context
stringlengths 11
9.12k
| question
stringlengths 0
1.06k
| SQL
stringlengths 2
4.44k
| source
stringclasses 28
values |
|---|---|---|---|
CREATE TABLE if not exists smart_contracts (id INT PRIMARY KEY, name TEXT, language TEXT, version TEXT); INSERT INTO smart_contracts (id, name, language, version) VALUES (1, 'CryptoKitties', 'Solidity', '0.4.24');
|
Insert a new row in the smart_contracts table with name 'Sushiswap' if it doesn't exist.
|
INSERT INTO smart_contracts (name, language, version) SELECT 'Sushiswap', 'Vyper', '0.3.0' WHERE NOT EXISTS (SELECT * FROM smart_contracts WHERE name = 'Sushiswap');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE financial_institutions (institution_id INT, institution_name TEXT); INSERT INTO financial_institutions (institution_id, institution_name) VALUES (1, 'GreenBank Europe'), (2, 'FairFinance Europe'), (3, 'EthicalBank Europe'); CREATE TABLE loans (loan_id INT, institution_id INT, loan_type TEXT); INSERT INTO loans (loan_id, institution_id, loan_type) VALUES (1, 1, 'socially responsible'), (2, 1, 'conventional'), (3, 2, 'socially responsible'), (4, 2, 'socially responsible'), (5, 3, 'conventional');
|
How many socially responsible loans were issued by financial institutions in Europe?
|
SELECT COUNT(*) FROM loans WHERE loan_type = 'socially responsible' AND institution_id IN (SELECT institution_id FROM financial_institutions WHERE institution_name LIKE '%Europe%');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE FacultyDemographics (id INT, name VARCHAR(255), rank VARCHAR(255), department VARCHAR(255), gender VARCHAR(10));
|
Determine the percentage of female and male faculty members in the College of Business and Management, for each rank, and order the results by rank.
|
SELECT rank, gender, COUNT(*) as count, ROUND(COUNT(*) * 100.0 / SUM(COUNT(*)) OVER (PARTITION BY rank), 2) as percentage FROM FacultyDemographics WHERE department LIKE 'Business%' GROUP BY rank, gender ORDER BY rank;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE producers (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255), production_volume INT);
|
List producers with a production volume greater than 1500
|
SELECT name FROM producers WHERE production_volume > (SELECT 1500);
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE transactions (id INT, supplier VARCHAR(50), Dysprosium_sold FLOAT, revenue FLOAT, datetime DATETIME); INSERT INTO transactions (id, supplier, Dysprosium_sold, revenue, datetime) VALUES (1, 'China National Nuke', 150.0, 2500.0, '2019-01-01 10:00:00'), (2, 'Korea Resource', 200.0, 3000.0, '2019-01-15 14:30:00');
|
Calculate the number of transactions and total revenue from Dysprosium sales by each supplier in Asia, for 2019.
|
SELECT supplier, COUNT(DISTINCT id) AS transactions, SUM(revenue) AS total_revenue FROM transactions WHERE YEAR(datetime) = 2019 AND supplier LIKE 'Asia%' GROUP BY supplier;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE field_production (field VARCHAR(50), year INT, oil_production FLOAT, gas_production FLOAT); INSERT INTO field_production (field, year, oil_production, gas_production) VALUES ('Girassol', 2019, 1234.5, 678.9);
|
What are the production figures for the 'Girassol' field for the year 2019?
|
SELECT year, oil_production, gas_production FROM field_production WHERE field = 'Girassol';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE EventAttendance (event_name VARCHAR(255), attendee_age INT, attendee_gender VARCHAR(50)); INSERT INTO EventAttendance (event_name, attendee_age, attendee_gender) VALUES ('Theater for All', 30, 'Male'), ('Theater for All', 40, 'Female'), ('Theater for All', 45, 'Non-binary'), ('Music for Everyone', 22, 'Male'), ('Music for Everyone', 27, 'Female'), ('Music for Everyone', 32, 'Non-binary');
|
What is the average age of attendees who attended 'Theater for All' and 'Music for Everyone' events?
|
SELECT AVG(attendee_age) FROM EventAttendance WHERE event_name IN ('Theater for All', 'Music for Everyone');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE initiative (id INT, name TEXT, location TEXT, economic_diversification_impact INT); INSERT INTO initiative (id, name, location, economic_diversification_impact) VALUES (1, 'Handicraft Training', 'Bangladesh', 50), (2, 'Agricultural Training', 'Pakistan', 70), (3, 'IT Training', 'Nepal', 90), (4, 'Fishery Training', 'Sri Lanka', 60);
|
Which community development initiatives have the lowest and highest economic diversification impact?
|
SELECT name, economic_diversification_impact FROM (SELECT name, economic_diversification_impact, RANK() OVER (ORDER BY economic_diversification_impact ASC) as low_rank, RANK() OVER (ORDER BY economic_diversification_impact DESC) as high_rank FROM initiative) sub WHERE low_rank = 1 OR high_rank = 1;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE climate_mitigation_projects ( id INT, name VARCHAR(255), location VARCHAR(255), funding FLOAT ); INSERT INTO climate_mitigation_projects (id, name, location, funding) VALUES (1, 'Project A', 'Brazil', 5000000);
|
What are the details of projects that have received funding for climate change mitigation in Brazil?
|
SELECT * FROM climate_mitigation_projects WHERE location = 'Brazil';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE energy_storage (id INT, name TEXT, capacity FLOAT, region TEXT); INSERT INTO energy_storage (id, name, capacity, region) VALUES (4, 'GHI Battery', 4000, 'East');
|
Delete the energy storage system with id 4 if it exists.
|
DELETE FROM energy_storage WHERE id = 4;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE socially_responsible_lending (lender_name TEXT, total_loans_issued NUMERIC, country TEXT); INSERT INTO socially_responsible_lending (lender_name, total_loans_issued, country) VALUES ('Amalgamated Bank', 3456, 'USA'); INSERT INTO socially_responsible_lending (lender_name, total_loans_issued, country) VALUES ('Beneficial State Bank', 2678, 'USA');
|
List the top 5 socially responsible lenders in the US by total loans issued?
|
SELECT lender_name, total_loans_issued FROM socially_responsible_lending WHERE country = 'USA' ORDER BY total_loans_issued DESC LIMIT 5;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE FlightSafety(id INT, aircraft_id INT, manufacturer VARCHAR(255), flight_hours INT); INSERT INTO FlightSafety(id, aircraft_id, manufacturer, flight_hours) VALUES (1, 1001, 'Boeing', 12000), (2, 1002, 'Airbus', 10500), (3, 1003, 'Boeing', 18000), (4, 1004, 'Airbus', 12000), (5, 1005, 'Airbus', 11000);
|
What is the minimum flight hours for aircrafts manufactured by Airbus?
|
SELECT MIN(flight_hours) FROM FlightSafety WHERE manufacturer = 'Airbus';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE passenger_counts (station VARCHAR(255), passenger_count INT);
|
List the stations with a passenger count greater than 1000, based on the 'passenger_counts' table.
