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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 Badges ( Id number, UserId number, Name text, Date time, Class number, TagBased boolean ) CREATE TABLE Users ( Id number, Reputation number, CreationDate time, DisplayName text, LastAccessDate time, WebsiteUrl text, Location text, AboutMe text, Views number, UpVotes number, DownVotes number, ProfileImageUrl text, EmailHash text, AccountId number ) CREATE TABLE TagSynonyms ( Id number, SourceTagName text, TargetTagName text, CreationDate time, OwnerUserId number, AutoRenameCount number, LastAutoRename time, Score number, ApprovedByUserId number, ApprovalDate time ) CREATE TABLE VoteTypes ( Id number, Name text ) CREATE TABLE PostNotices ( Id number, PostId number, PostNoticeTypeId number, CreationDate time, DeletionDate time, ExpiryDate time, Body text, OwnerUserId number, DeletionUserId 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 SuggestedEditVotes ( Id number, SuggestedEditId number, UserId number, VoteTypeId number, CreationDate time, TargetUserId number, TargetRepChange number ) CREATE TABLE ReviewTaskTypes ( Id number, Name text, Description text ) CREATE TABLE PostHistoryTypes ( Id number, Name text ) CREATE TABLE PostTags ( PostId number, TagId number ) CREATE TABLE Votes ( Id number, PostId number, VoteTypeId number, UserId number, CreationDate time, BountyAmount number ) CREATE TABLE Posts ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE PostTypes ( Id number, Name text ) CREATE TABLE ReviewTaskResultTypes ( Id number, Name text, Description text ) CREATE TABLE PostNoticeTypes ( Id number, ClassId number, Name text, Body text, IsHidden boolean, Predefined boolean, PostNoticeDurationId number ) CREATE TABLE FlagTypes ( Id number, Name text, Description text ) CREATE TABLE Tags ( Id number, TagName text, Count number, ExcerptPostId number, WikiPostId number ) CREATE TABLE ReviewTasks ( Id number, ReviewTaskTypeId number, CreationDate time, DeletionDate time, ReviewTaskStateId number, PostId number, SuggestedEditId number, CompletedByReviewTaskId number ) CREATE TABLE PostsWithDeleted ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE PostFeedback ( Id number, PostId number, IsAnonymous boolean, VoteTypeId number, CreationDate time ) CREATE TABLE CloseReasonTypes ( Id number, Name text, Description text ) CREATE TABLE ReviewTaskResults ( Id number, ReviewTaskId number, ReviewTaskResultTypeId number, CreationDate time, RejectionReasonId number, Comment text ) CREATE TABLE ReviewTaskStates ( Id number, Name text, Description text ) CREATE TABLE PostLinks ( Id number, CreationDate time, PostId number, RelatedPostId number, LinkTypeId 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 SuggestedEdits ( Id number, PostId number, CreationDate time, ApprovalDate time, RejectionDate time, OwnerUserId number, Comment text, Text text, Title text, Tags text, RevisionGUID other ) CREATE TABLE PendingFlags ( Id number, FlagTypeId number, PostId number, CreationDate time, CloseReasonTypeId number, CloseAsOffTopicReasonTypeId number, DuplicateOfQuestionId number, BelongsOnBaseHostAddress text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- JanitorTags: tag:Linux but focused on a distro (pacman).
SELECT Id AS "post_link", * FROM Posts JOIN PostTags ON Posts.Id = PostTags.PostId WHERE PostTags.TagId = 4 AND Body LIKE '%pacman%' ORDER BY CreationDate DESC
sede
CREATE TABLE table_203_815 ( id number, "pick #" number, "nfl team" text, "player" text, "position" text, "college" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- who was the only player from kansas state ?
SELECT "player" FROM table_203_815 WHERE "college" = 'kansas state'
squall
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 ) CREATE TABLE t_kc21_t_kc22 ( MED_CLINIC_ID text, MED_EXP_DET_ID number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 从00年10月1日到10年9月21日这个患者喻萍雅检查了多少次?
SELECT COUNT(*) FROM t_kc21 JOIN t_kc22 JOIN t_kc21_t_kc22 ON t_kc21.MED_CLINIC_ID = t_kc21_t_kc22.MED_CLINIC_ID AND t_kc21_t_kc22.MED_EXP_DET_ID = t_kc22.MED_EXP_DET_ID WHERE t_kc21.PERSON_NM = '喻萍雅' AND t_kc22.STA_DATE BETWEEN '2000-10-01' AND '2010-09-21' AND t_kc22.MED_INV_ITEM_TYPE = '检查费'
css
CREATE TABLE table_17232 ( "Disc" real, "Track" real, "English title" text, "Japanese title" text, "R\u014dmaji title" text, "Artist" text, "Track time" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the smallest track number?
SELECT MIN("Track") FROM table_17232
wikisql
CREATE TABLE course ( crs_code text, dept_code text, crs_description text, crs_credit number ) CREATE TABLE enroll ( class_code text, stu_num number, enroll_grade text ) CREATE TABLE employee ( emp_num number, emp_lname text, emp_fname text, emp_initial text, emp_jobcode text, emp_hiredate time, emp_dob time ) CREATE TABLE department ( dept_code text, dept_name text, school_code text, emp_num number, dept_address text, dept_extension text ) CREATE TABLE class ( class_code text, crs_code text, class_section text, class_time text, class_room text, prof_num number ) CREATE TABLE student ( stu_num number, stu_lname text, stu_fname text, stu_init text, stu_dob time, stu_hrs number, stu_class text, stu_gpa number, stu_transfer number, dept_code text, stu_phone text, prof_num number ) CREATE TABLE professor ( emp_num number, dept_code text, prof_office text, prof_extension text, prof_high_degree text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What are the first names, office locations of all lecturers who have taught some course?
SELECT T2.emp_fname, T4.prof_office, T3.crs_description FROM class AS T1 JOIN employee AS T2 ON T1.prof_num = T2.emp_num JOIN course AS T3 ON T1.crs_code = T3.crs_code JOIN professor AS T4 ON T2.emp_num = T4.emp_num
spider
CREATE TABLE table_4053 ( "Executed person" text, "Date of execution" text, "Place of execution" text, "Crime" text, "Method" text, "Under President" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- under which president was gunther volz executed?
SELECT "Under President" FROM table_4053 WHERE "Executed person" = 'Gunther Volz'
wikisql
CREATE TABLE table_72445 ( "County" text, "Population" real, "Per capita income" text, "Median household income" text, "Median family income" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the median family income for riverside
SELECT "Median family income" FROM table_72445 WHERE "County" = 'Riverside'
wikisql
CREATE TABLE table_name_77 ( home_team VARCHAR, away_team VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the home team for carlton away team
SELECT home_team FROM table_name_77 WHERE away_team = "carlton"
sql_create_context
CREATE TABLE jyjgzbb ( BGDH text, BGRQ time, CKZFWDX text, CKZFWSX number, CKZFWXX number, JCFF text, JCRGH text, JCRXM text, JCXMMC text, JCZBDM text, JCZBJGDL number, JCZBJGDW text, JCZBJGDX text, JCZBMC text, JLDW text, JYRQ time, JYZBLSH text, SBBM text, SHRGH text, SHRXM text, YLJGDM text, YQBH text, YQMC text ) CREATE TABLE jybgb ( BBCJBW text, BBDM text, BBMC text, BBZT number, BGDH text, BGJGDM text, BGJGMC text, BGRGH text, BGRQ time, BGRXM text, BGSJ time, CJRQ time, JSBBRQSJ time, JSBBSJ time, JYBBH text, JYJGMC text, JYJSGH text, JYJSQM text, JYKSBM text, JYKSMC text, JYLX number, JYRQ time, JYSQJGMC text, JYXMDM text, JYXMMC text, JZLSH text, JZLSH_MZJZJLB text, JZLSH_ZYJZJLB text, JZLX number, KSBM text, KSMC text, SHRGH text, SHRXM text, SHSJ time, SQKS text, SQKSMC text, SQRGH text, SQRQ time, SQRXM text, YLJGDM text, YLJGDM_MZJZJLB text, YLJGDM_ZYJZJLB text ) CREATE TABLE 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 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 hz_info ( KH text, KLX number, RYBH text, YLJGDM text, person_info_CSD text, person_info_CSRQ time, person_info_GJDM text, person_info_GJMC text, person_info_JGDM text, person_info_JGMC text, person_info_MZDM text, person_info_MZMC text, person_info_XBDM number, person_info_XBMC text, person_info_XLDM text, person_info_XLMC text, person_info_XM text, person_info_ZYLBDM text, person_info_ZYMC text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 在17年10月30日到18年12月8日期间,列出金宏茂患者所有检验结果指标记录中用的什么检测方法?
SELECT jyjgzbb.JCFF FROM hz_info JOIN mzjzjlb JOIN jybgb JOIN jyjgzbb ON hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND mzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH WHERE hz_info.person_info_XM = '金宏茂' AND jyjgzbb.JYRQ BETWEEN '2017-10-30' AND '2018-12-08' UNION SELECT jyjgzbb.JCFF FROM hz_info JOIN zyjzjlb JOIN jybgb JOIN jyjgzbb ON hz_info.YLJGDM = zyjzjlb.YLJGDM AND hz_info.KH = zyjzjlb.KH AND hz_info.KLX = zyjzjlb.KLX AND zyjzjlb.YLJGDM = jybgb.YLJGDM_ZYJZJLB AND zyjzjlb.JZLSH = jybgb.JZLSH_ZYJZJLB AND jybgb.YLJGDM = jyjgzbb.YLJGDM AND jybgb.BGDH = jyjgzbb.BGDH WHERE hz_info.person_info_XM = '金宏茂' AND jyjgzbb.JYRQ BETWEEN '2017-10-30' AND '2018-12-08'
css
CREATE TABLE table_22767 ( "Year" real, "World" real, "Asia" text, "Africa" text, "Europe" text, "Latin America/Caribbean" text, "Northern America" text, "Oceania" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- what will the population of Asia be when Latin America/Caribbean is 783 (7.5%)?
SELECT "Asia" FROM table_22767 WHERE "Latin America/Caribbean" = '783 (7.5%)'
wikisql
CREATE TABLE Student ( StuID INTEGER, LName VARCHAR(12), Fname VARCHAR(12), Age INTEGER, Sex VARCHAR(1), Major INTEGER, Advisor INTEGER, city_code VARCHAR(3) ) CREATE TABLE Faculty ( FacID INTEGER, Lname VARCHAR(15), Fname VARCHAR(15), Rank VARCHAR(15), Sex VARCHAR(1), Phone INTEGER, Room VARCHAR(5), Building VARCHAR(13) ) CREATE TABLE Faculty_Participates_in ( FacID INTEGER, actid INTEGER ) CREATE TABLE Activity ( actid INTEGER, activity_name varchar(25) ) CREATE TABLE Participates_in ( stuid INTEGER, actid INTEGER ) -- Using valid SQLite, answer the following questions for the tables provided above. -- How many faculty members do we have for each gender? Draw a bar chart, order by the Y-axis in descending.
SELECT Sex, COUNT(*) FROM Faculty GROUP BY Sex ORDER BY COUNT(*) DESC
nvbench
CREATE TABLE table_14656147_2 ( week VARCHAR, record VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- List the record of 0-1 from the table?
SELECT week FROM table_14656147_2 WHERE record = "0-1"
sql_create_context
CREATE TABLE table_name_24 ( silver VARCHAR, bronze VARCHAR, gold VARCHAR, rank VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which silver has a Gold smaller than 12, a Rank smaller than 5, and a Bronze of 5?
SELECT silver FROM table_name_24 WHERE gold < 12 AND rank < 5 AND bronze = 5
sql_create_context
CREATE TABLE table_47482 ( "Company name" text, "Hardware Model" text, "Accreditation type" text, "Accreditation level" text, "Date" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- When did Samsung Electronics Co LTD make the GT-i9100?
SELECT "Date" FROM table_47482 WHERE "Company name" = 'samsung electronics co ltd' AND "Hardware Model" = 'gt-i9100'
wikisql
