NATURAL_LANG
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446
| SCHEMA
stringlengths 27
2.21k
| SQL
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453
| input_ids
list | attention_mask
list | labels
list |
|---|---|---|---|---|---|
What is the average number of losses for teams with 0 draws and 0 byes?
|
CREATE TABLE table_name_78 (losses INTEGER, draws VARCHAR, byes VARCHAR)
|
SELECT AVG(losses) FROM table_name_78 WHERE draws = 0 AND byes < 0
|
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What position did Rich Manning play?
|
CREATE TABLE table_44001 (
"Player" text,
"Nationality" text,
"Position" text,
"Years for Grizzlies" text,
"School/Club Team" text
)
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SELECT "Position" FROM table_44001 WHERE "Player" = 'rich manning'
|
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Which Seattle quarterback has more than 81 career wins and less than 70 team wins?
|
CREATE TABLE table_38682 (
"Rank" real,
"Quarterback" text,
"Seasons" text,
"Teams" text,
"Team Wins" real,
"Team Losses" real,
"Career Wins" real,
"Career Losses" real,
"Ties" real
)
|
SELECT "Quarterback" FROM table_38682 WHERE "Career Wins" > '81' AND "Teams" = 'seattle' AND "Team Wins" < '70'
|
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What is the year of the disc with a catalogue number mash02?
|
CREATE TABLE table_10360 (
"Catalogue Number" text,
"Artist" text,
"Tracks" text,
"Type" text,
"Year" real
)
|
SELECT "Year" FROM table_10360 WHERE "Catalogue Number" = 'mash02'
|
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On what date was the record 39–54?
|
CREATE TABLE table_name_69 (date VARCHAR, record VARCHAR)
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SELECT date FROM table_name_69 WHERE record = "39–54"
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What is the league goals when the league cup goals is less than 0 and 16 (1) league apps?
|
CREATE TABLE table_name_95 (league_goals INTEGER, league_apps VARCHAR, league_cup_goals VARCHAR)
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SELECT AVG(league_goals) FROM table_name_95 WHERE league_apps = "16 (1)" AND league_cup_goals < 0
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What was the fewest number of viewers for the episode production number of 109 5-22?
|
CREATE TABLE table_40566 (
"Episode number Production number" text,
"Title" text,
"Original airing" text,
"Rating" real,
"Share" real,
"18-49" real,
"Total viewers (in millions)" real,
"Rank per week" text
)
|
SELECT MIN("Total viewers (in millions)") FROM table_40566 WHERE "Episode number Production number" = '109 5-22'
|
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Which After 1 year has an After 3 years of 80%?
|
CREATE TABLE table_name_40 (after_1_year VARCHAR, after_3_years VARCHAR)
|
SELECT after_1_year FROM table_name_40 WHERE after_3_years = "80%"
|
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Which Description has a Year of Issue of 1983, and a Weight of 3.50grams?
|
CREATE TABLE table_34807 (
"Year of Issue" real,
"Description" text,
"Weight" text,
"Diameter" text,
"Thickness" text,
"Edge" text
)
|
SELECT "Description" FROM table_34807 WHERE "Year of Issue" = '1983' AND "Weight" = '3.50grams'
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how many patients whose gender is f and lab test name is o2 flow?
|
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE 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
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.gender = "F" AND lab.label = "O2 Flow"
|
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-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100
] |
Return a histogram on how many entrepreneurs correspond to each investor?
|
CREATE TABLE people (
People_ID int,
Name text,
Height real,
Weight real,
Date_of_Birth text
)
CREATE TABLE entrepreneur (
Entrepreneur_ID int,
People_ID int,
Company text,
Money_Requested real,
Investor text
)
|
SELECT Investor, COUNT(*) FROM entrepreneur GROUP BY Investor
|
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32103,
32102,
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4386,
6048,
332,
17098,
151,
41,
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[
3,
23143,
14196,
16873,
6,
2847,
17161,
599,
1935,
61,
21680,
3,
12290,
350,
4630,
6880,
272,
476,
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-100,
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-100,
-100,
-100
] |
Visualize a bar chart about the distribution of All_Neutral and ACC_Percent , and sort by the x-axis in asc.
|
CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
)
CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
|
SELECT All_Neutral, ACC_Percent FROM basketball_match ORDER BY All_Neutral
|
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What is the highest number of points before 1954?
|
CREATE TABLE table_name_5 (points INTEGER, year INTEGER)
|
SELECT MAX(points) FROM table_name_5 WHERE year < 1954
|
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Name the best actor for uncle boonmee who can recall his past lives
|
CREATE TABLE table_72658 (
"Year" text,
"Best Film" text,
"Best Director" text,
"Best Actor" text,
"Best Actress" text,
"Best Supporting Actor" text,
"Best Supporting Actress" text
)
|
SELECT "Best Actor" FROM table_72658 WHERE "Best Film" = 'Uncle Boonmee Who Can Recall His Past Lives'
|
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How many Drawn have an Against smaller than 5, and a Played smaller than 3?