|
SELECT station FROM passenger_counts WHERE passenger_count > 1000;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE tours (id INT, name TEXT, country TEXT, co2_emission FLOAT); INSERT INTO tours (id, name, country, co2_emission) VALUES (1, 'Tour A', 'Germany', 2.5), (2, 'Tour B', 'Germany', 3.2);
|
What is the average CO2 emission of tours in Germany?
|
SELECT AVG(co2_emission) FROM tours WHERE country = 'Germany';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Inspections (id INT, restaurant_id INT, location VARCHAR(50), rating INT); INSERT INTO Inspections (id, restaurant_id, location, rating) VALUES (1, 1, 'New York', 5); INSERT INTO Inspections (id, restaurant_id, location, rating) VALUES (2, 2, 'Los Angeles', 3); INSERT INTO Inspections (id, restaurant_id, location, rating) VALUES (3, 3, 'Los Angeles', 4);
|
How many 4-star food safety inspections were there in Los Angeles?
|
SELECT COUNT(*) FROM Inspections WHERE location = 'Los Angeles' AND rating = 4;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE wildlife_habitats (id INT, region VARCHAR(255), habitat_type VARCHAR(255));
|
how many wildlife habitats are there in each region?
|
SELECT region, COUNT(DISTINCT id) as num_habitats FROM wildlife_habitats GROUP BY region;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE forests (id INT PRIMARY KEY, name VARCHAR(50), country VARCHAR(50), hectares DECIMAL(10,2)); CREATE TABLE animals (id INT PRIMARY KEY, species VARCHAR(50), population INT, forest_id INT, FOREIGN KEY (forest_id) REFERENCES forests(id)); INSERT INTO forests (id, name, country, hectares) VALUES (1, 'Savannah Forest', 'Africa', 300000.00); INSERT INTO animals (id, species, population, forest_id) VALUES (1, 'Koala', 20, 1);
|
Find the total hectares of forests in Africa with koala populations.
|
SELECT SUM(hectares) FROM forests INNER JOIN animals ON forests.id = animals.forest_id WHERE forests.country = 'Africa' AND animals.species = 'Koala';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE deep_sea_expeditions (expedition_name TEXT, year INT, new_species_discovered INT); INSERT INTO deep_sea_expeditions (expedition_name, year, new_species_discovered) VALUES ('Mariana Trench Exploration', 2017, 32), ('Atlantic Canyons Expedition', 2018, 28), ('Arctic Ocean Exploration', 2019, 15);
|
What is the average number of new species discovered per deep-sea expedition in the last 5 years?
|
SELECT AVG(new_species_discovered) FROM deep_sea_expeditions WHERE year >= 2017;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE UnderwritingData (PolicyholderID INT, Smoker BOOLEAN, VehicleYear INT, HouseLocation VARCHAR(25)); INSERT INTO UnderwritingData (PolicyholderID, Smoker, VehicleYear, HouseLocation) VALUES (1, True, 2015, 'Urban'); INSERT INTO UnderwritingData (PolicyholderID, Smoker, VehicleYear, HouseLocation) VALUES (2, False, 2018, 'Rural');CREATE TABLE RiskAssessment (PolicyholderID INT PRIMARY KEY, RiskScore INT); INSERT INTO RiskAssessment (PolicyholderID, RiskScore) VALUES (1, 50); INSERT INTO RiskAssessment (PolicyholderID, RiskScore) VALUES (2, 30);
|
What is the average risk score for policyholders living in rural areas?
|
SELECT AVG(RiskScore) FROM RiskAssessment WHERE PolicyholderID IN (SELECT PolicyholderID FROM UnderwritingData WHERE HouseLocation = 'Rural');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE ClimateAdaptationProjects (project_id INT, project_name VARCHAR(50), continent VARCHAR(50), year INT); INSERT INTO ClimateAdaptationProjects (project_id, project_name, continent, year) VALUES (1, 'Coastal Protection', 'South America', 2020), (2, 'Drought Resistance', 'South America', 2021);
|
What is the number of climate adaptation projects in South America for each year?
|
SELECT continent, year, COUNT(*) as num_projects FROM ClimateAdaptationProjects WHERE continent = 'South America' GROUP BY continent, year;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE marine_species (id INT PRIMARY KEY, species_name VARCHAR(255), conservation_status VARCHAR(255));
|
Delete a record of a marine species from the 'marine_species' table
|
DELETE FROM marine_species WHERE species_name = 'Green Sea Turtle';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE accommodations (accommodation_id INT, name VARCHAR(255), location VARCHAR(255), type VARCHAR(255), num_reviews INT, avg_review_score DECIMAL(5,2), country VARCHAR(255), revenue DECIMAL(10,2)); INSERT INTO accommodations (accommodation_id, name, location, type, num_reviews, avg_review_score, country, revenue) VALUES (1, 'Eco Lodge', 'Amazon Rainforest', 'Eco-friendly', 120, 4.8, 'Brazil', 50000), (2, 'Green Hotel', 'Barcelona', 'Eco-friendly', 150, 4.6, 'Spain', 80000);
|
What is the total revenue generated by sustainable tourism accommodations in each country?
|
SELECT country, SUM(revenue) AS total_revenue FROM accommodations GROUP BY country;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE therapy_sessions_london (id INT, patient_id INT, session_date DATE); INSERT INTO therapy_sessions_london (id, patient_id, session_date) VALUES (1, 1, '2021-01-01'), (2, 1, '2021-02-01'), (3, 2, '2021-03-01'), (4, 3, '2021-04-01'), (5, 3, '2021-04-15'), (6, 4, '2021-05-01');
|
What is the average number of therapy sessions per month for patients in London?
|
SELECT EXTRACT(MONTH FROM session_date) AS month, AVG(therapy_sessions_london.id) AS avg_sessions FROM therapy_sessions_london WHERE city = 'London' GROUP BY month;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE rice_yields (farmer_id INT, country VARCHAR(50), crop VARCHAR(50), yield INT, is_organic BOOLEAN); INSERT INTO rice_yields (farmer_id, country, crop, yield, is_organic) VALUES (1, 'Indonesia', 'Rice', 1000, true), (2, 'Indonesia', 'Rice', 1200, false), (3, 'Indonesia', 'Rice', 1500, true);
|
What is the average yield of rice crops in Indonesia, considering only organic farming methods?
|
SELECT AVG(yield) FROM rice_yields WHERE country = 'Indonesia' AND is_organic = true;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Workers (ID INT, Age INT, Gender VARCHAR(10), Salary DECIMAL(5,2), Industry VARCHAR(20), Ethical_Training BOOLEAN); INSERT INTO Workers (ID, Age, Gender, Salary, Industry, Ethical_Training) VALUES (1, 42, 'Female', 50000.00, 'Textile', FALSE); INSERT INTO Workers (ID, Age, Gender, Salary, Industry, Ethical_Training) VALUES (2, 35, 'Male', 55000.00, 'Textile', TRUE); INSERT INTO Workers (ID, Age, Gender, Salary, Industry, Ethical_Training) VALUES (3, 45, 'Female', 60000.00, 'Textile', FALSE);
|
Insert a new record for a worker in the 'Electronics' industry who is 30 years old, male, earns a salary of $65,000, and has received ethical manufacturing training.
