instruction
stringlengths 151
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stringlengths 2
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CREATE TABLE table_name_40 (
crowd INTEGER,
away_team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the crowd size of the match featuring North Melbourne as the away team?
|
SELECT MIN(crowd) FROM table_name_40 WHERE away_team = "north melbourne"
|
sql_create_context
|
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 state (
state_code text,
state_name text,
country_name text
)
CREATE TABLE class_of_service (
booking_class varchar,
rank int,
class_description text
)
CREATE TABLE flight_leg (
flight_id int,
leg_number int,
leg_flight int
)
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 date_day (
month_number int,
day_number int,
year int,
day_name varchar
)
CREATE TABLE ground_service (
city_code text,
airport_code text,
transport_type text,
ground_fare int
)
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 flight_fare (
flight_id int,
fare_id int
)
CREATE TABLE time_zone (
time_zone_code text,
time_zone_name text,
hours_from_gmt int
)
CREATE TABLE days (
days_code varchar,
day_name varchar
)
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 compartment_class (
compartment varchar,
class_type varchar
)
CREATE TABLE food_service (
meal_code text,
meal_number int,
compartment text,
meal_description varchar
)
CREATE TABLE city (
city_code varchar,
city_name varchar,
state_code varchar,
country_name varchar,
time_zone_code 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 time_interval (
period text,
begin_time int,
end_time int
)
CREATE TABLE fare_basis (
fare_basis_code text,
booking_class text,
class_type text,
premium text,
economy text,
discounted text,
night text,
season text,
basis_days text
)
CREATE TABLE 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 code_description (
code varchar,
description text
)
CREATE TABLE airline (
airline_code varchar,
airline_name text,
note 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 equipment_sequence (
aircraft_code_sequence varchar,
aircraft_code varchar
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- i'd like to find a flight from MIAMI FLORIDA to LAS VEGAS NEVADA that would arrive before 1600 on sunday
|
SELECT DISTINCT flight.flight_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, date_day, days, flight, state AS STATE_0, state AS STATE_1 WHERE ((((((flight.arrival_time < 41 OR flight.time_elapsed >= 60) AND flight.departure_time > flight.arrival_time) AND date_day.day_number = 27 AND date_day.month_number = 8 AND date_day.year = 1991 AND days.day_name = date_day.day_name AND flight.flight_days = days.days_code) OR (date_day.day_number = 27 AND date_day.month_number = 8 AND date_day.year = 1991 AND days.day_name = date_day.day_name AND flight.flight_days = days.days_code AND NOT ((flight.arrival_time < 41 OR flight.time_elapsed >= 60) AND flight.departure_time > flight.arrival_time))) AND flight.arrival_time < 1600) AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'LAS VEGAS' AND flight.to_airport = AIRPORT_SERVICE_1.airport_code AND STATE_1.state_code = CITY_1.state_code AND STATE_1.state_name = 'NEVADA') AND CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'MIAMI' AND flight.from_airport = AIRPORT_SERVICE_0.airport_code AND STATE_0.state_code = CITY_0.state_code AND STATE_0.state_name = 'FLORIDA'
|
atis
|
CREATE TABLE jyjgzbb (
JYZBLSH text,
YLJGDM text,
BGDH text,
BGRQ time,
JYRQ time,
JCRGH text,
JCRXM text,
SHRGH text,
SHRXM text,
JCXMMC text,
JCZBDM text,
JCFF text,
JCZBMC text,
JCZBJGDX text,
JCZBJGDL number,
JCZBJGDW text,
SBBM text,
YQBH text,
YQMC text,
CKZFWDX text,
CKZFWXX number,
CKZFWSX number,
JLDW text
)
CREATE TABLE mzjzjlb (
YLJGDM text,
JZLSH text,
KH text,
KLX number,
MJZH text,
HZXM text,
NLS number,
NLY number,
ZSEBZ number,
JZZTDM number,
JZZTMC text,
JZJSSJ time,
TXBZ number,
ZZBZ number,
WDBZ number,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
ZZYSGH text,
QTJZYSGH text,
JZZDBM text,
JZZDSM text,
MZZYZDZZBM text,
MZZYZDZZMC text,
SG number,
TZ number,
TW number,
SSY number,
SZY number,
XL number,
HXPLC number,
ML number,
JLSJ time
)
CREATE TABLE person_info (
RYBH text,
XBDM number,
XBMC text,
XM text,
CSRQ time,
CSD text,
MZDM text,
MZMC text,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
XLDM text,
XLMC text,
ZYLBDM text,
ZYMC text
)
CREATE TABLE hz_info (
KH text,
KLX number,
YLJGDM text,
RYBH text
)
CREATE TABLE jybgb (
YLJGDM text,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text,
BGDH text,
BGRQ time,
JYLX number,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SQRGH text,
SQRXM text,
BGRGH text,
BGRXM text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
JYKSBM text,
JYKSMC text,
BGJGDM text,
BGJGMC text,
SQRQ time,
CJRQ time,
JYRQ time,
BGSJ time,
BBDM text,
BBMC text,
JYBBH text,
BBZT number,
BBCJBW text,
JSBBSJ time,
JYXMMC text,
JYXMDM text,
JYSQJGMC text,
JYJGMC text,
JSBBRQSJ time,
JYJSQM text,
JYJSGH text
)
CREATE TABLE zyjzjlb (
YLJGDM text,
JZLSH text,
MZJZLSH text,
KH text,
KLX number,
HZXM text,
WDBZ number,
RYDJSJ time,
RYTJDM number,
RYTJMC text,
JZKSDM text,
JZKSMC text,
RZBQDM text,
RZBQMC text,
RYCWH text,
CYKSDM text,
CYKSMC text,
CYBQDM text,
CYBQMC text,
CYCWH text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text,
MZBMLX number,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYSJ time,
CYSJ time,
CYZTDM number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 6929712医疗机构在二零一四年三月十七日到二零一四年十月十四日期间一共多少特需门诊的就诊记录
|
SELECT COUNT(*) FROM mzjzjlb WHERE YLJGDM = '6929712' AND JZKSRQ BETWEEN '2014-03-17' AND '2014-10-14' AND TXBZ > 0
|
css
|
CREATE TABLE hz_info (
KH text,
KLX number,
RYBH text,
YLJGDM text
)
CREATE TABLE mzjzjlb_jybgb (
YLJGDM_MZJZJLB text,
BGDH number,
YLJGDM number
)
CREATE TABLE jybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH text,
BGJGDM text,
BGJGMC text,
BGRGH text,
BGRQ time,
BGRXM text,
BGSJ time,
CJRQ time,
JSBBRQSJ time,
JSBBSJ time,
JYBBH text,
JYJGMC text,
JYJSGH text,
JYJSQM text,
JYKSBM text,
JYKSMC text,
JYLX number,
JYRQ time,
JYSQJGMC text,
JYXMDM text,
JYXMMC text,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM text,
YLJGDM_ZYJZJLB text
)
CREATE TABLE mzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH text,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TXBZ number,
TZ number,
WDBZ number,
XL number,
YLJGDM text,
ZSEBZ number,
ZZBZ number,
ZZYSGH text
)
CREATE TABLE person_info (
CSD text,
CSRQ time,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
MZDM text,
MZMC text,
RYBH text,
XBDM number,
XBMC text,
XLDM text,
XLMC text,
XM text,
ZYLBDM text,
ZYMC text
)
CREATE TABLE jyjgzbb (
BGDH text,
BGRQ time,
CKZFWDX text,
CKZFWSX number,
CKZFWXX number,
JCFF text,
JCRGH text,
JCRXM text,
JCXMMC text,
JCZBDM text,
JCZBJGDL number,
JCZBJGDW text,
JCZBJGDX text,
JCZBMC text,
JLDW text,
JYRQ time,
JYZBLSH text,
SBBM text,
SHRGH text,
SHRXM text,
YLJGDM text,
YQBH text,
YQMC text
)
CREATE TABLE zyjzjlb (
CYBQDM text,
CYBQMC text,
CYCWH text,
CYKSDM text,
CYKSMC text,
CYSJ time,
CYZTDM number,
HZXM text,
JZKSDM text,
JZKSMC text,
JZLSH text,
KH text,
KLX number,
MZBMLX number,
MZJZLSH text,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYCWH text,
RYDJSJ time,
RYSJ time,
RYTJDM number,
RYTJMC text,
RZBQDM text,
RZBQMC text,
WDBZ number,
YLJGDM text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 患者郑欣嘉的检验报告单中有多少检验结果指标均异常？查询检验报告的单号
|
SELECT jybgb.BGDH FROM person_info JOIN hz_info JOIN mzjzjlb JOIN jybgb JOIN mzjzjlb_jybgb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = mzjzjlb_jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND mzjzjlb_jybgb.YLJGDM = jybgb.YLJGDM AND mzjzjlb_jybgb.BGDH = jybgb.BGDH AND mzjzjlb_jybgb.YLJGDM = jybgb.YLJGDM AND mzjzjlb_jybgb.BGDH = jybgb.BGDH WHERE person_info.XM = '郑欣嘉' AND NOT jybgb.BGDH IN (SELECT jyjgzbb.BGDH FROM jyjgzbb WHERE jyjgzbb.JCZBJGDL >= jyjgzbb.CKZFWXX AND jyjgzbb.JCZBJGDL <= jyjgzbb.CKZFWSX) UNION SELECT jybgb.BGDH FROM person_info JOIN hz_info JOIN zyjzjlb JOIN jybgb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = zyjzjlb.YLJGDM AND hz_info.KH = zyjzjlb.KH AND hz_info.KLX = zyjzjlb.KLX AND zyjzjlb.YLJGDM = jybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = jybgb.JZLSH_ZYJZJLB WHERE person_info.XM = '郑欣嘉' AND NOT jybgb.BGDH IN (SELECT jyjgzbb.BGDH FROM jyjgzbb WHERE jyjgzbb.JCZBJGDL >= jyjgzbb.CKZFWXX AND jyjgzbb.JCZBJGDL <= jyjgzbb.CKZFWSX)
|
css
|
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- provide the number of patients whose diagnosis long title is unspecified obesity and the drug route is pr.