|
CREATE TABLE table_name_38 (
drawn VARCHAR,
against VARCHAR,
played VARCHAR
)
|
SELECT COUNT(drawn) FROM table_name_38 WHERE against < 5 AND played < 3
|
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-100,
-100,
-100,
-100,
-100,
-100,
-100
] |
Find the major and age of students who do not have a cat pet.
|
CREATE TABLE student (stuid VARCHAR); CREATE TABLE has_pet (stuid VARCHAR, petid VARCHAR); CREATE TABLE pets (petid VARCHAR, pettype VARCHAR); CREATE TABLE student (major VARCHAR, age VARCHAR, stuid VARCHAR)
|
SELECT major, age FROM student WHERE NOT stuid IN (SELECT T1.stuid FROM student AS T1 JOIN has_pet AS T2 ON T1.stuid = T2.stuid JOIN pets AS T3 ON T3.petid = T2.petid WHERE T3.pettype = 'cat')
|
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What is the position of the player who went to college of notre dame?
|
CREATE TABLE table_53383 (
"Player" text,
"Position" text,
"School" text,
"Hometown" text,
"College" text
)
|
SELECT "Position" FROM table_53383 WHERE "College" = 'notre dame'
|
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In which of North Melbourne's away games was there the lowest crowd?
|
CREATE TABLE table_54314 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
)
|
SELECT MIN("Crowd") FROM table_54314 WHERE "Away team" = 'north melbourne'
|
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What is the Week # when the Beatles were the original artist and the theme was The Beatles?
|
CREATE TABLE table_name_18 (week__number VARCHAR, original_artist VARCHAR, theme VARCHAR)
|
SELECT week__number FROM table_name_18 WHERE original_artist = "the beatles" AND theme = "the beatles"
|
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What are the ids and names of the medicine that can interact with two or more enzymes?
|
CREATE TABLE medicine_enzyme_interaction (
medicine_id VARCHAR
)
CREATE TABLE medicine (
id VARCHAR,
Name VARCHAR
)
|
SELECT T1.id, T1.Name FROM medicine AS T1 JOIN medicine_enzyme_interaction AS T2 ON T2.medicine_id = T1.id GROUP BY T1.id HAVING COUNT(*) >= 2
|
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-100
] |
I want the displacement for version of db
|
CREATE TABLE table_name_28 (
displacement VARCHAR,
version VARCHAR
)
|
SELECT displacement FROM table_name_28 WHERE version = "db"
|
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what is the number of patients whose primary disease is morbid obesity/sda and year of death is less than or equal to 2174?
|
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "MORBID OBESITY/SDA" AND demographic.dod_year <= "2174.0"
|
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What was the result of the game in week 4?
|
CREATE TABLE table_name_32 (
result VARCHAR,
week VARCHAR
)
|
SELECT result FROM table_name_32 WHERE week = 4
|
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For those records from the products and each product's manufacturer, draw a bar chart about the distribution of name and revenue , and group by attribute name, rank from low to high by the y-axis.
|
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
)
|
SELECT T1.Name, T2.Revenue FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY T1.Name, T1.Name ORDER BY T2.Revenue
|
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What is the lost when the try bonus is 5, and points against is 298?
|
CREATE TABLE table_name_40 (lost VARCHAR, try_bonus VARCHAR, points_against VARCHAR)
|
SELECT lost FROM table_name_40 WHERE try_bonus = "5" AND points_against = "298"
|
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what is the total number of children born after 1675 ?
|
CREATE TABLE table_204_626 (
id number,
"image" number,
"name" text,
"birth date" text,
"death date" text,
"brief biography" text
)
|
SELECT COUNT("name") FROM table_204_626 WHERE "death date" > 1675
|
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What Canadian Championship has Ashtone Morgan Category:Articles with hcards as the name?
|
CREATE TABLE table_42018 (
"Name" text,
"Total" text,
"League" text,
"Canadian Championship" text,
"CONCACAF Champions League" text
)
|
SELECT "Canadian Championship" FROM table_42018 WHERE "Name" = 'ashtone morgan category:articles with hcards'
|
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Lowest larger than 288, and a Team of east stirlingshire has what lowest average?
|
CREATE TABLE table_34735 (
"Team" text,
"Stadium" text,
"Capacity" real,
"Highest" real,
"Lowest" real,
"Average" real
)
|
SELECT MIN("Average") FROM table_34735 WHERE "Lowest" > '288' AND "Team" = 'east stirlingshire'
|
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For those employees who did not have any job in the past, give me the comparison about the sum of department_id over the job_id , and group by attribute job_id, and show by the X-axis in ascending.
|
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
|
SELECT JOB_ID, SUM(DEPARTMENT_ID) FROM employees WHERE NOT EMPLOYEE_ID IN (SELECT EMPLOYEE_ID FROM job_history) GROUP BY JOB_ID ORDER BY JOB_ID
|
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1
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-100,
-100
] |
What are the statuses and average populations of each city. Plot them as bar chart.
