context stringlengths 11 9.12k | question stringlengths 0 1.06k | SQL stringlengths 2 4.44k | source stringclasses 28 values |
|---|---|---|---|
CREATE TABLE patients (patient_id INT, age INT, gender TEXT, treatment TEXT, state TEXT); INSERT INTO patients (patient_id, age, gender, treatment, state) VALUES (1, 30, 'Female', 'CBT', 'Texas'); INSERT INTO patients (patient_id, age, gender, treatment, state) VALUES (2, 45, 'Male', 'DBT', 'California'); INSERT INTO patients (patient_id, age, gender, treatment, state) VALUES (3, 25, 'Non-binary', 'Therapy', 'Washington'); INSERT INTO patients (patient_id, age, gender, treatment, state) VALUES (4, 55, 'Male', 'Therapy', 'Texas'); | What is the number of patients who identified as male and received therapy in Texas? | SELECT COUNT(*) FROM patients WHERE gender = 'Male' AND treatment = 'Therapy' AND state = 'Texas'; | gretelai_synthetic_text_to_sql |
CREATE TABLE chemical_table (chemical_id INT, chemical_name VARCHAR(50), safety_rating INT); CREATE TABLE environmental_impact_table (record_id INT, chemical_id INT, environmental_impact_float); | Insert records for a new chemical named 'Isopropyl Alcohol' in the chemical_table and environmental_impact_table | INSERT INTO chemical_table (chemical_name) VALUES ('Isopropyl Alcohol'); INSERT INTO environmental_impact_table (chemical_id, environmental_impact_float) VALUES ((SELECT chemical_id FROM chemical_table WHERE chemical_name = 'Isopropyl Alcohol'), 3.1); | gretelai_synthetic_text_to_sql |
CREATE TABLE cargos(id INT, vessel_id INT, num_containers INT); CREATE TABLE vessel_locations(id INT, vessel_id INT, location VARCHAR(50), timestamp TIMESTAMP); | What is the total number of containers transported from India to the US west coast in the past month? | SELECT SUM(num_containers) FROM cargos JOIN vessel_locations ON cargos.vessel_id = vessel_locations.vessel_id WHERE source_country = 'India' AND destination_country = 'US' AND location LIKE '%US West Coast%' AND timestamp > DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH) | gretelai_synthetic_text_to_sql |
CREATE TABLE supplier (supplier_id VARCHAR(10), name VARCHAR(50), country VARCHAR(50), primary key (supplier_id)); | Get all suppliers that have 'Fair Trade' in 'labor_practice' table | SELECT DISTINCT s.* FROM supplier s JOIN supplier_labor_practice slp ON s.supplier_id = slp.supplier_id JOIN labor_practice lp ON slp.practice_id = lp.practice_id WHERE lp.name = 'Fair Trade'; | gretelai_synthetic_text_to_sql |
CREATE TABLE DailySpotifyStreams (StreamID INT, TrackID INT, PlatformID INT, Date DATE, Streams INT); INSERT INTO DailySpotifyStreams (StreamID, TrackID, PlatformID, Date, Streams) VALUES (1, 1, 2, '2022-01-02', 200); | What is the total number of streams for Latin music on Spotify, grouped by day? | SELECT EXTRACT(DAY FROM Date) as Day, EXTRACT(MONTH FROM Date) as Month, EXTRACT(YEAR FROM Date) as Year, SUM(Streams) as TotalStreams FROM DailySpotifyStreams JOIN Tracks ON DailySpotifyStreams.TrackID = Tracks.TrackID JOIN StreamingPlatforms ON DailySpotifyStreams.PlatformID = StreamingPlatforms.PlatformID WHERE Genre = 'Latin' AND PlatformName = 'Spotify' GROUP BY Day, Month, Year; | gretelai_synthetic_text_to_sql |
CREATE TABLE shariah_compliant_investments (id INT PRIMARY KEY, institution_id INT, sukuk_type VARCHAR(255), value DECIMAL(10,2)); CREATE TABLE financial_institutions (id INT PRIMARY KEY, name VARCHAR(255), type VARCHAR(255), country VARCHAR(255)); | What are the names and SUKUK types of all Shariah-compliant investments in Malaysia worth more than 1000000? | SELECT financial_institutions.name, shariah_compliant_investments.sukuk_type, shariah_compliant_investments.value FROM financial_institutions JOIN shariah_compliant_investments ON financial_institutions.id = shariah_compliant_investments.institution_id WHERE financial_institutions.country = 'Malaysia' AND shariah_compliant_investments.value > 1000000; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, name TEXT, is_cruelty_free BOOLEAN, price DECIMAL); INSERT INTO products (product_id, name, is_cruelty_free, price) VALUES (1, 'Lipstick', TRUE, 12.99); INSERT INTO products (product_id, name, is_cruelty_free, price) VALUES (2, 'Eye Shadow', TRUE, 9.49); | What is the sum of the prices of all cruelty-free cosmetics? | SELECT SUM(price) FROM products WHERE is_cruelty_free = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE pedestrian_accidents (id INT, city VARCHAR(20), year INT, involved_pedestrian BOOLEAN, number_of_accidents INT); INSERT INTO pedestrian_accidents (id, city, year, involved_pedestrian, number_of_accidents) VALUES (1, 'Toronto', 2021, true, 120), (2, 'Toronto', 2022, true, 150), (3, 'Montreal', 2021, false, 90); | How many traffic accidents involved pedestrians in the city of Toronto during 2021 and 2022? | SELECT SUM(number_of_accidents) FROM pedestrian_accidents WHERE city = 'Toronto' AND involved_pedestrian = true AND year IN (2021, 2022); | gretelai_synthetic_text_to_sql |
CREATE TABLE Volunteers (id INT, program VARCHAR(50), volunteer_count INT, engagement_date DATE); INSERT INTO Volunteers (id, program, volunteer_count, engagement_date) VALUES (1, 'Education', 15, '2022-01-05'), (2, 'Health', 20, '2022-01-12'), (3, 'Education', 25, '2022-03-20'), (4, 'Health', 18, '2022-03-27'), (5, 'Environment', 30, '2022-04-01'), (6, 'Education', 35, '2022-05-15'); | Which programs had more than 25 volunteers in any month of 2022? | SELECT program, DATE_FORMAT(engagement_date, '%Y-%m') as engagement_month, SUM(volunteer_count) as total_volunteers FROM Volunteers WHERE engagement_date BETWEEN '2022-01-01' AND '2022-12-31' GROUP BY program, engagement_month HAVING total_volunteers > 25; | gretelai_synthetic_text_to_sql |