CREATE TABLE time_interval ( period text, begin_time int, end_time int ) CREATE TABLE flight_leg ( flight_id int, leg_number int, leg_flight int ) CREATE TABLE airline ( airline_code varchar, airline_name text, note text ) CREATE TABLE ground_service ( city_code text, airport_code text, transport_type text, ground_fare int ) CREATE TABLE class_of_service ( booking_class varchar, rank int, class_description text ) 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 date_day ( month_number int, day_number int, year int, day_name varchar ) CREATE TABLE dual_carrier ( main_airline varchar, low_flight_number int, high_flight_number int, dual_airline varchar, service_name text ) CREATE TABLE compartment_class ( compartment varchar, class_type varchar ) CREATE TABLE equipment_sequence ( aircraft_code_sequence varchar, aircraft_code varchar ) CREATE TABLE flight ( aircraft_code_sequence text, airline_code varchar, airline_flight text, arrival_time int, connections int, departure_time int, dual_carrier text, flight_days text, flight_id int, flight_number int, from_airport varchar, meal_code text, stops int, time_elapsed int, to_airport varchar ) CREATE TABLE month ( month_number int, month_name text ) CREATE TABLE code_description ( code varchar, description 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 state ( state_code text, state_name text, country_name text ) 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 time_zone ( time_zone_code text, time_zone_name text, hours_from_gmt 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 days ( days_code varchar, day_name varchar ) CREATE TABLE fare_basis ( fare_basis_code text, booking_class text, class_type text, premium text, economy text, discounted text, night text, season text, basis_days text ) CREATE TABLE 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 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 airport_service ( city_code varchar, airport_code varchar, miles_distant int, direction varchar, minutes_distant int ) -- Using valid SQLite, answer the following questions for the tables provided above. -- what are the early morning flights from BOSTON to DENVER
SELECT DISTINCT flight.flight_id FROM airport_service AS AIRPORT_SERVICE_0, airport_service AS AIRPORT_SERVICE_1, city AS CITY_0, city AS CITY_1, flight WHERE (CITY_0.city_code = AIRPORT_SERVICE_0.city_code AND CITY_0.city_name = 'BOSTON' AND CITY_1.city_code = AIRPORT_SERVICE_1.city_code AND CITY_1.city_name = 'DENVER' AND flight.from_airport = AIRPORT_SERVICE_0.airport_code AND flight.to_airport = AIRPORT_SERVICE_1.airport_code) AND flight.departure_time BETWEEN 0 AND 800
atis
CREATE TABLE table_148535_2 ( Id VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the most 3 credits
SELECT MIN(3 AS _credits) FROM table_148535_2
sql_create_context
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 ftxmzjzjlb ( HXPLC number, HZXM text, JLSJ time, JZJSSJ time, JZKSBM text, JZKSMC text, JZKSRQ time, JZLSH number, JZZDBM text, JZZDSM text, JZZTDM number, JZZTMC text, KH text, KLX number, MJZH text, ML number, MZZYZDZZBM text, MZZYZDZZMC text, NLS number, NLY number, QTJZYSGH text, SG number, SSY number, SZY number, TW number, TZ number, WDBZ number, XL number, YLJGDM number, ZSEBZ number, ZZBZ number, ZZYSGH text ) CREATE TABLE txmzjzjlb ( HXPLC number, HZXM text, JLSJ time, JZJSSJ time, JZKSBM text, JZKSMC text, JZKSRQ time, JZLSH number, JZZDBM text, JZZDSM text, JZZTDM number, JZZTMC text, KH text, KLX number, MJZH text, ML number, MZZYZDZZBM text, MZZYZDZZMC text, NLS number, NLY number, QTJZYSGH text, SG number, SSY number, SZY number, TW number, TZ number, WDBZ number, XL number, YLJGDM number, ZSEBZ number, ZZBZ number, ZZYSGH text ) CREATE TABLE jyjgzbb ( BGDH text, BGRQ time, CKZFWDX text, CKZFWSX number, CKZFWXX number, JCFF text, JCRGH text, JCRXM text, JCXMMC text, JCZBDM text, JCZBJGDL number, JCZBJGDW text, JCZBJGDX text, JCZBMC text, JLDW text, JYRQ time, JYZBLSH text, SBBM text, SHRGH text, SHRXM text, YLJGDM text, YQBH text, YQMC text ) CREATE TABLE jybgb ( BBCJBW text, BBDM text, BBMC text, BBZT number, BGDH text, BGJGDM text, BGJGMC text, BGRGH text, BGRQ time, BGRXM text, BGSJ time, CJRQ time, JSBBRQSJ time, JSBBSJ time, JYBBH text, JYJGMC text, JYJSGH text, JYJSQM text, JYKSBM text, JYKSMC text, JYLX number, JYRQ time, JYSQJGMC text, JYXMDM text, JYXMMC text, JZLSH text, JZLSH_MZJZJLB text, JZLSH_ZYJZJLB text, JZLX number, KSBM text, KSMC text, SHRGH text, SHRXM text, SHSJ time, SQKS text, SQKSMC text, SQRGH text, SQRQ time, SQRXM text, YLJGDM text, YLJGDM_MZJZJLB text, YLJGDM_ZYJZJLB text ) CREATE TABLE zyjzjlb ( CYBQDM text, CYBQMC text, CYCWH text, CYKSDM text, CYKSMC text, CYSJ time, CYZTDM number, HZXM text, JZKSDM text, JZKSMC text, JZLSH text, KH text, KLX number, MZBMLX number, MZJZLSH text, MZZDBM text, MZZDMC text, MZZYZDZZBM text, RYCWH text, RYDJSJ time, RYSJ time, RYTJDM number, RYTJMC text, RZBQDM text, RZBQMC text, WDBZ number, YLJGDM text, ZYBMLX number, ZYZDBM text, ZYZDMC text, ZYZYZDZZBM text, ZYZYZDZZMC text ) CREATE TABLE hz_info ( KH text, KLX number, RYBH text, YLJGDM text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 在08年7月28日到10年3月17日期间,陈浩淼这位患者找了多少医生看病
SELECT COUNT(txmzjzjlb.ZZYSGH) FROM person_info JOIN hz_info JOIN txmzjzjlb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = txmzjzjlb.YLJGDM AND hz_info.KH = txmzjzjlb.KH AND hz_info.KLX = txmzjzjlb.KLX WHERE person_info.XM = '陈浩淼' AND txmzjzjlb.JZKSRQ BETWEEN '2008-07-28' AND '2010-03-17' UNION SELECT COUNT(ftxmzjzjlb.ZZYSGH) FROM person_info JOIN hz_info JOIN ftxmzjzjlb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = ftxmzjzjlb.YLJGDM AND hz_info.KH = ftxmzjzjlb.KH AND hz_info.KLX = ftxmzjzjlb.KLX WHERE person_info.XM = '陈浩淼' AND ftxmzjzjlb.JZKSRQ BETWEEN '2008-07-28' AND '2010-03-17'
css
CREATE TABLE table_3791 ( "Year" text, "Stage" real, "Start of stage" text, "Distance (km)" text, "Category of climb" text, "Stage winner" text, "Nationality" text, "Yellow jersey" text, "Bend" real ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is every yellow jersey entry for the distance 125?
SELECT "Yellow jersey" FROM table_3791 WHERE "Distance (km)" = '125'
wikisql
CREATE TABLE table_name_63 ( years VARCHAR, goals VARCHAR, matches VARCHAR, rank VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- In what years was there a rank lower than 9, under 84 goals, and more than 158 matches?
SELECT years FROM table_name_63 WHERE matches > 158 AND rank > 9 AND goals < 84
sql_create_context
CREATE TABLE table_43208 ( "8:00" text, "8:30" text, "9:00" text, "9:30" text, "10:00" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What aired at 10:00 when Flashpoint aired at 9:30?
SELECT "10:00" FROM table_43208 WHERE "9:30" = 'flashpoint'
wikisql
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 prescriptions ( subject_id text, hadm_id text, icustay_id text, drug_type text, drug text, formulary_drug_cd text, route text, drug_dose text ) CREATE TABLE procedures ( subject_id text, hadm_id text, icd9_code text, short_title text, long_title text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- count the number of patients whose insurance is government and procedure short title is rt/left heart card cath?
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN procedures ON demographic.hadm_id = procedures.hadm_id WHERE demographic.insurance = "Government" AND procedures.short_title = "Rt/left heart card cath"
mimicsql_data
CREATE TABLE table_18904831_5 ( record VARCHAR, high_rebounds VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What was the record of the game in which Dydek (10) did the most high rebounds?
SELECT record FROM table_18904831_5 WHERE high_rebounds = "Dydek (10)"
sql_create_context
CREATE TABLE table_10130 ( "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. -- When was the game played at glenferrie oval?
SELECT "Date" FROM table_10130 WHERE "Venue" = 'glenferrie oval'
wikisql
CREATE TABLE table_7207 ( "Objects" text, "Date" text, "SiO 2" real, "Al 2 O 3" real, "Fe 2 O 3" real, "K 2 O" real, "Na 2 O" real ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the highest K 2 O, when Na 2 O is greater than 1.87, when Fe 2 O 3 is greater than 0.07, when Objects is Ritual Disk, and when Al 2 O 3 is less than 0.62?
SELECT MAX("K 2 O") FROM table_7207 WHERE "Na 2 O" > '1.87' AND "Fe 2 O 3" > '0.07' AND "Objects" = 'ritual disk' AND "Al 2 O 3" < '0.62'
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 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 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. -- what is the total number of patients diagnosed with icd9 code 45620 who had a blood test.
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE diagnoses.icd9_code = "45620" AND lab.fluid = "Blood"
mimicsql_data
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 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. -- count the number of patients whose primary disease is pneumonia;human immunodefiency virus;rule out tuberculosis and year of death is less than or equal to 2168?
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "PNEUMONIA;HUMAN IMMUNODEFIENCY VIRUS;RULE OUT TUBERCULOSIS" AND demographic.dod_year <= "2168.0"
mimicsql_data
CREATE TABLE t_kc21 ( CLINIC_ID text, CLINIC_TYPE text, COMP_ID text, DATA_ID text, DIFF_PLACE_FLG number, FERTILITY_STS number, FLX_MED_ORG_ID text, HOSP_LEV number, HOSP_STS number, IDENTITY_CARD text, INPT_AREA_BED text, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, IN_DIAG_DIS_CD text, IN_DIAG_DIS_NM text, IN_HOSP_DATE time, IN_HOSP_DAYS number, MAIN_COND_DES text, MED_AMOUT number, MED_CLINIC_ID text, MED_ORG_DEPT_CD text, MED_ORG_DEPT_NM text, MED_SER_ORG_NO text, MED_TYPE number, OUT_DIAG_DIS_CD text, OUT_DIAG_DIS_NM text, OUT_DIAG_DOC_CD text, OUT_DIAG_DOC_NM text, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, PERSON_AGE number, PERSON_ID text, PERSON_NM text, PERSON_SEX number, REIMBURSEMENT_FLG number, REMOTE_SETTLE_FLG text, SERVANT_FLG text, SOC_SRT_CARD text, SYNC_TIME time, TRADE_TYPE number ) CREATE TABLE t_kc21_t_kc22 ( MED_CLINIC_ID text, MED_EXP_DET_ID number ) CREATE TABLE t_kc24 ( ACCOUNT_DASH_DATE time, ACCOUNT_DASH_FLG number, CASH_PAY number, CIVIL_SUBSIDY number, CKC102 number, CLINIC_ID text, CLINIC_SLT_DATE time, COMP_ID text, COM_ACC_PAY number, COM_PAY number, DATA_ID text, ENT_ACC_PAY number, ENT_PAY number, FLX_MED_ORG_ID text, ILL_PAY number, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, LAS_OVE_PAY number, MED_AMOUT number, MED_CLINIC_ID text, MED_SAFE_PAY_ID text, MED_TYPE number, OLDC_FUND_PAY number, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, OVE_ADD_PAY number, OVE_PAY number, PERSON_ID text, PER_ACC_PAY number, PER_EXP number, PER_SOL number, RECEIVER_DEAL_ID text, RECEIVER_OFFSET_ID text, RECEIVER_REVOKE_ID text, RECIPE_BILL_ID text, REF_SLT_FLG number, REIMBURS_FLG number, SENDER_DEAL_ID text, SENDER_OFFSET_ID text, SENDER_REVOKE_ID text, SPE_FUND_PAY number, SUP_ADD_PAY number, SYNC_TIME time, TRADE_TYPE number ) 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. -- 编号为7367933的医院在医疗记录里写的出院诊断为复发性阿弗他溃疡的病患其最低和最高医疗费一共多少钱?
SELECT MIN(t_kc24.MED_AMOUT), MAX(t_kc24.MED_AMOUT) FROM t_kc24 WHERE t_kc24.MED_CLINIC_ID IN (SELECT t_kc21.MED_CLINIC_ID FROM t_kc21 WHERE t_kc21.MED_SER_ORG_NO = '7367933' AND t_kc21.OUT_DIAG_DIS_NM = '复发性阿弗他溃疡')
css
CREATE TABLE table_72013 ( "Season" text, "Level" text, "Division" text, "Section" text, "Position" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which section is in the 6th position?
SELECT "Section" FROM table_72013 WHERE "Position" = '6th'
wikisql
CREATE TABLE table_69300 ( "Name" text, "Years" text, "Gender" text, "Area" text, "Authority" text, "Decile" real, "Roll" real ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the area of the coed school with a state authority and a roll number of 122?
SELECT "Area" FROM table_69300 WHERE "Authority" = 'state' AND "Gender" = 'coed' AND "Roll" = '122'