|
CREATE TABLE competition_record (
Competition_ID int,
Farm_ID int,
Rank int
)
CREATE TABLE farm (
Farm_ID int,
Year int,
Total_Horses real,
Working_Horses real,
Total_Cattle real,
Oxen real,
Bulls real,
Cows real,
Pigs real,
Sheep_and_Goats real
)
CREATE TABLE city (
City_ID int,
Official_Name text,
Status text,
Area_km_2 real,
Population real,
Census_Ranking text
)
CREATE TABLE farm_competition (
Competition_ID int,
Year int,
Theme text,
Host_city_ID int,
Hosts text
)
|
SELECT Status, AVG(Population) FROM city GROUP BY Status
|
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minors ( less than 18 years of age )
|
CREATE TABLE table_train_68 (
"id" int,
"sequential_organ_failure_assessment_sofa" int,
"pregnancy_or_lactation" bool,
"piro_predispose_infection_response_organ_dysfunction_score" int,
"systolic_blood_pressure_sbp" int,
"hypotension" bool,
"age" float,
"lactate" int,
"NOUSE" float
)
|
SELECT * FROM table_train_68 WHERE age < 18
|
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count the number of patients whose primary disease is pneumonia?
|
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
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
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "PNEUMONIA"
|
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Show all track names that have had no races.
|
CREATE TABLE race (
race_id number,
name text,
class text,
date text,
track_id text
)
CREATE TABLE track (
track_id number,
name text,
location text,
seating number,
year_opened number
)
|
SELECT name FROM track WHERE NOT track_id IN (SELECT track_id FROM race)
|
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Who, was the coach with an actual adjusted record of 0 19?
|
CREATE TABLE table_33477 (
"Season" real,
"Coach" text,
"Record as played" text,
"Actual adjusted record" text,
"Regular season Vacated" text
)
|
SELECT "Coach" FROM table_33477 WHERE "Actual adjusted record" = '0–19'
|
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How many points occurred with a difference of 2 for position less than 4?
|
CREATE TABLE table_name_90 (
points VARCHAR,
difference VARCHAR,
position VARCHAR
)
|
SELECT COUNT(points) FROM table_name_90 WHERE difference = "2" AND position < 4
|
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What is the average laps for ralph firman with a grid of over 19?
|
CREATE TABLE table_55653 (
"Driver" text,
"Constructor" text,
"Laps" real,
"Time/Retired" text,
"Grid" real
)
|
SELECT AVG("Laps") FROM table_55653 WHERE "Driver" = 'ralph firman' AND "Grid" > '19'
|
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What are the first name and major of the students who are able to consume soy?
|
CREATE TABLE allergy_type (
allergy text,
allergytype text
)
CREATE TABLE student (
stuid number,
lname text,
fname text,
age number,
sex text,
major number,
advisor number,
city_code text
)
CREATE TABLE has_allergy (
stuid number,
allergy text
)
|
SELECT fname, major FROM student WHERE NOT stuid IN (SELECT stuid FROM has_allergy WHERE allergy = "Soy")
|
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Name the total number of pitcher for 9 overall rank
|
CREATE TABLE table_26720 (
"Pitcher" text,
"Strikeouts" real,
"Season" real,
"Team" text,
"League" text,
"Overall Rank" real
)
|
SELECT COUNT("Pitcher") FROM table_26720 WHERE "Overall Rank" = '9'
|
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Who was the candidate in the election in the Tennessee 9 district?
|
CREATE TABLE table_1342233_42 (candidates VARCHAR, district VARCHAR)
|
SELECT candidates FROM table_1342233_42 WHERE district = "Tennessee 9"
|
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Find the number and averaged salary of all instructors who are in the department with the highest budget.
|
CREATE TABLE department (
dept_name VARCHAR,
budget VARCHAR
)
CREATE TABLE instructor (
salary INTEGER,
dept_name VARCHAR
)
|
SELECT AVG(T1.salary), COUNT(*) FROM instructor AS T1 JOIN department AS T2 ON T1.dept_name = T2.dept_name ORDER BY T2.budget DESC LIMIT 1
|
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What percent did LINKE get in Tyrol?
|
CREATE TABLE table_name_99 (linke VARCHAR, state VARCHAR)
|
SELECT linke FROM table_name_99 WHERE state = "tyrol"
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What is Dates Administered, when Democrat: Carl Levin is 61%?
|
CREATE TABLE table_44561 (
"Poll Source" text,
"Dates administered" text,
"Democrat: Carl Levin" text,
"Republican: Jack Hoogendyk" text,
"Lead Margin" real
)
|
SELECT "Dates administered" FROM table_44561 WHERE "Democrat: Carl Levin" = '61%'
|
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Which Against has a Peel of waroona, and a Byes larger than 0?
|
CREATE TABLE table_name_55 (
against INTEGER,
peel VARCHAR,
byes VARCHAR
)
|
SELECT MAX(against) FROM table_name_55 WHERE peel = "waroona" AND byes > 0
|
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Find All_Home and Team_ID , and group by attribute ACC_Road, and visualize them by a bar chart, and I want to show total number from high to low order please.