CREATE TABLE renewable_projects (project_id INT, region VARCHAR(10), technology VARCHAR(20), installed_capacity INT); INSERT INTO renewable_projects (project_id, region, technology, installed_capacity) VALUES (1, 'EU', 'Wind', 5000), (2, 'EU', 'Solar', 7000), (3, 'AS', 'Wind', 3000), (4, 'AS', 'Solar', 4000); | Which renewable energy projects in Europe have a higher installed capacity than the average capacity in Asia? | SELECT region, technology, installed_capacity FROM renewable_projects WHERE region = 'EU' AND installed_capacity > (SELECT AVG(installed_capacity) FROM renewable_projects WHERE region = 'AS') | gretelai_synthetic_text_to_sql |
CREATE TABLE IF NOT EXISTS veteran_employment (employee_id INT, veteran_status VARCHAR(10), hire_date DATE, job_title VARCHAR(50), department VARCHAR(50)); | What is the percentage of veteran and non-veteran employees hired per quarter since 2017? | SELECT TO_CHAR(hire_date, 'YYYY-Q'), veteran_status, COUNT(*) as num_employees, COUNT(*) * 100.0 / SUM(COUNT(*)) OVER (PARTITION BY TO_CHAR(hire_date, 'YYYY-Q')) as hire_percentage FROM veteran_employment WHERE hire_date >= '2017-01-01' GROUP BY TO_CHAR(hire_date, 'YYYY-Q'), veteran_status; | gretelai_synthetic_text_to_sql |
CREATE TABLE Exhibitions (exhibition_id INT, city VARCHAR(20), country VARCHAR(20)); INSERT INTO Exhibitions (exhibition_id, city, country) VALUES (1, 'Rio de Janeiro', 'Brazil'), (2, 'São Paulo', 'Brazil'), (3, 'Brasilia', 'Brazil'); CREATE TABLE Visitors (visitor_id INT, exhibition_id INT, age INT); INSERT INTO Visitors (visitor_id, exhibition_id, age) VALUES (1, 1, 35), (2, 1, 40), (3, 2, 25), (4, 2, 28), (5, 3, 19), (6, 3, 32); | What is the total number of visitors who attended exhibitions in 'Rio de Janeiro' or 'São Paulo' and are above 30 years of age? | SELECT COUNT(visitor_id) FROM Visitors v JOIN Exhibitions e ON v.exhibition_id = e.exhibition_id WHERE e.city IN ('Rio de Janeiro', 'São Paulo') AND v.age > 30; | gretelai_synthetic_text_to_sql |
CREATE TABLE museum_revenue (museum_id INT, museum_name VARCHAR(100), year INT, virtual_tour_revenue FLOAT); INSERT INTO museum_revenue (museum_id, museum_name, year, virtual_tour_revenue) VALUES (1, 'Louvre Museum', 2021, 2000000); INSERT INTO museum_revenue (museum_id, museum_name, year, virtual_tour_revenue) VALUES (2, 'British Museum', 2021, 1500000); | What is the virtual tour revenue for the Louvre Museum in 2021? | SELECT virtual_tour_revenue FROM museum_revenue WHERE museum_name = 'Louvre Museum' AND year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (donation_id INT, donor_type VARCHAR(10), art_id INT, donation_date DATE); CREATE TABLE TraditionalArt (art_id INT, art_name VARCHAR(20), art_type VARCHAR(20)); | Insert new records of traditional art pieces donated by individuals and organizations. | INSERT INTO Donations (donation_id, donor_type, art_id, donation_date) VALUES (1, 'Individual', 1, '2022-01-01'), (2, 'Organization', 2, '2022-02-01'); INSERT INTO TraditionalArt (art_id, art_name, art_type) VALUES (1, 'Drum', 'Wood'), (2, 'Mask', 'Clay'); | gretelai_synthetic_text_to_sql |
CREATE TABLE materials (id INT, item_id INT, material VARCHAR(255)); INSERT INTO materials (id, item_id, material) VALUES (1, 1, 'cotton'), (2, 2, 'polyester'), (3, 3, 'cotton'); | Show the total price of all items that are made of a particular material and are produced using a particular manufacturing process | SELECT SUM(price) FROM sales s JOIN processes p ON s.item_id = p.item_id JOIN materials m ON s.item_id = m.item_id WHERE p.process = 'process A' AND m.material = 'cotton'; | gretelai_synthetic_text_to_sql |
CREATE TABLE investors (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255), investment_amount DECIMAL(10,2)); INSERT INTO investors (id, name, location, investment_amount) VALUES (1, 'Alice', 'USA', 5000.00), (2, 'Bob', 'Canada', 3000.00), (3, 'Charlie', 'UK', 4000.00), (4, 'Diana', 'Germany', 6000.00); | Who are the top 3 investors in terms of investment amount? | SELECT id, name, SUM(investment_amount) AS total_investment FROM investors GROUP BY id ORDER BY total_investment DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Sales (SaleID INT, VendorID INT, ProductID INT, ProductName VARCHAR(50), ProductCategory VARCHAR(50), Year INT, Revenue INT); INSERT INTO Sales VALUES (1, 1, 1, 'ProductA', 'CategoryA', 2020, 1000), (2, 2, 2, 'ProductB', 'CategoryB', 2021, 1500), (3, 1, 1, 'ProductA', 'CategoryA', 2020, 500); | Find the vendor with the lowest total sales for each product category, partitioned by year, ordered by product name? | SELECT ProductName, ProductCategory, Year, VendorID, MIN(Revenue) OVER (PARTITION BY ProductCategory, Year) AS LowestRevenue FROM Sales; | gretelai_synthetic_text_to_sql |