wikisql
CREATE TABLE table_name_1 ( type VARCHAR, location VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which type of institution is in Amherst, MA?
SELECT type FROM table_name_1 WHERE location = "amherst, ma"
sql_create_context
CREATE TABLE t_kc24 ( ACCOUNT_DASH_DATE time, ACCOUNT_DASH_FLG number, CASH_PAY number, CIVIL_SUBSIDY number, CKC102 number, CLINIC_ID text, CLINIC_SLT_DATE time, COMP_ID text, COM_ACC_PAY number, COM_PAY number, DATA_ID text, ENT_ACC_PAY number, ENT_PAY number, FLX_MED_ORG_ID text, ILL_PAY number, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, LAS_OVE_PAY number, MED_AMOUT number, MED_CLINIC_ID text, MED_SAFE_PAY_ID text, MED_TYPE number, OLDC_FUND_PAY number, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, OVE_ADD_PAY number, OVE_PAY number, PERSON_ID text, PER_ACC_PAY number, PER_EXP number, PER_SOL number, RECEIVER_DEAL_ID text, RECEIVER_OFFSET_ID text, RECEIVER_REVOKE_ID text, RECIPE_BILL_ID text, REF_SLT_FLG number, REIMBURS_FLG number, SENDER_DEAL_ID text, SENDER_OFFSET_ID text, SENDER_REVOKE_ID text, SPE_FUND_PAY number, SUP_ADD_PAY number, SYNC_TIME time, TRADE_TYPE number ) CREATE TABLE t_kc22 ( AMOUNT number, CHA_ITEM_LEV number, DATA_ID text, DIRE_TYPE number, DOSE_FORM text, DOSE_UNIT text, EACH_DOSAGE text, EXP_OCC_DATE time, FLX_MED_ORG_ID text, FXBZ number, HOSP_DOC_CD text, HOSP_DOC_NM text, MED_DIRE_CD text, MED_DIRE_NM text, MED_EXP_BILL_ID text, MED_EXP_DET_ID text, MED_INV_ITEM_TYPE text, MED_ORG_DEPT_CD text, MED_ORG_DEPT_NM text, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, OVE_SELF_AMO number, PRESCRIPTION_CODE text, PRESCRIPTION_ID text, QTY number, RECIPE_BILL_ID text, REF_STA_FLG number, REIMBURS_TYPE number, REMOTE_SETTLE_FLG text, RER_SOL number, SELF_PAY_AMO number, SELF_PAY_PRO number, SOC_SRT_DIRE_CD text, SOC_SRT_DIRE_NM text, SPEC text, STA_DATE time, STA_FLG number, SYNC_TIME time, TRADE_TYPE number, UNIVALENT number, UP_LIMIT_AMO number, USE_FRE text, VAL_UNIT text ) CREATE TABLE t_kc21 ( CLINIC_ID text, CLINIC_TYPE text, COMP_ID text, DATA_ID text, DIFF_PLACE_FLG number, FERTILITY_STS number, FLX_MED_ORG_ID text, HOSP_LEV number, HOSP_STS number, IDENTITY_CARD text, INPT_AREA_BED text, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, IN_DIAG_DIS_CD text, IN_DIAG_DIS_NM text, IN_HOSP_DATE time, IN_HOSP_DAYS number, MAIN_COND_DES text, MED_AMOUT number, MED_CLINIC_ID text, MED_ORG_DEPT_CD text, MED_ORG_DEPT_NM text, MED_SER_ORG_NO text, MED_TYPE number, OUT_DIAG_DIS_CD text, OUT_DIAG_DIS_NM text, OUT_DIAG_DOC_CD text, OUT_DIAG_DOC_NM text, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, PERSON_AGE number, PERSON_ID text, PERSON_NM text, PERSON_SEX number, REIMBURSEMENT_FLG number, REMOTE_SETTLE_FLG text, SERVANT_FLG text, SOC_SRT_CARD text, SYNC_TIME time, TRADE_TYPE number ) CREATE TABLE t_kc21_t_kc22 ( MED_CLINIC_ID text, MED_EXP_DET_ID number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 患者59902632最主要找哪位医生接受治疗,时间是从01年7月28日到06年7月31日
SELECT t_kc21.OUT_DIAG_DOC_CD, t_kc21.OUT_DIAG_DOC_NM FROM t_kc21 WHERE t_kc21.PERSON_ID = '59902632' AND t_kc21.IN_HOSP_DATE BETWEEN '2001-07-28' AND '2006-07-31' GROUP BY t_kc21.OUT_DIAG_DOC_CD ORDER BY COUNT(*) DESC LIMIT 1
css
CREATE TABLE table_21696 ( "Winner" text, "Country" text, "Winter Olympics" text, "FIS Nordic World Ski Championships" text, "Holmenkollen" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What years did Birger Ruud win the FIS Nordic World Ski Championships?
SELECT "FIS Nordic World Ski Championships" FROM table_21696 WHERE "Winner" = 'Birger Ruud'
wikisql
CREATE TABLE table_203_116 ( id number, "no." number, "player" text, "birth date" text, "weight" number, "height" number, "position" text, "current club" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- how many members of estonia 's men 's national volleyball team were born in 1988 ?
SELECT COUNT("player") FROM table_203_116 WHERE "birth date" = 1988
squall
CREATE TABLE table_2818164_5 ( no_in_season VARCHAR, original_air_date VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What episoe number in the season originally aired on February 11, 1988?
SELECT no_in_season FROM table_2818164_5 WHERE original_air_date = "February 11, 1988"
sql_create_context
CREATE TABLE table_60686 ( "Date" text, "Tournament" text, "Surface" text, "Opponent" text, "Score" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What date was the match against adri n men ndez-maceiras?
SELECT "Date" FROM table_60686 WHERE "Opponent" = 'adrián menéndez-maceiras'
wikisql
CREATE TABLE table_203_365 ( id number, "released" text, "video title" text, "company" text, "director" text, "notes" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- did shoko goto make more films in 2004 or 2005 ?
SELECT "released" FROM table_203_365 WHERE "released" IN (2004, 2005) GROUP BY "released" ORDER BY COUNT("video title") DESC LIMIT 1
squall
CREATE TABLE table_65116 ( "Date" text, "Venue" text, "Score" text, "Result" text, "Competition" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What venue listed is dated February 22, 2003?
SELECT "Venue" FROM table_65116 WHERE "Date" = 'february 22, 2003'
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 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. -- provide the number of patients whose admission type is emergency and lab test name is rbc, csf?
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.admission_type = "EMERGENCY" AND lab.label = "RBC, CSF"
mimicsql_data
CREATE TABLE course ( course_id int, name varchar, department varchar, number varchar, credits varchar, advisory_requirement varchar, enforced_requirement varchar, description varchar, num_semesters int, num_enrolled int, has_discussion varchar, has_lab varchar, has_projects varchar, has_exams varchar, num_reviews int, clarity_score int, easiness_score int, helpfulness_score int ) CREATE TABLE comment_instructor ( instructor_id int, student_id int, score int, comment_text varchar ) CREATE TABLE course_offering ( offering_id int, course_id int, semester int, section_number int, start_time time, end_time time, monday varchar, tuesday varchar, wednesday varchar, thursday varchar, friday varchar, saturday varchar, sunday varchar, has_final_project varchar, has_final_exam varchar, textbook varchar, class_address varchar, allow_audit varchar ) CREATE TABLE instructor ( instructor_id int, name varchar, uniqname varchar ) CREATE TABLE gsi ( course_offering_id int, student_id int ) CREATE TABLE student_record ( student_id int, course_id int, semester int, grade varchar, how varchar, transfer_source varchar, earn_credit varchar, repeat_term varchar, test_id varchar ) CREATE TABLE course_tags_count ( course_id int, clear_grading int, pop_quiz int, group_projects int, inspirational int, long_lectures int, extra_credit int, few_tests int, good_feedback int, tough_tests int, heavy_papers int, cares_for_students int, heavy_assignments int, respected int, participation int, heavy_reading int, tough_grader int, hilarious int, would_take_again int, good_lecture int, no_skip int ) CREATE TABLE requirement ( requirement_id int, requirement varchar, college varchar ) CREATE TABLE program ( program_id int, name varchar, college varchar, introduction varchar ) CREATE TABLE program_requirement ( program_id int, category varchar, min_credit int, additional_req varchar ) CREATE TABLE student ( student_id int, lastname varchar, firstname varchar, program_id int, declare_major varchar, total_credit int, total_gpa float, entered_as varchar, admit_term int, predicted_graduation_semester int, degree varchar, minor varchar, internship varchar ) CREATE TABLE area ( course_id int, area varchar ) CREATE TABLE jobs ( job_id int, job_title varchar, description varchar, requirement varchar, city varchar, state varchar, country varchar, zip int ) CREATE TABLE program_course ( program_id int, course_id int, workload int, category varchar ) CREATE TABLE course_prerequisite ( pre_course_id int, course_id int ) CREATE TABLE semester ( semester_id int, semester varchar, year int ) CREATE TABLE ta ( campus_job_id int, student_id int, location varchar ) CREATE TABLE offering_instructor ( offering_instructor_id int, offering_id int, instructor_id int ) -- Using valid SQLite, answer the following questions for the tables provided above. -- How often does the course POLSCI 659 meet ?
SELECT DISTINCT course_offering.friday, course_offering.monday, course_offering.saturday, course_offering.sunday, course_offering.thursday, course_offering.tuesday, course_offering.wednesday FROM course INNER JOIN course_offering ON course.course_id = course_offering.course_id INNER JOIN semester ON semester.semester_id = course_offering.semester WHERE course.department = 'POLSCI' AND course.number = 659 AND semester.semester = 'WN' AND semester.year = 2016
advising
CREATE TABLE table_40395 ( "Couple" text, "Style" text, "Music" text, "Choreographer(s)" text, "Results" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which couple participated in the Contemporary style of dance?
SELECT "Couple" FROM table_40395 WHERE "Style" = 'contemporary'
wikisql
CREATE TABLE table_28772 ( "Portuguese name" text, "English name" text, "Subdivides in" text, "Equivalence in Varas" text, "Metrical equivalence" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the metrical equivalence for linha
SELECT "Metrical equivalence" FROM table_28772 WHERE "Portuguese name" = 'Linha'
wikisql
CREATE TABLE t_kc24 ( ACCOUNT_DASH_DATE time, ACCOUNT_DASH_FLG number, CASH_PAY number, CIVIL_SUBSIDY number, CKC102 number, CLINIC_ID text, CLINIC_SLT_DATE time, COMP_ID text, COM_ACC_PAY number, COM_PAY number, DATA_ID text, ENT_ACC_PAY number, ENT_PAY number, FLX_MED_ORG_ID text, ILL_PAY number, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, LAS_OVE_PAY number, MED_AMOUT number, MED_CLINIC_ID text, MED_SAFE_PAY_ID text, MED_TYPE number, OLDC_FUND_PAY number, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, OVE_ADD_PAY number, OVE_PAY number, PERSON_ID text, PER_ACC_PAY number, PER_EXP number, PER_SOL number, RECEIVER_DEAL_ID text, RECEIVER_OFFSET_ID text, RECEIVER_REVOKE_ID text, RECIPE_BILL_ID text, REF_SLT_FLG number, REIMBURS_FLG number, SENDER_DEAL_ID text, SENDER_OFFSET_ID text, SENDER_REVOKE_ID text, SPE_FUND_PAY number, SUP_ADD_PAY number, SYNC_TIME time, TRADE_TYPE number ) CREATE TABLE gwyjzb ( CLINIC_ID text, CLINIC_TYPE text, COMP_ID text, DATA_ID text, DIFF_PLACE_FLG number, FERTILITY_STS number, FLX_MED_ORG_ID text, HOSP_LEV number, HOSP_STS number, IDENTITY_CARD text, INPT_AREA_BED text, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, IN_DIAG_DIS_CD text, IN_DIAG_DIS_NM text, IN_HOSP_DATE time, IN_HOSP_DAYS number, MAIN_COND_DES text, MED_AMOUT number, MED_CLINIC_ID number, MED_ORG_DEPT_CD text, MED_ORG_DEPT_NM text, MED_SER_ORG_NO text, MED_TYPE number, OUT_DIAG_DIS_CD text, OUT_DIAG_DIS_NM text, OUT_DIAG_DOC_CD text, OUT_DIAG_DOC_NM text, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, PERSON_AGE number, PERSON_ID text, PERSON_NM text, PERSON_SEX number, REIMBURSEMENT_FLG number, REMOTE_SETTLE_FLG text, SOC_SRT_CARD text, SYNC_TIME time, TRADE_TYPE number ) CREATE TABLE t_kc22 ( AMOUNT number, CHA_ITEM_LEV number, DATA_ID text, DIRE_TYPE number, DOSE_FORM text, DOSE_UNIT text, EACH_DOSAGE text, EXP_OCC_DATE time, FLX_MED_ORG_ID text, FXBZ number, HOSP_DOC_CD text, HOSP_DOC_NM text, MED_CLINIC_ID text, MED_DIRE_CD text, MED_DIRE_NM text, MED_EXP_BILL_ID text, MED_EXP_DET_ID text, MED_INV_ITEM_TYPE text, MED_ORG_DEPT_CD text, MED_ORG_DEPT_NM text, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, OVE_SELF_AMO number, PRESCRIPTION_CODE text, PRESCRIPTION_ID text, QTY number, RECIPE_BILL_ID text, REF_STA_FLG number, REIMBURS_TYPE number, REMOTE_SETTLE_FLG text, RER_SOL number, SELF_PAY_AMO number, SELF_PAY_PRO number, SOC_SRT_DIRE_CD text, SOC_SRT_DIRE_NM text, SPEC text, STA_DATE time, STA_FLG number, SYNC_TIME time, TRADE_TYPE number, UNIVALENT number, UP_LIMIT_AMO number, USE_FRE text, VAL_UNIT text ) CREATE TABLE fgwyjzb ( CLINIC_ID text, CLINIC_TYPE text, COMP_ID text, DATA_ID text, DIFF_PLACE_FLG number, FERTILITY_STS number, FLX_MED_ORG_ID text, HOSP_LEV number, HOSP_STS number, IDENTITY_CARD text, INPT_AREA_BED text, INSURED_IDENTITY number, INSURED_STS text, INSU_TYPE text, IN_DIAG_DIS_CD text, IN_DIAG_DIS_NM text, IN_HOSP_DATE time, IN_HOSP_DAYS number, MAIN_COND_DES text, MED_AMOUT number, MED_CLINIC_ID number, MED_ORG_DEPT_CD text, MED_ORG_DEPT_NM text, MED_SER_ORG_NO text, MED_TYPE number, OUT_DIAG_DIS_CD text, OUT_DIAG_DIS_NM text, OUT_DIAG_DOC_CD text, OUT_DIAG_DOC_NM text, OUT_HOSP_DATE time, OVERALL_CD_ORG text, OVERALL_CD_PERSON text, PERSON_AGE number, PERSON_ID text, PERSON_NM text, PERSON_SEX number, REIMBURSEMENT_FLG number, REMOTE_SETTLE_FLG text, SOC_SRT_CARD text, SYNC_TIME time, TRADE_TYPE number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 郑丽容患者在医院5352405的出院诊断结果中哪个出院诊断医生姓沈,需要这个结果的详情