|
CREATE TABLE basketball_match (
Team_ID int,
School_ID int,
Team_Name text,
ACC_Regular_Season text,
ACC_Percent text,
ACC_Home text,
ACC_Road text,
All_Games text,
All_Games_Percent int,
All_Home text,
All_Road text,
All_Neutral text
)
CREATE TABLE university (
School_ID int,
School text,
Location text,
Founded real,
Affiliation text,
Enrollment real,
Nickname text,
Primary_conference text
)
|
SELECT All_Home, Team_ID FROM basketball_match GROUP BY ACC_Road, All_Home ORDER BY Team_ID DESC
|
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What is the Average of bergen, norway?
|
CREATE TABLE table_name_81 (average INTEGER, city VARCHAR)
|
SELECT MIN(average) FROM table_name_81 WHERE city = "bergen, norway"
|
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Which round was 2:30?
|
CREATE TABLE table_38546 (
"Res." text,
"Record" text,
"Opponent" text,
"Method" text,
"Event" text,
"Round" text,
"Time" text,
"Location" text
)
|
SELECT "Round" FROM table_38546 WHERE "Time" = '2:30'
|
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] |
what is the difference between the number of games won and the number of games lost ?
|
CREATE TABLE table_204_523 (
id number,
"week" number,
"date" text,
"opponent" text,
"score" text,
"result" text,
"attendance" number,
"record" text
)
|
SELECT ABS((SELECT COUNT(*) FROM table_204_523 WHERE "result" = 'win') - (SELECT COUNT(*) FROM table_204_523 WHERE "result" = 'loss'))
|
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Who was the First Baseman when the Shortstop was zoilo versalles?
|
CREATE TABLE table_name_53 (
first_baseman VARCHAR,
shortstop VARCHAR
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|
SELECT first_baseman FROM table_name_53 WHERE shortstop = "zoilo versalles"
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Which Report is on 1 june?
|
CREATE TABLE table_name_13 (
report VARCHAR,
date VARCHAR
)
|
SELECT report FROM table_name_13 WHERE date = "1 june"
|
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For all employees who have the letters D or S in their first name, a line chart shows the trend of salary over hire_date , and rank from high to low by the x axis.
|
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE 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 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 jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
|
SELECT HIRE_DATE, SALARY FROM employees WHERE FIRST_NAME LIKE '%D%' OR FIRST_NAME LIKE '%S%' ORDER BY HIRE_DATE DESC
|
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Which players college was Baylor?
|
CREATE TABLE table_53331 (
"Player" text,
"Height" text,
"School" text,
"Hometown" text,
"College" text,
"NBA Draft" text
)
|
SELECT "Player" FROM table_53331 WHERE "College" = 'baylor'
|
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What rank has less than 22 wins
|
CREATE TABLE table_name_88 (
rank VARCHAR,
wins INTEGER
)
|
SELECT COUNT(rank) FROM table_name_88 WHERE wins < 22
|
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What is the method when the opponent is Andre Roberts?
|
CREATE TABLE table_name_34 (
method VARCHAR,
opponent VARCHAR
)
|
SELECT method FROM table_name_34 WHERE opponent = "andre roberts"
|
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] |
give the number of patients who passed away in or before the year 2154 had femoral artery thrombosis.
|
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 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
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic WHERE demographic.diagnosis = "FEMORAL ARTERY THROMBOSIS" AND demographic.dod_year <= "2154.0"
|
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What Inclination has Eccentricity of 0.06 +0.06 −0.11?
|
CREATE TABLE table_name_81 (inclination VARCHAR, eccentricity VARCHAR)
|
SELECT inclination FROM table_name_81 WHERE eccentricity = "0.06 +0.06 −0.11"
|
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What original title has a year of 1978?
|
CREATE TABLE table_68614 (
"Year" text,
"English title" text,
"Original title" text,
"Country" text,
"Director" text
)
|
SELECT "Original title" FROM table_68614 WHERE "Year" = '1978'
|
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What is the goal difference when there are fewer than 12 wins, 32 goals against and 8 draws?
|
CREATE TABLE table_name_3 (
goal_difference INTEGER,
wins VARCHAR,
draws VARCHAR,
goals_against VARCHAR
)
|
SELECT SUM(goal_difference) FROM table_name_3 WHERE draws = 8 AND goals_against = 32 AND wins < 12
|
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What stadium was the Fiesta Bowl played at?
|
CREATE TABLE table_name_74 (stadium VARCHAR, bowl_game VARCHAR)
|
SELECT stadium FROM table_name_74 WHERE bowl_game = "fiesta bowl"
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-100
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What average game was held on february 24 and has an attendance smaller than 16,541?
|
CREATE TABLE table_name_7 (game INTEGER, date VARCHAR, attendance VARCHAR)
|
SELECT AVG(game) FROM table_name_7 WHERE date = "february 24" AND attendance < 16 OFFSET 541
|
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How many players named Dean Kirkland were picked
|
CREATE TABLE table_1227 (
"Round #" real,
"Pick #" real,
"Player" text,
"Position" text,
"College" text
)
|
SELECT COUNT("Pick #") FROM table_1227 WHERE "Player" = 'Dean Kirkland'
|
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What was the location when the opposition was East Coast?
