TABLE employees (
employee_id number,
employee_address_id number,
employee_name text,
employee_phone text
)
CREATE TABLE delivery_route_locations (
location_code text,
route_id number,
location_address_id number,
location_name text
)
CREATE TABLE addresses (
address_id number,
address_details text,
city text,
zip_postcode text,
state_province_county text,
country text
)
CREATE TABLE trucks (
truck_id number,
truck_licence_number text,
truck_details text
)
CREATE TABLE customers (
customer_id number,
payment_method text,
customer_name text,
customer_phone text,
customer_email text,
date_became_customer time
)
CREATE TABLE customer_addresses (
customer_id number,
address_id number,
date_from time,
address_type text,
date_to time
)
CREATE TABLE actual_order_products (
actual_order_id number,
product_id number
)
CREATE TABLE order_deliveries (
location_code text,
actual_order_id number,
delivery_status_code text,
driver_employee_id number,
truck_id number,
delivery_date time
)
CREATE TABLE actual_orders (
actual_order_id number,
order_status_code text,
regular_order_id number,
actual_order_date time
)
CREATE TABLE regular_orders (
regular_order_id number,
distributer_id number
)
CREATE TABLE delivery_routes (
route_id number,
route_name text,
other_route_details text
)
CREATE TABLE products (
product_id number,
product_name text,
product_price number,
product_description text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the ids of orders whose status is 'Success'.
|
SELECT actual_order_id FROM actual_orders WHERE order_status_code = 'Success'
|
spider
|
CREATE TABLE table_45145 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" real,
"Time" text,
"Location" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which event had a time of 2:34?
|
SELECT "Event" FROM table_45145 WHERE "Time" = '2:34'
|
wikisql
|
CREATE TABLE table_36648 (
"Club" text,
"Played" text,
"Drawn" text,
"Lost" text,
"Points for" text,
"Points against" text,
"Tries for" text,
"Tries against" text,
"Try bonus" text,
"Losing bonus" text,
"Points" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the drawn by the club with 542 points against?
|
SELECT "Drawn" FROM table_36648 WHERE "Points against" = '542'
|
wikisql
|
CREATE TABLE table_26681728_1 (
rank_final INTEGER,
apparatus VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the maximum rank-final score on the floor exercise?
|
SELECT MAX(rank_final) FROM table_26681728_1 WHERE apparatus = "Floor Exercise"
|
sql_create_context
|
CREATE TABLE table_203_42 (
id number,
"model" text,
"class" text,
"length" text,
"fuel" text,
"starting price" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- which model is at the top of the list with the highest starting price ?
|
SELECT "model" FROM table_203_42 ORDER BY "starting price" DESC LIMIT 1
|
squall
|
CREATE TABLE table_6291 (
"Player" text,
"Result" text,
"Appeared" real,
"RR W\u2013L" text,
"RR W Rate" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For Angelique Kerber who had an RR Rate of less than 0.33, what's the appeared?
|
SELECT SUM("Appeared") FROM table_6291 WHERE "RR W Rate" < '0.33' AND "Player" = 'angelique kerber'
|
wikisql
|
CREATE TABLE table_name_33 (
acquisition_via VARCHAR,
name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the Acquisition via for Dennis Miranda?
|
SELECT acquisition_via FROM table_name_33 WHERE name = "dennis miranda"
|
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_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_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_t_kc22 (
MED_CLINIC_ID text,
MED_EXP_DET_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13年6月2日到2020年5月10日时间里，手术量排名前21的科室编码和名称都有哪些？
|
SELECT t_kc22.MED_ORG_DEPT_CD, t_kc22.MED_ORG_DEPT_NM FROM t_kc22 WHERE t_kc22.STA_DATE BETWEEN '2013-06-02' AND '2020-05-10' AND t_kc22.MED_INV_ITEM_TYPE = '手术费' GROUP BY t_kc22.MED_ORG_DEPT_CD ORDER BY COUNT(*) DESC LIMIT 21
|
css
|
CREATE TABLE table_name_2 (
total VARCHAR,
gold VARCHAR,
silver VARCHAR,
rank VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What's the total of rank 8 when Silver medals are 0 and gold is more than 1?
|
SELECT COUNT(total) FROM table_name_2 WHERE silver = 0 AND rank = 8 AND gold > 1
|
sql_create_context
|
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_kc22 (
MED_EXP_DET_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
MED_CLINIC_ID text,
MED_EXP_BILL_ID text,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
DIRE_TYPE number,
CHA_ITEM_LEV number,
MED_INV_ITEM_TYPE text,
MED_DIRE_CD text,
MED_DIRE_NM text,
VAL_UNIT text,
DOSE_UNIT text,
DOSE_FORM text,
SPEC text,
USE_FRE text,
EACH_DOSAGE text,
QTY number,
UNIVALENT number,
AMOUNT number,
SELF_PAY_PRO number,
RER_SOL number,
SELF_PAY_AMO number,
UP_LIMIT_AMO number,
OVE_SELF_AMO number,
EXP_OCC_DATE time,
RECIPE_BILL_ID text,
FLX_MED_ORG_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
REF_STA_FLG number,
DATA_ID text,
SYNC_TIME time,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
TRADE_TYPE number,
STA_FLG number,
STA_DATE time,
REIMBURS_TYPE number,
FXBZ number,
REMOTE_SETTLE_FLG text
)
CREATE TABLE t_kc21 (
MED_CLINIC_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
COMP_ID text,
PERSON_ID text,
PERSON_NM text,
IDENTITY_CARD text,
SOC_SRT_CARD text,
PERSON_SEX number,
PERSON_AGE number,
IN_HOSP_DATE time,
OUT_HOSP_DATE time,
DIFF_PLACE_FLG number,
FLX_MED_ORG_ID text,
MED_SER_ORG_NO text,
CLINIC_TYPE text,
MED_TYPE number,
CLINIC_ID text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
INPT_AREA_BED text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
MAIN_COND_DES text,
INSU_TYPE text,
IN_HOSP_DAYS number,
MED_AMOUT number,
FERTILITY_STS number,
DATA_ID text,
SYNC_TIME time,
REIMBURSEMENT_FLG number,
HOSP_LEV number,
HOSP_STS number,
INSURED_IDENTITY number,
SERVANT_FLG text,
TRADE_TYPE number,
INSURED_STS text,
REMOTE_SETTLE_FLG text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 患者61183552在二00三年六月二十四日到二00八年六月十四日期间，刷医保卡的医疗费总额有多少
|
SELECT SUM(MED_AMOUT) FROM t_kc24 WHERE PERSON_ID = '61183552' AND CLINIC_SLT_DATE BETWEEN '2003-06-24' AND '2008-06-14'
|
css
|
CREATE TABLE table_name_10 (
goals_conceded INTEGER,
points VARCHAR,
draws VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Goals conceded has Points of 6 and Draws larger than 0?
|
SELECT MAX(goals_conceded) FROM table_name_10 WHERE points = 6 AND draws > 0
|
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 microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE 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 diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom 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 d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE 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.