SELECT gwyjzb.OUT_DIAG_DIS_CD, gwyjzb.OUT_DIAG_DIS_NM FROM gwyjzb WHERE gwyjzb.PERSON_NM = '郑丽容' AND gwyjzb.MED_SER_ORG_NO = '5352405' AND gwyjzb.OUT_DIAG_DOC_NM LIKE '沈%' UNION SELECT fgwyjzb.OUT_DIAG_DIS_CD, fgwyjzb.OUT_DIAG_DIS_NM FROM fgwyjzb WHERE fgwyjzb.PERSON_NM = '郑丽容' AND fgwyjzb.MED_SER_ORG_NO = '5352405' AND fgwyjzb.OUT_DIAG_DOC_NM LIKE '沈%'
css
CREATE TABLE mzjybgb ( BBCJBW text, BBDM text, BBMC text, BBZT number, BGDH number, BGJGDM text, BGJGMC text, BGRGH text, BGRQ time, BGRXM text, BGSJ time, CJRQ time, JSBBRQSJ time, JSBBSJ time, JYBBH text, JYJGMC text, JYJSGH text, JYJSQM text, JYKSBM text, JYKSMC text, JYLX number, JYRQ time, JYSQJGMC text, JYXMDM text, JYXMMC text, JZLSH text, JZLSH_MZJZJLB text, JZLSH_ZYJZJLB text, KSBM text, KSMC text, SHRGH text, SHRXM text, SHSJ time, SQKS text, SQKSMC text, SQRGH text, SQRQ time, SQRXM text, YLJGDM number, YLJGDM_MZJZJLB text, YLJGDM_ZYJZJLB text ) CREATE TABLE jyjgzbb ( BGDH text, BGRQ time, CKZFWDX text, CKZFWSX number, CKZFWXX number, JCFF text, JCRGH text, JCRXM text, JCXMMC text, JCZBDM text, JCZBJGDL number, JCZBJGDW text, JCZBJGDX text, JCZBMC text, JLDW text, JYRQ time, JYZBLSH text, SBBM text, SHRGH text, SHRXM text, YLJGDM text, YQBH text, YQMC text ) CREATE TABLE person_info ( CSD text, CSRQ time, GJDM text, GJMC text, JGDM text, JGMC text, MZDM text, MZMC text, RYBH text, XBDM number, XBMC text, XLDM text, XLMC text, XM text, ZYLBDM text, ZYMC text ) CREATE TABLE zyjybgb ( BBCJBW text, BBDM text, BBMC text, BBZT number, BGDH number, BGJGDM text, BGJGMC text, BGRGH text, BGRQ time, BGRXM text, BGSJ time, CJRQ time, JSBBRQSJ time, JSBBSJ time, JYBBH text, JYJGMC text, JYJSGH text, JYJSQM text, JYKSBM text, JYKSMC text, JYLX number, JYRQ time, JYSQJGMC text, JYXMDM text, JYXMMC text, JZLSH text, JZLSH_MZJZJLB text, JZLSH_ZYJZJLB text, KSBM text, KSMC text, SHRGH text, SHRXM text, SHSJ time, SQKS text, SQKSMC text, SQRGH text, SQRQ time, SQRXM text, YLJGDM number, YLJGDM_MZJZJLB text, YLJGDM_ZYJZJLB text ) CREATE TABLE hz_info ( KH text, KLX number, RYBH text, YLJGDM text ) CREATE TABLE 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 mzjzjlb ( HXPLC number, HZXM text, JLSJ time, JZJSSJ time, JZKSBM text, JZKSMC text, JZKSRQ time, JZLSH text, JZZDBM text, JZZDSM text, JZZTDM number, JZZTMC text, KH text, KLX number, MJZH text, ML number, MZZYZDZZBM text, MZZYZDZZMC text, NLS number, NLY number, QTJZYSGH text, SG number, SSY number, SZY number, TW number, TXBZ number, TZ number, WDBZ number, XL number, YLJGDM text, ZSEBZ number, ZZBZ number, ZZYSGH text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 患者56570950在二零零七年十月九日之后有哪些门诊就诊的检验报告单?列出门诊就诊流水号
SELECT mzjzjlb.JZLSH FROM hz_info JOIN mzjzjlb ON hz_info.YLJGDM = mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX WHERE hz_info.RYBH = '56570950' AND NOT mzjzjlb.JZLSH IN (SELECT zyjybgb.JZLSH FROM zyjybgb WHERE zyjybgb.BGRQ <= '2007-10-09' UNION SELECT mzjybgb.JZLSH FROM mzjybgb WHERE mzjybgb.BGRQ <= '2007-10-09')
css
CREATE TABLE table_27132791_3 ( position VARCHAR, college VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- If the college is SMU, what is the position?
SELECT position FROM table_27132791_3 WHERE college = "SMU"
sql_create_context
CREATE TABLE table_21876 ( "Season" real, "Date" text, "Winning Driver" text, "Car #" real, "Sponsor" text, "Make" text, "Team" text, "Avg Speed" text, "Margin of Victory" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What was the represented team on June 27?
SELECT "Team" FROM table_21876 WHERE "Date" = 'June 27'
wikisql
CREATE TABLE artist ( artist_id number, artist text, age number, famous_title text, famous_release_date text ) CREATE TABLE music_festival ( id number, music_festival text, date_of_ceremony text, category text, volume number, result text ) CREATE TABLE volume ( volume_id number, volume_issue text, issue_date text, weeks_on_top number, song text, artist_id number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Please show the songs that have result 'nominated' at music festivals.
SELECT T2.song FROM music_festival AS T1 JOIN volume AS T2 ON T1.volume = T2.volume_id WHERE T1.result = "Nominated"
spider
CREATE TABLE elimination ( elimination_id text, wrestler_id text, team text, eliminated_by text, elimination_move text, time text ) CREATE TABLE wrestler ( wrestler_id number, name text, reign text, days_held text, location text, event text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which teams had more than 3 eliminations?
SELECT team FROM elimination GROUP BY team HAVING COUNT(*) > 3
spider
CREATE TABLE table_204_910 ( id number, "rank" number, "name" text, "nationality" text, "result" number, "notes" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- how many athletes had a better result than tatyana bocharova ?
SELECT COUNT("name") FROM table_204_910 WHERE "result" > (SELECT "result" FROM table_204_910 WHERE "name" = 'tatyana bocharova')
squall
CREATE TABLE table_8430 ( "Number" text, "Builder" text, "Type" text, "Date" real, "Length" text, "Capacity" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which Type has a Capacity of 28 passengers, and a Number of 16?
SELECT "Type" FROM table_8430 WHERE "Capacity" = '28 passengers' AND "Number" = '16'
wikisql
CREATE TABLE people ( people_id number, district text, name text, party text, age number ) CREATE TABLE debate_people ( debate_id number, affirmative number, negative number, if_affirmative_win others ) CREATE TABLE debate ( debate_id number, date text, venue text, num_of_audience number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Show the names of people, and dates and venues of debates they are on the negative side, ordered in ascending alphabetical order of name.
SELECT T3.name, T2.date, T2.venue FROM debate_people AS T1 JOIN debate AS T2 ON T1.debate_id = T2.debate_id JOIN people AS T3 ON T1.negative = T3.people_id ORDER BY T3.name
spider
CREATE TABLE table_203_564 ( id number, "hand" text, "1 credit" number, "2 credits" number, "3 credits" number, "4 credits" number, "5 credits" number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- is a 2 credit full house the same as a 5 credit three of a kind ?
SELECT (SELECT "2 credits" FROM table_203_564 WHERE "hand" = 'full house') = (SELECT "5 credits" FROM table_203_564 WHERE "hand" = 'three of a kind')
squall
CREATE TABLE area ( course_id int, area varchar ) CREATE TABLE program ( program_id int, name varchar, college varchar, introduction varchar ) CREATE TABLE ta ( campus_job_id int, student_id int, location varchar ) CREATE TABLE course ( course_id int, name varchar, department varchar, number varchar, credits varchar, advisory_requirement varchar, enforced_requirement varchar, description varchar, num_semesters int, num_enrolled int, has_discussion varchar, has_lab varchar, has_projects varchar, has_exams varchar, num_reviews int, clarity_score int, easiness_score int, helpfulness_score int ) CREATE TABLE offering_instructor ( offering_instructor_id int, offering_id int, instructor_id int ) CREATE TABLE course_prerequisite ( pre_course_id int, course_id int ) CREATE TABLE requirement ( requirement_id int, requirement varchar, college varchar ) CREATE TABLE jobs ( job_id int, job_title varchar, description varchar, requirement varchar, city varchar, state varchar, country varchar, zip int ) CREATE TABLE student ( student_id int, lastname varchar, firstname varchar, program_id int, declare_major varchar, total_credit int, total_gpa float, entered_as varchar, admit_term int, predicted_graduation_semester int, degree varchar, minor varchar, internship varchar ) CREATE TABLE course_offering ( offering_id int, course_id int, semester int, section_number int, start_time time, end_time time, monday varchar, tuesday varchar, wednesday varchar, thursday varchar, friday varchar, saturday varchar, sunday varchar, has_final_project varchar, has_final_exam varchar, textbook varchar, class_address varchar, allow_audit varchar ) CREATE TABLE comment_instructor ( instructor_id int, student_id int, score int, comment_text varchar ) CREATE TABLE gsi ( course_offering_id int, student_id int ) CREATE TABLE program_course ( program_id int, course_id int, workload int, category varchar ) CREATE TABLE program_requirement ( program_id int, category varchar, min_credit int, additional_req varchar ) CREATE TABLE course_tags_count ( course_id int, clear_grading int, pop_quiz int, group_projects int, inspirational int, long_lectures int, extra_credit int, few_tests int, good_feedback int, tough_tests int, heavy_papers int, cares_for_students int, heavy_assignments int, respected int, participation int, heavy_reading int, tough_grader int, hilarious int, would_take_again int, good_lecture int, no_skip int ) CREATE TABLE student_record ( student_id int, course_id int, semester int, grade varchar, how varchar, transfer_source varchar, earn_credit varchar, repeat_term varchar, test_id varchar ) CREATE TABLE semester ( semester_id int, semester varchar, year int ) CREATE TABLE instructor ( instructor_id int, name varchar, uniqname varchar ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Next semester , what time does the EDUC 510 lecture begin ?
SELECT DISTINCT course_offering.start_time FROM course INNER JOIN program_course ON program_course.course_id = course.course_id INNER JOIN course_offering ON course.course_id = course_offering.course_id INNER JOIN semester ON semester.semester_id = course_offering.semester WHERE course.department = 'EDUC' AND course.number = 510 AND semester.semester = 'FA' AND semester.year = 2016
advising
CREATE TABLE Manufacturers ( Code INTEGER, Name VARCHAR(255), Headquarter VARCHAR(255), Founder VARCHAR(255), Revenue REAL ) CREATE TABLE Products ( Code INTEGER, Name VARCHAR(255), Price DECIMAL, Manufacturer INTEGER ) -- Using valid SQLite, answer the following questions for the tables provided above. -- For those records from the products and each product's manufacturer, a bar chart shows the distribution of name and the sum of code , and group by attribute name, sort total number of code in asc order.