|
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.long_title = "Obesity, unspecified" AND prescriptions.route = "PR"
|
mimicsql_data
|
CREATE TABLE table_name_28 (
team VARCHAR,
recopa_sudamericana_1992 VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which Team has a Recopa Sudamericana 1992 of runner-up?
|
SELECT team FROM table_name_28 WHERE recopa_sudamericana_1992 = "runner-up"
|
sql_create_context
|
CREATE TABLE table_19613 (
"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 hand for 1 credit 200
|
SELECT "Hand" FROM table_19613 WHERE "1 credit" = '200'
|
wikisql
|
CREATE TABLE table_name_51 (
pick INTEGER,
position VARCHAR,
player VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- When was chuck morris, back, drafted?
|
SELECT MIN(pick) FROM table_name_51 WHERE position = "back" AND player = "chuck morris"
|
sql_create_context
|
CREATE TABLE table_23281862_9 (
record VARCHAR,
high_assists VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the record where aaron brooks (6) is high assists?
|
SELECT record FROM table_23281862_9 WHERE high_assists = "Aaron Brooks (6)"
|
sql_create_context
|
CREATE TABLE table_10104 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the score for the away team at Essendon?
|
SELECT "Away team score" FROM table_10104 WHERE "Away team" = 'essendon'
|
wikisql
|
CREATE TABLE table_name_71 (
winner VARCHAR,
week_of VARCHAR,
runner_up VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who is the winner in the week listed as 26 June 2 weeks, when the runner-up is Arantxa S nchez Vicario?
|
SELECT winner FROM table_name_71 WHERE week_of = "26 june 2 weeks" AND runner_up = "arantxa sánchez vicario"
|
sql_create_context
|
CREATE TABLE table_11857 (
"Client" text,
"Windows" text,
"GNU/Linux" text,
"Mac OS X" text,
"Haiku" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which client had no GNU/Linux?
|
SELECT "Client" FROM table_11857 WHERE "GNU/Linux" = 'no'
|
wikisql
|
CREATE TABLE table_name_89 (
grand_rapids__grr_ VARCHAR,
detroit__dtw_ VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the passenger fare for Grand Rapids, when the passenger fare for Detroit was $378.55?
|
SELECT grand_rapids__grr_ FROM table_name_89 WHERE detroit__dtw_ = "$378.55"
|
sql_create_context
|
CREATE TABLE table_name_4 (
density__hab__km²__ VARCHAR,
population_censo_2007_hab_ VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the density (hab/km ) with a population censo 2007(hab) of 336.293*?
|
SELECT density__hab__km²__ FROM table_name_4 WHERE population_censo_2007_hab_ = "336.293*"
|
sql_create_context
|
CREATE TABLE table_204_736 (
id number,
"party" text,
"candidate" text,
"votes" number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- which candidate of the citizens committee has the most votes ?
|
SELECT "candidate" FROM table_204_736 WHERE "party" = "citizens' committee" ORDER BY "votes" DESC LIMIT 1
|
squall
|
CREATE TABLE station (
Station_ID int,
Name text,
Annual_entry_exit real,
Annual_interchanges real,
Total_Passengers real,
Location text,
Main_Services text,
Number_of_Platforms int
)
CREATE TABLE train (
Train_ID int,
Name text,
Time text,
Service text
)
CREATE TABLE train_station (
Train_ID int,
Station_ID int
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the number of platforms for each location? Show the comparison with a bar chart, I want to order by the Y in asc.
|
SELECT Location, SUM(Number_of_Platforms) FROM station GROUP BY Location ORDER BY SUM(Number_of_Platforms)
|
nvbench
|
CREATE TABLE table_4993 (
"Version" text,
"Length" text,
"Album" text,
"Remixed by" text,
"Year" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the total number of Year that has an Album of Remixes?
|
SELECT SUM("Year") FROM table_4993 WHERE "Album" = 'remixes'
|
wikisql
|
CREATE TABLE table_70621 (
"Team" text,
"Truck(s)" text,
"Driver(s)" text,
"Primary Sponsor(s)" text,
"Owner(s)" text,
"Crew Chief" text,
"Rounds" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the most number of rounds that the Team from RBR Enterprises and having a Chevrolet Silverado ran?
|
SELECT MAX("Rounds") FROM table_70621 WHERE "Truck(s)" = 'chevrolet silverado' AND "Team" = 'rbr enterprises'
|
wikisql
|
CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description text
)
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE 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 PostTypes (
Id number,
Name 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 PostFeedback (
Id number,
PostId number,
IsAnonymous boolean,
VoteTypeId number,
CreationDate time
)
CREATE TABLE Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE SuggestedEditVotes (
Id number,
SuggestedEditId number,
UserId number,
VoteTypeId number,
CreationDate time,
TargetUserId number,
TargetRepChange number
)
CREATE TABLE CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE PostLinks (
Id number,
CreationDate time,
PostId number,
RelatedPostId number,
LinkTypeId number
)
CREATE TABLE TagSynonyms (
Id number,
SourceTagName text,
TargetTagName text,
CreationDate time,
OwnerUserId number,
AutoRenameCount number,
LastAutoRename time,
Score number,
ApprovedByUserId number,
ApprovalDate time
)
CREATE TABLE 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 PostTags (
PostId number,
TagId number
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
CREATE TABLE 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 ReviewTaskResults (
Id number,
ReviewTaskId number,
ReviewTaskResultTypeId number,
CreationDate time,
RejectionReasonId number,
Comment text
)
CREATE TABLE PendingFlags (
Id number,
FlagTypeId number,
PostId number,
CreationDate time,
CloseReasonTypeId number,
CloseAsOffTopicReasonTypeId number,
DuplicateOfQuestionId number,
BelongsOnBaseHostAddress text
)
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 Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
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 VoteTypes (
Id number,
Name text
)
CREATE TABLE PostNotices (
Id number,
PostId number,
PostNoticeTypeId number,
CreationDate time,
DeletionDate time,
ExpiryDate time,
Body text,
OwnerUserId number,
DeletionUserId number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Average answer score by reputation (mid-tier rep). A graph the average score of answers, grouped by the reputation of the users who posted them. ('Zoomed in' to exclude high-rep users.)