-- what was the top four most frequent diagnosis that was diagnosed for patients in the same month after receiving a opn/oth rep aortic valve procedure in 2105?
|
SELECT d_icd_diagnoses.short_title FROM d_icd_diagnoses WHERE d_icd_diagnoses.icd9_code IN (SELECT t3.icd9_code FROM (SELECT t2.icd9_code, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM (SELECT admissions.subject_id, procedures_icd.charttime FROM procedures_icd JOIN admissions ON procedures_icd.hadm_id = admissions.hadm_id WHERE procedures_icd.icd9_code = (SELECT d_icd_procedures.icd9_code FROM d_icd_procedures WHERE d_icd_procedures.short_title = 'opn/oth rep aortic valve') AND STRFTIME('%y', procedures_icd.charttime) = '2105') AS t1 JOIN (SELECT admissions.subject_id, diagnoses_icd.icd9_code, diagnoses_icd.charttime FROM diagnoses_icd JOIN admissions ON diagnoses_icd.hadm_id = admissions.hadm_id WHERE STRFTIME('%y', diagnoses_icd.charttime) = '2105') AS t2 ON t1.subject_id = t2.subject_id WHERE t1.charttime < t2.charttime AND DATETIME(t1.charttime, 'start of month') = DATETIME(t2.charttime, 'start of month') GROUP BY t2.icd9_code) AS t3 WHERE t3.c1 <= 4)
|
mimic_iii
|
CREATE TABLE table_35154 (
"Season" text,
"Record" text,
"Pct." real,
"Games" real,
"Attendance" real,
"Average" real,
"Sellouts" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the full amount of averages when the sellouts are less than 14, the season is 2011-12, and attendance is less than 162,474?
|
SELECT COUNT("Average") FROM table_35154 WHERE "Sellouts" < '14' AND "Season" = '2011-12' AND "Attendance" < '162,474'
|
wikisql
|
CREATE TABLE table_36670 (
"Date" text,
"Visitor" text,
"Score" text,
"Home" text,
"Attendance" real,
"Record" text,
"Points" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Date has a Home of pittsburgh, and a Record of 3 6 5?
|
SELECT "Date" FROM table_36670 WHERE "Home" = 'pittsburgh' AND "Record" = '3–6–5'
|
wikisql
|
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE 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 d_items (
row_id number,
itemid number,
label text,
linksto 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 d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name 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 prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- until 2104, how many patients were diagnosed with neuropathy in diabetes during the same hospital encounter after they were diagnosed with fall on stair/step nec?
|
SELECT COUNT(DISTINCT t1.subject_id) FROM (SELECT admissions.subject_id, diagnoses_icd.charttime, admissions.hadm_id FROM diagnoses_icd JOIN admissions ON diagnoses_icd.hadm_id = admissions.hadm_id WHERE diagnoses_icd.icd9_code = (SELECT d_icd_diagnoses.icd9_code FROM d_icd_diagnoses WHERE d_icd_diagnoses.short_title = 'neuropathy in diabetes') AND STRFTIME('%y', diagnoses_icd.charttime) <= '2104') AS t1 JOIN (SELECT admissions.subject_id, diagnoses_icd.charttime, admissions.hadm_id FROM diagnoses_icd JOIN admissions ON diagnoses_icd.hadm_id = admissions.hadm_id WHERE diagnoses_icd.icd9_code = (SELECT d_icd_diagnoses.icd9_code FROM d_icd_diagnoses WHERE d_icd_diagnoses.short_title = 'fall on stair/step nec') AND STRFTIME('%y', diagnoses_icd.charttime) <= '2104') AS t2 ON t1.subject_id = t2.subject_id WHERE t1.charttime < t2.charttime AND t1.hadm_id = t2.hadm_id
|
mimic_iii
|
CREATE TABLE management (
department_id number,
head_id number,
temporary_acting text
)
CREATE TABLE head (
head_id number,
name text,
born_state text,
age number
)
CREATE TABLE department (
department_id number,
name text,
creation text,
ranking number,
budget_in_billions number,
num_employees number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- In which year were most departments established?
|
SELECT creation FROM department GROUP BY creation ORDER BY COUNT(*) DESC LIMIT 1
|
spider
|
CREATE TABLE table_19420 (
"School Year" text,
"Class A" text,
"Class AA" text,
"Class AAA" text,
"Class AAAA" text,
"Class AAAAA" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the class a for pearland
|
SELECT "Class A" FROM table_19420 WHERE "Class AAAAA" = 'Pearland'
|
wikisql
|
CREATE TABLE table_26866205_1 (
original_airdate VARCHAR,
series__number VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is every original air date for series# of 26?
|
SELECT original_airdate FROM table_26866205_1 WHERE series__number = 26
|
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 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
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- give me the number of patients diagnosed under diagnoses icd9 code 4659 whose drug type is additive.
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE diagnoses.icd9_code = "4659" AND prescriptions.drug_type = "ADDITIVE"
|
mimicsql_data
|
CREATE TABLE table_18712423_3 (
series_episode INTEGER,
viewers__millions_ VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the show episode number of the episode that reached 1.215 millions views?