SELECT T2.Name, T1.Code FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY T2.Name ORDER BY T1.Code
nvbench
CREATE TABLE table_name_18 ( round INTEGER, school VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What was the highest round that had northwestern?
SELECT MAX(round) FROM table_name_18 WHERE school = "northwestern"
sql_create_context
CREATE TABLE table_name_19 ( wins INTEGER, position VARCHAR, poles VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the smallest Wins with a Position of 20th, and Poles smaller than 0?
SELECT MIN(wins) FROM table_name_19 WHERE position = "20th" AND poles < 0
sql_create_context
CREATE TABLE table_30306 ( "Year Location" text, "Mens Singles" text, "Womens Singles" text, "Mens Doubles" text, "Womens Doubles" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Who is listed under mens singles when womens has wang nan zhang yining?
SELECT "Mens Singles" FROM table_30306 WHERE "Womens Doubles" = 'Wang Nan Zhang Yining'
wikisql
CREATE TABLE Behavior_Incident ( date_incident_start VARCHAR, date_incident_end VARCHAR, incident_type_code VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What are the start and end dates for incidents with incident type code 'NOISE'?
SELECT date_incident_start, date_incident_end FROM Behavior_Incident WHERE incident_type_code = "NOISE"
sql_create_context
CREATE TABLE countries ( COUNTRY_ID varchar(2), COUNTRY_NAME varchar(40), REGION_ID decimal(10,0) ) CREATE TABLE employees ( EMPLOYEE_ID decimal(6,0), FIRST_NAME varchar(20), LAST_NAME varchar(25), EMAIL varchar(25), PHONE_NUMBER varchar(20), HIRE_DATE date, JOB_ID varchar(10), SALARY decimal(8,2), COMMISSION_PCT decimal(2,2), MANAGER_ID decimal(6,0), DEPARTMENT_ID decimal(4,0) ) CREATE TABLE jobs ( JOB_ID varchar(10), JOB_TITLE varchar(35), MIN_SALARY decimal(6,0), MAX_SALARY decimal(6,0) ) CREATE TABLE departments ( DEPARTMENT_ID decimal(4,0), DEPARTMENT_NAME varchar(30), MANAGER_ID decimal(6,0), LOCATION_ID decimal(4,0) ) CREATE TABLE job_history ( EMPLOYEE_ID decimal(6,0), START_DATE date, END_DATE date, JOB_ID varchar(10), 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) ) CREATE TABLE regions ( REGION_ID decimal(5,0), REGION_NAME varchar(25) ) -- Using valid SQLite, answer the following questions for the tables provided above. -- For those employees whose salary is in the range of 8000 and 12000 and commission is not null or department number does not equal to 40, return a bar chart about the distribution of hire_date and the average of manager_id bin hire_date by weekday, display by the the average of manager id in ascending please.
SELECT HIRE_DATE, AVG(MANAGER_ID) FROM employees WHERE SALARY BETWEEN 8000 AND 12000 AND COMMISSION_PCT <> "null" OR DEPARTMENT_ID <> 40 ORDER BY AVG(MANAGER_ID)
nvbench
CREATE TABLE table_204_988 ( id number, "responsible minister(s)" text, "crown entities" text, "monitoring department(s)" text, "category / type" text, "empowering legislation" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- who is listed as the last responsible mister -lrb- s -rrb- on this chart ?
SELECT "responsible minister(s)" FROM table_204_988 ORDER BY id DESC LIMIT 1
squall
CREATE TABLE ReviewTaskResults ( Id number, ReviewTaskId number, ReviewTaskResultTypeId number, CreationDate time, RejectionReasonId number, Comment 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 SuggestedEdits ( Id number, PostId number, CreationDate time, ApprovalDate time, RejectionDate time, OwnerUserId number, Comment text, Text text, Title text, Tags text, RevisionGUID other ) CREATE TABLE FlagTypes ( Id number, Name text, Description text ) CREATE TABLE PostFeedback ( Id number, PostId number, IsAnonymous boolean, VoteTypeId number, CreationDate time ) CREATE TABLE SuggestedEditVotes ( Id number, SuggestedEditId number, UserId number, VoteTypeId number, CreationDate time, TargetUserId number, TargetRepChange 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 Comments ( Id number, PostId number, Score number, Text text, CreationDate time, UserDisplayName text, UserId number, 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 CloseReasonTypes ( Id number, Name text, Description text ) CREATE TABLE PostTypes ( Id number, Name text ) CREATE TABLE PostNoticeTypes ( Id number, ClassId number, Name text, Body text, IsHidden boolean, Predefined boolean, PostNoticeDurationId number ) CREATE TABLE ReviewTaskStates ( Id number, Name text, Description text ) CREATE TABLE ReviewTaskResultTypes ( Id number, Name text, Description text ) CREATE TABLE Posts ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE VoteTypes ( Id number, Name text ) CREATE TABLE PostHistoryTypes ( Id number, Name text ) CREATE TABLE PostsWithDeleted ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE ReviewRejectionReasons ( Id number, Name text, Description text, PostTypeId number ) CREATE TABLE ReviewTaskTypes ( Id number, Name text, Description text ) CREATE TABLE Badges ( Id number, UserId number, Name text, Date time, Class number, TagBased boolean ) 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 Tags ( Id number, TagName text, Count number, ExcerptPostId number, WikiPostId number ) CREATE TABLE Votes ( Id number, PostId number, VoteTypeId number, UserId number, CreationDate time, BountyAmount number ) CREATE TABLE PostNotices ( Id number, PostId number, PostNoticeTypeId number, CreationDate time, DeletionDate time, ExpiryDate time, Body text, OwnerUserId number, DeletionUserId number ) CREATE TABLE PendingFlags ( Id number, FlagTypeId number, PostId number, CreationDate time, CloseReasonTypeId number, CloseAsOffTopicReasonTypeId number, DuplicateOfQuestionId number, BelongsOnBaseHostAddress text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Users with highest reputation both in SO and Math ( geometric mean = average digits).
SELECT s.DisplayName, s.Reputation AS RepSO, m.Reputation AS RepMath, (LOG10(s.Reputation) + LOG10(m.Reputation)) / 2 AS RepAvDigits FROM "stackexchange.math".Users AS m, "stackoverflow".Users AS s WHERE s.Reputation > 10000 AND m.Reputation > 10000 AND s.AccountId = m.AccountId ORDER BY 4 DESC
sede
CREATE TABLE table_29747178_2 ( series__number VARCHAR, directed_by VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the series # when the director is john showalter?
SELECT series__number FROM table_29747178_2 WHERE directed_by = "John Showalter"
sql_create_context
CREATE TABLE demographic ( subject_id text, hadm_id text, name text, marital_status text, age text, dob text, gender text, language text, religion text, admission_type text, days_stay text, insurance text, ethnicity text, expire_flag text, admission_location text, discharge_location text, diagnosis text, dod text, dob_year text, dod_year text, admittime text, dischtime text, admityear text ) CREATE TABLE lab ( subject_id text, hadm_id text, itemid text, charttime text, flag text, value_unit text, label text, fluid text ) CREATE TABLE prescriptions ( subject_id text, hadm_id text, icustay_id text, drug_type text, drug text, formulary_drug_cd text, route text, drug_dose text ) CREATE TABLE diagnoses ( subject_id text, hadm_id text, icd9_code text, short_title text, long_title text ) CREATE TABLE procedures ( subject_id text, hadm_id text, icd9_code text, short_title text, long_title text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- provide the number of patients whose admission type is emergency and diagnosis long title is other drugs and medicinal substances causing adverse effects in therapeutic use.
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.admission_type = "EMERGENCY" AND diagnoses.long_title = "Other drugs and medicinal substances causing adverse effects in therapeutic use"
mimicsql_data
CREATE TABLE table_19191 ( "Year" real, "League" text, "Reg. Season" text, "Playoffs" text, "US Open Cup" text, "Avg. Attendance" real ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What was the regular season standings for the year when the playoffs reached the conference semifinals and the team did not qualify for the US Open Cup?
SELECT "Reg. Season" FROM table_19191 WHERE "Playoffs" = 'Conference Semifinals' AND "US Open Cup" = 'Did not qualify'
wikisql
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. -- 在医疗就诊45488624657中,开出的哪些药的名称中包含丁酸?其对应的价格呢
SELECT SOC_SRT_DIRE_CD, SOC_SRT_DIRE_NM, AMOUNT FROM t_kc22 WHERE MED_CLINIC_ID = '45488624657' AND SOC_SRT_DIRE_NM LIKE '%丁酸%'
css
CREATE TABLE table_37490 ( "Name" text, "Gain" real, "Loss" real, "Long" real, "Avg/G" real ) -- Using valid SQLite, answer the following questions for the tables provided above. -- How much Long has a Loss larger than 2, and a Gain of 157, and an Avg/G smaller than 129?
SELECT SUM("Long") FROM table_37490 WHERE "Loss" > '2' AND "Gain" = '157' AND "Avg/G" < '129'
wikisql
CREATE TABLE table_7363 ( "Vol. #" real, "Title" text, "Material collected" text, "Pages" real, "ISBN" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- How many pages does the edition with a volume # smaller than 8 and an ISBM of 1-40122-892-5 have?
SELECT SUM("Pages") FROM table_7363 WHERE "Vol. #" < '8' AND "ISBN" = '1-40122-892-5'
wikisql
CREATE TABLE hz_info_mzjzjlb ( JZLSH number, YLJGDM number, mzjzjlb_id number ) CREATE TABLE zyjzjlb ( CYBQDM text, CYBQMC text, CYCWH text, CYKSDM text, CYKSMC text, CYSJ time, CYZTDM number, HZXM text, JZKSDM text, JZKSMC text, JZLSH text, KH text, KLX number, MZBMLX number, MZJZLSH text, MZZDBM text, MZZDMC text, MZZYZDZZBM text, RYCWH text, RYDJSJ time, RYSJ time, RYTJDM number, RYTJMC text, RZBQDM text, RZBQMC text, WDBZ number, YLJGDM text, ZYBMLX number, ZYZDBM text, ZYZDMC text, ZYZYZDZZBM text, ZYZYZDZZMC text ) CREATE TABLE person_info ( CSD text, CSRQ time, GJDM text, GJMC text, JGDM text, JGMC text, MZDM text, MZMC text, RYBH text, XBDM number, XBMC text, XLDM text, XLMC text, XM text, ZYLBDM text, ZYMC text ) CREATE TABLE hz_info ( KH text, KLX number, RYBH text, YLJGDM text ) CREATE TABLE jyjgzbb ( BGDH text, BGRQ time, CKZFWDX text, CKZFWSX number, CKZFWXX number, JCFF text, JCRGH text, JCRXM text, JCXMMC text, JCZBDM text, JCZBJGDL number, JCZBJGDW text, JCZBJGDX text, JCZBMC text, JLDW text, JYRQ time, JYZBLSH text, SBBM text, SHRGH text, SHRXM text, YLJGDM text, YQBH text, YQMC text ) CREATE TABLE jybgb ( BBCJBW text, BBDM text, BBMC text, BBZT number, BGDH text, BGJGDM text, BGJGMC text, BGRGH text, BGRQ time, BGRXM text, BGSJ time, CJRQ time, JSBBRQSJ time, JSBBSJ time, JYBBH text, JYJGMC text, JYJSGH text, JYJSQM text, JYKSBM text, JYKSMC text, JYLX number, JYRQ time, JYSQJGMC text, JYXMDM text, JYXMMC text, JZLSH text, JZLSH_MZJZJLB text, JZLSH_ZYJZJLB text, JZLX number, KSBM text, KSMC text, SHRGH text, SHRXM text, SHSJ time, SQKS text, SQKSMC text, SQRGH text, SQRQ time, SQRXM text, YLJGDM text, YLJGDM_MZJZJLB text, YLJGDM_ZYJZJLB text ) CREATE TABLE mzjzjlb ( HXPLC number, HZXM text, JLSJ time, JZJSSJ time, JZKSBM text, JZKSMC text, JZKSRQ time, JZLSH text, JZZDBM text, JZZDSM text, JZZTDM number, JZZTMC text, KH text, KLX number, MJZH text, ML number, MZZYZDZZBM text, MZZYZDZZMC text, NLS number, NLY number, QTJZYSGH text, SG number, SSY number, SZY number, TW number, TXBZ number, TZ number, WDBZ number, XL number, ZSEBZ number, ZZBZ number, ZZYSGH text, mzjzjlb_id number ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 从13年5月11日到2020年4月11日这段时间,列出患者杨丹红所有检验报告单的审核日期时间吗?