|
INSERT INTO Workers (ID, Age, Gender, Salary, Industry, Ethical_Training) VALUES (4, 30, 'Male', 65000.00, 'Electronics', TRUE);
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE fire_data (fire_id INT, fire_type TEXT, district TEXT, date DATE);
|
How many fires were reported in the 'Harlem' district during each month in 2022?
|
SELECT district, EXTRACT(MONTH FROM date) AS month, COUNT(*) AS num_fires FROM fire_data WHERE district = 'Harlem' AND date BETWEEN '2022-01-01' AND '2022-12-31' GROUP BY district, month;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE claims (claim_number INT, policy_number INT, claim_amount INT, claim_date DATE);
|
Update the claims table and insert a new claim record for policy number 3 with a claim amount of 5000 and claim date of '2021-03-15'
|
INSERT INTO claims (claim_number, policy_number, claim_amount, claim_date) VALUES (1, 3, 5000, '2021-03-15'); UPDATE claims SET claim_amount = 6000 WHERE policy_number = 3 AND claim_date = '2020-01-01';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE habitats (id INT, habitat_type VARCHAR(255)); INSERT INTO habitats (id, habitat_type) VALUES (1, 'Forest'), (2, 'Savannah'), (3, 'Wetlands');
|
Delete all records from the 'Habitats' table.
|
DELETE FROM habitats;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE sector_year_consumption (year INT, sector INT, consumption FLOAT, PRIMARY KEY(year, sector)); INSERT INTO sector_year_consumption (year, sector, consumption) VALUES (2015, 1, 15000), (2015, 2, 20000), (2015, 3, 30000), (2016, 1, 16000), (2016, 2, 22000), (2016, 3, 32000), (2017, 1, 17000), (2017, 2, 24000), (2017, 3, 34000);
|
What is the total water consumption by each sector in the most recent year?
|
SELECT syc.sector, SUM(syc.consumption) as total_consumption FROM sector_year_consumption syc JOIN (SELECT MAX(year) as most_recent_year FROM sector_year_consumption) max_year ON 1=1 WHERE syc.year = max_year.most_recent_year GROUP BY syc.sector;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE volunteers (id INT, project_id INT, name TEXT); INSERT INTO volunteers (id, project_id, name) VALUES (1, 1, 'Alice'), (2, 1, 'Bob'), (3, 2, 'Charlie'); CREATE TABLE projects (id INT, funder TEXT, total_funding DECIMAL); INSERT INTO projects (id, funder, total_funding) VALUES (1, 'European Union', 20000.00), (2, 'United Nations', 30000.00);
|
How many total volunteers have there been in projects funded by the European Union?
|
SELECT COUNT(*) FROM volunteers INNER JOIN projects ON volunteers.project_id = projects.id WHERE projects.funder = 'European Union';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE organizations (id INT, name VARCHAR(50), country VARCHAR(50), num_volunteers INT); INSERT INTO organizations (id, name, country, num_volunteers) VALUES (1, 'UNICEF', 'India', 500), (2, 'Red Cross', 'China', 700), (3, 'Greenpeace', 'Japan', 300);
|
Find the top 5 organizations with the largest number of volunteers in Asia.
|
SELECT name, num_volunteers FROM organizations WHERE country IN ('India', 'China', 'Japan', 'Pakistan', 'Indonesia') ORDER BY num_volunteers DESC LIMIT 5;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE broadband_subscribers (subscriber_id INT, monthly_bill FLOAT, city VARCHAR(20)); INSERT INTO broadband_subscribers (subscriber_id, monthly_bill, city) VALUES (1, 60.5, 'San Francisco'), (2, 70.3, 'Houston'), (3, 55.7, 'San Francisco');
|
What is the minimum monthly bill for broadband subscribers in the city of San Francisco?
|
SELECT MIN(monthly_bill) FROM broadband_subscribers WHERE city = 'San Francisco';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Inventory (garment_type VARCHAR(20)); INSERT INTO Inventory (garment_type) VALUES ('Dress'), ('Shirt'), ('Pants'), ('Unisex');
|
List all unique garment types in the 'Inventory' table, excluding 'Unisex' entries.
|
SELECT DISTINCT garment_type FROM Inventory WHERE garment_type != 'Unisex';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Flight_Data (flight_date DATE, aircraft_model VARCHAR(255), flight_time TIME); INSERT INTO Flight_Data (flight_date, aircraft_model, flight_time) VALUES ('2020-01-01', 'Boeing 737', '03:00:00'), ('2020-02-01', 'Boeing 737', '04:00:00'), ('2020-03-01', 'Boeing 737', '05:00:00'), ('2020-04-01', 'Boeing 737', '03:30:00'), ('2020-05-01', 'Boeing 737', '04:15:00');
|
What is the maximum flight time for Boeing 737 aircraft?
|
SELECT MAX(EXTRACT(EPOCH FROM flight_time)) / 60.0 AS max_flight_time FROM Flight_Data WHERE aircraft_model = 'Boeing 737';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE albums (id INT, title TEXT, release_date DATE); INSERT INTO albums (id, title, release_date) VALUES (1, 'Millennium', '1999-12-31'), (2, 'Hybrid Theory', '2000-01-02');
|
What is the earliest release date of any album?
|
SELECT MIN(release_date) FROM albums;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE MineSites (SiteID INT PRIMARY KEY, Name VARCHAR(50), Country VARCHAR(50), LaborProductivityDecimal FLOAT); CREATE VIEW LaborProductivityView AS SELECT Employees.SiteID, AVG(LaborProductivity.ProductivityDecimal) AS AverageProductivity FROM Employees JOIN LaborProductivity ON Employees.EmployeeID = LaborProductivity.EmployeeID GROUP BY Employees.SiteID;
|
Identify the top 3 mine sites with the highest labor productivity.
|
SELECT MineSites.Name, AVG(LaborProductivityView.AverageProductivity) AS AverageProductivity FROM MineSites JOIN LaborProductivityView ON MineSites.SiteID = LaborProductivityView.SiteID GROUP BY MineSites.Name ORDER BY AverageProductivity DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE MakeupSales (sale_id INT, product_name VARCHAR(100), category VARCHAR(50), price DECIMAL(10,2), quantity INT, sale_date DATE, country VARCHAR(50), vegan BOOLEAN);
|
What is the total revenue of vegan makeup products in the UK in 2021?
|
SELECT SUM(price * quantity) FROM MakeupSales WHERE category = 'Makeup' AND country = 'UK' AND vegan = TRUE AND sale_date >= '2021-01-01' AND sale_date < '2022-01-01';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE teams (team_id INT, team_name VARCHAR(50));CREATE TABLE games (game_id INT, team_id INT, home_team BOOLEAN, price DECIMAL(5,2), attendance INT, fan_country VARCHAR(50));INSERT INTO teams (team_id, team_name) VALUES (1, 'Knicks'), (2, 'Lakers');INSERT INTO games (game_id, team_id, home_team, price, attendance, fan_country) VALUES (1, 1, 1, 100.00, 20000, 'USA'), (2, 2, 1, 120.00, 35000, 'Canada'), (3, 1, 0, 80.00, 18000, 'Mexico');
|
List the number of fans from different countries who have attended home games of each team, excluding games with attendance less than 15000.