CREATE TABLE suppliers(id INT PRIMARY KEY, name VARCHAR(50), certified_date DATE, certification_expiration_date DATE); INSERT INTO suppliers(id, name, certified_date, certification_expiration_date) VALUES (1, 'Supplier A', '2020-01-01', '2022-12-31'), (2, 'Supplier B', '2019-06-15', '2021-06-14'), (3, 'Supplier C', '2021-08-08', '2023-08-07'); CREATE TABLE products(id INT PRIMARY KEY, name VARCHAR(50), type VARCHAR(50)); INSERT INTO products(id, name, type) VALUES (1, 'free-range eggs', 'eggs'), (2, 'cage-free eggs', 'eggs'), (3, 'conventional eggs', 'eggs'); | List all the suppliers providing "free-range eggs", along with their certification date and expiration date. | SELECT s.name, s.certified_date, s.certification_expiration_date FROM suppliers s JOIN products p ON s.id = p.id WHERE p.name = 'free-range eggs'; | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_price (region VARCHAR(20), price FLOAT); INSERT INTO carbon_price (region, price) VALUES ('European Union', 25.1), ('European Union', 25.4), ('United Kingdom', 30.2), ('United Kingdom', 30.5); | What is the average carbon price in the European Union and United Kingdom? | SELECT AVG(price) as avg_price, region FROM carbon_price GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE Budget_Allocation (id INT, department VARCHAR(50), year INT, allocation DECIMAL(10,2)); INSERT INTO Budget_Allocation (id, department, year, allocation) VALUES (1, 'Student Services', 2020, 50000.00), (2, 'Faculty Development', 2020, 35000.00); | What is the average budget allocation for inclusion efforts by department and year? | SELECT AVG(Budget_Allocation.allocation) as average, Budget_Allocation.department, Budget_Allocation.year FROM Budget_Allocation GROUP BY Budget_Allocation.department, Budget_Allocation.year; | gretelai_synthetic_text_to_sql |
CREATE TABLE research_vessels (id INT, name VARCHAR(50), type VARCHAR(20), launch_date DATE); INSERT INTO research_vessels (id, name, type, launch_date) VALUES (1, 'RV Ocean Explorer', 'Oceanographic', '2017-01-01'), (2, 'RV Deep Diver', 'Underwater', '2016-05-15'), (3, 'RV Sea Rover', 'Hydrographic', '2021-02-28'); | What is the total number of research vessels that were launched in the last 5 years? | SELECT COUNT(*) FROM research_vessels WHERE launch_date BETWEEN '2016-01-01' AND '2021-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Species (Name VARCHAR(50) PRIMARY KEY, Population INT); INSERT INTO Species (Name, Population) VALUES ('Coral', 1000); | Delete the "Species" record with a name of Coral | DELETE FROM Species WHERE Name = 'Coral'; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, product_name TEXT, is_cruelty_free BOOLEAN, country TEXT); CREATE TABLE sales (sale_id INT, product_id INT, sale_country TEXT); INSERT INTO products VALUES (1, 'ProductA', true, 'US'), (2, 'ProductB', false, 'Canada'), (3, 'ProductC', true, 'Canada'), (4, 'ProductD', true, 'US'); INSERT INTO sales VALUES (1, 1, 'US'), (2, 3, 'Canada'), (3, 4, 'US'), (4, 1, 'Canada'); | Which cruelty-free certified products were sold in the US and Canada? | SELECT products.product_name FROM products JOIN sales ON products.product_id = sales.product_id WHERE products.is_cruelty_free = true AND (sales.sale_country = 'US' OR sales.sale_country = 'Canada') | gretelai_synthetic_text_to_sql |
CREATE TABLE Attorneys (AttorneyID INT, Name TEXT, Wins INT); INSERT INTO Attorneys VALUES (1, 'Smith', 10), (2, 'Johnson', 5), (3, 'Williams', 15); CREATE TABLE NYCases (CaseID INT, AttorneyID INT, Outcome TEXT); INSERT INTO NYCases VALUES (1, 1, 'Won'), (2, 2, 'Lost'), (3, 3, 'Won'); CREATE TABLE CACases (CaseID INT, AttorneyID INT, Outcome TEXT); INSERT INTO CACases VALUES (1, 1, 'Won'), (2, 3, 'Won'); | What are the names of attorneys who have won cases in both New York and California? | SELECT a.Name FROM Attorneys a INNER JOIN NYCases n ON a.AttorneyID = n.AttorneyID WHERE n.Outcome = 'Won' INTERSECT SELECT a.Name FROM Attorneys a INNER JOIN CACases c ON a.AttorneyID = c.AttorneyID WHERE c.Outcome = 'Won'; | gretelai_synthetic_text_to_sql |
CREATE TABLE company (name VARCHAR(255), founder_underrepresented BOOLEAN, founder_name VARCHAR(100)); INSERT INTO company (name, founder_underrepresented, founder_name) VALUES ('CompanyA', FALSE, 'John Smith'), ('CompanyB', TRUE, 'Jane Doe'), ('CompanyC', TRUE, 'Michael Brown'), ('CompanyD', FALSE, 'Sarah Johnson'), ('CompanyE', TRUE, 'David Kim'), ('CompanyF', FALSE, 'Emily Wong'); CREATE TABLE funding (company_name VARCHAR(255), amount INT); INSERT INTO funding (company_name, amount) VALUES ('CompanyA', 2000000), ('CompanyB', 3500000), ('CompanyC', 4000000), ('CompanyD', 1000000), ('CompanyE', 3000000), ('CompanyF', 5000000); | Who are the founders of the startups that have received funding of over 3000000 and are from underrepresented communities? | SELECT company.founder_name FROM company INNER JOIN funding ON company.name = funding.company_name WHERE funding.amount > 3000000 AND company.founder_underrepresented = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE Manufacturers (ManufacturerID INT, ManufacturerName VARCHAR(50));CREATE TABLE GarmentDates (GarmentID INT, ManufacturerID INT, AddedDate DATE); | Show the number of garments added per month for a specific manufacturer. | SELECT M.ManufacturerName, EXTRACT(MONTH FROM G.AddedDate) AS Month, COUNT(G.GarmentID) AS NewGarments FROM Manufacturers M JOIN GarmentDates G ON M.ManufacturerID = G.ManufacturerID WHERE M.ManufacturerName = 'GreenThreads' GROUP BY Month; | gretelai_synthetic_text_to_sql |
CREATE TABLE farm_soil_moisture (farm_id INT, timestamp TIMESTAMP, soil_moisture INT); | Determine the change in soil moisture for each farm, partitioned by month. | SELECT farm_id, EXTRACT(MONTH FROM timestamp) AS month, soil_moisture - LAG(soil_moisture) OVER (PARTITION BY farm_id ORDER BY EXTRACT(MONTH FROM timestamp)) AS moisture_change FROM farm_soil_moisture; | gretelai_synthetic_text_to_sql |