Full dataset: https://data.stackexchange.com/stackoverflow/query/544952/
Lower-rep users: https://data.stackexchange.com/stackoverflow/query/544955/
|
SELECT AVG(CAST(ROUND(Reputation, -FLOOR(LOG(10, Reputation))) AS INT)) AS UserReputation, AVG(CAST(Posts.Score AS FLOAT)) AS AverageAnswerScore FROM Posts INNER JOIN Users ON (Users.Id = Posts.OwnerUserId) WHERE PostTypeId = 2 AND Reputation < 10000 GROUP BY ROUND(Reputation, -FLOOR(LOG(10, Reputation))) ORDER BY UserReputation
|
sede
|
CREATE TABLE table_56593 (
"Driver" text,
"Constructor" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what average grid has laps larger than 52 and contains the driver of andrea de adamich?
|
SELECT AVG("Grid") FROM table_56593 WHERE "Laps" > '52' AND "Driver" = 'andrea de adamich'
|
wikisql
|
CREATE TABLE table_name_11 (
debut VARCHAR,
position VARCHAR,
name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What round was the debut of defender Stephen Laybutt?
|
SELECT debut FROM table_name_11 WHERE position = "defender" AND name = "stephen laybutt"
|
sql_create_context
|
CREATE TABLE table_26493 (
"No. in series" real,
"No. in season" real,
"Title" text,
"Directed by" text,
"Written by" text,
"Original air date" text,
"Production code" real,
"U.S. viewers (millions)" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is writtenand directed by shannon flynn?
|
SELECT "Written by" FROM table_26493 WHERE "Directed by" = 'Shannon Flynn'
|
wikisql
|
CREATE TABLE table_203_491 (
id number,
"year" number,
"title" text,
"us hot 100" number,
"us modern rock" number,
"us mainstream rock" number,
"album" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the only single from 2009 ?
|
SELECT "title" FROM table_203_491 WHERE "year" = 2009
|
squall
|
CREATE TABLE table_33952 (
"Round" real,
"Pick #" real,
"Overall" real,
"Name" text,
"Position" text,
"College" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Arkansas State's total pick number with an overal lower than 242?
|
SELECT COUNT("Pick #") FROM table_33952 WHERE "College" = 'arkansas state' AND "Overall" < '242'
|
wikisql
|
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE 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 procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- count the number of patients whose marital status is married and primary disease is coronary artery disease\coronary artery bypass graft with mvr; ? maze?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.marital_status = "MARRIED" AND demographic.diagnosis = "CORONARY ARTERY DISEASE\CORONARY ARTERY BYPASS GRAFT WITH MVR; ? MAZE"
|
mimicsql_data
|
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_kc24 (
MED_SAFE_PAY_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
MED_CLINIC_ID text,
REF_SLT_FLG number,
CLINIC_SLT_DATE time,
COMP_ID text,
PERSON_ID text,
FLX_MED_ORG_ID text,
INSU_TYPE text,
MED_AMOUT number,
PER_ACC_PAY number,
OVE_PAY number,
ILL_PAY number,
CIVIL_SUBSIDY number,
PER_SOL number,
PER_EXP number,
DATA_ID text,
SYNC_TIME time,
OUT_HOSP_DATE time,
CLINIC_ID text,
MED_TYPE number,
INSURED_STS text,
INSURED_IDENTITY number,
TRADE_TYPE number,
RECIPE_BILL_ID text,
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
RECEIVER_DEAL_ID text,
SENDER_REVOKE_ID text,
RECEIVER_REVOKE_ID text,
SENDER_OFFSET_ID text,
RECEIVER_OFFSET_ID text,
LAS_OVE_PAY number,
OVE_ADD_PAY number,
SUP_ADD_PAY number,
CKC102 number,
CASH_PAY number,
COM_ACC_PAY number,
ENT_ACC_PAY number,
ENT_PAY number,
COM_PAY number,
OLDC_FUND_PAY number,
SPE_FUND_PAY number
)
CREATE TABLE t_kc21 (
MED_CLINIC_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
COMP_ID text,
PERSON_ID text,
PERSON_NM text,
IDENTITY_CARD text,
SOC_SRT_CARD text,
PERSON_SEX number,
PERSON_AGE number,
IN_HOSP_DATE time,
OUT_HOSP_DATE time,
DIFF_PLACE_FLG number,
FLX_MED_ORG_ID text,
MED_SER_ORG_NO text,
CLINIC_TYPE text,
MED_TYPE number,
CLINIC_ID text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
INPT_AREA_BED text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
MAIN_COND_DES text,
INSU_TYPE text,
IN_HOSP_DAYS number,
MED_AMOUT number,
FERTILITY_STS number,
DATA_ID text,
SYNC_TIME time,
REIMBURSEMENT_FLG number,
HOSP_LEV number,
HOSP_STS number,
INSURED_IDENTITY number,
SERVANT_FLG text,
TRADE_TYPE number,
INSURED_STS text,
REMOTE_SETTLE_FLG text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 09967594504好在医疗就诊期间开出的医疗发票项目类别药品3338是哪类？
|
SELECT MED_INV_ITEM_TYPE FROM t_kc22 WHERE MED_CLINIC_ID = '09967594504' AND SOC_SRT_DIRE_CD = '3338'
|
css
|
CREATE TABLE d_labitems (
row_id number,
itemid number,
label 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 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 diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE 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 inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what was the name of the first of the outputs that patient 60219 had since 04/25/2103?
|
SELECT d_items.label FROM d_items WHERE d_items.itemid IN (SELECT outputevents.itemid FROM outputevents WHERE outputevents.icustay_id IN (SELECT icustays.icustay_id FROM icustays WHERE icustays.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 60219)) AND STRFTIME('%y-%m-%d', outputevents.charttime) >= '2103-04-25' ORDER BY outputevents.charttime LIMIT 1)
|
mimic_iii
|
CREATE TABLE zyjzjlb (
CYBQDM text,
CYBQMC text,
CYCWH text,
CYKSDM text,
CYKSMC text,
CYSJ time,
CYZTDM number,
HZXM text,
JZKSDM text,
JZKSMC text,
JZLSH text,
KH text,
KLX number,
MZBMLX number,
MZJZLSH text,
MZZDBM text,
MZZDMC text,
MZZYZDZZBM text,
RYCWH text,
RYDJSJ time,
RYSJ time,
RYTJDM number,
RYTJMC text,
RZBQDM text,
RZBQMC text,
WDBZ number,
YLJGDM text,
ZYBMLX number,
ZYZDBM text,
ZYZDMC text,
ZYZYZDZZBM text,
ZYZYZDZZMC text
)
CREATE TABLE hz_info (
KH text,
KLX number,
YLJGDM text
)
CREATE TABLE jybgb (
BBCJBW text,
BBDM text,
BBMC text,
BBZT number,
BGDH text,
BGJGDM text,
BGJGMC text,
BGRGH text,
BGRQ time,
BGRXM text,
BGSJ time,
CJRQ time,
JSBBRQSJ time,
JSBBSJ time,
JYBBH text,
JYJGMC text,
JYJSGH text,
JYJSQM text,
JYKSBM text,
JYKSMC text,
JYLX number,
JYRQ time,
JYSQJGMC text,
JYXMDM text,
JYXMMC text,
JZLSH text,
JZLSH_MZJZJLB text,
JZLSH_ZYJZJLB text,
JZLX number,
KSBM text,
KSMC text,
SHRGH text,
SHRXM text,
SHSJ time,
SQKS text,
SQKSMC text,
SQRGH text,
SQRQ time,
SQRXM text,
YLJGDM text,
YLJGDM_MZJZJLB text,
YLJGDM_ZYJZJLB text
)
CREATE TABLE person_info_hz_info (
RYBH text,
KH number,
KLX number,
YLJGDM number
)
CREATE TABLE jyjgzbb (
BGDH text,
BGRQ time,
CKZFWDX text,
CKZFWSX number,
CKZFWXX number,
JCFF text,
JCRGH text,
JCRXM text,
JCXMMC text,
JCZBDM text,
JCZBJGDL number,
JCZBJGDW text,
JCZBJGDX text,
JCZBMC text,
JLDW text,
JYRQ time,
JYZBLSH text,
SBBM text,
SHRGH text,
SHRXM text,
YLJGDM text,
YQBH text,
YQMC text
)
CREATE TABLE mzjzjlb (
HXPLC number,
HZXM text,
JLSJ time,
JZJSSJ time,
JZKSBM text,
JZKSMC text,
JZKSRQ time,
JZLSH text,
JZZDBM text,
JZZDSM text,
JZZTDM number,
JZZTMC text,
KH text,
KLX number,
MJZH text,
ML number,
MZZYZDZZBM text,
MZZYZDZZMC text,
NLS number,
NLY number,
QTJZYSGH text,
SG number,
SSY number,
SZY number,
TW number,
TXBZ number,
TZ number,
WDBZ number,
XL number,
YLJGDM text,
ZSEBZ number,
ZZBZ number,
ZZYSGH text
)
CREATE TABLE person_info (
CSD text,
CSRQ time,
GJDM text,
GJMC text,
JGDM text,
JGMC text,
MZDM text,
MZMC text,
RYBH text,
XBDM number,
XBMC text,
XLDM text,
XLMC text,
XM text,
ZYLBDM text,
ZYMC text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 列出韩安和这位病患在11年3月21日到19年12月12日内接受检查时开出的所有检验报告单中的标本采集部位
|
SELECT jybgb.BBCJBW FROM person_info JOIN hz_info JOIN mzjzjlb JOIN jybgb JOIN person_info_hz_info ON person_info.RYBH = person_info_hz_info.RYBH AND hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX WHERE person_info.XM = '韩安和' AND jybgb.BGRQ BETWEEN '2011-03-21' AND '2019-12-12' UNION SELECT jybgb.BBCJBW FROM person_info JOIN hz_info JOIN zyjzjlb JOIN jybgb JOIN person_info_hz_info ON person_info.RYBH = person_info_hz_info.RYBH AND hz_info.YLJGDM = zyjzjlb.YLJGDM AND hz_info.KH = zyjzjlb.KH AND hz_info.KLX = zyjzjlb.KLX AND zyjzjlb.YLJGDM = jybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = jybgb.JZLSH_ZYJZJLB AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX AND person_info_hz_info.YLJGDM = hz_info.YLJGDM AND person_info_hz_info.KH = hz_info.KH AND person_info_hz_info.KLX = hz_info.KLX WHERE person_info.XM = '韩安和' AND jybgb.BGRQ BETWEEN '2011-03-21' AND '2019-12-12'
|
css
|
CREATE TABLE t_kc24 (
MED_SAFE_PAY_ID text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
MED_CLINIC_ID text,
REF_SLT_FLG number,
CLINIC_SLT_DATE time,
COMP_ID text,
PERSON_ID text,
FLX_MED_ORG_ID text,
INSU_TYPE text,
MED_AMOUT number,
PER_ACC_PAY number,
OVE_PAY number,
ILL_PAY number,
CIVIL_SUBSIDY number,
PER_SOL number,
PER_EXP number,
DATA_ID text,
SYNC_TIME time,
OUT_HOSP_DATE time,
CLINIC_ID text,
MED_TYPE number,
INSURED_STS text,
INSURED_IDENTITY number,
TRADE_TYPE number,
RECIPE_BILL_ID text,
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
RECEIVER_DEAL_ID text,
SENDER_REVOKE_ID text,
RECEIVER_REVOKE_ID text,
SENDER_OFFSET_ID text,
RECEIVER_OFFSET_ID text,
LAS_OVE_PAY number,
OVE_ADD_PAY number,
SUP_ADD_PAY number,
CKC102 number,
CASH_PAY number,
COM_ACC_PAY number,
ENT_ACC_PAY number,
ENT_PAY number,
COM_PAY number,
OLDC_FUND_PAY number,
SPE_FUND_PAY number
)
CREATE TABLE t_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.