|
SELECT t.team_name, COUNT(DISTINCT g.fan_country) AS unique_fan_countries FROM teams t INNER JOIN games g ON t.team_id = g.team_id AND g.home_team = t.team_id WHERE g.attendance >= 15000 GROUP BY t.team_name;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Inventory (restaurant VARCHAR(20), item_type VARCHAR(15), cost DECIMAL(5,2)); INSERT INTO Inventory (restaurant, item_type, cost) VALUES ('GreenLeaf', 'vegan', 5.50), ('GreenLeaf', 'gluten-free', 4.75), ('Sprout', 'vegan', 6.25), ('Sprout', 'gluten-free', 5.00);
|
Show the total inventory cost for 'vegan' and 'gluten-free' items across all restaurants.
|
SELECT SUM(cost) FROM Inventory WHERE item_type IN ('vegan', 'gluten-free');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE PlayersLA (PlayerID INT, PlayerName VARCHAR(100), Country VARCHAR(50)); INSERT INTO PlayersLA (PlayerID, PlayerName, Country) VALUES (1, 'Pedro Alvarez', 'Brazil'), (2, 'Jose Garcia', 'Argentina'), (3, 'Maria Rodriguez', 'Colombia'); CREATE TABLE GameSessionsLA (SessionID INT, PlayerID INT, GameID INT); INSERT INTO GameSessionsLA (SessionID, PlayerID, GameID) VALUES (1, 1, 101), (2, 1, 102), (3, 1, 103), (4, 2, 101), (5, 2, 104), (6, 3, 102), (7, 3, 103), (8, 3, 104), (9, 3, 105); CREATE TABLE GamesLA (GameID INT, GameName VARCHAR(50)); INSERT INTO GamesLA (GameID, GameName) VALUES (101, 'GameA'), (102, 'GameB'), (103, 'GameC'), (104, 'GameD'), (105, 'GameE');
|
What is the count of players from Latin America who have played at least 5 different games?
|
SELECT COUNT(DISTINCT PlayerID) FROM (SELECT PlayerID FROM GameSessionsLA JOIN PlayersLA ON GameSessionsLA.PlayerID = PlayersLA.PlayerID GROUP BY PlayerID HAVING COUNT(DISTINCT GameID) >= 5) AS Subquery;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE viewership (id INT, event VARCHAR(50), platform VARCHAR(20), viewers INT); INSERT INTO viewership (id, event, platform, viewers) VALUES (1, 'Music Concert', 'Streaming', 500000), (2, 'Sports Event', 'Streaming', 750000), (3, 'Movie Night', 'Theater', 300000);
|
How many viewers watched the 'Music Concert' from the 'Streaming' platform?
|
SELECT viewers FROM viewership WHERE event = 'Music Concert' AND platform = 'Streaming';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Donations (DonationID INT, DonorID INT, DonationDate DATE, DonationAmount DECIMAL(10,2), DonationPurpose VARCHAR(50)); CREATE TABLE Donors (DonorID INT, DonorName VARCHAR(50), DonationType VARCHAR(50));
|
What is the average donation amount for each category?
|
SELECT DonationPurpose, AVG(DonationAmount) FROM Donations d JOIN Donors don ON d.DonorID = don.DonorID GROUP BY DonationPurpose;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE SustainabilityMetrics (ProductID INT, SustainabilityRating INT, CarbonFootprint INT); INSERT INTO SustainabilityMetrics (ProductID, SustainabilityRating, CarbonFootprint) VALUES (1, 90, 50); INSERT INTO SustainabilityMetrics (ProductID, SustainabilityRating, CarbonFootprint) VALUES (2, 85, 75);
|
Assign a quartile rank based on carbon footprint, ordered by carbon footprint in ascending order.
|
SELECT ProductID, SustainabilityRating, CarbonFootprint, NTILE(4) OVER (ORDER BY CarbonFootprint ASC) as 'Quartile' FROM SustainabilityMetrics;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE court_cases (case_id INT, judge_name TEXT, case_state TEXT); INSERT INTO court_cases (case_id, judge_name, case_state) VALUES (11111, 'Judge Smith', 'Texas'); INSERT INTO court_cases (case_id, judge_name, case_state) VALUES (22222, 'Judge Johnson', 'Texas');
|
Identify the number of cases heard by each judge, along with the judge's name, in the state of Texas.
|
SELECT judge_name, COUNT(*) as cases_heard FROM court_cases WHERE case_state = 'Texas' GROUP BY judge_name;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE exhibitions (exhibition_id INT, exhibition_name VARCHAR(255), start_date DATE, end_date DATE); INSERT INTO exhibitions (exhibition_id, exhibition_name, start_date, end_date) VALUES (1, 'Art of the Renaissance', '2020-01-01', '2020-12-31'); CREATE TABLE visitors (visitor_id INT, exhibition_id INT, age INT, gender VARCHAR(10)); INSERT INTO visitors (visitor_id, exhibition_id, age, gender) VALUES (1, 1, 35, 'Female'), (2, 1, 42, 'Male');
|
What was the average age of visitors who attended the 'Art of the Renaissance' exhibition?
|
SELECT AVG(age) FROM visitors WHERE exhibition_id = 1;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE campaigns (id INT PRIMARY KEY, name VARCHAR(255), start_date DATE, end_date DATE); INSERT INTO campaigns (id, name, start_date, end_date) VALUES (7, 'Mindfulness in Daily Life', '2023-01-02', '2023-12-31');
|
What are the campaigns running after January 1, 2023?
|
SELECT * FROM campaigns WHERE start_date >= '2023-01-01';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE ticket_sales (sale_id INT, team VARCHAR(50), quantity INT); INSERT INTO ticket_sales (sale_id, team, quantity) VALUES (1, 'home_team', 100); INSERT INTO ticket_sales (sale_id, team, quantity) VALUES (2, 'away_team', 75);
|
How many tickets were sold for the home_team in the ticket_sales table?
|
SELECT SUM(quantity) FROM ticket_sales WHERE team = 'home_team';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Exhibitions (id INT, title VARCHAR(255), genre VARCHAR(255), century VARCHAR(255));
|
Add a new exhibition with ID 3, title 'Surrealism in the 20th Century', genre 'Surrealism', and century '20th Century'.
|
INSERT INTO Exhibitions (id, title, genre, century) VALUES (3, 'Surrealism in the 20th Century', 'Surrealism', '20th Century');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE startups (id INT, name VARCHAR(50), location VARCHAR(50), funding FLOAT); INSERT INTO startups (id, name, location, funding) VALUES (1, 'Genomic Solutions', 'USA', 5000000), (2, 'BioTech Innovations', 'Europe', 7000000), (3, 'Medical Innovations', 'UK', 6000000), (4, 'Innovative Biotech', 'India', 8000000);
|
What is the total funding received by biotech startups located in India?
|
SELECT SUM(funding) FROM startups WHERE location = 'India';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE carbon_prices (country VARCHAR(255), date DATE, price FLOAT); INSERT INTO carbon_prices VALUES ('USA', '2023-01-01', 10), ('Canada', '2023-01-01', 15), ('USA', '2023-02-01', 11), ('Canada', '2023-02-01', 16);
|
Identify the carbon price for a specific country on a particular date.