SELECT jybgb.SHSJ FROM person_info JOIN hz_info JOIN mzjzjlb JOIN jybgb JOIN hz_info_mzjzjlb ON person_info.RYBH = hz_info.RYBH AND hz_info.YLJGDM = hz_info_mzjzjlb.YLJGDM AND hz_info.KH = mzjzjlb.KH AND hz_info.KLX = mzjzjlb.KLX AND hz_info_mzjzjlb.YLJGDM = jybgb.YLJGDM_MZJZJLB AND mzjzjlb.JZLSH = jybgb.JZLSH_MZJZJLB AND hz_info_mzjzjlb.JZLSH = mzjzjlb.JZLSH AND hz_info_mzjzjlb.YLJGDM = hz_info_mzjzjlb.YLJGDM AND hz_info_mzjzjlb.JZLSH = mzjzjlb.JZLSH AND hz_info_mzjzjlb.mzjzjlb_id = mzjzjlb.mzjzjlb_id WHERE person_info.XM = '杨丹红' AND jybgb.BGRQ BETWEEN '2013-05-11' AND '2020-04-11' UNION SELECT jybgb.SHSJ 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 = '杨丹红' AND jybgb.BGRQ BETWEEN '2013-05-11' AND '2020-04-11'
css
CREATE TABLE PendingFlags ( Id number, FlagTypeId number, PostId number, CreationDate time, CloseReasonTypeId number, CloseAsOffTopicReasonTypeId number, DuplicateOfQuestionId number, BelongsOnBaseHostAddress text ) CREATE TABLE PostFeedback ( Id number, PostId number, IsAnonymous boolean, VoteTypeId number, CreationDate time ) CREATE TABLE 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 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 ReviewTaskResults ( Id number, ReviewTaskId number, ReviewTaskResultTypeId number, CreationDate time, RejectionReasonId number, Comment text ) CREATE TABLE Badges ( Id number, UserId number, Name text, Date time, Class number, TagBased boolean ) CREATE TABLE PostNoticeTypes ( Id number, ClassId number, Name text, Body text, IsHidden boolean, Predefined boolean, PostNoticeDurationId number ) CREATE TABLE ReviewTaskTypes ( Id number, Name text, Description text ) CREATE TABLE PostHistory ( Id number, PostHistoryTypeId number, PostId number, RevisionGUID other, CreationDate time, UserId number, UserDisplayName text, Comment text, Text text, ContentLicense text ) CREATE TABLE Votes ( Id number, PostId number, VoteTypeId number, UserId number, CreationDate time, BountyAmount number ) CREATE TABLE CloseReasonTypes ( Id number, Name text, Description text ) CREATE TABLE PostLinks ( Id number, CreationDate time, PostId number, RelatedPostId number, LinkTypeId number ) CREATE TABLE ReviewTasks ( Id number, ReviewTaskTypeId number, CreationDate time, DeletionDate time, ReviewTaskStateId number, PostId number, SuggestedEditId number, CompletedByReviewTaskId number ) CREATE TABLE VoteTypes ( Id number, Name text ) CREATE TABLE ReviewTaskStates ( Id number, Name text, Description 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 TagSynonyms ( Id number, SourceTagName text, TargetTagName text, CreationDate time, OwnerUserId number, AutoRenameCount number, LastAutoRename time, Score number, ApprovedByUserId number, ApprovalDate time ) CREATE TABLE Tags ( Id number, TagName text, Count number, ExcerptPostId number, WikiPostId number ) CREATE TABLE PostHistoryTypes ( Id number, Name text ) CREATE TABLE PostTypes ( Id number, Name text ) CREATE TABLE ReviewTaskResultTypes ( Id number, Name text, Description text ) CREATE TABLE ReviewRejectionReasons ( Id number, Name text, Description text, PostTypeId number ) CREATE TABLE Comments ( Id number, PostId number, Score number, Text text, CreationDate time, UserDisplayName text, UserId number, ContentLicense text ) CREATE TABLE Posts ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE 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 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 FlagTypes ( Id number, Name text, Description text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Ranking of questions by score.
SELECT Posts.Id AS "post_link", Posts.Title, Posts.Score AS Score FROM Posts ORDER BY Posts.Score DESC LIMIT 100
sede
CREATE TABLE table_name_40 ( game VARCHAR, score VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Which Game has a Score of w 90 82 (ot)?
SELECT game FROM table_name_40 WHERE score = "w 90–82 (ot)"
sql_create_context
CREATE TABLE table_name_67 ( crowd INTEGER, away_team VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What was the largest crowd when Collingwood was the away team?
SELECT MAX(crowd) FROM table_name_67 WHERE away_team = "collingwood"
sql_create_context
CREATE TABLE table_24185 ( "Station" text, "Line" text, "Planned" real, "Cancelled" real, "Proposal" text, "Details" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the number of cancelled for turnham green
SELECT COUNT("Cancelled") FROM table_24185 WHERE "Station" = 'Turnham Green'
wikisql
CREATE TABLE table_name_59 ( attendance INTEGER, score VARCHAR, away VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the highest attendance of the match with a 2:0 score and vida as the away team?
SELECT MAX(attendance) FROM table_name_59 WHERE score = "2:0" AND away = "vida"
sql_create_context
CREATE TABLE track ( Track_ID int, Name text, Location text, Seating real, Year_Opened real ) CREATE TABLE race ( Race_ID int, Name text, Class text, Date text, Track_ID text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Visualize a pie chart with what are the names and seatings for all tracks opened after 2000?
SELECT Name, Seating FROM track WHERE Year_Opened > 2000
nvbench
CREATE TABLE storm ( Storm_ID int, Name text, Dates_active text, Max_speed int, Damage_millions_USD real, Number_Deaths int ) CREATE TABLE region ( Region_id int, Region_code text, Region_name text ) CREATE TABLE affected_region ( Region_id int, Storm_ID int, Number_city_affected real ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Show the name for regions and the number of storms for each region by a bar chart, and sort from high to low by the X-axis.
SELECT Region_name, COUNT(*) FROM region AS T1 JOIN affected_region AS T2 ON T1.Region_id = T2.Region_id GROUP BY T1.Region_id ORDER BY Region_name DESC
nvbench
CREATE TABLE table_name_44 ( attendance INTEGER, record VARCHAR, points VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the Attendance of the game with a Record of 37 21 12 and less than 86 Points?
SELECT AVG(attendance) FROM table_name_44 WHERE record = "37–21–12" AND points < 86
sql_create_context
CREATE TABLE table_name_17 ( yards_per_attempt INTEGER, net_yards INTEGER ) -- Using valid SQLite, answer the following questions for the tables provided above. -- How many yards per attempt have net yards greater than 631?
SELECT SUM(yards_per_attempt) FROM table_name_17 WHERE net_yards > 631
sql_create_context
CREATE TABLE procedures ( subject_id text, hadm_id text, icd9_code text, short_title text, long_title text ) CREATE TABLE lab ( subject_id text, hadm_id text, itemid text, charttime text, flag text, value_unit text, label text, fluid text ) CREATE TABLE diagnoses ( subject_id text, hadm_id text, icd9_code text, short_title text, long_title text ) CREATE TABLE prescriptions ( subject_id text, hadm_id text, icustay_id text, drug_type text, drug text, formulary_drug_cd text, route text, drug_dose text ) CREATE TABLE demographic ( subject_id text, hadm_id text, name text, marital_status text, age text, dob text, gender text, language text, religion text, admission_type text, days_stay text, insurance text, ethnicity text, expire_flag text, admission_location text, discharge_location text, diagnosis text, dod text, dob_year text, dod_year text, admittime text, dischtime text, admityear text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the primary disease and diagnosis icd9 code of Josette Orr?
SELECT demographic.diagnosis, diagnoses.icd9_code FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.name = "Josette Orr"
mimicsql_data
CREATE TABLE table_23575917_2 ( scores VARCHAR, davids_team VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the scores for david baddiel and maureen lipman
SELECT COUNT(scores) FROM table_23575917_2 WHERE davids_team = "David Baddiel and Maureen Lipman"
sql_create_context
CREATE TABLE table_name_62 ( role VARCHAR, studio VARCHAR, title VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the role for mono studio and title of paradise canyon
SELECT role FROM table_name_62 WHERE studio = "mono" AND title = "paradise canyon"
sql_create_context
CREATE TABLE table_name_24 ( total VARCHAR, finish VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the total with finish of t22
SELECT total FROM table_name_24 WHERE finish = "t22"
sql_create_context
CREATE TABLE table_3782 ( "Game" real, "January" real, "Opponent" text, "Score" text, "Decision" text, "Location/Attendance" text, "Record" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- If the opponent was @ Boston Bruins, what was the Location/Attendance?
SELECT "Location/Attendance" FROM table_3782 WHERE "Opponent" = '@ Boston Bruins'
wikisql
CREATE TABLE table_64443 ( "Date(s)" text, "Venue" text, "City" text, "Ticket price(s)" text, "Ticket sold / available" text, "Ticket grossing" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What was the ticket price on September 16, 1986?
SELECT "Ticket price(s)" FROM table_64443 WHERE "Date(s)" = 'september 16, 1986'
wikisql
CREATE TABLE table_17060277_7 ( high_rebounds VARCHAR, team VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the high rebounds for memphis
SELECT high_rebounds FROM table_17060277_7 WHERE team = "Memphis"
sql_create_context
CREATE TABLE settlements ( settlement_id number, claim_id number, date_claim_made time, date_claim_settled time, amount_claimed number, amount_settled number, customer_policy_id number ) CREATE TABLE customers ( customer_id number, customer_details text ) CREATE TABLE claims ( claim_id number, policy_id number, date_claim_made time, date_claim_settled time, amount_claimed number, amount_settled number ) CREATE TABLE payments ( payment_id number, settlement_id number, payment_method_code text, date_payment_made time, amount_payment number ) CREATE TABLE customer_policies ( policy_id number, customer_id number, policy_type_code text, start_date time, end_date time ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Tell me the the date when the first claim was made.
SELECT date_claim_made FROM claims ORDER BY date_claim_made LIMIT 1
spider
CREATE TABLE table_77878 ( "Team" text, "Outgoing manager" text, "Manner of departure" text, "Date of vacancy" text, "Replaced by" text, "Date of appointment" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Tell me the outgoing manager for 22 november date of vacancy
SELECT "Outgoing manager" FROM table_77878 WHERE "Date of vacancy" = '22 november'
wikisql
CREATE TABLE Products ( Code INTEGER, Name VARCHAR(255), Price DECIMAL, Manufacturer INTEGER ) CREATE TABLE Manufacturers ( Code INTEGER, Name VARCHAR(255), Headquarter VARCHAR(255), Founder VARCHAR(255), Revenue REAL ) -- Using valid SQLite, answer the following questions for the tables provided above. -- For those products with a price between 60 and 120, return a bar chart about the distribution of name and manufacturer , and sort in desc by the y-axis.
SELECT Name, Manufacturer FROM Products WHERE Price BETWEEN 60 AND 120 ORDER BY Manufacturer DESC
nvbench
CREATE TABLE table_50927 ( "Winner" text, "Country" text, "Winter Olympics" real, "FIS Nordic World Ski Championships" text, "Holmenkollen" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Who won the FIS Nordic World Ski Championships in 1972?
SELECT "Winner" FROM table_50927 WHERE "FIS Nordic World Ski Championships" = '1972'