CREATE TABLE electronics_advanced_training (country VARCHAR(50), min_salary NUMERIC, max_salary NUMERIC, master_degree BOOLEAN); INSERT INTO electronics_advanced_training (country, min_salary, max_salary, master_degree) VALUES ('China', 12000, 22000, true), ('Vietnam', 9000, 19000, true), ('Malaysia', 14000, 26000, true), ('Indonesia', 10000, 20000, false), ('Philippines', 13000, 24000, false); | What is the average salary for workers in the electronics industry who have completed a master's degree, by country? | SELECT country, AVG( (max_salary + min_salary) / 2.0) as avg_salary FROM electronics_advanced_training WHERE master_degree = true GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE fans (fan_id INT, country VARCHAR(20)); CREATE TABLE tickets (ticket_id INT, fan_id INT, team_id INT); CREATE TABLE teams (team_id INT, team_name VARCHAR(20)); INSERT INTO teams (team_id, team_name) VALUES (2, 'LA Lakers'); INSERT INTO fans (fan_id, country) VALUES (2, 'USA'); INSERT INTO tickets (ticket_id, fan_id, team_id) VALUES (2, 2, 2); | How many fans from each country have purchased tickets to see the LA Lakers? | SELECT COUNT(DISTINCT fans.fan_id), fans.country FROM fans INNER JOIN tickets ON fans.fan_id = tickets.fan_id INNER JOIN teams ON tickets.team_id = teams.team_id WHERE teams.team_name = 'LA Lakers' GROUP BY fans.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE bakken_wells (well text); INSERT INTO bakken_wells VALUES ('Well1'), ('Well2'), ('Well3'), ('Well4'), ('Well5'), ('Well6'), ('Well7'), ('Well8'), ('Well9'), ('Well10'); | Find the total number of wells in the 'Bakken' shale play. | SELECT COUNT(well) FROM bakken_wells; | gretelai_synthetic_text_to_sql |
CREATE TABLE products_vegan (id INT, product_name TEXT, vegan BOOLEAN); INSERT INTO products_vegan (id, product_name, vegan) VALUES (1, 'Lotion', false), (2, 'Shampoo', true), (3, 'Soap', false); | What is the total number of vegan and non-vegan products? | SELECT vegan, COUNT(*) FROM products_vegan GROUP BY vegan; | gretelai_synthetic_text_to_sql |
CREATE TABLE production (item_name VARCHAR(255), material VARCHAR(255), quantity INT, supplier VARCHAR(255)); INSERT INTO production (item_name, material, quantity, supplier) VALUES ('T-Shirt', 'Organic Cotton', 10, 'Supplier A'), ('Shirt', 'Organic Cotton', 15, 'Supplier A'), ('Pants', 'Organic Cotton', 20, 'Supplier A'), ('T-Shirt', 'Recycled Polyester', 12, 'Supplier B'), ('Shirt', 'Recycled Polyester', 18, 'Supplier B'), ('Pants', 'Hemp', 25, 'Supplier C'); | What is the total quantity of sustainable materials used in production by supplier? | SELECT supplier, SUM(quantity) FROM production GROUP BY supplier; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_temperature (id INT, datetime DATE, temperature FLOAT, sea TEXT); INSERT INTO water_temperature (id, datetime, temperature, sea) VALUES (1, '2022-01-01', 10.5, 'Black Sea'), (2, '2022-02-01', 9.8, 'Black Sea'), (3, '2022-03-01', 8.9, 'Black Sea'); | What is the average water temperature in the Black Sea by month? | SELECT EXTRACT(MONTH FROM datetime) AS month, AVG(temperature) FROM water_temperature WHERE sea = 'Black Sea' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (DonationID INT, DonorID INT, DonationDate DATE, DonationAmount DECIMAL(10,2)); | List all donations made in the month of January 2022 | SELECT * FROM Donations WHERE DonationDate BETWEEN '2022-01-01' AND '2022-01-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE citizen_feedback (state VARCHAR(20), service VARCHAR(20)); INSERT INTO citizen_feedback (state, service) VALUES ('New York', 'public transportation'); INSERT INTO citizen_feedback (state, service) VALUES ('New York', 'public transportation'); INSERT INTO citizen_feedback (state, service) VALUES ('New York', 'public libraries'); INSERT INTO citizen_feedback (state, service) VALUES ('Texas', 'public schools'); | What is the total number of citizen feedback records for public services in the state of New York? | SELECT COUNT(*) FROM citizen_feedback WHERE state = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_usage (id INT PRIMARY KEY, region VARCHAR(20), usage FLOAT); | Delete all records from the 'water_usage' table where the 'region' is 'Southwest' | DELETE FROM water_usage WHERE region = 'Southwest'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ap_projects (organization_name TEXT, region TEXT, budget INTEGER); INSERT INTO ap_projects (organization_name, region, budget) VALUES ('TechCorp', 'Asia-Pacific', 1500000), ('InnoAI', 'Asia-Pacific', 1200000), ('GreenTech', 'Asia-Pacific', 1800000); | What is the average budget spent on AI projects by organizations in the Asia-Pacific region? | SELECT AVG(budget) FROM ap_projects WHERE region = 'Asia-Pacific'; | gretelai_synthetic_text_to_sql |
CREATE TABLE shipments (shipment_id INT, warehouse_id VARCHAR(5), quantity INT); CREATE TABLE warehouses (warehouse_id VARCHAR(5), city VARCHAR(5), state VARCHAR(3)); INSERT INTO shipments VALUES (1, 'LAX', 200), (2, 'NYC', 300), (3, 'LAX', 100), (4, 'JFK', 50); INSERT INTO warehouses VALUES ('LAX', 'Los', ' Angeles'), ('NYC', 'New', ' York'), ('JFK', 'New', ' York'); | What is the total number of shipments for each warehouse? | SELECT warehouses.warehouse_id, COUNT(shipments.shipment_id) FROM warehouses LEFT JOIN shipments ON warehouses.warehouse_id = shipments.warehouse_id GROUP BY warehouses.warehouse_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE Warehouse (item VARCHAR(10), quantity INT); | Add a new record for item 'C303' with a quantity of 120 pieces to the Warehouse table | INSERT INTO Warehouse (item, quantity) VALUES ('C303', 120); | gretelai_synthetic_text_to_sql |