|
SELECT price FROM carbon_prices WHERE country = 'Canada' AND date = '2023-02-01';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE feedback (id INT, created_at DATETIME); INSERT INTO feedback (id, created_at) VALUES (1, '2023-01-01 12:34:56'), (2, '2023-01-15 10:20:34'), (3, '2023-02-20 16:45:01');
|
What is the average number of citizen feedback records per month for 2023?
|
SELECT AVG(num_records) FROM (SELECT DATE_FORMAT(created_at, '%Y-%m') as month, COUNT(*) as num_records FROM feedback WHERE created_at BETWEEN '2023-01-01' AND '2023-12-31' GROUP BY month) as subquery;
|
gretelai_synthetic_text_to_sql
|
SELECT * FROM policyholder_claim_info;
|
Write a SQL query to retrieve the policyholder information and corresponding claim data from the view you created
|
SELECT * FROM policyholder_claim_info;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE agricultural_innovation_projects (id INT, country VARCHAR(255), start_year INT, end_year INT, started INT); INSERT INTO agricultural_innovation_projects (id, country, start_year, end_year, started) VALUES (1, 'Nigeria', 2010, 2014, 1), (2, 'Nigeria', 2012, 2016, 1), (3, 'Nigeria', 2011, 2015, 1);
|
How many agricultural innovation projects were started in Nigeria between 2010 and 2014?'
|
SELECT COUNT(*) FROM agricultural_innovation_projects WHERE country = 'Nigeria' AND start_year >= 2010 AND end_year <= 2014 AND started = 1;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE startup (id INT, name TEXT, industry TEXT, founding_date DATE, founder_race TEXT); INSERT INTO startup (id, name, industry, founding_date, founder_race) VALUES (1, 'AptDeco', 'E-commerce', '2014-02-14', 'Black'), (2, 'Blavity', 'Media', '2014-07-17', 'Black');
|
What is the number of startups founded by individuals from underrepresented racial or ethnic backgrounds in the tech sector?
|
SELECT COUNT(*) FROM startup WHERE industry = 'Tech' AND founder_race IN ('Black', 'Hispanic', 'Indigenous', 'Asian', 'Pacific Islander', 'Multiracial');
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE volunteer_program (id INT, name VARCHAR(50), age INT, location VARCHAR(30)); INSERT INTO volunteer_program (id, name, age, location) VALUES (1, 'John Doe', 25, 'New York'), (2, 'Jane Smith', 32, 'California'), (3, 'Alice Johnson', 22, 'Texas');
|
What is the average age of volunteers in the 'volunteer_program' table?
|
SELECT AVG(age) FROM volunteer_program;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Vaccination (ID INT, Age INT, Population INT, Vaccinated INT); INSERT INTO Vaccination (ID, Age, Population, Vaccinated) VALUES (1, 18, 1000, 800), (2, 19, 1000, 850), (3, 20, 1000, 750);
|
What is the percentage of the population that is fully vaccinated, broken down by age group?
|
SELECT Age, (SUM(Vaccinated) OVER (PARTITION BY Age)::FLOAT / SUM(Population) OVER (PARTITION BY Age)) * 100 as VaccinationPercentage FROM Vaccination;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE research_projects (project_id INT PRIMARY KEY, project_name VARCHAR(50), project_status VARCHAR(50));
|
Update the 'project_status' for 'Project 123' in the 'research_projects' table to 'completed'
|
UPDATE research_projects SET project_status = 'completed' WHERE project_name = 'Project 123';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE smart_contracts (contract_address VARCHAR(64), user_address VARCHAR(64));
|
Delete all smart contracts for a specific user '0xabc...'.
|
DELETE FROM smart_contracts WHERE user_address = '0xabc...';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE donations (donor_id INT, donation_date DATE, donation_amount FLOAT); INSERT INTO donations (donor_id, donation_date, donation_amount) VALUES (1, '2020-01-01', 50.00), (2, '2019-12-31', 100.00), (3, '2020-05-15', 25.00);
|
How many donations were made by first-time donors in the year 2020?
|
SELECT COUNT(*) FROM donations WHERE YEAR(donation_date) = 2020 AND donor_id NOT IN (SELECT donor_id FROM donations WHERE YEAR(donation_date) < 2020);
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE marine_species (id INT, species_name VARCHAR(50), common_name VARCHAR(50), region VARCHAR(20));INSERT INTO marine_species (id, species_name, common_name, region) VALUES (1, 'Orcinus_orca', 'Killer Whale', 'Arctic');INSERT INTO marine_species (id, species_name, common_name, region) VALUES (2, 'Balaenoptera_bonaerensis', 'Antarctic Minke Whale', 'Antarctic');
|
Which marine species have been observed in more than one region?
|
SELECT species_name FROM marine_species GROUP BY species_name HAVING COUNT(DISTINCT region) > 1;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Crops(CropID INT, CropName VARCHAR(50), CropYield INT); INSERT INTO Crops(CropID, CropName, CropYield) VALUES (1, 'Corn', 25), (2, 'Soybean', 30), (3, 'Wheat', 18);
|
Delete all records in the 'Crops' table where the 'CropYield' is less than 20
|
DELETE FROM Crops WHERE CropYield < 20;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Refugees (RefugeeID INT, Region VARCHAR(20)); INSERT INTO Refugees (RefugeeID, Region) VALUES (1, 'Africa'), (2, 'Asia'), (3, 'Europe');
|
How many refugees were supported in each region?
|
SELECT Region, COUNT(RefugeeID) as NumRefugees FROM Refugees GROUP BY Region;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE sustainable_metrics (brand VARCHAR(255) PRIMARY KEY, metric VARCHAR(255), value INT); INSERT INTO sustainable_metrics (brand, metric, value) VALUES ('AnotherBrand', 'CarbonFootprint', 12), ('BrandX', 'WaterConsumption', 15);
|
Insert a new record in the sustainable_metrics table for brand 'EcoFriendlyBrand', metric 'WaterConsumption' and value 10
|
INSERT INTO sustainable_metrics (brand, metric, value) VALUES ('EcoFriendlyBrand', 'WaterConsumption', 10);
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE fleet_management (vessel_id INT, vessel_name VARCHAR(50), total_capacity INT); INSERT INTO fleet_management (vessel_id, vessel_name, total_capacity) VALUES (1, 'Vessel_A', 5000), (2, 'Vessel_B', 6000), (3, 'Vessel_C', 4000);
|
What is the total capacity of containers for all vessels in the fleet_management table?
|
SELECT SUM(total_capacity) FROM fleet_management;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE mobile_subscribers (region VARCHAR(50), subscriber_id INT); INSERT INTO mobile_subscribers VALUES ('Region A', 100); INSERT INTO mobile_subscribers VALUES ('Region A', 200); INSERT INTO mobile_subscribers VALUES ('Region B', 300); INSERT INTO mobile_subscribers VALUES ('Region C', 400); INSERT INTO broadband_subscribers VALUES ('Region A', 150); INSERT INTO broadband_subscribers VALUES ('Region A', 250); INSERT INTO broadband_subscribers VALUES ('Region B', 350); INSERT INTO broadband_subscribers VALUES ('Region C', 450);
|
What is the total number of mobile and broadband subscribers for each sales region?