|
CREATE TABLE table_26847237_1 (location VARCHAR, opposition VARCHAR)
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SELECT location FROM table_26847237_1 WHERE opposition = "East Coast"
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What is the home team of the game with tie number 34?
|
CREATE TABLE table_name_76 (home_team VARCHAR, tie_no VARCHAR)
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SELECT home_team FROM table_name_76 WHERE tie_no = "34"
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what is the total number of total w l where doubles w l is 11 11
|
CREATE TABLE table_30 (
"Player" text,
"Total W\u2013L" text,
"Singles W\u2013L" text,
"Doubles W\u2013L" text,
"Ties played" real,
"Debut" real,
"Years played" real
)
|
SELECT COUNT("Total W\u2013L") FROM table_30 WHERE "Doubles W\u2013L" = '11–11'
|
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Who was replaced on 11 July?
|
CREATE TABLE table_17327458_1 (replaced_by VARCHAR, date_of_appointment VARCHAR)
|
SELECT replaced_by FROM table_17327458_1 WHERE date_of_appointment = "11 July"
|
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Which of the second parties has second member Charles Robert Colvile, a conservative first party, and first member William Mundy?
|
CREATE TABLE table_name_31 (second_party VARCHAR, first_member VARCHAR, second_member VARCHAR, first_party VARCHAR)
|
SELECT second_party FROM table_name_31 WHERE second_member = "charles robert colvile" AND first_party = "conservative" AND first_member = "william mundy"
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What is the production code fore the episode titled, life's no fun anymore?
|
CREATE TABLE table_7465 (
"Ep No" text,
"Prod Code" text,
"Original Air Date" text,
"Episode Title" text,
"Ratings" text
)
|
SELECT "Prod Code" FROM table_7465 WHERE "Episode Title" = 'life''s no fun anymore'
|
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What is every year born for height of 1.88?
|
CREATE TABLE table_23670057_7 (
year_born VARCHAR,
height__m_ VARCHAR
)
|
SELECT year_born FROM table_23670057_7 WHERE height__m_ = "1.88"
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What was the original air date for the episode with 3.90 u.s. viewers (millions)?
|
CREATE TABLE table_12722302_2 (
original_air_date VARCHAR,
us_viewers__million_ VARCHAR
)
|
SELECT original_air_date FROM table_12722302_2 WHERE us_viewers__million_ = "3.90"
|
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What was the crowd size when the home team scored 10.10 (70)?
|
CREATE TABLE table_32868 (
"Home team" text,
"Home team score" text,
"Away team" text,
"Away team score" text,
"Venue" text,
"Crowd" real,
"Date" text
)
|
SELECT "Crowd" FROM table_32868 WHERE "Home team score" = '10.10 (70)'
|
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Name the date for game site of riverfront stadium
|
CREATE TABLE table_name_31 (
date VARCHAR,
game_site VARCHAR
)
|
SELECT date FROM table_name_31 WHERE game_site = "riverfront stadium"
|
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Name the points for games of 16 16
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CREATE TABLE table_name_43 (points VARCHAR, games VARCHAR)
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SELECT points FROM table_name_43 WHERE games = "16 16"
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Who was the home team on January 2 with 23 points?
|
CREATE TABLE table_name_57 (
home VARCHAR,
points VARCHAR,
date VARCHAR
)
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SELECT home FROM table_name_57 WHERE points = 23 AND date = "january 2"
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how many patients of white ethnicity are diagnosed with hx of bladder malignancy?
|
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
CREATE TABLE demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE diagnoses (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
CREATE TABLE procedures (
subject_id text,
hadm_id text,
icd9_code text,
short_title text,
long_title text
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.ethnicity = "WHITE" AND diagnoses.short_title = "Hx of bladder malignancy"
|
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What is the latest year for first elected with john hostettler as incumbent and a result of lost re-election democratic gain?
|
CREATE TABLE table_name_40 (first_elected INTEGER, results VARCHAR, incumbent VARCHAR)
|
SELECT MAX(first_elected) FROM table_name_40 WHERE results = "lost re-election democratic gain" AND incumbent = "john hostettler"
|
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how many nations won more than one silver medal ?
|
CREATE TABLE table_204_595 (
id number,
"rank" number,
"nation" text,
"gold" number,
"silver" number,
"bronze" number,
"total" number
)
|
SELECT COUNT("nation") FROM table_204_595 WHERE "silver" > 1
|
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For those employees who do not work in departments with managers that have ids between 100 and 200, return a line chart about the change of salary over hire_date , and show in descending by the x axis.