CREATE TABLE fairness_algorithms (transaction_id INT, user_id INT, algorithm_type VARCHAR(255)); INSERT INTO fairness_algorithms (transaction_id, user_id, algorithm_type) VALUES (1, 1001, 'bias-mitigation'), (2, 1002, 'explainability'), (3, 1001, 'bias-mitigation'); CREATE TABLE safety_algorithms (transaction_id INT, user_id INT, algorithm_type VARCHAR(255)); INSERT INTO safety_algorithms (transaction_id, user_id, algorithm_type) VALUES (4, 1003, 'robustness'), (5, 1002, 'transparency'), (6, 1003, 'robustness'); | Find users who have interacted with both fairness and safety algorithms. | SELECT f.user_id FROM fairness_algorithms f INNER JOIN safety_algorithms s ON f.user_id = s.user_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE posts (id INT, user_id INT, content TEXT, post_date DATETIME); | Find the total number of posts in the "ocean_conservation" schema that were published after January 1, 2021, and contain the word "marine". | SELECT COUNT(*) FROM posts WHERE post_date > '2021-01-01' AND content LIKE '%marine%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Port (port_id INT, port_name TEXT, country TEXT); INSERT INTO Port (port_id, port_name, country) VALUES (1, 'Port of Shanghai', 'China'); INSERT INTO Port (port_id, port_name, country) VALUES (2, 'Port of Singapore', 'Singapore'); INSERT INTO Port (port_id, port_name, country) VALUES (3, 'Port of Oakland', 'USA'); CREATE TABLE Shipment (shipment_id INT, container_id INT, port_id INT, shipping_date DATE); CREATE TABLE Container (container_id INT, weight FLOAT); | How many containers were shipped from the Port of Oakland to Canada in the first quarter of 2022? | SELECT COUNT(*) FROM Container c JOIN Shipment s ON c.container_id = s.container_id JOIN Port p ON s.port_id = p.port_id WHERE p.port_name = 'Port of Oakland' AND c.container_id IN (SELECT container_id FROM Shipment WHERE shipping_date >= '2022-01-01' AND shipping_date < '2022-04-01' AND port_id IN (SELECT port_id FROM Port WHERE country = 'Canada')); | gretelai_synthetic_text_to_sql |
CREATE TABLE projects(name VARCHAR(50), location VARCHAR(20), biosensor_used BOOLEAN);INSERT INTO projects(name, location, biosensor_used) VALUES('ProjectX', 'US', true), ('ProjectY', 'Germany', false), ('ProjectZ', 'US', false); | Which genetic research projects did not use biosensor technologies in the US? | SELECT name FROM projects WHERE location = 'US' AND biosensor_used = false; | gretelai_synthetic_text_to_sql |
CREATE TABLE wells (well_id INT, well_name VARCHAR(50), region VARCHAR(20), production FLOAT, year INT); INSERT INTO wells (well_id, well_name, region, production, year) VALUES (1, 'Well A', 'onshore', 100.0, 2024); INSERT INTO wells (well_id, well_name, region, production, year) VALUES (2, 'Well B', 'offshore', 200.0, 2023); INSERT INTO wells (well_id, well_name, region, production, year) VALUES (3, 'Well C', 'sahara', 170.0, 2024); | What is the average production for wells in the 'sahara' region in 2024? | SELECT AVG(production) FROM wells WHERE region = 'sahara' AND year = 2024; | gretelai_synthetic_text_to_sql |
CREATE TABLE Meditation (MemberID INT, Duration INT); INSERT INTO Meditation (MemberID, Duration) VALUES (1, 30), (1, 45); | Find the max duration of meditation sessions for each member. | SELECT MemberID, MAX(Duration) FROM Meditation GROUP BY MemberID; | gretelai_synthetic_text_to_sql |
CREATE TABLE world_series (year INT, attendance INT); CREATE TABLE super_bowl (year INT, attendance INT); | What is the difference in attendance between the World Series and the Super Bowl in the last 10 years? | SELECT YEAR(world_series.year), AVG(world_series.attendance) - AVG(super_bowl.attendance) as attendance_difference FROM world_series, super_bowl WHERE world_series.year BETWEEN 2012 AND 2021 AND super_bowl.year BETWEEN 2012 AND 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE Shipments (id INT, source VARCHAR(50), destination VARCHAR(50), weight FLOAT, ship_date DATE); INSERT INTO Shipments (id, source, destination, weight, ship_date) VALUES (18, 'Brazil', 'Germany', 600, '2022-07-01'); INSERT INTO Shipments (id, source, destination, weight, ship_date) VALUES (19, 'Argentina', 'France', 800, '2022-07-15'); INSERT INTO Shipments (id, source, destination, weight, ship_date) VALUES (20, 'Colombia', 'Spain', 1000, '2022-07-30'); | What was the total weight of shipments from South America to Europe in July 2022? | SELECT SUM(weight) FROM Shipments WHERE (source = 'Brazil' OR source = 'Argentina' OR source = 'Colombia') AND (destination = 'Germany' OR destination = 'France' OR destination = 'Spain') AND ship_date = '2022-07-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE researchers (researcher_id INT PRIMARY KEY, name VARCHAR(255), region VARCHAR(255), experience INT); | Insert a new record into the "researchers" table with the following information: "researcher_id": 301, "name": "Amina Ali", "region": "Asia", "experience": 5. | INSERT INTO researchers (researcher_id, name, region, experience) VALUES (301, 'Amina Ali', 'Asia', 5); | gretelai_synthetic_text_to_sql |