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, t_kc21_CLINIC_ID text, t_kc21_CLINIC_TYPE text, t_kc21_COMP_ID text, t_kc21_DATA_ID text, t_kc21_DIFF_PLACE_FLG number, t_kc21_FERTILITY_STS number, t_kc21_FLX_MED_ORG_ID text, t_kc21_HOSP_LEV number, t_kc21_HOSP_STS number, t_kc21_IDENTITY_CARD text, t_kc21_INPT_AREA_BED text, t_kc21_INSURED_IDENTITY number, t_kc21_INSURED_STS text, t_kc21_INSU_TYPE text, t_kc21_IN_DIAG_DIS_CD text, t_kc21_IN_DIAG_DIS_NM text, t_kc21_IN_HOSP_DATE time, t_kc21_IN_HOSP_DAYS number, t_kc21_MAIN_COND_DES text, t_kc21_MED_AMOUT number, t_kc21_MED_ORG_DEPT_CD text, t_kc21_MED_ORG_DEPT_NM text, t_kc21_MED_SER_ORG_NO text, t_kc21_MED_TYPE number, t_kc21_OUT_DIAG_DIS_CD text, t_kc21_OUT_DIAG_DIS_NM text, t_kc21_OUT_DIAG_DOC_CD text, t_kc21_OUT_DIAG_DOC_NM text, t_kc21_OUT_HOSP_DATE time, t_kc21_OVERALL_CD_ORG text, t_kc21_OVERALL_CD_PERSON text, t_kc21_PERSON_AGE number, t_kc21_PERSON_ID text, t_kc21_PERSON_NM text, t_kc21_PERSON_SEX number, t_kc21_REIMBURSEMENT_FLG number, t_kc21_REMOTE_SETTLE_FLG text, t_kc21_SERVANT_FLG text, t_kc21_SOC_SRT_CARD text, t_kc21_SYNC_TIME time, t_kc21_TRADE_TYPE number ) 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. -- 编号10534580的参保人从0六年六月十八日到一四年十月二十六日,门诊开出的检查项目总共有多少金额
SELECT SUM(t_kc22.AMOUNT) FROM t_kc22 WHERE t_kc22.t_kc21_PERSON_ID = '10534580' AND t_kc22.t_kc21_CLINIC_TYPE = '门诊' AND t_kc22.STA_DATE BETWEEN '2006-06-18' AND '2014-10-26' AND t_kc22.MED_INV_ITEM_TYPE = '检查费'
css
CREATE TABLE locations ( LOCATION_ID decimal(4,0), STREET_ADDRESS varchar(40), POSTAL_CODE varchar(12), CITY varchar(30), STATE_PROVINCE varchar(25), COUNTRY_ID varchar(2) ) CREATE TABLE countries ( COUNTRY_ID varchar(2), COUNTRY_NAME varchar(40), REGION_ID decimal(10,0) ) CREATE TABLE regions ( REGION_ID decimal(5,0), REGION_NAME varchar(25) ) CREATE TABLE jobs ( JOB_ID varchar(10), JOB_TITLE varchar(35), MIN_SALARY decimal(6,0), MAX_SALARY decimal(6,0) ) 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 departments ( DEPARTMENT_ID decimal(4,0), DEPARTMENT_NAME varchar(30), MANAGER_ID decimal(6,0), LOCATION_ID decimal(4,0) ) CREATE TABLE job_history ( EMPLOYEE_ID decimal(6,0), START_DATE date, END_DATE date, JOB_ID varchar(10), DEPARTMENT_ID decimal(4,0) ) -- Using valid SQLite, answer the following questions for the tables provided above. -- For those employees who was hired before 2002-06-21, give me the comparison about the average of department_id over the job_id , and group by attribute job_id, show x-axis in descending order.
SELECT JOB_ID, AVG(DEPARTMENT_ID) FROM employees WHERE HIRE_DATE < '2002-06-21' GROUP BY JOB_ID ORDER BY JOB_ID DESC
nvbench
CREATE TABLE table_2187178_1 ( listed_owner_s_ VARCHAR, team VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the listed owners for brevak racing
SELECT listed_owner_s_ FROM table_2187178_1 WHERE team = "Brevak Racing"
sql_create_context
CREATE TABLE table_7061 ( "Year" real, "Foundry" text, "Diameter (mm)" real, "Weight (kg)" text, "Nominal Tone" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is the sum total of all the years with a bell that weighed 857 kilograms?
SELECT SUM("Year") FROM table_7061 WHERE "Weight (kg)" = '857'
wikisql
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 txmzjzjlb ( HXPLC number, HZXM text, JLSJ time, JZJSSJ time, JZKSBM text, JZKSMC text, JZKSRQ time, JZLSH number, JZZDBM text, JZZDSM text, JZZTDM number, JZZTMC text, KH text, KLX number, MJZH text, ML number, MZZYZDZZBM text, MZZYZDZZMC text, NLS number, NLY number, QTJZYSGH text, SG number, SSY number, SZY number, TW number, TZ number, WDBZ number, XL number, YLJGDM number, ZSEBZ number, ZZBZ number, ZZYSGH text ) CREATE TABLE hz_info ( KH text, KLX number, RYBH text, YLJGDM text ) CREATE TABLE ftxmzjzjlb ( HXPLC number, HZXM text, JLSJ time, JZJSSJ time, JZKSBM text, JZKSMC text, JZKSRQ time, JZLSH number, JZZDBM text, JZZDSM text, JZZTDM number, JZZTMC text, KH text, KLX number, MJZH text, ML number, MZZYZDZZBM text, MZZYZDZZMC text, NLS number, NLY number, QTJZYSGH text, SG number, SSY number, SZY number, TW number, TZ number, WDBZ number, XL number, YLJGDM number, ZSEBZ number, ZZBZ number, ZZYSGH text ) CREATE TABLE 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 jyjgzbb ( BGDH text, BGRQ time, CKZFWDX text, CKZFWSX number, CKZFWXX number, JCFF text, JCRGH text, JCRXM text, JCXMMC text, JCZBDM text, JCZBJGDL number, JCZBJGDW text, JCZBJGDX text, JCZBMC text, JLDW text, JYRQ time, JYZBLSH text, SBBM text, SHRGH text, SHRXM text, YLJGDM text, YQBH text, YQMC text ) CREATE TABLE person_info ( CSD text, CSRQ time, GJDM text, GJMC text, JGDM text, JGMC text, MZDM text, MZMC text, RYBH text, XBDM number, XBMC text, XLDM text, XLMC text, XM text, ZYLBDM text, ZYMC text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 从18年2月23日到21年7月20日科室97321的门诊量是多少?
SELECT COUNT(*) FROM txmzjzjlb WHERE txmzjzjlb.JZKSBM = '97321' AND txmzjzjlb.JZKSRQ BETWEEN '2018-02-23' AND '2021-07-20' UNION SELECT COUNT(*) FROM ftxmzjzjlb WHERE ftxmzjzjlb.JZKSBM = '97321' AND ftxmzjzjlb.JZKSRQ BETWEEN '2018-02-23' AND '2021-07-20'
css
CREATE TABLE SuggestedEditVotes ( Id number, SuggestedEditId number, UserId number, VoteTypeId number, CreationDate time, TargetUserId number, TargetRepChange number ) CREATE TABLE PostNoticeTypes ( Id number, ClassId number, Name text, Body text, IsHidden boolean, Predefined boolean, PostNoticeDurationId number ) CREATE TABLE Tags ( Id number, TagName text, Count number, ExcerptPostId number, WikiPostId number ) CREATE TABLE PostHistory ( Id number, PostHistoryTypeId number, PostId number, RevisionGUID other, CreationDate time, UserId number, UserDisplayName text, Comment text, Text text, ContentLicense text ) CREATE TABLE Users ( Id number, Reputation number, CreationDate time, DisplayName text, LastAccessDate time, WebsiteUrl text, Location text, AboutMe text, Views number, UpVotes number, DownVotes number, ProfileImageUrl text, EmailHash text, AccountId number ) CREATE TABLE Votes ( Id number, PostId number, VoteTypeId number, UserId number, CreationDate time, BountyAmount 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 ReviewTaskResultTypes ( Id number, Name text, Description text ) CREATE TABLE PostsWithDeleted ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE Badges ( Id number, UserId number, Name text, Date time, Class number, TagBased boolean ) CREATE TABLE 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 ReviewTaskResults ( Id number, ReviewTaskId number, ReviewTaskResultTypeId number, CreationDate time, RejectionReasonId number, Comment text ) CREATE TABLE ReviewTasks ( Id number, ReviewTaskTypeId number, CreationDate time, DeletionDate time, ReviewTaskStateId number, PostId number, SuggestedEditId number, CompletedByReviewTaskId number ) CREATE TABLE PostTags ( PostId number, TagId number ) CREATE TABLE TagSynonyms ( Id number, SourceTagName text, TargetTagName text, CreationDate time, OwnerUserId number, AutoRenameCount number, LastAutoRename time, Score number, ApprovedByUserId number, ApprovalDate time ) CREATE TABLE ReviewTaskStates ( Id number, Name text, Description text ) CREATE TABLE PendingFlags ( Id number, FlagTypeId number, PostId number, CreationDate time, CloseReasonTypeId number, CloseAsOffTopicReasonTypeId number, DuplicateOfQuestionId number, BelongsOnBaseHostAddress text ) CREATE TABLE PostTypes ( Id number, Name text ) CREATE TABLE SuggestedEdits ( Id number, PostId number, CreationDate time, ApprovalDate time, RejectionDate time, OwnerUserId number, Comment text, Text text, Title text, Tags text, RevisionGUID other ) CREATE TABLE PostHistoryTypes ( Id number, Name text ) CREATE TABLE Posts ( Id number, PostTypeId number, AcceptedAnswerId number, ParentId number, CreationDate time, DeletionDate time, Score number, ViewCount number, Body text, OwnerUserId number, OwnerDisplayName text, LastEditorUserId number, LastEditorDisplayName text, LastEditDate time, LastActivityDate time, Title text, Tags text, AnswerCount number, CommentCount number, FavoriteCount number, ClosedDate time, CommunityOwnedDate time, ContentLicense text ) CREATE TABLE FlagTypes ( Id number, Name text, Description text ) CREATE TABLE PostFeedback ( Id number, PostId number, IsAnonymous boolean, VoteTypeId number, CreationDate time ) CREATE TABLE ReviewTaskTypes ( Id number, Name text, Description text ) CREATE TABLE PostLinks ( Id number, CreationDate time, PostId number, RelatedPostId number, LinkTypeId number ) CREATE TABLE PostNotices ( Id number, PostId number, PostNoticeTypeId number, CreationDate time, DeletionDate time, ExpiryDate time, Body text, OwnerUserId number, DeletionUserId number ) CREATE TABLE ReviewRejectionReasons ( Id number, Name text, Description text, PostTypeId number ) CREATE TABLE VoteTypes ( Id number, Name text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Questions with 'Magento' in title.
SELECT Id AS "post_link" FROM Posts WHERE Title LIKE '%Magento%'
sede
CREATE TABLE table_name_46 ( money___$__ VARCHAR, player VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What is Chris Riley's Money?
SELECT money___$__ FROM table_name_46 WHERE player = "chris riley"
sql_create_context
CREATE TABLE country ( country_id number, name text, population number, area number, languages text ) CREATE TABLE roller_coaster ( roller_coaster_id number, name text, park text, country_id number, length number, height number, speed text, opened text, status text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What are the speeds of the longest roller coaster?
SELECT speed FROM roller_coaster ORDER BY length DESC LIMIT 1
spider
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 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 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 hz_info ( KH text, KLX number, YLJGDM text, RYBH 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 ) 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 ) -- Using valid SQLite, answer the following questions for the tables provided above. -- 检验报告单58816470229与检验报告单88055478674中是否有名称相同的检测指标?列出这些检测指标有什么名称?
(SELECT JCZBMC FROM jyjgzbb WHERE BGDH = '88055478674') INTERSECT (SELECT JCZBMC FROM jyjgzbb WHERE BGDH = '58816470229')
css
CREATE TABLE table_name_48 ( points INTEGER, year VARCHAR, goals VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- What are the lowest points with 2013 as the year, and goals less than 0?
SELECT MIN(points) FROM table_name_48 WHERE year = "2013" AND goals < 0
sql_create_context
CREATE TABLE table_16888 ( "Year" real, "Championship" text, "54 holes" text, "Winning score" text, "Margin of victory" text, "Runner(s)-up" text ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Who were the runner(s)-up when Tiger won by 11 strokes?
SELECT "Runner(s)-up" FROM table_16888 WHERE "Margin of victory" = '11 strokes'
wikisql
CREATE TABLE table_15187735_8 ( segment_a VARCHAR, series_ep VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- Name the segment a for 8-08
SELECT segment_a FROM table_15187735_8 WHERE series_ep = "8-08"
sql_create_context
CREATE TABLE table_25276250_3 ( outputs VARCHAR, notes VARCHAR ) -- Using valid SQLite, answer the following questions for the tables provided above. -- How many outputs are there for solid state, battery operated for portable use listed in notes?
SELECT COUNT(outputs) FROM table_25276250_3 WHERE notes = "Solid state, battery operated for portable use"
sql_create_context