|
SELECT MIN(series_episode) FROM table_18712423_3 WHERE viewers__millions_ = "1.215"
|
sql_create_context
|
CREATE TABLE date_day (
month_number int,
day_number int,
year int,
day_name varchar
)
CREATE TABLE fare (
fare_id int,
from_airport varchar,
to_airport varchar,
fare_basis_code text,
fare_airline text,
restriction_code text,
one_direction_cost int,
round_trip_cost int,
round_trip_required varchar
)
CREATE TABLE dual_carrier (
main_airline varchar,
low_flight_number int,
high_flight_number int,
dual_airline varchar,
service_name text
)
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 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 state (
state_code text,
state_name text,
country_name text
)
CREATE TABLE time_zone (
time_zone_code text,
time_zone_name text,
hours_from_gmt int
)
CREATE TABLE compartment_class (
compartment varchar,
class_type varchar
)
CREATE TABLE time_interval (
period text,
begin_time int,
end_time int
)
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 restriction (
restriction_code text,
advance_purchase int,
stopovers text,
saturday_stay_required text,
minimum_stay int,
maximum_stay int,
application text,
no_discounts text
)
CREATE TABLE airport (
airport_code varchar,
airport_name text,
airport_location text,
state_code varchar,
country_name varchar,
time_zone_code varchar,
minimum_connect_time int
)
CREATE TABLE city (
city_code varchar,
city_name varchar,
state_code varchar,
country_name varchar,
time_zone_code varchar
)
CREATE TABLE month (
month_number int,
month_name text
)
CREATE TABLE airport_service (
city_code varchar,
airport_code varchar,
miles_distant int,
direction varchar,
minutes_distant 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 airline (
airline_code varchar,
airline_name text,
note text
)
CREATE TABLE days (
days_code varchar,
day_name varchar
)
CREATE TABLE food_service (
meal_code text,
meal_number int,
compartment text,
meal_description varchar
)
CREATE TABLE class_of_service (
booking_class varchar,
rank int,
class_description text
)
CREATE TABLE equipment_sequence (
aircraft_code_sequence varchar,
aircraft_code varchar
)
CREATE TABLE flight_fare (
flight_id int,
fare_id int
)
CREATE TABLE flight_leg (
flight_id int,
leg_number int,
leg_flight int
)
CREATE TABLE ground_service (
city_code text,
airport_code text,
transport_type text,
ground_fare int
)
CREATE TABLE code_description (
code varchar,
description text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- i need a flight from PHILADELPHIA to DENVER
|
SELECT DISTINCT flight.flight_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, flight WHERE CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'PHILADELPHIA' AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'DENVER' AND flight.from_airport = AIRPORT_SERVICE_0.airport_code AND flight.to_airport = AIRPORT_SERVICE_1.airport_code
|
atis
|
CREATE TABLE table_204_469 (
id number,
"coach" text,
"years" text,
"seasons" number,
"wins" number,
"losses" number,
"ties" number,
"pct" number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- which coach has the least number of total games on their record ?
|
SELECT "coach" FROM table_204_469 ORDER BY "wins" + "losses" + "ties" LIMIT 1
|
squall
|
CREATE TABLE table_37085 (
"Round" real,
"Player" text,
"Position" text,
"Nationality" text,
"College/Junior/Club Team (League)" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What country does Round 4 come from?
|
SELECT "Nationality" FROM table_37085 WHERE "Round" = '4'
|
wikisql
|
CREATE TABLE table_name_58 (
lost INTEGER,
points VARCHAR,
against VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the highest number lost with more than 29 points and an against less than 19?
|
SELECT MAX(lost) FROM table_name_58 WHERE points > 29 AND against < 19
|
sql_create_context
|
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime 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 inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
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 cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name 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 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 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 d_labitems (
row_id number,
itemid number,
label text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- has patient 12274 undergone any coronar arteriogr-1 cath treatment in 2105?
|
SELECT COUNT(*) > 0 FROM procedures_icd WHERE procedures_icd.icd9_code = (SELECT d_icd_procedures.icd9_code FROM d_icd_procedures WHERE d_icd_procedures.short_title = 'coronar arteriogr-1 cath') AND procedures_icd.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 12274) AND STRFTIME('%y', procedures_icd.charttime) = '2105'
|
mimic_iii
|
CREATE TABLE table_12668 (
"Rank" real,
"Result" text,
"Wind" text,
"Athlete" text,
"Date" text,
"Location" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What kind of Wind has a Result of 21.69?
|
SELECT "Wind" FROM table_12668 WHERE "Result" = '21.69'
|
wikisql
|
CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
)
CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those records from the products and each product's manufacturer, return a bar chart about the distribution of name and code , and group by attribute name, display in desc by the X.
|
SELECT T1.Name, T1.Code FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY T1.Name, T1.Name ORDER BY T1.Name DESC
|
nvbench
|
CREATE TABLE table_69615 (
"Player" text,
"Country" text,
"Year(s) won" text,
"Total" real,
"To par" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the average total of Gay Brewer from the United States with a to par of 9?
|
SELECT AVG("Total") FROM table_69615 WHERE "Country" = 'united states' AND "To par" = '9' AND "Player" = 'gay brewer'
|
wikisql
|
CREATE TABLE table_50328 (
"Season" text,
"North" text,
"South" text,
"East" text,
"West" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was west when ev f rstenfeldbruck was south?
|
SELECT "West" FROM table_50328 WHERE "South" = 'ev fürstenfeldbruck'
|
wikisql
|
CREATE TABLE table_name_25 (
score VARCHAR,
competition VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the score of the 1998 FIFA World Cup qualification competition?
|
SELECT score FROM table_name_25 WHERE competition = "1998 fifa world cup qualification"
|
sql_create_context
|
CREATE TABLE table_31144 (
"Season" real,
"Winner" text,
"Runner-up" text,
"Third place" text,
"Fourth place" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many seasons did Otsuka Pharmaceuticals come in third?
|
SELECT COUNT("Season") FROM table_31144 WHERE "Third place" = 'Otsuka Pharmaceuticals'
|
wikisql
|
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_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 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
)
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 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_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 在零九年九月二十号直到一六年十月三十号之中患者李雅蕊被开出药品255778471-s总数是多少？
|
SELECT COUNT(*) FROM qtb JOIN t_kc22 ON qtb.MED_CLINIC_ID = t_kc22.MED_CLINIC_ID WHERE qtb.PERSON_NM = '李雅蕊' AND t_kc22.STA_DATE BETWEEN '2009-09-20' AND '2016-10-30' AND t_kc22.SOC_SRT_DIRE_CD = '255778471-s' UNION SELECT COUNT(*) FROM gyb JOIN t_kc22 ON gyb.MED_CLINIC_ID = t_kc22.MED_CLINIC_ID WHERE gyb.PERSON_NM = '李雅蕊' AND t_kc22.STA_DATE BETWEEN '2009-09-20' AND '2016-10-30' AND t_kc22.SOC_SRT_DIRE_CD = '255778471-s' UNION SELECT COUNT(*) FROM zyb JOIN t_kc22 ON zyb.MED_CLINIC_ID = t_kc22.MED_CLINIC_ID WHERE zyb.PERSON_NM = '李雅蕊' AND t_kc22.STA_DATE BETWEEN '2009-09-20' AND '2016-10-30' AND t_kc22.SOC_SRT_DIRE_CD = '255778471-s' UNION SELECT COUNT(*) FROM mzb JOIN t_kc22 ON mzb.MED_CLINIC_ID = t_kc22.MED_CLINIC_ID WHERE mzb.PERSON_NM = '李雅蕊' AND t_kc22.STA_DATE BETWEEN '2009-09-20' AND '2016-10-30' AND t_kc22.SOC_SRT_DIRE_CD = '255778471-s'
|
css
|
CREATE TABLE table_33041 (
"Week" real,
"Date" text,
"Opponent" text,
"Result" text,
"Attendance" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the attendance of the game on December 11, 2005?