CREATE TABLE ca_events (id INT, num_attendees INT, avg_age FLOAT); CREATE TABLE ca_event_types (id INT, event_type VARCHAR(15)); INSERT INTO ca_events (id, num_attendees, avg_age) VALUES (1, 1200, 35.5), (2, 1800, 40.2); INSERT INTO ca_event_types (id, event_type) VALUES (1, 'Dance'), (2, 'Music'); | What is the average age of attendees at arts events in California and how many unique events have there been? | SELECT AVG(ce.avg_age), COUNT(DISTINCT cet.event_type) FROM ca_events ce INNER JOIN ca_event_types cet ON TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE construction_labor (id INT, worker_name VARCHAR(50), hours_worked INT, project_type VARCHAR(20), state VARCHAR(20)); INSERT INTO construction_labor (id, worker_name, hours_worked, project_type, state) VALUES (1, 'John Doe', 100, 'Sustainable', 'California'); INSERT INTO construction_labor (id, worker_name, hours_worked, project_type, state) VALUES (2, 'Jane Doe', 80, 'Sustainable', 'California'); | Calculate the average number of labor hours worked per sustainable project in the state of California. | SELECT AVG(hours_worked) FROM (SELECT SUM(hours_worked) as hours_worked FROM construction_labor WHERE project_type = 'Sustainable' AND state = 'California' GROUP BY project_type, state) as subquery; | gretelai_synthetic_text_to_sql |
CREATE TABLE vulnerabilities (id INT, name VARCHAR(255), severity VARCHAR(50), description TEXT, affected_products TEXT, date_discovered DATE); | What is the total number of vulnerabilities in the 'vulnerabilities' table? | SELECT COUNT(*) FROM vulnerabilities; | gretelai_synthetic_text_to_sql |
CREATE TABLE garment_sales (id INT PRIMARY KEY, garment_id INT, store_id INT, sale_date DATE, quantity INT, price DECIMAL(5,2)); INSERT INTO garment_sales (id, garment_id, store_id, sale_date, quantity, price) VALUES (1, 1001, 101, '2022-01-01', 5, 150.00), (2, 1002, 101, '2022-01-02', 10, 120.00), (3, 1003, 102, '2022-01-03', 8, 180.00); | Which stores have generated a total revenue of more than $50,000 between January 1, 2022 and January 14, 2022? | SELECT store_id, SUM(quantity * price) AS total_revenue FROM garment_sales WHERE sale_date BETWEEN '2022-01-01' AND '2022-01-14' GROUP BY store_id HAVING total_revenue > 50000; | gretelai_synthetic_text_to_sql |
CREATE TABLE farm (id INT, name VARCHAR(255), type VARCHAR(255), region VARCHAR(255)); INSERT INTO farm (id, name, type, region) VALUES (1, 'Smith Farm', 'organic', 'Midwest'), (2, 'Johnson Farm', 'conventional', 'South'), (3, 'Brown Farm', 'organic', 'Midwest'), (4, 'Davis Farm', 'conventional', 'West'); | List the names and types of all farms in the 'farming' database that are located in a specific region. | SELECT name, type FROM farm WHERE region = 'Midwest'; | gretelai_synthetic_text_to_sql |
CREATE TABLE textile_supplier (id INT, name TEXT, qty_sustainable_material FLOAT, q2_2021_revenue FLOAT); | Which textile suppliers provided the most sustainable materials in Q2 of 2021? | SELECT name, SUM(qty_sustainable_material) AS total_sustainable_material FROM textile_supplier WHERE EXTRACT(QUARTER FROM date) = 2 AND YEAR(date) = 2021 GROUP BY name ORDER BY total_sustainable_material DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotels (hotel_id INT, name TEXT, city TEXT, ai_concierge BOOLEAN); | What is the number of hotels in 'Dubai' with an AI concierge? | SELECT city, COUNT(*) as num_hotels FROM hotels WHERE city = 'Dubai' AND ai_concierge = TRUE GROUP BY city; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, Gender VARCHAR(10), Department VARCHAR(20)); INSERT INTO Employees (EmployeeID, Gender, Department) VALUES (1, 'Female', 'Sales'), (2, 'Male', 'IT'), (3, 'Female', 'IT'), (4, 'Male', 'Finance'); | How many female employees are there in the Sales department? | SELECT COUNT(*) FROM Employees WHERE Gender = 'Female' AND Department = 'Sales'; | gretelai_synthetic_text_to_sql |
CREATE TABLE hiring (id INT, employee_id INT, hire_date DATE, department VARCHAR(255)); INSERT INTO hiring (id, employee_id, hire_date, department) VALUES (1, 101, '2020-01-02', 'HR'); INSERT INTO hiring (id, employee_id, hire_date, department) VALUES (2, 102, '2019-12-20', 'IT'); | Find the number of employees hired in 2020 from the 'hiring' table | SELECT COUNT(*) FROM hiring WHERE YEAR(hire_date) = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE food_suppliers (supplier_id INT PRIMARY KEY, name VARCHAR(255), rating INT); | Calculate the average rating of food suppliers in 'Florida' | SELECT AVG(rating) FROM food_suppliers WHERE state = 'Florida'; | gretelai_synthetic_text_to_sql |
CREATE TABLE dances (id INT, name VARCHAR(50), description VARCHAR(100), origin_country VARCHAR(50)); | Insert records of new traditional dances | INSERT INTO dances (id, name, description, origin_country) VALUES (5, 'Sankirtana', 'Manipuri religious dance drama', 'India'), (6, 'Hula', 'Hawaiian storytelling dance', 'USA') | gretelai_synthetic_text_to_sql |