-- 在01年12月15日到06年8月16日期间，药品4859的开药量在骨伤是多少？
|
SELECT COUNT(*) FROM t_kc22 WHERE MED_ORG_DEPT_NM = '创伤骨科' AND STA_DATE BETWEEN '2001-12-15' AND '2006-08-16' AND SOC_SRT_DIRE_CD = '4859'
|
css
|
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 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 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 在2016年3月8日到2016年7月24日内在科室55664因为糖尿病而住院的费用平均为多少？
|
SELECT AVG(zyb.MED_CLINIC_ID) FROM zyb WHERE zyb.MED_ORG_DEPT_NM = '55664' AND zyb.IN_HOSP_DAYS BETWEEN '2016-03-08' AND '2016-07-24' AND zyb.IN_HOSP_DATE = '糖尿病'
|
css
|
CREATE TABLE table_16306 (
"Village (German)" text,
"Village (Slovenian)" text,
"Number of people 1991" real,
"Percent of Slovenes 1991" text,
"Percent of Slovenes 1951" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What are the slovenian names of the villages that had 65.9% of slovenes in 1951?
|
SELECT "Village (Slovenian)" FROM table_16306 WHERE "Percent of Slovenes 1951" = '65.9%'
|
wikisql
|
CREATE TABLE table_12960 (
"Year" real,
"Delegate" text,
"Hometown" text,
"Placement in Miss World" text,
"Other awards" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What's the latest year with a hometown of san carlos, pangasinan?
|
SELECT MAX("Year") FROM table_12960 WHERE "Hometown" = 'san carlos, pangasinan'
|
wikisql
|
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what was the last respiration value for patient 025-60951 on 10/07/this year?
|
SELECT vitalperiodic.respiration FROM vitalperiodic WHERE vitalperiodic.patientunitstayid IN (SELECT patient.patientunitstayid FROM patient WHERE patient.patienthealthsystemstayid IN (SELECT patient.patienthealthsystemstayid FROM patient WHERE patient.uniquepid = '025-60951')) AND NOT vitalperiodic.respiration IS NULL AND DATETIME(vitalperiodic.observationtime, 'start of year') = DATETIME(CURRENT_TIME(), 'start of year', '-0 year') AND STRFTIME('%m-%d', vitalperiodic.observationtime) = '10-07' ORDER BY vitalperiodic.observationtime DESC LIMIT 1
|
eicu
|
CREATE TABLE table_name_93 (
college VARCHAR,
name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which College has a Name of hardy brown?
|
SELECT college FROM table_name_93 WHERE name = "hardy brown"
|
sql_create_context
|
CREATE TABLE table_71333 (
"Country" text,
"Currency" text,
"1 Euro =" real,
"1 USD =" real,
"Central bank" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the 1USD= that has the Uruguayan Peso (uyu) and 1 Euro is greater than 25.3797?
|
SELECT SUM("1 USD =") FROM table_71333 WHERE "Currency" = 'uruguayan peso (uyu)' AND "1 Euro =" > '25.3797'
|
wikisql
|
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod 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 d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
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_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE d_labitems (
row_id number,
itemid number,
label text
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many days since first time patient 55360 was diagnosed with hepatic encephalopathy during this hospital encounter?
|
SELECT 1 * (STRFTIME('%j', CURRENT_TIME()) - STRFTIME('%j', diagnoses_icd.charttime)) FROM diagnoses_icd WHERE diagnoses_icd.icd9_code = (SELECT d_icd_diagnoses.icd9_code FROM d_icd_diagnoses WHERE d_icd_diagnoses.short_title = 'hepatic encephalopathy') AND diagnoses_icd.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.subject_id = 55360 AND admissions.dischtime IS NULL) ORDER BY diagnoses_icd.charttime LIMIT 1
|
mimic_iii
|
CREATE TABLE table_name_98 (
score VARCHAR,
country VARCHAR,
player VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is Score, when Country is 'United States', and when Player is 'Raymond Floyd'?
|
SELECT score FROM table_name_98 WHERE country = "united states" AND player = "raymond floyd"
|
sql_create_context
|
CREATE TABLE table_12551 (
"Position" real,
"Played" real,
"Points" real,
"Wins" real,
"Draws" real,
"Losses" real,
"Goals for" real,
"Goals against" real,
"Goal Difference" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the lowest Goals For, when Draws is less than 4, and when Points is less than 27?
|
SELECT MIN("Goals for") FROM table_12551 WHERE "Draws" < '4' AND "Points" < '27'
|
wikisql
|
CREATE TABLE member (
Member_ID int,
Member_Name text,
Party_ID text,
In_office text
)
CREATE TABLE party (
Party_ID int,
Minister text,
Took_office text,
Left_office text,
Region_ID int,
Party_name text
)
CREATE TABLE party_events (
Event_ID int,
Event_Name text,
Party_ID int,
Member_in_charge_ID int
)
CREATE TABLE region (
Region_ID int,
Region_name text,
Date text,
Label text,
Format text,
Catalogue text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Bar graph to show the number of took office from different took office, I want to sort in desc by the Y please.
|
SELECT Took_office, COUNT(Took_office) FROM party ORDER BY COUNT(Took_office) DESC
|
nvbench
|
CREATE TABLE table_55505 (
"PRR Class" text,
"Builder\u2019s Model" text,
"Build date" text,
"Total produced" real,
"Wheel arrangement" text,
"Service" text,
"Power output" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who built the train in 1966 with over 40 produced?
|
SELECT "Builder\u2019s Model" FROM table_55505 WHERE "Total produced" > '40' AND "Build date" = '1966'
|
wikisql
|
CREATE TABLE student (
stuid number,
lname text,
fname text,
age number,
sex text,
major number,
advisor number,
city_code text
)
CREATE TABLE department (
dno number,
division text,
dname text,
room text,
building text,
dphone number
)
CREATE TABLE faculty (
facid number,
lname text,
fname text,
rank text,
sex text,
phone number,
room text,
building text
)
CREATE TABLE enrolled_in (
stuid number,
cid text,
grade text
)
CREATE TABLE minor_in (
stuid number,
dno number
)
CREATE TABLE gradeconversion (
lettergrade text,
gradepoint number
)
CREATE TABLE course (
cid text,
cname text,
credits number,
instructor number,
days text,
hours text,
dno number
)
CREATE TABLE member_of (
facid number,
dno number,
appt_type text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Find the first name of students in the descending order of age.
|
SELECT fname FROM student ORDER BY age DESC
|
spider
|
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many patients diagnosed with poisoning by other opiates and related narcotics had a psychiatric facility-partial hospitalization discharge?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.discharge_location = "DISCH-TRAN TO PSYCH HOSP" AND diagnoses.long_title = "Poisoning by other opiates and related narcotics"
|
mimicsql_data
|
CREATE TABLE transfers (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
eventtype text,
careunit text,
wardid number,
intime time,
outtime time
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE inputevents_cv (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
amount number
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE d_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE 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 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 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 chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what percentile is 66.0 calculated total co2 in a patient of the same age as patient 26469 on their first hospital visit?