Dataset Summary

NSText2SQL dataset used to train NSQL models. The data is curated from more than 20 different public sources across the web with permissable licenses (listed below). All of these datasets come with existing text-to-SQL pairs. We apply various data cleaning and pre-processing techniques including table schema augmentation, SQL cleaning, and instruction generation using existing LLMs. The resulting dataset contains around 290,000 samples of text-to-SQL pairs.

For more information and code, please see this repository.

How to use it

from datasets import load_dataset

dataset = load_dataset("NumbersStation/NSText2SQL")

Dataset Structure

Data Instances

Each data instance in this dataset represents a text-to-SQL entry where the instruction has been formatted with the table schema and question. The output is the SQL in SQlite dialect.

Data Fields

  • instruction (string): the instruction to generate SQL.
  • output (string): the ground truth SQL.
  • source (string): the source dataset of the sample.

Languages

The language of the data is primarily English.

Source Data and Licensing Information

NSText2SQL is sourced from repositories with various licenses. Any use of all or part of the data gathered in NSText2SQL must abide by the terms of the original licenses, including attribution clauses when relevant. We thank all authors who provided these datasets. We provide provenance information for each dataset below.

Datasets License Link
academic Not Found https://github.com/jkkummerfeld/text2sql-data
advising CC-BY-4.0 https://github.com/jkkummerfeld/text2sql-data
atis Not Found https://github.com/jkkummerfeld/text2sql-data
restaurants Not Found https://github.com/jkkummerfeld/text2sql-data
scholar Not Found https://github.com/jkkummerfeld/text2sql-data
imdb Not Found https://github.com/jkkummerfeld/text2sql-data
yelp Not Found https://github.com/jkkummerfeld/text2sql-data
criteria2sql Apache-2.0 https://github.com/xiaojingyu92/Criteria2SQL
css CC-BY-4.0 https://huggingface.co/datasets/zhanghanchong/css
eICU CC-BY-4.0 https://github.com/glee4810/EHRSQL
mimic_iii CC-BY-4.0 https://github.com/glee4810/EHRSQL
geonucleardata CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
greatermanchestercrime CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
studentmathscore CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
thehistoryofbaseball CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
uswildfires CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
whatcdhiphop CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
worldsoccerdatabase CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
pesticide CC-BY-SA-4.0 https://github.com/chiahsuan156/KaggleDBQA
mimicsql_data MIT https://github.com/wangpinggl/TREQS
nvbench MIT https://github.com/TsinghuaDatabaseGroup/nvBench
sede Apache-2.0 https://github.com/hirupert/sede
spider CC-BY-SA-4.0 https://huggingface.co/datasets/spider
sql_create_context CC-BY-4.0 https://huggingface.co/datasets/b-mc2/sql-create-context
squall CC-BY-SA-4.0 https://github.com/tzshi/squall
wikisql BSD 3-Clause https://github.com/salesforce/WikiSQL

Citing this work

If you use this data in your work, please cite our work and the appropriate original sources:

To cite NSText2SQL, please use:

@software{numbersstation2023NSText2SQL,
  author    = {Numbers Station Labs},
  title     = {NSText2SQL: An Open Source Text-to-SQL Dataset for Foundation Model Training},
  month     = {July},
  year      = {2023},
  url       = {https://github.com/NumbersStationAI/NSQL},
}

To cite dataset used in this work, please use:

Datasets Cite
academic \cite{data-advising,data-academic}
advising \cite{data-advising}
atis \cite{data-advising,data-atis-original,data-atis-geography-scholar}
restaurants \cite{data-advising,data-restaurants-logic,data-restaurants-original,data-restaurants}
scholar \cite{data-advising,data-atis-geography-scholar}
imdb \cite{data-advising,data-imdb-yelp}
yelp \cite{data-advising,data-imdb-yelp}
criteria2sql \cite{Criteria-to-SQL}
css \cite{zhang2023css}
eICU \cite{lee2022ehrsql}
mimic_iii \cite{lee2022ehrsql}
geonucleardata \cite{lee-2021-kaggle-dbqa}
greatermanchestercrime \cite{lee-2021-kaggle-dbqa}
studentmathscore \cite{lee-2021-kaggle-dbqa}
thehistoryofbaseball \cite{lee-2021-kaggle-dbqa}
uswildfires \cite{lee-2021-kaggle-dbqa}
whatcdhiphop \cite{lee-2021-kaggle-dbqa}
worldsoccerdatabase \cite{lee-2021-kaggle-dbqa}
pesticide \cite{lee-2021-kaggle-dbqa}
mimicsql_data \cite{wang2020text}
nvbench \cite{nvBench_SIGMOD21}
sede \cite{hazoom2021text}
spider \cite{data-spider}
sql_create_context Not Found
squall \cite{squall}
wikisql \cite{data-wikisql}
@InProceedings{data-advising,
  dataset   = {Advising},
  author    = {Catherine Finegan-Dollak, Jonathan K. Kummerfeld, Li Zhang, Karthik Ramanathan, Sesh Sadasivam, Rui Zhang, and Dragomir Radev},
  title     = {Improving Text-to-SQL Evaluation Methodology},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2018},
  location  = {Melbourne, Victoria, Australia},
  pages     = {351--360},
  url       = {http://aclweb.org/anthology/P18-1033},
}

@InProceedings{data-imdb-yelp,
  dataset   = {IMDB and Yelp},
  author    = {Navid Yaghmazadeh, Yuepeng Wang, Isil Dillig, and Thomas Dillig},
  title     = {SQLizer: Query Synthesis from Natural Language},
  booktitle = {International Conference on Object-Oriented Programming, Systems, Languages, and Applications, ACM},
  month     = {October},
  year      = {2017},
  pages     = {63:1--63:26},
  url       = {http://doi.org/10.1145/3133887},
}

@article{data-academic,
  dataset   = {Academic},
  author    = {Fei Li and H. V. Jagadish},
  title     = {Constructing an Interactive Natural Language Interface for Relational Databases},
  journal   = {Proceedings of the VLDB Endowment},
  volume    = {8},
  number    = {1},
  month     = {September},
  year      = {2014},
  pages     = {73--84},
  url       = {http://dx.doi.org/10.14778/2735461.2735468},
} 

@InProceedings{data-atis-geography-scholar,
  dataset   = {Scholar, and Updated ATIS and Geography},
  author    = {Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, and Luke Zettlemoyer},
  title     = {Learning a Neural Semantic Parser from User Feedback},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year      = {2017},
  pages     = {963--973},
  location  = {Vancouver, Canada},
  url       = {http://www.aclweb.org/anthology/P17-1089},
}

@article{data-atis-original,
  dataset   = {ATIS, original},
  author    = {Deborah A. Dahl, Madeleine Bates, Michael Brown, William Fisher, Kate Hunicke-Smith, David Pallett, Christine Pao, Alexander Rudnicky, and Elizabeth Shriber},
  title     = {{Expanding the scope of the ATIS task: The ATIS-3 corpus}},
  journal   = {Proceedings of the workshop on Human Language Technology},
  year      = {1994},
  pages     = {43--48},
  url       = {http://dl.acm.org/citation.cfm?id=1075823},
}

@inproceedings{data-restaurants-logic,
  author    = {Lappoon R. Tang and Raymond J. Mooney},
  title     = {Automated Construction of Database Interfaces: Intergrating Statistical and Relational Learning for Semantic Parsing},
  booktitle = {2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora},
  year      = {2000},
  pages     = {133--141},
  location  = {Hong Kong, China},
  url       = {http://www.aclweb.org/anthology/W00-1317},
}

@inproceedings{data-restaurants-original,
 author    = {Ana-Maria Popescu, Oren Etzioni, and Henry Kautz},
 title     = {Towards a Theory of Natural Language Interfaces to Databases},
 booktitle = {Proceedings of the 8th International Conference on Intelligent User Interfaces},
 year      = {2003},
 location  = {Miami, Florida, USA},
 pages     = {149--157},
 url       = {http://doi.acm.org/10.1145/604045.604070},
}

@inproceedings{data-restaurants,
  author    = {Alessandra Giordani and Alessandro Moschitti},
  title     = {Automatic Generation and Reranking of SQL-derived Answers to NL Questions},
  booktitle = {Proceedings of the Second International Conference on Trustworthy Eternal Systems via Evolving Software, Data and Knowledge},
  year      = {2012},
  location  = {Montpellier, France},
  pages     = {59--76},
  url       = {https://doi.org/10.1007/978-3-642-45260-4_5},
}

@InProceedings{data-spider,
  author    = {Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, Zilin Zhang, and Dragomir Radev},
  title     = {Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task},
  booktitle = {Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing},
  year      = {2018},
  location  = {Brussels, Belgium},
  pages     = {3911--3921},
  url       = {http://aclweb.org/anthology/D18-1425},
}

@article{data-wikisql,
  author    = {Victor Zhong, Caiming Xiong, and Richard Socher},
  title     = {Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning},
  year      = {2017},
  journal   = {CoRR},
  volume    = {abs/1709.00103},
}

@InProceedings{Criteria-to-SQL,
  author    = {Yu, Xiaojing  and  Chen, Tianlong  and  Yu, Zhengjie  and  Li, Huiyu  and  Yang, Yang  and  Jiang, Xiaoqian  and  Jiang, Anxiao},
  title     = {Dataset and Enhanced Model for Eligibility Criteria-to-SQL Semantic Parsing},
  booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
  month     = {May},
  year      = {2020},
  address   = {Marseille, France},
  publisher = {European Language Resources Association},
  pages     = {5831--5839},
}

@misc{zhang2023css,
  title     = {CSS: A Large-scale Cross-schema Chinese Text-to-SQL Medical Dataset}, 
  author    = {Hanchong Zhang and Jieyu Li and Lu Chen and Ruisheng Cao and Yunyan Zhang and Yu Huang and Yefeng Zheng and Kai Yu},
  year      = {2023},
}

@article{lee2022ehrsql,
  title     = {EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records},
  author    = {Lee, Gyubok and Hwang, Hyeonji and Bae, Seongsu and Kwon, Yeonsu and Shin, Woncheol and Yang, Seongjun and Seo, Minjoon and Kim, Jong-Yeup and Choi, Edward},
  journal   = {Advances in Neural Information Processing Systems},
  volume    = {35},
  pages     = {15589--15601},
  year      = {2022},
}

@inproceedings{lee-2021-kaggle-dbqa,
  title     = {KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers},
  author    = {Lee, Chia-Hsuan and Polozov, Oleksandr and Richardson, Matthew},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)},
  pages     = {2261--2273},
  year      = {2021},
}

@inproceedings{squall,
  title     = {On the Potential of Lexico-logical Alignments for Semantic Parsing to {SQL} Queries},
  author    = {Tianze Shi and Chen Zhao and Jordan Boyd-Graber and Hal {Daum\'{e} III} and Lillian Lee},
  booktitle = {Findings of EMNLP},
  year      = {2020},
}

@article{hazoom2021text,
  title     = {Text-to-SQL in the wild: a naturally-occurring dataset based on Stack exchange data},
  author    = {Hazoom, Moshe and Malik, Vibhor and Bogin, Ben},
  journal   = {arXiv preprint arXiv:2106.05006},
  year      = {2021},
}

@inproceedings{wang2020text,
  title     = {Text-to-SQL Generation for Question Answering on Electronic Medical Records},
  author    = {Wang, Ping and Shi, Tian and Reddy, Chandan K},
  booktitle = {Proceedings of The Web Conference 2020},
  pages     = {350--361},
  year      = {2020},
}

@inproceedings{nvBench_SIGMOD21,
  title     = {Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks},
  author    = {Yuyu Luo and Nan Tang and Guoliang Li and Chengliang Chai and Wenbo Li and Xuedi Qin},
  booktitle = {Proceedings of the 2021 International Conference on Management of Data, {SIGMOD} Conference 2021, June 20–25, 2021, Virtual Event, China},
  publisher = {ACM},
  year      = {2021},
}
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