|
SELECT "Attendance" FROM table_33041 WHERE "Date" = 'december 11, 2005'
|
wikisql
|
CREATE TABLE table_name_42 (
author VARCHAR,
language VARCHAR,
book_title VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which author wrote Sironia, Texas in English?
|
SELECT author FROM table_name_42 WHERE language = "english" AND book_title = "sironia, texas"
|
sql_create_context
|
CREATE TABLE table_69025 (
"Appearances" real,
"Team" text,
"Wins" real,
"Losses" real,
"Winning percentage" real,
"Season(s)" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- With Appearances larger than 1, what is the Wins for the Reno Aces Team?
|
SELECT MIN("Wins") FROM table_69025 WHERE "Team" = 'reno aces' AND "Appearances" > '1'
|
wikisql
|
CREATE TABLE organization_contact_individuals (
individual_id number,
organization_id number,
date_contact_from time,
date_contact_to time
)
CREATE TABLE services (
service_id number,
service_type_code text,
service_name text,
service_descriptio text
)
CREATE TABLE forms (
form_id number,
form_type_code text,
service_id number,
form_number text,
form_name text,
form_description text
)
CREATE TABLE parties (
party_id number,
payment_method_code text,
party_phone text,
party_email text
)
CREATE TABLE addresses (
address_id number,
line_1_number_building text,
town_city text,
zip_postcode text,
state_province_county text,
country text
)
CREATE TABLE party_services (
booking_id number,
customer_id number,
service_id number,
service_datetime time,
booking_made_date time
)
CREATE TABLE party_forms (
party_id number,
form_id number,
date_completion_started time,
form_status_code text,
date_fully_completed time
)
CREATE TABLE organizations (
organization_id number,
date_formed time,
organization_name text,
uk_vat_number text
)
CREATE TABLE party_addresses (
party_id number,
address_id number,
date_address_from time,
address_type_code text,
date_address_to time
)
CREATE TABLE individuals (
individual_id number,
individual_first_name text,
individual_middle_name text,
inidividual_phone text,
individual_email text,
individual_address text,
individual_last_name text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the name of the organization that was formed most recently?
|
SELECT organization_name FROM organizations ORDER BY date_formed DESC LIMIT 1
|
spider
|
CREATE TABLE table_36176 (
"Character" text,
"Actor" text,
"Duration" text,
"Role" text,
"Appearances" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the duration for nickolas grace as the actor?
|
SELECT "Duration" FROM table_36176 WHERE "Actor" = 'nickolas grace'
|
wikisql
|
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc21_t_kc22 (
MED_CLINIC_ID text,
MED_EXP_DET_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_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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 小儿麻醉科因疾病T40.906而住院花费所以的平均费用是多少钱从2003年5月11日开始到2016年12月20日结束？
|
SELECT AVG(t_kc21.MED_AMOUT) FROM t_kc21 WHERE t_kc21.MED_ORG_DEPT_NM = '小儿麻醉科' AND t_kc21.IN_HOSP_DATE BETWEEN '2003-05-11' AND '2016-12-20' AND t_kc21.IN_DIAG_DIS_CD = 'T40.906' AND t_kc21.CLINIC_TYPE = '住院'
|
css
|
CREATE TABLE gwyjzb (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID number,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_CLINIC_ID text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE fgwyjzb (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID number,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 在以前这个患者戚智纯有得过哪些疾病呢？
|
SELECT gwyjzb.IN_DIAG_DIS_CD, gwyjzb.IN_DIAG_DIS_NM FROM gwyjzb WHERE gwyjzb.PERSON_NM = '戚智纯' UNION SELECT fgwyjzb.IN_DIAG_DIS_CD, fgwyjzb.IN_DIAG_DIS_NM FROM fgwyjzb WHERE fgwyjzb.PERSON_NM = '戚智纯'
|
css
|
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
CREATE TABLE Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense 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 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 ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
CREATE TABLE PostFeedback (
Id number,
PostId number,
IsAnonymous boolean,
VoteTypeId number,
CreationDate time
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
CREATE TABLE CloseReasonTypes (
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 ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE VoteTypes (
Id number,
Name text
)
CREATE TABLE PostTypes (
Id number,
Name 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 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 PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description 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 PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE ReviewTaskResultTypes (
Id number,
Name text,
Description text
)
CREATE TABLE TagSynonyms (
Id number,
SourceTagName text,
TargetTagName text,
CreationDate time,
OwnerUserId number,
AutoRenameCount number,
LastAutoRename time,
Score number,
ApprovedByUserId number,
ApprovalDate time
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE PendingFlags (
Id number,
FlagTypeId number,
PostId number,
CreationDate time,
CloseReasonTypeId number,
CloseAsOffTopicReasonTypeId number,
DuplicateOfQuestionId number,
BelongsOnBaseHostAddress text
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Search users by tag and location.
|
SELECT u.Id AS "user_link", SUM(Score) AS totalscore FROM Posts AS p INNER JOIN PostTags AS pt ON pt.PostId = p.Id OR pt.PostId = p.ParentId INNER JOIN Tags AS t ON t.Id = pt.TagId INNER JOIN Users AS u ON u.Id = p.OwnerUserId WHERE TagName = '##tag1:string##' COLLATE SQL_Latin1_General_CP1_CI_AI AND Location LIKE '%' + '##location:string##' + '%' COLLATE SQL_Latin1_General_CP1_CI_AI GROUP BY u.Id ORDER BY SUM(Score) DESC
|
sede
|
CREATE TABLE table_45673 (
"City" text,
"Country" text,
"IATA" text,
"ICAO" text,
"Airport" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the city in India with an airport named Sardar Vallabhbhai Patel International Airport?