|
SELECT region, COUNT(mobile_subscribers.subscriber_id) + COUNT(broadband_subscribers.subscriber_id) as total_subscribers FROM mobile_subscribers FULL OUTER JOIN broadband_subscribers ON mobile_subscribers.region = broadband_subscribers.region GROUP BY region;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE CountryData (Country VARCHAR(20), Year INT, Visitors INT); INSERT INTO CountryData (Country, Year, Visitors) VALUES ('France', 2021, 6000), ('Spain', 2021, 4000), ('Germany', 2021, 7000), ('France', 2020, 5000);
|
List the countries that had more than 5000 visitors in 2021.
|
SELECT Country FROM CountryData WHERE Year = 2021 AND Visitors > 5000;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE students (id INT, name VARCHAR(255), grade INT, mental_health_score INT); INSERT INTO students (id, name, grade, mental_health_score) VALUES (1, 'Jane Doe', 12, 80);
|
What is the average mental health score for students in grade 12?
|
SELECT AVG(mental_health_score) FROM students WHERE grade = 12;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE warehouse_costs (warehouse_id INT, warehouse_location VARCHAR(255), cost DECIMAL(10,2), quarter INT, year INT); INSERT INTO warehouse_costs (warehouse_id, warehouse_location, cost, quarter, year) VALUES (1, 'NYC Warehouse', 2500.00, 2, 2022), (2, 'LA Warehouse', 3000.00, 2, 2022), (3, 'CHI Warehouse', 2000.00, 2, 2022);
|
What are the average warehouse management costs for each warehouse in Q2 2022?
|
SELECT warehouse_location, AVG(cost) as avg_cost FROM warehouse_costs WHERE quarter = 2 AND year = 2022 GROUP BY warehouse_location;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE marine_protected_areas (name VARCHAR(255), location VARCHAR(255), avg_depth FLOAT); INSERT INTO marine_protected_areas (name, location, avg_depth) VALUES ('MPA 1', 'Indian Ocean', 700.0), ('MPA 2', 'Atlantic Ocean', 300.0);
|
Which marine protected areas in the Indian Ocean have an average depth greater than 500 meters?
|
SELECT name FROM marine_protected_areas WHERE location = 'Indian Ocean' AND avg_depth > 500;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE violations (id INT, location TEXT, type TEXT, date DATE); INSERT INTO violations (id, location, type, date) VALUES (1, 'California', 'wage theft', '2021-01-01'); CREATE TABLE months (id INT, month TEXT, year INT); INSERT INTO months (id, month, year) VALUES (1, 'January', 2021), (2, 'February', 2021);
|
What is the total number of labor rights violations reported each month, including months with no violations?
|
SELECT m.month, m.year, COALESCE(SUM(v.id), 0) FROM months m LEFT JOIN violations v ON EXTRACT(MONTH FROM v.date) = m.id AND EXTRACT(YEAR FROM v.date) = m.year GROUP BY m.month, m.year;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE states (state_abbr CHAR(2), state_name VARCHAR(50)); INSERT INTO states VALUES ('CA', 'California'), ('NY', 'New York'), ('TX', 'Texas'); CREATE TABLE hospitals (hospital_id INT, hospital_name VARCHAR(100), state_abbr CHAR(2)); INSERT INTO hospitals VALUES (1, 'UCSF Medical Center', 'CA'), (2, 'NY Presbyterian', 'NY'), (3, 'MD Anderson Cancer Center', 'TX'); CREATE TABLE clinics (clinic_id INT, clinic_name VARCHAR(100), state_abbr CHAR(2)); INSERT INTO clinics VALUES (1, 'Kaiser Permanente', 'CA'), (2, 'Mount Sinai Doctors', 'NY'), (3, 'Texas Children''s Pediatrics', 'TX');
|
What is the number of hospitals and clinics in each state?
|
SELECT s.state_name, COUNT(h.hospital_id) AS hospitals, COUNT(c.clinic_id) AS clinics FROM states s LEFT JOIN hospitals h ON s.state_abbr = h.state_abbr LEFT JOIN clinics c ON s.state_abbr = c.state_abbr GROUP BY s.state_name;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE arctic_zones (id INT, zone VARCHAR(255), depth INT, pollution_level INT); INSERT INTO arctic_zones VALUES (1, 'Zone A', 4000, 30); INSERT INTO arctic_zones VALUES (2, 'Zone B', 5000, 20); INSERT INTO arctic_zones VALUES (3, 'Zone C', 3500, 45);
|
Find the average depth of the Arctic Ocean floor mapping project zones with pollution levels above the median.
|
SELECT AVG(depth) FROM arctic_zones WHERE pollution_level > (SELECT AVG(pollution_level) FROM arctic_zones);
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE DriverMaintenance (MaintenanceID INT, DriverID INT, MaintenanceCost DECIMAL(5,2), Service VARCHAR(50), MaintenanceDate DATE); INSERT INTO DriverMaintenance (MaintenanceID, DriverID, MaintenanceCost, Service, MaintenanceDate) VALUES (1, 1, 200.00, 'Tram', '2022-02-01'), (2, 1, 250.00, 'Tram', '2022-02-03'), (3, 2, 300.00, 'Tram', '2022-02-02'), (4, 3, 400.00, 'Tram', '2022-02-04'), (5, 1, 150.00, 'Tram', '2022-02-05'), (6, 4, 175.00, 'Tram', '2022-02-06'), (7, 5, 350.00, 'Tram', '2022-02-07');
|
What is the average maintenance cost for each driver in the 'Tram' service in the last month?
|
SELECT d.DriverName, AVG(dm.MaintenanceCost) as AvgMaintenanceCost FROM Drivers d JOIN DriverMaintenance dm ON d.DriverID = dm.DriverID WHERE d.Service = 'Tram' AND dm.MaintenanceDate >= DATEADD(month, -1, GETDATE()) GROUP BY d.DriverName;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE incident_monthly (id INT, incident_date DATE, severity VARCHAR(10)); INSERT INTO incident_monthly (id, incident_date, severity) VALUES (1, '2022-01-01', 'Low'), (2, '2022-01-15', 'Medium'), (3, '2022-02-01', 'High'), (4, '2022-03-01', 'Critical'), (5, '2022-03-15', 'Low'), (6, '2022-04-01', 'Medium');
|
Show the number of security incidents and their severity by month
|
SELECT EXTRACT(MONTH FROM incident_date) as month, severity, COUNT(*) as incidents FROM incident_monthly GROUP BY month, severity;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE RealEstateCoOwnership.Properties (id INT, city VARCHAR(50)); INSERT INTO RealEstateCoOwnership.Properties (id, city) VALUES (1, 'San Francisco'), (2, 'New York'); CREATE TABLE RealEstateCoOwnership.CoOwnership (property_id INT, coowner VARCHAR(50)); INSERT INTO RealEstateCoOwnership.CoOwnership (property_id, coowner) VALUES (1, 'John'), (1, 'Jane'), (2, 'Bob');
|
List all co-owned properties and their corresponding city in the RealEstateCoOwnership schema.