|
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE jobs (
JOB_ID varchar(10),
JOB_TITLE varchar(35),
MIN_SALARY decimal(6,0),
MAX_SALARY decimal(6,0)
)
CREATE TABLE departments (
DEPARTMENT_ID decimal(4,0),
DEPARTMENT_NAME varchar(30),
MANAGER_ID decimal(6,0),
LOCATION_ID decimal(4,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
|
SELECT HIRE_DATE, SALARY FROM employees WHERE NOT DEPARTMENT_ID IN (SELECT DEPARTMENT_ID FROM departments WHERE MANAGER_ID BETWEEN 100 AND 200) ORDER BY HIRE_DATE DESC
|
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what is the maximum lead margin on august 5, 2008?
|
CREATE TABLE table_16751596_5 (
lead_margin INTEGER,
dates_administered VARCHAR
)
|
SELECT MAX(lead_margin) FROM table_16751596_5 WHERE dates_administered = "August 5, 2008"
|
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WHAT IS THE SNATCH WITH TOTAL KG SMALLER THAN 318, AND CLEAN JERK LARGER THAN 175?
|
CREATE TABLE table_name_45 (
snatch INTEGER,
total__kg_ VARCHAR,
clean_ VARCHAR,
_jerk VARCHAR
)
|
SELECT MIN(snatch) FROM table_name_45 WHERE total__kg_ < 318 AND clean_ & _jerk > 175
|
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] |
Which Bleeding has a Condition of congenital afibrinogenemia?
|
CREATE TABLE table_76036 (
"Condition" text,
"Prothrombin time" text,
"Partial thromboplastin time" text,
"Bleeding time" text,
"Platelet count" text
)
|
SELECT "Bleeding time" FROM table_76036 WHERE "Condition" = 'congenital afibrinogenemia'
|
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] |
How many places of whatever size have a 2007 population estimation of 7996?
|
CREATE TABLE table_14325808_1 (area__km²_ VARCHAR, population__2007_estimation_ VARCHAR)
|
SELECT COUNT(area__km²_) FROM table_14325808_1 WHERE population__2007_estimation_ = 7996
|
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What is Wayne Grady's total?
|
CREATE TABLE table_60665 (
"Player" text,
"Country" text,
"Year(s) won" text,
"Total" real,
"To par" text,
"Finish" text
)
|
SELECT SUM("Total") FROM table_60665 WHERE "Player" = 'wayne grady'
|
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What is the host city during the 2012 season?
|
CREATE TABLE table_name_47 (host_city VARCHAR, season VARCHAR)
|
SELECT host_city FROM table_name_47 WHERE season = 2012
|
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Which Poles has a Wins larger than 0, and a Podiums smaller than 17?
|
CREATE TABLE table_5462 (
"Season" text,
"Races" real,
"Wins" real,
"Podiums" real,
"Poles" real,
"Fastest Laps" real
)
|
SELECT "Poles" FROM table_5462 WHERE "Wins" > '0' AND "Podiums" < '17' AND "Fastest Laps" = '0'
|
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-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
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-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100
] |
For those records from the products and each product's manufacturer, return a bar chart about the distribution of name and code , and group by attribute headquarter, show bar from low to high order.
|
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
)
|
SELECT T1.Name, T1.Code FROM Products AS T1 JOIN Manufacturers AS T2 ON T1.Manufacturer = T2.Code GROUP BY Headquarter, T1.Name ORDER BY T1.Name
|
[
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
7554,
41,
3636,
3,
21342,
17966,
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5570,
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3,
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32103,
242,
273,
3187,
45,
8,
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11,
284,
556,
31,
7,
4818,
6,
1205,
3,
9,
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81,
8,
3438,
13,
564,
11,
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3,
6,
11,
563,
57,
15816,
819,
19973,
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504,
1207,
45,
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306,
455,
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] |
[
3,
23143,
14196,
332,
5411,
23954,
6,
332,
5411,
22737,
21680,
7554,
6157,
332,
536,
3,
15355,
3162,
15248,
7,
6157,
332,
357,
9191,
332,
5411,
7296,
76,
8717,
450,
49,
3274,
332,
4416,
22737,
350,
4630,
6880,
272,
476,
3642,
19973,
6,
332,
5411,
23954,
4674,
11300,
272,
476,
332,
5411,
23954,
1,
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-100,
-100,
-100,
-100
] |
display job Title, the difference between minimum and maximum salaries for those jobs which max salary within the range 12000 to 18000.
|
CREATE TABLE jobs (
job_title VARCHAR,
max_salary INTEGER,
min_salary VARCHAR
)
|
SELECT job_title, max_salary - min_salary FROM jobs WHERE max_salary BETWEEN 12000 AND 18000
|
[
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
2476,
41,
613,
834,
21869,
584,
4280,
28027,
6,
9858,
834,
7,
138,
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3,
21342,
17966,
6,
3519,
834,
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1208,
584,
4280,
28027,
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61,
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32103,
32101,
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613,
11029,
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344,
2559,
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21331,
21,
273,
2476,
84,
9858,
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441,
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620,
586,
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what is the number of patients whose gender is m and diagnoses icd9 code is 25002?