|
SELECT "City" FROM table_45673 WHERE "Country" = 'india' AND "Airport" = 'sardar vallabhbhai patel international airport'
|
wikisql
|
CREATE TABLE club (
club_id number,
name text,
region text,
start_year text
)
CREATE TABLE competition_result (
competition_id number,
club_id_1 number,
club_id_2 number,
score text
)
CREATE TABLE player (
player_id number,
name text,
position text,
club_id number,
apps number,
tries number,
goals text,
points number
)
CREATE TABLE competition (
competition_id number,
year number,
competition_type text,
country text
)
CREATE TABLE club_rank (
rank number,
club_id number,
gold number,
silver number,
bronze number,
total number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the total number of clubs that have less than 10 medals in total?
|
SELECT COUNT(*) FROM club_rank WHERE total < 10
|
spider
|
CREATE TABLE table_name_22 (
to_par VARCHAR,
country VARCHAR,
place VARCHAR,
score VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the to par of the player from the United States with a t6 place and a score of 70-73-68-73=284?
|
SELECT to_par FROM table_name_22 WHERE country = "united states" AND place = "t6" AND score = 70 - 73 - 68 - 73 = 284
|
sql_create_context
|
CREATE TABLE bridge (
architect_id int,
id int,
name text,
location text,
length_meters real,
length_feet real
)
CREATE TABLE architect (
id text,
name text,
nationality text,
gender text
)
CREATE TABLE mill (
architect_id int,
id int,
location text,
name text,
type text,
built_year int,
notes text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What are the ids and names of the architects who built at least 3 bridges , I want to rank in asc by the x-axis.
|
SELECT T1.name, T1.id FROM architect AS T1 JOIN bridge AS T2 ON T1.id = T2.architect_id ORDER BY T1.name
|
nvbench
|
CREATE TABLE table_name_65 (
away_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What did carlton score while away?
|
SELECT away_team AS score FROM table_name_65 WHERE away_team = "carlton"
|
sql_create_context
|
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those employees who do not work in departments with managers that have ids between 100 and 200, draw a line chart about the change of manager_id over hire_date .
|
SELECT HIRE_DATE, MANAGER_ID FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200)
|
nvbench
|
CREATE TABLE table_48355 (
"Date" text,
"Opponent" text,
"Site" text,
"Result" text,
"Attendance" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What were the Results for 25,000 Attendance?
|
SELECT "Result" FROM table_48355 WHERE "Attendance" = '25,000'
|
wikisql
|
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 lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE 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 medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many patients were tested for abscess?
|
SELECT COUNT(DISTINCT patient.uniquepid) FROM patient WHERE patient.patientunitstayid IN (SELECT microlab.patientunitstayid FROM microlab WHERE microlab.culturesite = 'abscess')
|
eicu
|
CREATE TABLE table_22660 (
"Game" real,
"Date" text,
"Opponent" text,
"Score" text,
"High points" text,
"High rebounds" text,
"High assists" text,
"Location" text,
"Record" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the record of the game in which Dydek (10) did the most high rebounds?
|
SELECT "Record" FROM table_22660 WHERE "High rebounds" = 'Dydek (10)'
|
wikisql
|
CREATE TABLE table_14316 (
"Outcome" text,
"Date" text,
"Tournament" text,
"Surface" text,
"Partnering" text,
"Opponents" text,
"Score" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who was the parter against Marin ili lovro Zovko?
|
SELECT "Partnering" FROM table_14316 WHERE "Opponents" = 'marin čilić lovro zovko'
|
wikisql
|
CREATE TABLE table_203_308 (
id number,
"athlete" text,
"nation" text,
"olympics" text,
"gold" number,
"silver" number,
"bronze" number,
"total" number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- who has earned the most medals ?
|
SELECT "athlete" FROM table_203_308 ORDER BY "total" DESC LIMIT 1
|
squall
|
CREATE TABLE table_29590 (
"Players" text,
"Games Won" real,
"Games Lost" real,
"Total points" real,
"Grand Average" text,
"Best Winning Average" text,
"Best Run" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- if the best run was 138, what is the amount of games lost?
|
SELECT "Games Lost" FROM table_29590 WHERE "Best Run" = '138'
|
wikisql
|
CREATE TABLE table_name_30 (
round VARCHAR,
position VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which round's position is according to official website?
|
SELECT round FROM table_name_30 WHERE position = "according to official website"
|
sql_create_context
|
CREATE TABLE table_28441 (
"Name" text,
"Original Club" text,
"Stadium" text,
"City" text,
"Country" text,
"Sport" text,
"Founded" real,
"Reason for foundation with source" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many clubs were founded in the westfalenstadion stadium?
|
SELECT COUNT("Founded") FROM table_28441 WHERE "Stadium" = 'Westfalenstadion'
|
wikisql
|
CREATE TABLE table_name_51 (
laps VARCHAR,
time_retired VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many laps have a time/retired of +23.080?
|
SELECT laps FROM table_name_51 WHERE time_retired = "+23.080"
|
sql_create_context
|
CREATE TABLE table_39250 (
"Rank" real,
"Town" text,
"Population" real,
"Year" real,
"Borough" text,
"Definition" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Year is the highest one that has a Population larger than 13,012, and a Borough of richmondshire?
|
SELECT MAX("Year") FROM table_39250 WHERE "Population" > '13,012' AND "Borough" = 'richmondshire'
|
wikisql
|
CREATE TABLE table_47315 (
"Title" text,
"Parent magazine" text,
"Magazine type" text,
"Frequency" text,
"First published" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the frequency that the magazine issues that was first published on april 27, 2010?
|
SELECT "Frequency" FROM table_47315 WHERE "First published" = 'april 27, 2010'
|
wikisql
|
CREATE TABLE table_47471 (
"Subclass" text,
"Part 1" text,
"Part 2" text,
"Part 3" text,
"Part 4" text,
"Verb meaning" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the part 4 with *heguldun *febungun in part 3?
|
SELECT "Part 4" FROM table_47471 WHERE "Part 3" = '*heguldun *febungun'
|
wikisql
|
CREATE TABLE school_performance (
School_Id int,
School_Year text,
Class_A text,
Class_AA text
)
CREATE TABLE school (
School_ID int,
School text,
Location text,
Enrollment real,
Founded real,
Denomination text,
Boys_or_Girls text,
Day_or_Boarding text,
Year_Entered_Competition real,
School_Colors text
)
CREATE TABLE player (
Player_ID int,
Player text,
Team text,
Age int,
Position text,
School_ID int
)
CREATE TABLE school_details (
School_ID int,
Nickname text,
Colors text,
League text,
Class text,
Division text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For each denomination, return the denomination and the count of schools with that denomination. Visualize by pie chart.