CREATE TABLE fish_farms (id INT, name TEXT, location TEXT, water_type TEXT, water_temperature DECIMAL(5,2)); INSERT INTO fish_farms (id, name, location, water_type, water_temperature) VALUES (1, 'Tropical Reef Aquaculture', 'Indonesia', 'tropical', 28.5), (2, 'Atlantic Salmon Farm', 'Norway', 'cold', 8.0); | What is the average water temperature in February for tropical fish farms? | SELECT AVG(water_temperature) FROM fish_farms WHERE EXTRACT(MONTH FROM date) = 2 AND water_type = 'tropical'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Suppliers (SupplierID int, SupplierName varchar(50)); INSERT INTO Suppliers VALUES (1, 'SupplierA'), (2, 'SupplierB'); CREATE TABLE Sales (SaleID int, SupplierID int, TimberVolume float, SaleYear int); INSERT INTO Sales VALUES (1, 1, 500, 2020), (2, 1, 700, 2019), (3, 2, 600, 2020); | What is the total volume of timber sold by each supplier in a specific year? | SELECT Suppliers.SupplierName, Sales.SaleYear, SUM(Sales.TimberVolume) as TotalTimberVolume FROM Suppliers INNER JOIN Sales ON Suppliers.SupplierID = Sales.SupplierID GROUP BY Suppliers.SupplierName, Sales.SaleYear; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (donor_id INT, donation_amount DECIMAL(10, 2), cause_category VARCHAR(255)); INSERT INTO donations (donor_id, donation_amount, cause_category) VALUES (1, 5000.00, 'Education'), (2, 3000.00, 'Health'), (3, 7000.00, 'Environment'); | What is the distribution of donation amounts by cause category, ranked by total donation amount? | SELECT cause_category, SUM(donation_amount) AS total_donation, ROW_NUMBER() OVER (ORDER BY SUM(donation_amount) DESC) AS rank FROM donations GROUP BY cause_category; | gretelai_synthetic_text_to_sql |
CREATE TABLE GamePlayers (GameID int, GameName varchar(50), Category varchar(50), PlayerID int); | What is the number of players who have played each game in the "RPG" category? | SELECT Category, COUNT(DISTINCT PlayerID) OVER(PARTITION BY Category) as PlayersCount FROM GamePlayers; | gretelai_synthetic_text_to_sql |
CREATE TABLE LegalTech (case_id INT, case_status VARCHAR(10)); INSERT INTO LegalTech (case_id, case_status) VALUES (1, 'open'), (2, 'closed'), (3, 'in_progress'), (4, 'closed'); | Show the 'case_status' for cases in the 'LegalTech' table where the 'case_status' is not 'closed' | SELECT DISTINCT case_status FROM LegalTech WHERE case_status != 'closed'; | gretelai_synthetic_text_to_sql |
CREATE TABLE alerts (id INT, rule VARCHAR(255), alert_date DATE); | How many times was the rule 'Unusual Outbound Traffic' triggered in the last week? | SELECT COUNT(*) FROM alerts WHERE rule = 'Unusual Outbound Traffic' AND alert_date >= DATEADD(week, -1, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (id INT, donor_id INT, program_id INT, donation_amount DECIMAL, donation_date DATE); | What is the average donation amount per program by donors from the US? | SELECT programs.name as program_name, AVG(donations.donation_amount) as avg_donation_amount FROM donations INNER JOIN donors ON donations.donor_id = donors.id INNER JOIN programs ON donations.program_id = programs.id WHERE donors.country = 'US' GROUP BY programs.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE startup_founders (id INT PRIMARY KEY, name VARCHAR(255), veteran_status VARCHAR(255), industry VARCHAR(255), total_funding FLOAT); | What is the total funding for startups founded by veterans? | SELECT SUM(total_funding) FROM startup_founders WHERE veteran_status = 'yes'; | gretelai_synthetic_text_to_sql |
CREATE TABLE policies (id INT, state VARCHAR(2), policy_type VARCHAR(20), sale_date DATE); INSERT INTO policies (id, state, policy_type, sale_date) VALUES (1, 'NY', 'Home', '2021-05-15'), (2, 'NY', 'Auto', '2022-06-23'), (3, 'TX', 'Home', '2021-11-28'); | How many home insurance policies were sold in New York in the last year? | SELECT COUNT(*) FROM policies WHERE state = 'NY' AND policy_type = 'Home' AND YEAR(sale_date) = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE makeup_products(product_name TEXT, rating INTEGER, cruelty_free BOOLEAN, sale_country TEXT); INSERT INTO makeup_products(product_name, rating, cruelty_free, sale_country) VALUES ('Liquid Eyeliner', 5, true, 'US'); | List all cruelty-free makeup products with a 4-star rating or higher sold in the US. | SELECT product_name FROM makeup_products WHERE rating >= 4 AND cruelty_free = true AND sale_country = 'US'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Volunteers (VolunteerID INT, VolunteerName TEXT, ServiceHours INT, City TEXT); INSERT INTO Volunteers (VolunteerID, VolunteerName, ServiceHours, City) VALUES (1, 'Alice Johnson', 50, 'Chicago'); INSERT INTO Volunteers (VolunteerID, VolunteerName, ServiceHours, City) VALUES (2, 'Bob Brown', 75, 'San Francisco'); INSERT INTO Volunteers (VolunteerID, VolunteerName, ServiceHours, City) VALUES (3, 'Charlie Davis', 30, 'Chicago'); | What is the average number of hours served by volunteers in the city of Chicago? | SELECT AVG(ServiceHours) FROM Volunteers WHERE City = 'Chicago'; | gretelai_synthetic_text_to_sql |
CREATE TABLE AthleteWellbeing (AthleteID INT, ProgramName VARCHAR(50)); CREATE TABLE AthleteInjuries (AthleteID INT, InjuryDate DATE); | List all athletes who participated in the wellbeing program but did not have any injuries in the last season. | SELECT AthleteID FROM AthleteWellbeing WHERE AthleteID NOT IN (SELECT AthleteID FROM AthleteInjuries WHERE InjuryDate >= DATEADD(YEAR, -1, GETDATE())); | gretelai_synthetic_text_to_sql |
CREATE TABLE BankruptcyCases (CaseID INT, CaseType VARCHAR(20), BillingAmount DECIMAL(10,2)); INSERT INTO BankruptcyCases (CaseID, CaseType, BillingAmount) VALUES (1, 'Bankruptcy', 8000.00), (2, 'Bankruptcy', 4000.00); | What is the maximum billing amount for cases in the 'Bankruptcy' case type? | SELECT MAX(BillingAmount) FROM BankruptcyCases WHERE CaseType = 'Bankruptcy'; | gretelai_synthetic_text_to_sql |