|
SELECT Properties.id, Properties.city, CoOwnership.coowner FROM RealEstateCoOwnership.Properties INNER JOIN RealEstateCoOwnership.CoOwnership ON Properties.id = CoOwnership.property_id;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE offenders (id INT, name TEXT, state TEXT, community_service_hours INT); INSERT INTO offenders (id, name, state, community_service_hours) VALUES (1, 'John Doe', 'Washington', 50); INSERT INTO offenders (id, name, state, community_service_hours) VALUES (2, 'Jane Smith', 'Oregon', 75); INSERT INTO offenders (id, name, state, community_service_hours) VALUES (3, 'Mike Brown', 'Washington', 100);
|
How many community service hours were completed by offenders in each state?
|
SELECT state, SUM(community_service_hours) FROM offenders GROUP BY state
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Employees (id INT, Gender TEXT, Department TEXT, WeeklyWage DECIMAL);
|
What is the average weekly wage for male workers in the 'Manufacturing' industry?
|
SELECT AVG(WeeklyWage) FROM Employees WHERE Gender = 'Male' AND Department = 'Manufacturing';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE products (product_id INT PRIMARY KEY, product_name TEXT, discontinued_date DATE);
|
Delete records of products that have been discontinued in the past 3 years from the products table.
|
DELETE FROM products WHERE discontinued_date >= DATE(NOW()) - INTERVAL 3 YEAR;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Members (MemberID INT, Name VARCHAR(50), Age INT, Gender VARCHAR(10), City VARCHAR(50), State VARCHAR(20)); INSERT INTO Members (MemberID, Name, Age, Gender, City, State) VALUES (1011, 'Ella Nguyen', 33, 'Female', 'Hanoi', 'Vietnam'); INSERT INTO Members (MemberID, Name, Age, Gender, City, State) VALUES (1012, 'Alioune Diop', 40, 'Male', 'Dakar', 'Senegal');
|
SELECT MemberID, COUNT(*) as WorkoutCountLastMonth FROM Workouts WHERE DATE_TRUNC('month', Date) = DATE_TRUNC('month', CURRENT_DATE - INTERVAL '1 month') GROUP BY MemberID ORDER BY WorkoutCountLastMonth DESC;
|
SELECT MemberID, WorkoutType, DATE_TRUNC('hour', Date) as Hour, COUNT(*) as WorkoutCountPerHour FROM Workouts GROUP BY MemberID, WorkoutType, Hour ORDER BY Hour;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE HealthcareAccess (Location VARCHAR(50), Continent VARCHAR(50), Year INT, Score FLOAT); INSERT INTO HealthcareAccess (Location, Continent, Year, Score) VALUES ('Rural', 'Africa', 2018, 65.2), ('Urban', 'Africa', 2018, 80.5);
|
What is the healthcare access score for urban areas in Africa in 2018?
|
SELECT Score FROM HealthcareAccess WHERE Location = 'Urban' AND Continent = 'Africa' AND Year = 2018;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE ai_companies (id INT PRIMARY KEY, name VARCHAR(50), year_founded INT, region VARCHAR(50)); INSERT INTO ai_companies (id, name, year_founded, region) VALUES (1, 'AlphaAI', 2010, 'North America'); INSERT INTO ai_companies (id, name, year_founded, region) VALUES (2, 'BetaTech', 2015, 'Europe'); INSERT INTO ai_companies (id, name, year_founded, region) VALUES (3, 'GammaAI', 2012, 'Asia'); INSERT INTO ai_companies (id, name, year_founded, region) VALUES (4, 'DeltaSystems', 2014, 'Asia');
|
Who are the founders of AI companies in 'Asia' and when were they founded?
|
SELECT name, year_founded FROM ai_companies WHERE region = 'Asia';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Cases (CaseID INT, CaseOpenDate DATETIME, CaseCloseDate DATETIME);
|
List all cases that were opened more than 30 days ago, but have not yet been closed.
|
SELECT CaseID, CaseOpenDate, CaseCloseDate FROM Cases WHERE CaseOpenDate < DATE_SUB(CURDATE(), INTERVAL 30 DAY) AND CaseCloseDate IS NULL;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE ContractNegotiations (contract_id INT, contractor VARCHAR(50), contract_cost DECIMAL(10, 2)); INSERT INTO ContractNegotiations (contract_id, contractor, contract_cost) VALUES (1, 'ABC', 1000000.00); INSERT INTO ContractNegotiations (contract_id, contractor, contract_cost) VALUES (2, 'DEF', 2000000.00);
|
What is the total number of contracts negotiated by each contractor and their total cost?
|
SELECT contractor, COUNT(*) as total_contracts, SUM(contract_cost) as total_cost FROM ContractNegotiations GROUP BY contractor;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Safety_Tests_2 (Test_Quarter INT, Vehicle_Type VARCHAR(20)); INSERT INTO Safety_Tests_2 (Test_Quarter, Vehicle_Type) VALUES (1, 'Autonomous'), (1, 'Gasoline'), (2, 'Autonomous'), (2, 'Gasoline'), (3, 'Autonomous'), (3, 'Gasoline'), (4, 'Autonomous'), (4, 'Gasoline');
|
How many safety tests were conducted on autonomous vehicles in Q1 2021?
|
SELECT COUNT(*) FROM Safety_Tests_2 WHERE Vehicle_Type = 'Autonomous' AND Test_Quarter = 1;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE equipment_rentals (id INT, equipment_id INT, rental_dates DATE);
|
Delete records in the 'equipment_rentals' table that have rental_dates older than 2 years
|
DELETE FROM equipment_rentals WHERE rental_dates < DATE_SUB(CURDATE(), INTERVAL 2 YEAR);
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE cases (id INT, category VARCHAR(255), description TEXT, created_at TIMESTAMP); INSERT INTO cases (id, category, description, created_at) VALUES (1, 'Civil', 'Case description 1', '2021-01-01 10:00:00'), (2, 'Criminal', 'Case description 2', '2021-01-02 10:00:00'), (3, 'Civil', 'Case description 3', '2021-01-03 10:00:00');
|
What is the total number of cases in each category, ordered by the total count?
|
SELECT category, COUNT(*) as total_cases FROM cases GROUP BY category ORDER BY total_cases DESC;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE HumanitarianAssistance (Country VARCHAR(50), Year INT, Amount FLOAT); INSERT INTO HumanitarianAssistance (Country, Year, Amount) VALUES ('Country 1', 2009, 1000000), ('Country 2', 2009, 1100000);
|
What was the total humanitarian assistance provided in 2009?
|
SELECT SUM(Amount) FROM HumanitarianAssistance WHERE Year = 2009;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE donors (id INT, name TEXT, donation_amount DECIMAL(10,2), donation_date DATE); INSERT INTO donors (id, name, donation_amount, donation_date) VALUES (1, 'John Doe', 1000.00, '2020-01-05'); INSERT INTO donors (id, name, donation_amount, donation_date) VALUES (2, 'Jane Smith', 1500.00, '2020-03-12');
|
Who are the top 3 donors in terms of total donation amount in 2020, and how much did they donate in total?