|
SELECT Denomination, COUNT(*) FROM school GROUP BY Denomination
|
nvbench
|
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 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
)
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 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 提供一下04488736077医疗就诊参与人员的姓名、性别、年龄，还有他们的公民身份号码
|
SELECT qtb.PERSON_NM, qtb.PERSON_SEX, qtb.PERSON_AGE, qtb.IDENTITY_CARD FROM qtb WHERE qtb.MED_CLINIC_ID = '75285494355' UNION SELECT gyb.PERSON_NM, gyb.PERSON_SEX, gyb.PERSON_AGE, gyb.IDENTITY_CARD FROM gyb WHERE gyb.MED_CLINIC_ID = '75285494355' UNION SELECT zyb.PERSON_NM, zyb.PERSON_SEX, zyb.PERSON_AGE, zyb.IDENTITY_CARD FROM zyb WHERE zyb.MED_CLINIC_ID = '75285494355' UNION SELECT mzb.PERSON_NM, mzb.PERSON_SEX, mzb.PERSON_AGE, mzb.IDENTITY_CARD FROM mzb WHERE mzb.MED_CLINIC_ID = '75285494355'
|
css
|
CREATE TABLE table_name_53 (
date VARCHAR,
home_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Date, when Home Team is 'Luton Town'?
|
SELECT date FROM table_name_53 WHERE home_team = "luton town"
|
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 diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
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.
-- give the number of patients whose lab test abnormal status is delta and lab test name is promyelocytes.
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE lab.flag = "delta" AND lab.label = "Promyelocytes"
|
mimicsql_data
|
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 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 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
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 在编号为1303547的医院，查出非科室乳腺负责的在2003-02-21到2005-09-08内所有医疗就诊记录
|
SELECT * FROM qtb WHERE qtb.MED_SER_ORG_NO = '1303547' AND qtb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' UNION SELECT * FROM gyb WHERE gyb.MED_SER_ORG_NO = '1303547' AND gyb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' UNION SELECT * FROM zyb WHERE zyb.MED_SER_ORG_NO = '1303547' AND zyb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' UNION SELECT * FROM mzb WHERE mzb.MED_SER_ORG_NO = '1303547' AND mzb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' EXCEPT SELECT * FROM qtb WHERE qtb.MED_SER_ORG_NO = '1303547' AND qtb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' AND qtb.MED_ORG_DEPT_NM = '乳腺外科' UNION SELECT * FROM gyb WHERE gyb.MED_SER_ORG_NO = '1303547' AND gyb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' AND gyb.MED_ORG_DEPT_NM = '乳腺外科' UNION SELECT * FROM zyb WHERE zyb.MED_SER_ORG_NO = '1303547' AND zyb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' AND zyb.MED_ORG_DEPT_NM = '乳腺外科' UNION SELECT * FROM mzb WHERE mzb.MED_SER_ORG_NO = '1303547' AND mzb.IN_HOSP_DATE BETWEEN '2003-02-21' AND '2005-09-08' AND mzb.MED_ORG_DEPT_NM = '乳腺外科'
|
css
|
CREATE TABLE table_name_86 (
away_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the away team score for South Melbourne?
|
SELECT away_team AS score FROM table_name_86 WHERE away_team = "south melbourne"
|
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 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 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 gender is m and drug name is ciprofloxacin?
|
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 = "Ciprofloxacin"
|
mimicsql_data
|
CREATE TABLE table_19611 (
"Hand" text,
"1 credit" real,
"2 credits" real,
"3 credits" real,
"4 credits" real,
"5 credits" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the least 2 credits for straight hand
|
SELECT MIN("2 credits") FROM table_19611 WHERE "Hand" = 'Straight'
|
wikisql
|
CREATE TABLE table_name_14 (
location VARCHAR,
year VARCHAR,
second VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- In years after 1999, what was the location where Anja Huber finished 2nd?
|
SELECT location FROM table_name_14 WHERE year > 1999 AND second = "anja huber"
|
sql_create_context
|
CREATE TABLE table_18288 (
"District" text,
"Incumbent" text,
"Party" text,
"First elected" real,
"Result" text,
"Candidates" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who were the candidates in the Louisiana 4 district?
|
SELECT "Candidates" FROM table_18288 WHERE "District" = 'Louisiana 4'
|
wikisql
|
CREATE TABLE table_39245 (
"Date" text,
"Visitor" text,
"Score" text,
"Home" text,
"Leading scorer" text,
"Attendance" real,
"Record" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the name of the leading scorer when the record was 9 6?
|
SELECT "Leading scorer" FROM table_39245 WHERE "Record" = '9–6'
|
wikisql
|
CREATE TABLE table_60687 (
"Golden Rivers" text,
"Wins" real,
"Byes" real,
"Losses" real,
"Draws" real,
"Against" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the highest number of wins for Quambatook when Against is less than 1129?
|
SELECT MAX("Wins") FROM table_60687 WHERE "Golden Rivers" = 'quambatook' AND "Against" < '1129'
|
wikisql
|
CREATE TABLE Participates_in (
stuid INTEGER,
actid INTEGER
)
CREATE TABLE Student (
StuID INTEGER,
LName VARCHAR(12),
Fname VARCHAR(12),
Age INTEGER,
Sex VARCHAR(1),
Major INTEGER,
Advisor INTEGER,
city_code VARCHAR(3)
)
CREATE TABLE Faculty_Participates_in (
FacID INTEGER,
actid INTEGER
)
CREATE TABLE Activity (
actid INTEGER,
activity_name varchar(25)
)
CREATE TABLE Faculty (
FacID INTEGER,
Lname VARCHAR(15),
Fname VARCHAR(15),
Rank VARCHAR(15),
Sex VARCHAR(1),
Phone INTEGER,
Room VARCHAR(5),
Building VARCHAR(13)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Show how many rank from each rank, show X-axis in ascending order.
|
SELECT Rank, COUNT(Rank) FROM Faculty GROUP BY Rank ORDER BY Rank
|
nvbench
|
CREATE TABLE table_11536 (
"Player" text,
"Nationality" text,
"Position" text,
"Years for Jazz" text,
"School/Club Team" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who is the player who went to Stanford?