|
SELECT DISTINCT t1.c1 FROM (SELECT labevents.valuenum, PERCENT_RANK() OVER (ORDER BY labevents.valuenum) AS c1 FROM labevents WHERE labevents.itemid IN (SELECT d_labitems.itemid FROM d_labitems WHERE d_labitems.label = 'calculated total co2') AND labevents.hadm_id IN (SELECT admissions.hadm_id FROM admissions WHERE admissions.age = (SELECT admissions.age FROM admissions WHERE admissions.subject_id = 26469 AND NOT admissions.dischtime IS NULL ORDER BY admissions.admittime LIMIT 1))) AS t1 WHERE t1.valuenum = 66.0
|
mimic_iii
|
CREATE TABLE treatment (
treatmentid number,
patientunitstayid number,
treatmentname text,
treatmenttime time
)
CREATE TABLE cost (
costid number,
uniquepid text,
patienthealthsystemstayid number,
eventtype text,
eventid number,
chargetime time,
cost number
)
CREATE TABLE intakeoutput (
intakeoutputid number,
patientunitstayid number,
cellpath text,
celllabel text,
cellvaluenumeric number,
intakeoutputtime time
)
CREATE TABLE patient (
uniquepid text,
patienthealthsystemstayid number,
patientunitstayid number,
gender text,
age text,
ethnicity text,
hospitalid number,
wardid number,
admissionheight number,
admissionweight number,
dischargeweight number,
hospitaladmittime time,
hospitaladmitsource text,
unitadmittime time,
unitdischargetime time,
hospitaldischargetime time,
hospitaldischargestatus text
)
CREATE TABLE microlab (
microlabid number,
patientunitstayid number,
culturesite text,
organism text,
culturetakentime time
)
CREATE TABLE diagnosis (
diagnosisid number,
patientunitstayid number,
diagnosisname text,
diagnosistime time,
icd9code text
)
CREATE TABLE vitalperiodic (
vitalperiodicid number,
patientunitstayid number,
temperature number,
sao2 number,
heartrate number,
respiration number,
systemicsystolic number,
systemicdiastolic number,
systemicmean number,
observationtime time
)
CREATE TABLE medication (
medicationid number,
patientunitstayid number,
drugname text,
dosage text,
routeadmin text,
drugstarttime time,
drugstoptime time
)
CREATE TABLE allergy (
allergyid number,
patientunitstayid number,
drugname text,
allergyname text,
allergytime time
)
CREATE TABLE lab (
labid number,
patientunitstayid number,
labname text,
labresult number,
labresulttime time
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many patients until 2104 were prescribed with nacl 0.9% mbp within 2 months after the mechanical ventilation procedure?
|
SELECT COUNT(DISTINCT t1.uniquepid) FROM (SELECT patient.uniquepid, treatment.treatmenttime FROM treatment JOIN patient ON treatment.patientunitstayid = patient.patientunitstayid WHERE treatment.treatmentname = 'mechanical ventilation' AND STRFTIME('%y', treatment.treatmenttime) <= '2104') AS t1 JOIN (SELECT patient.uniquepid, medication.drugstarttime FROM medication JOIN patient ON medication.patientunitstayid = patient.patientunitstayid WHERE medication.drugname = 'nacl 0.9% mbp' AND STRFTIME('%y', medication.drugstarttime) <= '2104') AS t2 WHERE t1.treatmenttime < t2.drugstarttime AND DATETIME(t2.drugstarttime) BETWEEN DATETIME(t1.treatmenttime) AND DATETIME(t1.treatmenttime, '+2 month')
|
eicu
|
CREATE TABLE table_name_88 (
method VARCHAR,
round VARCHAR,
record VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Round of 1, and a Record of 10 2 had what method?
|
SELECT method FROM table_name_88 WHERE round = "1" AND record = "10–2"
|
sql_create_context
|
CREATE TABLE table_53568 (
"Date" text,
"Opponent" text,
"Score" text,
"Loss" text,
"Record" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the score June 22?
|
SELECT "Loss" FROM table_53568 WHERE "Date" = 'june 22'
|
wikisql
|
CREATE TABLE table_203_639 (
id number,
"year" text,
"number" text,
"name" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how long was w.b. kingsmill club president ?
|
SELECT "year" - "year" FROM table_203_639 WHERE "name" = 'w.b. kingsmill'
|
squall
|
CREATE TABLE table_1199219_2 (
successor VARCHAR,
district VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many successors were seated in the New York 20th district?
|
SELECT COUNT(successor) FROM table_1199219_2 WHERE district = "New York 20th"
|
sql_create_context
|
CREATE TABLE table_7336 (
"Tournament" text,
"1986" text,
"1987" text,
"1988" text,
"1989" text,
"1990" text,
"1991" text,
"1992" text,
"1993" text,
"1994" text,
"1995" text,
"1996" text,
"1997" text,
"Career SR" text,
"Career Win-Loss" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What shows for 1997 when 1987 is 2r?
|
SELECT "1997" FROM table_7336 WHERE "1987" = '2r'
|
wikisql
|
CREATE TABLE swimmer (
ID int,
name text,
Nationality text,
meter_100 real,
meter_200 text,
meter_300 text,
meter_400 text,
meter_500 text,
meter_600 text,
meter_700 text,
Time text
)
CREATE TABLE stadium (
ID int,
name text,
Capacity int,
City text,
Country text,
Opening_year int
)
CREATE TABLE record (
ID int,
Result text,
Swimmer_ID int,
Event_ID int
)
CREATE TABLE event (
ID int,
Name text,
Stadium_ID int,
Year text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Draw a bar chart about the distribution of Nationality and the average of meter_100 , and group by attribute Nationality.
|
SELECT Nationality, AVG(meter_100) FROM swimmer GROUP BY Nationality
|
nvbench
|
CREATE TABLE table_name_48 (
height VARCHAR,
hometown VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How tall is the player from Chicago, IL?
|
SELECT height FROM table_name_48 WHERE hometown = "chicago, il"
|
sql_create_context
|
CREATE TABLE d_labitems (
row_id number,
itemid number,
label 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_items (
row_id number,
itemid number,
label text,
linksto text
)
CREATE TABLE d_icd_procedures (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE microbiologyevents (
row_id number,
subject_id number,
hadm_id number,
charttime time,
spec_type_desc text,
org_name text
)
CREATE TABLE 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 prescriptions (
row_id number,
subject_id number,
hadm_id number,
startdate time,
enddate time,
drug text,
dose_val_rx text,
dose_unit_rx text,
route text
)
CREATE TABLE d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE outputevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
charttime time,
itemid number,
value number
)
CREATE TABLE labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
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 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 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.
-- how many are current patients of the age 20s?
|
SELECT COUNT(DISTINCT admissions.subject_id) FROM admissions WHERE admissions.dischtime IS NULL AND admissions.age BETWEEN 20 AND 29
|
mimic_iii
|
CREATE TABLE table_32428 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who is the home side when the away side score is 11.14 (80)?
|
SELECT "Home team" FROM table_32428 WHERE "Away team score" = '11.14 (80)'
|
wikisql
|
CREATE TABLE table_65162 (
"HR no." text,
"HR name" text,
"CR no." real,
"LMS no." real,
"Built" text,
"Works" text,
"Withdrawn" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What's the built date when the CR number is more than 940 and the LMS number is 14760?
|
SELECT "Built" FROM table_65162 WHERE "CR no." > '940' AND "LMS no." = '14760'
|
wikisql
|
CREATE TABLE t_kc21_t_kc22 (
MED_CLINIC_ID text,
MED_EXP_DET_ID number
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
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.