|
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 demographic (
subject_id text,
hadm_id text,
name text,
marital_status text,
age text,
dob text,
gender text,
language text,
religion text,
admission_type text,
days_stay text,
insurance text,
ethnicity text,
expire_flag text,
admission_location text,
discharge_location text,
diagnosis text,
dod text,
dob_year text,
dod_year text,
admittime text,
dischtime text,
admityear text
)
CREATE TABLE prescriptions (
subject_id text,
hadm_id text,
icustay_id text,
drug_type text,
drug text,
formulary_drug_cd text,
route text,
drug_dose text
)
CREATE TABLE lab (
subject_id text,
hadm_id text,
itemid text,
charttime text,
flag text,
value_unit text,
label text,
fluid text
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN diagnoses ON demographic.hadm_id = diagnoses.hadm_id WHERE demographic.gender = "M" AND diagnoses.icd9_code = "25002"
|
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] |
Which venue has a scoreof 2–0?
|
CREATE TABLE table_name_60 (venue VARCHAR, score VARCHAR)
|
SELECT venue FROM table_name_60 WHERE score = "2–0"
|
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What nationality is keith carney?
|
CREATE TABLE table_2897457_5 (
nationality VARCHAR,
player VARCHAR
)
|
SELECT nationality FROM table_2897457_5 WHERE player = "Keith Carney"
|
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834,
755,
549,
17444,
427,
1959,
3274,
96,
439,
15,
23,
189,
1184,
3186,
121,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
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-100,
-100,
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-100,
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-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100
] |
Show the number of fate from each fate
|
CREATE TABLE ship (
Ship_ID int,
Name text,
Type text,
Nationality text,
Tonnage int
)
CREATE TABLE mission (
Mission_ID int,
Ship_ID int,
Code text,
Launched_Year int,
Location text,
Speed_knots int,
Fate text
)
|
SELECT Fate, COUNT(Fate) FROM mission GROUP BY Fate
|
[
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
4383,
41,
15508,
834,
4309,
16,
17,
6,
5570,
1499,
6,
6632,
1499,
6,
868,
485,
1499,
6,
8475,
9761,
16,
17,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
2253,
41,
8960,
834,
4309,
16,
17,
6,
15508,
834,
4309,
16,
17,
6,
3636,
1499,
6,
17113,
15,
26,
834,
476,
2741,
16,
17,
6,
10450,
1499,
6,
9913,
834,
157,
2264,
7,
16,
17,
6,
11762,
15,
1499,
3,
61,
3,
32102,
32103,
32101,
32103,
3111,
8,
381,
13,
15126,
45,
284,
15126,
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] |
[
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
1,
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1,
1,
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] |
[
3,
23143,
14196,
11762,
15,
6,
2847,
17161,
599,
371,
342,
61,
21680,
2253,
350,
4630,
6880,
272,
476,
11762,
15,
1,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
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-100,
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-100,
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-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100,
-100
] |
For all employees who have the letters D or S in their first name, find job_id and the average of manager_id , and group by attribute job_id, and visualize them by a bar chart.
|
CREATE TABLE employees (
EMPLOYEE_ID decimal(6,0),
FIRST_NAME varchar(20),
LAST_NAME varchar(25),
EMAIL varchar(25),
PHONE_NUMBER varchar(20),
HIRE_DATE date,
JOB_ID varchar(10),
SALARY decimal(8,2),
COMMISSION_PCT decimal(2,2),
MANAGER_ID decimal(6,0),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE job_history (
EMPLOYEE_ID decimal(6,0),
START_DATE date,
END_DATE date,
JOB_ID varchar(10),
DEPARTMENT_ID decimal(4,0)
)
CREATE TABLE 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 countries (
COUNTRY_ID varchar(2),
COUNTRY_NAME varchar(40),
REGION_ID decimal(10,0)
)
CREATE TABLE locations (
LOCATION_ID decimal(4,0),
STREET_ADDRESS varchar(40),
POSTAL_CODE varchar(12),
CITY varchar(30),
STATE_PROVINCE varchar(25),
COUNTRY_ID varchar(2)
)
CREATE TABLE regions (
REGION_ID decimal(5,0),
REGION_NAME varchar(25)
)
|
SELECT JOB_ID, AVG(MANAGER_ID) FROM employees WHERE FIRST_NAME LIKE '%D%' OR FIRST_NAME LIKE '%S%' GROUP BY JOB_ID
|
[
32100,
32103,
32102,
205,
4386,
6048,
332,
17098,
1652,
41,
262,
5244,
5017,
476,
5080,
834,
4309,
7908,
1982,
599,
11071,
632,
201,
30085,
834,
567,
17683,
3,
4331,
4059,
599,
1755,
201,
301,
12510,
834,
567,
17683,
3,
4331,
4059,
599,
1828,
201,
3,
20211,
3502,
3,
4331,
4059,
599,
1828,
201,
3,
8023,
7894,
834,
567,
6122,
12920,
3,
4331,
4059,
599,
1755,
201,
454,
14132,
834,
308,
6048,
833,
6,
446,
10539,
834,
4309,
3,
4331,
4059,
599,
16968,
6,
180,
4090,
24721,
7908,
1982,
599,
11864,
7318,
6,
3,
6657,
329,
16994,
9215,
834,
4051,
382,
7908,
1982,
599,
4482,
7318,
6,
283,
15610,
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834,
4309,
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599,
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61,
3,
61,
3,
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32103,
32102,
205,
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6048,
332,
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613,
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10193,
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41,
262,
5244,
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632,
201,
5097,
8241,
834,
308,
6048,
833,
6,
3,
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834,
308,
6048,
833,
6,
446,
10539,
834,
4309,
3,
4331,
4059,
599,
16968,
6,
3396,
19846,
11810,
834,
4309,
7908,
1982,
599,
8525,
632,
61,
3,
61,
3,
32102,
32103,
32102,
205,
4386,
6048,
332,
17098,
2476,
41,
446,
10539,
834,
4309,
3,
4331,
4059,
599,
16968,
6,
446,
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382,
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3765,
3,
4331,
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201,
3,
17684,
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24721,
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4,
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599,
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632,
61,
3,
61,
3,
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32103,
32102,
205,
4386,
6048,
332,
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10521,
41,
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3396,
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3,
61,
3,
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41,
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3,
4331,
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3,
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3,
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3,
61,
3,
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32102,
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599,
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632,
201,
4083,
517,
9215,
834,
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What's the highest attendance for a game the Texan's played at Arrowhead Stadium?