|
SELECT "Player" FROM table_11536 WHERE "School/Club Team" = 'stanford'
|
wikisql
|
CREATE TABLE Products (
Code INTEGER,
Name VARCHAR(255),
Price DECIMAL,
Manufacturer INTEGER
)
CREATE TABLE Manufacturers (
Code INTEGER,
Name VARCHAR(255),
Headquarter VARCHAR(255),
Founder VARCHAR(255),
Revenue REAL
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Give me a bar chart to show the revenue of the company that earns the highest revenue in each headquarter city, and rank Y-axis from low to high order.
|
SELECT Headquarter, MAX(Revenue) FROM Manufacturers GROUP BY Headquarter ORDER BY MAX(Revenue)
|
nvbench
|
CREATE TABLE table_9130 (
"Tournament" text,
"Surface" text,
"Week" text,
"Winner" text,
"Finalist" text,
"Semifinalists" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What type of surface was played at the tournament in berlin?
|
SELECT "Surface" FROM table_9130 WHERE "Tournament" = 'berlin'
|
wikisql
|
CREATE TABLE table_72361 (
"District" text,
"Incumbent" text,
"Party" text,
"First elected" real,
"Results" text,
"Candidates" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many candidates were elected first in 1980?
|
SELECT COUNT("Candidates") FROM table_72361 WHERE "First elected" = '1980'
|
wikisql
|
CREATE TABLE film (
film_id number,
title text,
studio text,
director text,
gross_in_dollar number
)
CREATE TABLE market (
market_id number,
country text,
number_cities number
)
CREATE TABLE film_market_estimation (
estimation_id number,
low_estimate number,
high_estimate number,
film_id number,
type text,
market_id number,
year number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Show the distinct director of films with market estimation in the year of 1995.
|
SELECT DISTINCT T1.director FROM film AS T1 JOIN film_market_estimation AS T2 ON T1.film_id = T2.film_id WHERE T2.year = 1995
|
spider
|
CREATE TABLE table_name_25 (
chassis VARCHAR,
rank VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the chassis when the rank is 3rd?
|
SELECT chassis FROM table_name_25 WHERE rank = "3rd"
|
sql_create_context
|
CREATE TABLE table_name_65 (
tournament VARCHAR,
partner VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What Tournament has a Partner of tom gorman?
|
SELECT tournament FROM table_name_65 WHERE partner = "tom gorman"
|
sql_create_context
|
CREATE TABLE table_72711 (
"Season" real,
"Date" text,
"Location" text,
"Driver" text,
"Chassis" text,
"Engine" text,
"Team" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What engine does Galles Racing use?
|
SELECT "Engine" FROM table_72711 WHERE "Team" = 'Galles Racing'
|
wikisql
|
CREATE TABLE offering_instructor (
offering_instructor_id int,
offering_id int,
instructor_id int
)
CREATE TABLE comment_instructor (
instructor_id int,
student_id int,
score int,
comment_text varchar
)
CREATE TABLE gsi (
course_offering_id int,
student_id int
)
CREATE TABLE course (
course_id int,
name varchar,
department varchar,
number varchar,
credits varchar,
advisory_requirement varchar,
enforced_requirement varchar,
description varchar,
num_semesters int,
num_enrolled int,
has_discussion varchar,
has_lab varchar,
has_projects varchar,
has_exams varchar,
num_reviews int,
clarity_score int,
easiness_score int,
helpfulness_score int
)
CREATE TABLE 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 jobs (
job_id int,
job_title varchar,
description varchar,
requirement varchar,
city varchar,
state varchar,
country varchar,
zip int
)
CREATE TABLE requirement (
requirement_id int,
requirement varchar,
college varchar
)
CREATE TABLE area (
course_id int,
area varchar
)
CREATE TABLE course_prerequisite (
pre_course_id int,
course_id int
)
CREATE TABLE semester (
semester_id int,
semester varchar,
year int
)
CREATE TABLE program_requirement (
program_id int,
category varchar,
min_credit int,
additional_req 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 instructor (
instructor_id int,
name varchar,
uniqname varchar
)
CREATE TABLE program_course (
program_id int,
course_id int,
workload int,
category varchar
)
CREATE TABLE ta (
campus_job_id int,
student_id int,
location varchar
)
CREATE TABLE program (
program_id int,
name varchar,
college varchar,
introduction 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 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which upper level CS classes are offered next semester ?
|
SELECT DISTINCT course.department, course.name, course.number FROM course INNER JOIN program_course ON program_course.course_id = course.course_id INNER JOIN course_offering ON course.course_id = course_offering.course_id INNER JOIN semester ON semester.semester_id = course_offering.semester WHERE program_course.category LIKE '%ULCS%' AND semester.semester = 'FA' AND semester.year = 2016
|
advising
|
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE 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 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 d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE 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 d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label 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 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 d_items (
row_id number,
itemid number,
label text,
linksto 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 outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what was the name of the procedure that patient 8098 received two or more times until 02/2105.
|
SELECT d_icd_procedures.short_title FROM d_icd_procedures WHERE d_icd_procedures.icd9_code IN (SELECT t1.icd9_code FROM (SELECT procedures_icd.icd9_code, COUNT(procedures_icd.charttime) AS c1 FROM procedures_icd WHERE procedures_icd.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 8098) AND STRFTIME('%y-%m', procedures_icd.charttime) <= '2105-02' GROUP BY procedures_icd.icd9_code) AS t1 WHERE t1.c1 >= 2)
|
mimic_iii
|
CREATE TABLE table_13780 (
"Team 1" text,
"Agg." text,
"Team 2" text,
"1st leg" text,
"2nd leg" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the 1st leg when team 2 is Asil Lysi?
|
SELECT "1st leg" FROM table_13780 WHERE "Team 2" = 'asil lysi'
|
wikisql
|
CREATE TABLE table_name_71 (
score VARCHAR,
game VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the score for game number 30?
|
SELECT score FROM table_name_71 WHERE game = 30
|
sql_create_context
|
CREATE TABLE table_55011 (
"Date" text,
"Ship" text,
"Type" text,
"Nationality" text,
"Tonnage GRT" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Date has a Ship of hallbjorg?
|
SELECT "Date" FROM table_55011 WHERE "Ship" = 'hallbjorg'
|
wikisql
|
CREATE TABLE table_67034 (
"Name" text,
"Species/Authority" text,
"Order" text,
"Family" text,
"Red List" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which family has a Name of humpback whale?
|
SELECT "Family" FROM table_67034 WHERE "Name" = 'humpback whale'
|
wikisql
|
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE 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 countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those employees who do not work in departments with managers that have ids between 100 and 200, visualize a bar chart about the distribution of phone_number and salary .