-- 2012年9月30日到2012年12月13日，编号为2529055的医院有多少科室涉及的医疗费总额不低于2796.97元
|
SELECT COUNT(*) FROM (SELECT t_kc21.MED_ORG_DEPT_CD FROM t_kc21 JOIN t_kc24 ON t_kc21.MED_CLINIC_ID = t_kc24.MED_CLINIC_ID WHERE t_kc21.MED_SER_ORG_NO = '2529055' AND t_kc24.CLINIC_SLT_DATE BETWEEN '2012-09-30' AND '2012-12-13' GROUP BY t_kc21.MED_ORG_DEPT_CD HAVING SUM(t_kc24.MED_AMOUT) >= 2796.97) AS T
|
css
|
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_CLINIC_ID text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE t_kc21 (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SERVANT_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_ID number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 名叫王芳茵的参保人住院时支付的金额中有多少次是整数？
|
SELECT COUNT(*) FROM t_kc21 WHERE t_kc21.PERSON_NM = '王芳茵' AND t_kc21.CLINIC_TYPE = '住院' AND MOD(t_kc21.MED_AMOUT, 1) = 0
|
css
|
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE 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 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)
)
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)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- For those employees who was hired before 2002-06-21, find hire_date and the sum of department_id bin hire_date by weekday, and visualize them by a bar chart, and list sum department id in ascending order.
|
SELECT HIRE_DATE, SUM(DEPARTMENT_ID) FROM employees WHERE HIRE_DATE < '2002-06-21' ORDER BY SUM(DEPARTMENT_ID)
|
nvbench
|
CREATE TABLE table_name_78 (
european_cup VARCHAR,
season VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which European Cup is in the 1990-91 season?
|
SELECT european_cup FROM table_name_78 WHERE season = "1990-91"
|
sql_create_context
|
CREATE TABLE table_name_1 (
attendance VARCHAR,
opponent VARCHAR,
week VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the Attendance for Opponent Boston Patriots and Week is greater than 14?
|
SELECT COUNT(attendance) FROM table_name_1 WHERE opponent = "boston patriots" AND week > 14
|
sql_create_context
|
CREATE TABLE customers (
town_city VARCHAR,
customer_type_code VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Which city has the least number of customers whose type code is 'Good Credit Rating'?
|
SELECT town_city FROM customers WHERE customer_type_code = "Good Credit Rating" GROUP BY town_city ORDER BY COUNT(*) LIMIT 1
|
sql_create_context
|
CREATE TABLE table_name_15 (
income_inequality_1994_2011__latest_available_ VARCHAR,
country VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the current income inequality for the country of Seychelles?
|
SELECT income_inequality_1994_2011__latest_available_ FROM table_name_15 WHERE country = "seychelles"
|
sql_create_context
|
CREATE TABLE t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_ID number
)
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_CLINIC_ID text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE t_kc21 (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SERVANT_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- 患者44017290在二00五年十月十八日到二0一二年二月二十八日期间，最常去的是哪家医院
|
SELECT t_kc21.MED_SER_ORG_NO FROM t_kc21 WHERE t_kc21.PERSON_ID = '44017290' AND t_kc21.IN_HOSP_DATE BETWEEN '2005-10-18' AND '2012-02-28' GROUP BY t_kc21.MED_SER_ORG_NO ORDER BY COUNT(*) DESC LIMIT 1
|
css
|
CREATE TABLE table_72852 (
"Game" real,
"Date" text,
"Opponent" text,
"Score/Time" text,
"High points" text,
"High rebounds" text,
"High assists" text,
"Arena/Attendance" text,
"Record" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the total number of opponent of record 9-2
|
SELECT COUNT("Opponent") FROM table_72852 WHERE "Record" = '9-2'
|
wikisql
|
CREATE TABLE t_kc22 (
AMOUNT number,
CHA_ITEM_LEV number,
DATA_ID text,
DIRE_TYPE number,
DOSE_FORM text,
DOSE_UNIT text,
EACH_DOSAGE text,
EXP_OCC_DATE time,
FLX_MED_ORG_ID text,
FXBZ number,
HOSP_DOC_CD text,
HOSP_DOC_NM text,
MED_CLINIC_ID text,
MED_DIRE_CD text,
MED_DIRE_NM text,
MED_EXP_BILL_ID text,
MED_EXP_DET_ID text,
MED_INV_ITEM_TYPE text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_SELF_AMO number,
PRESCRIPTION_CODE text,
PRESCRIPTION_ID text,
QTY number,
RECIPE_BILL_ID text,
REF_STA_FLG number,
REIMBURS_TYPE number,
REMOTE_SETTLE_FLG text,
RER_SOL number,
SELF_PAY_AMO number,
SELF_PAY_PRO number,
SOC_SRT_DIRE_CD text,
SOC_SRT_DIRE_NM text,
SPEC text,
STA_DATE time,
STA_FLG number,
SYNC_TIME time,
TRADE_TYPE number,
UNIVALENT number,
UP_LIMIT_AMO number,
USE_FRE text,
VAL_UNIT text
)
CREATE TABLE 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 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.
-- 对于编号为67164533的患者医疗记录中医疗费总额大于等于五千二百六十九点一五元的出院诊断疾病编码和名称都是什么？
|
SELECT gwyjzb.OUT_DIAG_DIS_CD, gwyjzb.OUT_DIAG_DIS_NM FROM gwyjzb WHERE gwyjzb.PERSON_ID = '67164533' AND gwyjzb.MED_CLINIC_ID IN (SELECT t_kc24.MED_CLINIC_ID FROM t_kc24 WHERE t_kc24.MED_AMOUT >= 5269.15) UNION SELECT fgwyjzb.OUT_DIAG_DIS_CD, fgwyjzb.OUT_DIAG_DIS_NM FROM fgwyjzb WHERE fgwyjzb.PERSON_ID = '67164533' AND fgwyjzb.MED_CLINIC_ID IN (SELECT t_kc24.MED_CLINIC_ID FROM t_kc24 WHERE t_kc24.MED_AMOUT >= 5269.15)
|
css
|
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 demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many patients admitted before 2111 were ordered to get ascitic fluid lab test?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.admityear < "2111" AND lab.fluid = "Ascites"
|
mimicsql_data
|
CREATE TABLE table_67339 (
"Call sign" text,
"Frequency MHz" text,
"City of license" text,
"ERP W" real,
"Class" text,
"FCC info" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Can you tell me what is FCC info for harmony township, new jersey?
|
SELECT "FCC info" FROM table_67339 WHERE "City of license" = 'harmony township, new jersey'
|
wikisql
|
CREATE TABLE table_name_13 (
match VARCHAR,
team VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the match number for Start Gniezno?
|
SELECT match FROM table_name_13 WHERE team = "start gniezno"
|
sql_create_context
|
CREATE TABLE Detention (
detention_id INTEGER,
detention_type_code VARCHAR(10),
teacher_id INTEGER,
datetime_detention_start DATETIME,
datetime_detention_end DATETIME,
detention_summary VARCHAR(255),
other_details VARCHAR(255)
)
CREATE TABLE Teachers (
teacher_id INTEGER,
address_id INTEGER,
first_name VARCHAR(80),
middle_name VARCHAR(80),
last_name VARCHAR(80),
gender VARCHAR(1),
cell_mobile_number VARCHAR(40),
email_address VARCHAR(40),
other_details VARCHAR(255)
)
CREATE TABLE Ref_Detention_Type (
detention_type_code VARCHAR(10),
detention_type_description VARCHAR(80)
)
CREATE TABLE Behavior_Incident (
incident_id INTEGER,
incident_type_code VARCHAR(10),
student_id INTEGER,
date_incident_start DATETIME,
date_incident_end DATETIME,
incident_summary VARCHAR(255),
recommendations VARCHAR(255),
other_details VARCHAR(255)
)
CREATE TABLE Ref_Address_Types (
address_type_code VARCHAR(15),
address_type_description VARCHAR(80)
)
CREATE TABLE Assessment_Notes (
notes_id INTEGER,
student_id INTEGER,
teacher_id INTEGER,
date_of_notes DATETIME,
text_of_notes VARCHAR(255),
other_details VARCHAR(255)
)
CREATE TABLE Student_Addresses (
student_id INTEGER,
address_id INTEGER,
date_address_from DATETIME,
date_address_to DATETIME,
monthly_rental DECIMAL(19,4),
other_details VARCHAR(255)
)
CREATE TABLE Students (
student_id INTEGER,
address_id INTEGER,
first_name VARCHAR(80),
middle_name VARCHAR(40),
last_name VARCHAR(40),
cell_mobile_number VARCHAR(40),
email_address VARCHAR(40),
date_first_rental DATETIME,
date_left_university DATETIME,
other_student_details VARCHAR(255)
)
CREATE TABLE Students_in_Detention (
student_id INTEGER,
detention_id INTEGER,
incident_id INTEGER
)
CREATE TABLE Addresses (
address_id INTEGER,
line_1 VARCHAR(120),
line_2 VARCHAR(120),
line_3 VARCHAR(120),
city VARCHAR(80),
zip_postcode VARCHAR(20),
state_province_county VARCHAR(50),
country VARCHAR(50),
other_address_details VARCHAR(255)
)
CREATE TABLE Ref_Incident_Type (
incident_type_code VARCHAR(10),
incident_type_description VARCHAR(80)
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Return a bar chart about the distribution of date_address_to and the average of monthly_rental , and group by attribute other_details and bin date_address_to by weekday.
|
SELECT date_address_to, AVG(monthly_rental) FROM Student_Addresses GROUP BY other_details ORDER BY monthly_rental DESC
|
nvbench
|
CREATE TABLE table_name_83 (
runs INTEGER,
name VARCHAR,
inns VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name of clem hill, and Inns larger than 126 has the lowest runs?