|
SELECT name, SUM(donation_amount) AS total_donation FROM donors WHERE donation_date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY name ORDER BY total_donation DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE HybridSales (Id INT, Vehicle VARCHAR(255), ModelYear INT, State VARCHAR(255), QuantitySold INT, Quarter INT); INSERT INTO HybridSales (Id, Vehicle, ModelYear, State, QuantitySold, Quarter) VALUES (1, 'Toyota Prius', 2021, 'Washington', 3000, 4), (2, 'Honda Insight', 2021, 'Washington', 1500, 4), (3, 'Hyundai Ioniq', 2021, 'Washington', 2000, 4);
|
How many hybrid vehicles were sold in Washington in Q4 of 2021?
|
SELECT SUM(QuantitySold) FROM HybridSales WHERE ModelYear = 2021 AND State = 'Washington' AND Quarter = 4 AND Vehicle LIKE '%Hybrid%'
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE marine_protected_areas (id INT, name VARCHAR(255), area_size FLOAT, region VARCHAR(255)); INSERT INTO marine_protected_areas (id, name, area_size, region) VALUES (1, 'Chagos Marine Reserve', 640000, 'Indian');
|
What is the maximum size of a marine protected area (in square kilometers) in the Indian Ocean?
|
SELECT MAX(area_size) FROM marine_protected_areas WHERE region = 'Indian';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Education_Programs AS SELECT 'Young_Protectors' AS program, 11000 AS budget UNION SELECT 'Green_Champions', 13000;
|
What is the minimum budget for any education program?
|
SELECT MIN(budget) FROM Education_Programs;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE music_platform (id INT, genre VARCHAR(50), streams INT, country VARCHAR(50));
|
What is the total number of streams for all songs in the R&B genre on the music streaming platform in Germany?
|
SELECT SUM(streams) as total_streams FROM music_platform WHERE genre = 'R&B' AND country = 'Germany';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE intelligence_agency_leaders (id INT, agency_name VARCHAR(255), leader_name VARCHAR(255), leader_background TEXT); INSERT INTO intelligence_agency_leaders (id, agency_name, leader_name, leader_background) VALUES (1, 'CSIS', 'David Vigneault', 'David Vigneault has been the Director of the Canadian Security Intelligence Service since June 2017. He has extensive experience in national security and law enforcement, including previous roles as Associate Deputy Minister of National Defence and Assistant Deputy Minister of Public Safety for the Government of Canada.');
|
Who is the head of the Canadian Security Intelligence Service and what is their background?
|
SELECT leader_name, leader_background FROM intelligence_agency_leaders WHERE agency_name = 'CSIS';
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE wells (well_id INT, drill_date DATE); INSERT INTO wells (well_id, drill_date) VALUES (1, '2018-01-01'), (2, '2019-01-01'), (3, '2020-01-01'), (4, '2021-01-01'), (5, '2022-01-01');
|
How many wells were drilled each year in the last 5 years?
|
SELECT YEAR(drill_date) AS Year, COUNT(*) AS Number_of_Wells FROM wells WHERE drill_date >= DATEADD(year, -5, GETDATE()) GROUP BY YEAR(drill_date) ORDER BY Year
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE transactions (transaction_date DATE, customer_id INT, transaction_amt DECIMAL(10, 2)); INSERT INTO transactions (transaction_date, customer_id, transaction_amt) VALUES ('2022-01-01', 1, 200.00), ('2022-01-02', 1, 250.00), ('2022-01-03', 1, 300.00);
|
What is the difference in transaction amount between consecutive transactions for each customer?
|
SELECT transaction_date, customer_id, transaction_amt, LAG(transaction_amt, 1) OVER (PARTITION BY customer_id ORDER BY transaction_date) AS previous_transaction_amt, transaction_amt - LAG(transaction_amt, 1) OVER (PARTITION BY customer_id ORDER BY transaction_date) AS transaction_diff FROM transactions;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE reefs (reef_id INT, reef_name TEXT, temperature FLOAT, depth FLOAT, conservation_status TEXT);
|
Update the 'reefs' table to set the conservation_status to 'critical' for the reef with reef_id '10'.
|
UPDATE reefs SET conservation_status = 'critical' WHERE reef_id = 10;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE Sales (SaleID INT, Item TEXT, Region TEXT, IsEcoFriendly BOOLEAN); INSERT INTO Sales (SaleID, Item, Region, IsEcoFriendly) VALUES (1, 'T-Shirt', 'North', TRUE), (2, 'Pants', 'South', FALSE), (3, 'Jacket', 'East', TRUE), (4, 'Hat', 'West', FALSE);
|
What are the total sales of eco-friendly clothing items in each region?
|
SELECT Region, SUM(TotalSales) FROM (SELECT Region, Item, IsEcoFriendly, COUNT(*) AS TotalSales FROM Sales GROUP BY Region, Item, IsEcoFriendly) AS Subquery WHERE IsEcoFriendly = TRUE GROUP BY Region;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE posts (id INT, user_id INT, post_date DATE); INSERT INTO posts (id, user_id, post_date) VALUES (1, 1, '2021-01-01'), (2, 2, '2021-01-02'), (3, 3, '2021-01-03'); CREATE TABLE users (id INT, country VARCHAR(50)); INSERT INTO users (id, country) VALUES (1, 'Iran'), (2, 'Saudi Arabia'), (3, 'Turkey');
|
Show the number of posts made by users from the Middle East, grouped by day of the week.
|
SELECT DATE_FORMAT(post_date, '%W') as day_of_week, COUNT(*) as post_count FROM posts JOIN users ON posts.user_id = users.id WHERE users.country IN ('Iran', 'Saudi Arabia', 'Turkey') GROUP BY day_of_week;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE DroughtImpact (Id INT, Location VARCHAR(50), Impact DECIMAL(5,2), Date DATE); INSERT INTO DroughtImpact (Id, Location, Impact, Date) VALUES (1, 'Texas', 0.8, '2021-06-15'); INSERT INTO DroughtImpact (Id, Location, Impact, Date) VALUES (2, 'Texas', 0.6, '2021-07-01');
|
On which dates did Texas have a drought impact greater than 0.7?
|
SELECT Date, AVG(Impact) FROM DroughtImpact WHERE Location = 'Texas' GROUP BY Date HAVING AVG(Impact) > 0.7;
|
gretelai_synthetic_text_to_sql
|
CREATE TABLE crop_nutrient_levels (crop_type VARCHAR(255), nutrient_name VARCHAR(255), level INT, record_date DATE); INSERT INTO crop_nutrient_levels (crop_type, nutrient_name, level, record_date) VALUES ('corn', 'nitrogen', 100, '2022-02-01'), ('soybeans', 'nitrogen', 110, '2022-02-02'), ('corn', 'nitrogen', 95, '2022-02-03'), ('soybeans', 'nitrogen', 105, '2022-02-04'), ('wheat', 'nitrogen', 115, '2022-02-05');
|
Update the nitrogen level for crop type 'wheat' to 120 in the last 60 days.
|
UPDATE crop_nutrient_levels SET level = 120 WHERE crop_type = 'wheat' AND record_date >= DATE_SUB(CURDATE(), INTERVAL 60 DAY);
|
gretelai_synthetic_text_to_sql
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.