|
CREATE TABLE table_name_87 (
attendance INTEGER,
game_site VARCHAR
)
|
SELECT MAX(attendance) FROM table_name_87 WHERE game_site = "arrowhead stadium"
|
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What was the callsign in Zamboanga?
|
CREATE TABLE table_12547903_3 (callsign VARCHAR, location VARCHAR)
|
SELECT callsign FROM table_12547903_3 WHERE location = "Zamboanga"
|
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Who is the center position of Years for Jazz, Greg Ostertag?
|
CREATE TABLE table_52031 (
"Player" text,
"Nationality" text,
"Position" text,
"Years for Jazz" text,
"School/Club Team" text
)
|
SELECT "Years for Jazz" FROM table_52031 WHERE "Position" = 'center' AND "Player" = 'greg ostertag'
|
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what is the production in 2010 with rank of 8?
|
CREATE TABLE table_67332 (
"Rank" text,
"Country" text,
"2009" text,
"2010" text,
"2011" text
)
|
SELECT "2010" FROM table_67332 WHERE "Rank" = '8'
|
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What is the home record for the Maccabi Tel-Aviv club?
|
CREATE TABLE table_name_85 (home VARCHAR, club VARCHAR)
|
SELECT home FROM table_name_85 WHERE club = "maccabi tel-aviv"
|
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provide the number of patients whose admission location is phys referral/normal deli and lab test item id is 51379.
|
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
)
|
SELECT COUNT(DISTINCT demographic.subject_id) FROM demographic INNER JOIN lab ON demographic.hadm_id = lab.hadm_id WHERE demographic.admission_location = "PHYS REFERRAL/NORMAL DELI" AND lab.itemid = "51379"
|
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What is the date that has a winning score of 67-70-68-67=272?
|
CREATE TABLE table_name_84 (
date VARCHAR,
winning_score VARCHAR
)
|
SELECT date FROM table_name_84 WHERE winning_score = 67 - 70 - 68 - 67 = 272
|
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Show all party names and the number of members in each party with a bar chart, and rank in desc by the y-axis.
|
CREATE TABLE party_events (
Event_ID int,
Event_Name text,
Party_ID int,
Member_in_charge_ID int
)
CREATE TABLE member (
Member_ID int,
Member_Name text,
Party_ID text,
In_office text
)
CREATE TABLE party (
Party_ID int,
Minister text,
Took_office text,
Left_office text,
Region_ID int,
Party_name text
)
CREATE TABLE region (
Region_ID int,
Region_name text,
Date text,
Label text,
Format text,
Catalogue text
)
|
SELECT Party_name, COUNT(*) FROM member AS T1 JOIN party AS T2 ON T1.Party_ID = T2.Party_ID GROUP BY T1.Party_ID ORDER BY COUNT(*) DESC
|
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What is the largest week number for the venue of League Park for the date of November 25, 1920?
|
CREATE TABLE table_36833 (
"Week" real,
"Date" text,
"Opponent" text,
"Result" text,
"Venue" text,
"Attendance" text,
"Record" text
)
|
SELECT MAX("Week") FROM table_36833 WHERE "Venue" = 'league park' AND "Date" = 'november 25, 1920'
|
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Name the most goals with losses less than 15 and position more than 8 with points of 42+4
|
CREATE TABLE table_71415 (
"Position" real,
"Club" text,
"Played" real,
"Points" text,
"Wins" real,
"Draws" real,
"Losses" real,
"Goals for" real,
"Goals against" real,
"Goal Difference" real
)
|
SELECT MAX("Goals for") FROM table_71415 WHERE "Losses" < '15' AND "Position" > '8' AND "Points" = '42+4'
|
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