|
SELECT MIN(runs) FROM table_name_83 WHERE name = "clem hill" AND inns > 126
|
sql_create_context
|
CREATE TABLE table_name_44 (
time_retired VARCHAR,
driver VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was Riccardo Patrese's time/retired?
|
SELECT time_retired FROM table_name_44 WHERE driver = "riccardo patrese"
|
sql_create_context
|
CREATE TABLE table_32225 (
"Network" text,
"Origin of Programming" text,
"Language" text,
"Genre" text,
"Service" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What language is the moviein that is on UMP movies network through Sky service?
|
SELECT "Language" FROM table_32225 WHERE "Genre" = 'movies' AND "Service" = 'sky' AND "Network" = 'ump movies'
|
wikisql
|
CREATE TABLE table_7105 (
"Tournament" text,
"Wins" real,
"Top-5" real,
"Top-10" real,
"Top-25" real,
"Events" real,
"Cuts made" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the lowest top-5 of the tournament with less than 1 top-10 and less than 1 top-25?
|
SELECT MIN("Top-5") FROM table_7105 WHERE "Top-10" < '1' AND "Top-25" < '1'
|
wikisql
|
CREATE TABLE table_41913 (
"Date" text,
"Cover model" text,
"Centerfold model" text,
"Interview subject" text,
"20 Questions" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Who was the Centerfold model on 5-88?
|
SELECT "Centerfold model" FROM table_41913 WHERE "Date" = '5-88'
|
wikisql
|
CREATE TABLE table_name_69 (
location_attendance VARCHAR,
record VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the location and attendance when the record was 19-17?
|
SELECT location_attendance FROM table_name_69 WHERE record = "19-17"
|
sql_create_context
|
CREATE TABLE player (
Player VARCHAR,
Years_Played VARCHAR,
Team VARCHAR
)
CREATE TABLE team (
Team_id VARCHAR,
Name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Show the players and years played for players from team 'Columbus Crew'.
|
SELECT T1.Player, T1.Years_Played FROM player AS T1 JOIN team AS T2 ON T1.Team = T2.Team_id WHERE T2.Name = "Columbus Crew"
|
sql_create_context
|
CREATE TABLE table_34160 (
"Tournament" text,
"1990" text,
"1991" text,
"1992" text,
"1993" text,
"1994" text,
"1995" text,
"1996" text,
"1997" text,
"1998" text,
"1999" text,
"2000" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What 1997 has grand slams for the 1999?
|
SELECT "1997" FROM table_34160 WHERE "1999" = 'grand slams'
|
wikisql
|
CREATE TABLE table_name_77 (
conceded VARCHAR,
wins VARCHAR,
points VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How much Conceded has Wins smaller than 3, and Points larger than 11?
|
SELECT COUNT(conceded) FROM table_name_77 WHERE wins < 3 AND points > 11
|
sql_create_context
|
CREATE TABLE t_kc21_t_kc24 (
MED_CLINIC_ID text,
MED_SAFE_PAY_ID number
)
CREATE TABLE t_kc24 (
ACCOUNT_DASH_DATE time,
ACCOUNT_DASH_FLG number,
CASH_PAY number,
CIVIL_SUBSIDY number,
CKC102 number,
CLINIC_ID text,
CLINIC_SLT_DATE time,
COMP_ID text,
COM_ACC_PAY number,
COM_PAY number,
DATA_ID text,
ENT_ACC_PAY number,
ENT_PAY number,
FLX_MED_ORG_ID text,
ILL_PAY number,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
LAS_OVE_PAY number,
MED_AMOUT number,
MED_SAFE_PAY_ID text,
MED_TYPE number,
OLDC_FUND_PAY number,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
OVE_ADD_PAY number,
OVE_PAY number,
PERSON_ID text,
PER_ACC_PAY number,
PER_EXP number,
PER_SOL number,
RECEIVER_DEAL_ID text,
RECEIVER_OFFSET_ID text,
RECEIVER_REVOKE_ID text,
RECIPE_BILL_ID text,
REF_SLT_FLG number,
REIMBURS_FLG number,
SENDER_DEAL_ID text,
SENDER_OFFSET_ID text,
SENDER_REVOKE_ID text,
SPE_FUND_PAY number,
SUP_ADD_PAY number,
SYNC_TIME time,
TRADE_TYPE number
)
CREATE TABLE t_kc21 (
CLINIC_ID text,
CLINIC_TYPE text,
COMP_ID text,
DATA_ID text,
DIFF_PLACE_FLG number,
FERTILITY_STS number,
FLX_MED_ORG_ID text,
HOSP_LEV number,
HOSP_STS number,
IDENTITY_CARD text,
INPT_AREA_BED text,
INSURED_IDENTITY number,
INSURED_STS text,
INSU_TYPE text,
IN_DIAG_DIS_CD text,
IN_DIAG_DIS_NM text,
IN_HOSP_DATE time,
IN_HOSP_DAYS number,
MAIN_COND_DES text,
MED_AMOUT number,
MED_CLINIC_ID text,
MED_ORG_DEPT_CD text,
MED_ORG_DEPT_NM text,
MED_SER_ORG_NO text,
MED_TYPE number,
OUT_DIAG_DIS_CD text,
OUT_DIAG_DIS_NM text,
OUT_DIAG_DOC_CD text,
OUT_DIAG_DOC_NM text,
OUT_HOSP_DATE time,
OVERALL_CD_ORG text,
OVERALL_CD_PERSON text,
PERSON_AGE number,
PERSON_ID text,
PERSON_NM text,
PERSON_SEX number,
REIMBURSEMENT_FLG number,
REMOTE_SETTLE_FLG text,
SERVANT_FLG text,
SOC_SRT_CARD text,
SYNC_TIME time,
TRADE_TYPE number
)
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.
-- 编号为6281887的这个医院的医疗记录中，入院诊断为J30.696的最少医疗费总额是多少？最多医疗费总额是多少
|
SELECT MIN(t_kc24.MED_AMOUT), MAX(t_kc24.MED_AMOUT) FROM t_kc24 WHERE t_kc21_t_kc24.MED_CLINIC_ID IN (SELECT t_kc21.MED_CLINIC_ID FROM t_kc21 WHERE t_kc21.MED_SER_ORG_NO = '6281887' AND t_kc21.IN_DIAG_DIS_CD = 'J30.696')
|
css
|
CREATE TABLE table_26820 (
"Rank" real,
"Senator" text,
"Date of birth" text,
"Entered Senate" text,
"Left Senate" text,
"State served" text,
"Party" text,
"Time since entry" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- On what date did congressman joseph tydings enter take his seat?
|
SELECT "Entered Senate" FROM table_26820 WHERE "Senator" = 'Joseph Tydings'
|
wikisql
|
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 admissions (
row_id number,
subject_id number,
hadm_id number,
admittime time,
dischtime time,
admission_type text,
admission_location text,
discharge_location text,
insurance text,
language text,
marital_status text,
ethnicity text,
age number
)
CREATE TABLE icustays (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
first_careunit text,
last_careunit text,
first_wardid number,
last_wardid number,
intime time,
outtime time
)
CREATE TABLE 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 labevents (
row_id number,
subject_id number,
hadm_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE procedures_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime time
)
CREATE TABLE diagnoses_icd (
row_id number,
subject_id number,
hadm_id number,
icd9_code text,
charttime 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 patients (
row_id number,
subject_id number,
gender text,
dob time,
dod time
)
CREATE TABLE cost (
row_id number,
subject_id number,
hadm_id number,
event_type text,
event_id number,
chargetime time,
cost number
)
CREATE TABLE chartevents (
row_id number,
subject_id number,
hadm_id number,
icustay_id number,
itemid number,
charttime time,
valuenum number,
valueuom text
)
CREATE TABLE 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 d_icd_diagnoses (
row_id number,
icd9_code text,
short_title text,
long_title text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- until 4 years ago what are the three most common medications prescribed during the same hospital visit to the patients aged 50s after being diagnosed with dmii wo cmp nt st uncntr?
|
SELECT t3.drug FROM (SELECT t2.drug, DENSE_RANK() OVER (ORDER BY COUNT(*) DESC) AS c1 FROM (SELECT admissions.subject_id, diagnoses_icd.charttime, admissions.hadm_id FROM diagnoses_icd JOIN admissions ON diagnoses_icd.hadm_id = admissions.hadm_id WHERE diagnoses_icd.icd9_code = (SELECT d_icd_diagnoses.icd9_code FROM d_icd_diagnoses WHERE d_icd_diagnoses.short_title = 'dmii wo cmp nt st uncntr') AND DATETIME(diagnoses_icd.charttime) <= DATETIME(CURRENT_TIME(), '-4 year')) AS t1 JOIN (SELECT admissions.subject_id, prescriptions.drug, prescriptions.startdate, admissions.hadm_id FROM prescriptions JOIN admissions ON prescriptions.hadm_id = admissions.hadm_id WHERE admissions.age BETWEEN 50 AND 59 AND DATETIME(prescriptions.startdate) <= DATETIME(CURRENT_TIME(), '-4 year')) AS t2 ON t1.subject_id = t2.subject_id WHERE t1.charttime < t2.startdate AND t1.hadm_id = t2.hadm_id GROUP BY t2.drug) AS t3 WHERE t3.c1 <= 3
|
mimic_iii
|
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- calculate the total number of patients with percutaneous aspiration of liver who were discharged for home health care.