|
SELECT PHONE_NUMBER, SALARY FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200)
|
nvbench
|
CREATE TABLE table_42954 (
"Member state" text,
"Population millions" real,
"MEPs" real,
"Inhabitants per MEP" real,
"Influence" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the lowest population in millions that has inhabitants per MEP less than 414,538, and an influence of 2.06, and MEPs less than 13?
|
SELECT MIN("Population millions") FROM table_42954 WHERE "Inhabitants per MEP" < '414,538' AND "Influence" = '2.06' AND "MEPs" < '13'
|
wikisql
|
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 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)
)
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 regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Give me a bar chart that groups and count the job id for all employees in the Finance department, and could you list by the bar in descending?
|
SELECT JOB_ID, COUNT(JOB_ID) FROM employees AS T1 JOIN departments AS T2 ON T1.DEPARTMENT_ID = T2.DEPARTMENT_ID WHERE T2.DEPARTMENT_NAME = 'Finance' GROUP BY JOB_ID ORDER BY JOB_ID DESC
|
nvbench
|
CREATE TABLE department (
dept_name varchar(20),
building varchar(15),
budget numeric(12,2)
)
CREATE TABLE course (
course_id varchar(8),
title varchar(50),
dept_name varchar(20),
credits numeric(2,0)
)
CREATE TABLE advisor (
s_ID varchar(5),
i_ID varchar(5)
)
CREATE TABLE student (
ID varchar(5),
name varchar(20),
dept_name varchar(20),
tot_cred numeric(3,0)
)
CREATE TABLE teaches (
ID varchar(5),
course_id varchar(8),
sec_id varchar(8),
semester varchar(6),
year numeric(4,0)
)
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)
)
CREATE TABLE instructor (
ID varchar(5),
name varchar(20),
dept_name varchar(20),
salary numeric(8,2)
)
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 takes (
ID varchar(5),
course_id varchar(8),
sec_id varchar(8),
semester varchar(6),
year numeric(4,0),
grade varchar(2)
)
CREATE TABLE classroom (
building varchar(15),
room_number varchar(7),
capacity numeric(4,0)
)
CREATE TABLE prereq (
course_id varchar(8),
prereq_id varchar(8)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the greatest capacity for rooms in each building? Draw a bar chart.
|
SELECT building, MAX(capacity) FROM classroom GROUP BY building
|
nvbench
|
CREATE TABLE table_59618 (
"Combined" text,
"50 yard Freestyle" text,
"100 yard Freestyle" text,
"200 yard Freestyle" text,
"500 yard Freestyle" text,
"100 yard Backstroke" text,
"100 yard Butterfly" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What 500 yard Freestyle has a Combined of palo verde, and a 100 yard Butterfly of edward kollar (douglas)?
|
SELECT "500 yard Freestyle" FROM table_59618 WHERE "Combined" = 'palo verde' AND "100 yard Butterfly" = 'edward kollar (douglas)'
|
wikisql
|
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
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 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 employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- You can return a bar chart to show the employees' first name and the corresponding manager's id.
|
SELECT FIRST_NAME, MANAGER_ID FROM employees
|
nvbench
|
CREATE TABLE table_51500 (
"Pick" real,
"Round" text,
"Player" text,
"Position" text,
"School" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What position does gerald carter play?
|
SELECT "Position" FROM table_51500 WHERE "Player" = 'gerald carter'
|
wikisql
|
CREATE TABLE table_name_92 (
district VARCHAR,
incumbent VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which district has an incumbent of Sanford Bishop?
|
SELECT district FROM table_name_92 WHERE incumbent = "sanford bishop"
|
sql_create_context
|
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 Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment 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 VoteTypes (
Id number,
Name text
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
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 CloseReasonTypes (
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 PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
CREATE TABLE SuggestedEdits (
Id number,
PostId number,
CreationDate time,
ApprovalDate time,
RejectionDate time,
OwnerUserId number,
Comment text,
Text text,
Title text,
Tags text,
RevisionGUID other
)
CREATE TABLE FlagTypes (
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 PostTypes (
Id number,
Name text
)
CREATE TABLE PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId 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 PostHistory (
Id number,
PostHistoryTypeId number,
PostId number,
RevisionGUID other,
CreationDate time,
UserId number,
UserDisplayName text,
Comment text,
Text text,
ContentLicense text
)
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE ReviewTaskResultTypes (
Id number,
Name text,
Description 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 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.
-- Top Android users in Canada.
|
WITH USER_BY_TAG AS (SELECT ROW_NUMBER() OVER (ORDER BY COUNT(*) DESC) AS Rank, u.Id AS "user_link", COUNT(*) AS UpVotes FROM Tags AS t INNER JOIN PostTags AS pt ON pt.TagId = t.Id INNER JOIN Posts AS p ON p.ParentId = pt.PostId INNER JOIN Votes AS v ON v.PostId = p.Id AND VoteTypeId = 2 INNER JOIN Users AS u ON u.Id = p.OwnerUserId WHERE LOWER(Location) LIKE '%canada%' AND TagName = 'android' GROUP BY u.Id, TagName) SELECT * FROM USER_BY_TAG WHERE rank <= 1000 ORDER BY UpVotes DESC
|
sede
|
CREATE TABLE table_203_835 (
id number,
"season" text,
"club" text,
"country" text,
"competition" text,
"apps." number,
"goals" number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- which country has the least amount of total goals ?
|
SELECT "country" FROM table_203_835 GROUP BY "country" ORDER BY SUM("goals") LIMIT 1
|
squall
|
CREATE TABLE table_1341663_33 (
district VARCHAR,
incumbent VARCHAR,
party VARCHAR,
first_elected VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What district did the Democratic party incumbent Stephen J. Solarz get first elected to in 1974?
|
SELECT district FROM table_1341663_33 WHERE party = "Democratic" AND first_elected = 1974 AND incumbent = "Stephen J. Solarz"
|
sql_create_context
|
CREATE TABLE party (
party_id number,
year number,
party text,
governor text,
lieutenant_governor text,
comptroller text,
attorney_general text,
us_senate text
)
CREATE TABLE election (
election_id number,
counties_represented text,
district number,
delegate text,
party number,
first_elected number,
committee text
)
CREATE TABLE county (
county_id number,
county_name text,
population number,
zip_code text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the parties associated with the delegates from district 1. Who served as governors of the parties?
|
SELECT T2.governor FROM election AS T1 JOIN party AS T2 ON T1.party = T2.party_id WHERE T1.district = 1
|
spider
|
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