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.discharge_location = "HOME HEALTH CARE" AND procedures.long_title = "Percutaneous aspiration of liver"
|
mimicsql_data
|
CREATE TABLE PostTypes (
Id number,
Name 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 Badges (
Id number,
UserId number,
Name text,
Date time,
Class number,
TagBased boolean
)
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 ReviewTaskResultTypes (
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 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 Votes (
Id number,
PostId number,
VoteTypeId number,
UserId number,
CreationDate time,
BountyAmount number
)
CREATE TABLE ReviewTasks (
Id number,
ReviewTaskTypeId number,
CreationDate time,
DeletionDate time,
ReviewTaskStateId number,
PostId number,
SuggestedEditId number,
CompletedByReviewTaskId number
)
CREATE TABLE CloseAsOffTopicReasonTypes (
Id number,
IsUniversal boolean,
InputTitle text,
MarkdownInputGuidance text,
MarkdownPostOwnerGuidance text,
MarkdownPrivilegedUserGuidance text,
MarkdownConcensusDescription text,
CreationDate time,
CreationModeratorId number,
ApprovalDate time,
ApprovalModeratorId number,
DeactivationDate time,
DeactivationModeratorId number
)
CREATE TABLE PostHistory (
Id number,
PostHistoryTypeId number,
PostId number,
RevisionGUID other,
CreationDate time,
UserId number,
UserDisplayName text,
Comment text,
Text text,
ContentLicense text
)
CREATE TABLE PostTags (
PostId number,
TagId number
)
CREATE TABLE ReviewTaskStates (
Id number,
Name text,
Description 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 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 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 CloseReasonTypes (
Id number,
Name text,
Description text
)
CREATE TABLE Comments (
Id number,
PostId number,
Score number,
Text text,
CreationDate time,
UserDisplayName text,
UserId number,
ContentLicense text
)
CREATE TABLE ReviewRejectionReasons (
Id number,
Name text,
Description text,
PostTypeId number
)
CREATE TABLE ReviewTaskTypes (
Id number,
Name text,
Description text
)
CREATE TABLE VoteTypes (
Id number,
Name text
)
CREATE TABLE FlagTypes (
Id number,
Name text,
Description text
)
CREATE TABLE Tags (
Id number,
TagName text,
Count number,
ExcerptPostId number,
WikiPostId number
)
CREATE TABLE PostNoticeTypes (
Id number,
ClassId number,
Name text,
Body text,
IsHidden boolean,
Predefined boolean,
PostNoticeDurationId number
)
CREATE TABLE PostHistoryTypes (
Id number,
Name text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- How many answers by reputable users are accepted, and their accepted percentage?.
|
SELECT u.Id AS "user_link", COUNT(*) AS NumAnswers, SUM(CASE WHEN q.AcceptedAnswerId = a.Id THEN 1 ELSE 0 END) AS NumAccepted, (SUM(CASE WHEN q.AcceptedAnswerId = a.Id THEN 1 ELSE 0 END) * 100.0 / COUNT(*)) AS AcceptedPercent FROM Posts AS a INNER JOIN Users AS u ON u.Id = a.OwnerUserId INNER JOIN Posts AS q ON a.ParentId = q.Id WHERE (q.OwnerUserId != u.Id OR q.OwnerUserId IS NULL) GROUP BY u.Id ORDER BY AcceptedPercent DESC, NumAnswers DESC LIMIT 100
|
sede
|
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- out of total number of patients treated with gentamicin sulfate, how many of them have a confirmed death status?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN prescriptions ON demographic.hadm_id = prescriptions.hadm_id WHERE demographic.expire_flag = "1" AND prescriptions.drug = "Gentamicin Sulfate"
|
mimicsql_data
|
CREATE TABLE table_30073089_2 (
date VARCHAR,
season VARCHAR,
position VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the date for 2011 and position larger than 2.0
|
SELECT date FROM table_30073089_2 WHERE season = 2011 AND position > 2.0
|
sql_create_context
|
CREATE TABLE table_37387 (
"Series Ep." text,
"Episode" real,
"Netflix" text,
"Segment A" text,
"Segment B" text,
"Segment C" text,
"Segment D" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the segment c with episode less than 179 and segment b of s sticker
|
SELECT "Segment C" FROM table_37387 WHERE "Episode" < '179' AND "Segment B" = 's sticker'
|
wikisql
|
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Get the number of male patients who had a heparin lmw lab test done.
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.gender = "M" AND lab.label = "Heparin, LMW"
|
mimicsql_data
|
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 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 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.
-- what is maximum age of patients whose marital status is married and admission year is greater than or equal to 2194?
|
SELECT MAX(demographic.age) FROM demographic WHERE demographic.marital_status = "MARRIED" AND demographic.admityear >= "2194"
|
mimicsql_data
|
CREATE TABLE table_16751596_12 (
democrat VARCHAR,
lead_margin VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- When the lead margin was 35, what were the Democrat: Vivian Davis Figures?
|
SELECT democrat AS :_vivian_davis_figures FROM table_16751596_12 WHERE lead_margin = 35
|
sql_create_context
|
CREATE TABLE table_203_28 (
id number,
"year" number,
"competition" text,
"venue" text,
"position" text,
"event" text,
"notes" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- how many times did they participate in the olympic games ?
|
SELECT COUNT(*) FROM table_203_28 WHERE "competition" = 'olympic games'
|
squall
|
CREATE TABLE table_name_74 (
type VARCHAR,
name VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the type of station for ESPN International Sports?
|
SELECT type FROM table_name_74 WHERE name = "espn international sports"
|
sql_create_context
|
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE 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
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the number of patients whose admission type is elective and insurance is private?
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.admission_type = "ELECTIVE" AND demographic.insurance = "Private"
|
mimicsql_data
|
CREATE TABLE table_13888 (
"Draw" real,
"Song" text,
"Artist" text,
"Points" real,
"Place" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the Place of the Song by Artist Rosie Hunter with a Draw of 1 or larger?
|
SELECT COUNT("Place") FROM table_13888 WHERE "Artist" = 'rosie hunter' AND "Draw" > '1'
|
wikisql
|
CREATE TABLE table_name_47 (
draw INTEGER,
match INTEGER
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What is the average number of draws for teams with more than 10 matches?
|
SELECT AVG(draw) FROM table_name_47 WHERE match > 10
|
sql_create_context
|
CREATE TABLE table_11621915_1 (
winner VARCHAR,
tournament VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what's the winner with tournament value of kroger senior classic
|
SELECT winner FROM table_11621915_1 WHERE tournament = "Kroger Senior Classic"
|
sql_create_context
|
CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
)
CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Draw a bar chart about the distribution of All_Home and the average of School_ID , and group by attribute All_Home, order from low to high by the x-axis please.
|
SELECT All_Home, AVG(School_ID) FROM basketball_match GROUP BY All_Home ORDER BY All_Home
|
nvbench
|
CREATE TABLE table_name_27 (
result VARCHAR,
week VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- What was the result on week 1?
|
SELECT result FROM table_name_27 WHERE week = 1
|
sql_create_context
|
CREATE TABLE table_12325 (
"Place" text,
"Player" text,
"Country" text,
"Score" text,
"To par" text
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Where did Trinidad and Tobago play?
|
SELECT "Place" FROM table_12325 WHERE "Country" = 'trinidad and tobago'
|
wikisql
|
CREATE TABLE table_55467 (
"Driver" text,
"Constructor" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- what is the time/retired when the laps is less than 4?
|
SELECT "Time/Retired" FROM table_55467 WHERE "Laps" < '4'
|
wikisql
|
CREATE TABLE table_name_67 (
laps VARCHAR,
grid VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Tell me the laps for 3 grids
|
SELECT laps FROM table_name_67 WHERE grid = 3
|
sql_create_context
|
CREATE TABLE table_17425749_1 (
colorado VARCHAR,
alaska VARCHAR
)
-- Using valid SQLite, answer the following questions for the tables provided above.
-- Name the colorado when alaska is connecticut
|
SELECT colorado FROM table_17425749_1 WHERE alaska = "Connecticut"
|
sql_create_context
|
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