CREATE TABLE weddell_sea_species (species_name TEXT, habitat TEXT); INSERT INTO weddell_sea_species (species_name, habitat) VALUES ('Weddell Seal', 'Weddell Sea'), ('Crabeater Seal', 'Weddell Sea'), ('Antarctic Krill', 'Weddell Sea'); | What is the number of marine species observed in the Weddell Sea? | SELECT COUNT(*) FROM weddell_sea_species; | gretelai_synthetic_text_to_sql |
CREATE TABLE Artists (ArtistID int, ArtistName text, Specialization text); INSERT INTO Artists (ArtistID, ArtistName, Specialization) VALUES (1, 'Amina Ahmed', 'Indian Miniature Painting'), (2, 'Bertina Lopes', 'Mozambican Modern Art'), (3, 'Fernando de Szyszlo', 'Peruvian Abstract Art'); | Find artists who have mastered traditional arts from Africa, Asia, and South America. | SELECT ArtistName FROM Artists WHERE Specialization LIKE '%African%' INTERSECT SELECT ArtistName FROM Artists WHERE Specialization LIKE '%Asian%' INTERSECT SELECT ArtistName FROM Artists WHERE Specialization LIKE '%South% American%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE EmployeeData (EmployeeID INT, Department VARCHAR(50), Salary DECIMAL(10, 2)); INSERT INTO EmployeeData VALUES (1, 'IT', 50000); INSERT INTO EmployeeData VALUES (2, 'HR', 45000); INSERT INTO EmployeeData VALUES (3, 'Finance', 60000); INSERT INTO EmployeeData VALUES (4, 'IT', 40000); | Delete all employee records with a salary below the minimum for their respective departments. | DELETE FROM EmployeeData WHERE Salary < (SELECT MIN(Salary) FROM EmployeeData e2 WHERE EmployeeData.Department = e2.Department); | gretelai_synthetic_text_to_sql |
CREATE TABLE environment (mine_id INT, impact_score DECIMAL); INSERT INTO environment (mine_id, impact_score) VALUES (1, 4.2), (2, 4.8), (3, 4.5), (4, 3.9), (5, 5.1); | What is the environmental impact score per mine? | SELECT mine_id, impact_score FROM environment; | gretelai_synthetic_text_to_sql |
CREATE TABLE cultural_sites (site_name VARCHAR(255), continent VARCHAR(64), visitors INT); INSERT INTO cultural_sites (site_name, continent, visitors) VALUES ('Acropolis', 'Europe', 3000), ('Taj Mahal', 'Asia', 5000), ('Pyramids of Giza', 'Africa', 4000), ('Angkor Wat', 'Asia', 6000), ('Machu Picchu', 'South America', 2000), ('Forbidden City', 'Asia', 7000), ('Eiffel Tower', 'Europe', 8000), ('Sphinx', 'Africa', 3000); | What is the total number of tourists visiting cultural heritage sites in Europe, Asia, and Africa, grouped by continent? | SELECT continent, SUM(visitors) as total_visitors FROM cultural_sites GROUP BY continent; | gretelai_synthetic_text_to_sql |
CREATE TABLE aircraft (maker TEXT, model TEXT, mass INTEGER); INSERT INTO aircraft (maker, model, mass) VALUES ('Boeing', '747', 350000), ('Boeing', '777', 400000), ('Airbus', 'A320', 280000), ('Airbus', 'A350', 320000); | What is the total mass of aircraft manufactured by Airbus? | SELECT SUM(mass) FROM aircraft WHERE maker = 'Airbus'; | gretelai_synthetic_text_to_sql |
CREATE TABLE manufacturing_processes (process_id INT, name TEXT); CREATE TABLE waste_generation (process_id INT, waste_amount INT, date DATE); | Show the total amount of waste generated by each manufacturing process in the past year. | SELECT manufacturing_processes.name, SUM(waste_generation.waste_amount) FROM manufacturing_processes INNER JOIN waste_generation ON manufacturing_processes.process_id = waste_generation.process_id WHERE waste_generation.date > DATEADD(year, -1, GETDATE()) GROUP BY manufacturing_processes.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers (subscriber_id INT, join_date DATE); INSERT INTO subscribers (subscriber_id, join_date) VALUES (1, '2021-01-05'), (2, '2021-03-17'), (3, '2020-12-28'); CREATE TABLE usage (subscriber_id INT, data_usage INT, usage_date DATE); INSERT INTO usage (subscriber_id, data_usage, usage_date) VALUES (1, 3000, '2021-02-01'), (1, 4000, '2021-03-01'), (2, 2500, '2021-03-15'), (2, 2800, '2021-04-15'), (3, 3500, '2021-01-10'), (3, 4500, '2021-02-10'); | What is the average monthly data usage for customers who joined in Q1 2021? | SELECT AVG(data_usage) FROM usage JOIN subscribers ON usage.subscriber_id = subscribers.subscriber_id WHERE YEAR(join_date) = 2021 AND QUARTER(join_date) = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE mine (name VARCHAR(255), location VARCHAR(255)); CREATE TABLE gold_mine_production (mine_name VARCHAR(255), quantity INT); CREATE TABLE silver_mine_production (mine_name VARCHAR(255), quantity INT); | Find the average gold and silver production quantities for each mine, excluding mines with missing data. | SELECT gold_mine_production.mine_name, AVG(gold_mine_production.quantity) AS avg_gold_quantity, AVG(silver_mine_production.quantity) AS avg_silver_quantity FROM gold_mine_production INNER JOIN silver_mine_production ON gold_mine_production.mine_name = silver_mine_production.mine_name GROUP BY gold_mine_production.mine_name HAVING COUNT(*) = 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE Investments (id INT, company_id INT, investment_amount INT, investment_date DATE); | Insert a new investment into the Investments table. | INSERT INTO Investments (id, company_id, investment_amount, investment_date) VALUES (3, 1, 3000000, '2022-03-01'); | gretelai_synthetic_text_to_sql |
CREATE TABLE charging_stations (id INT, cs_type VARCHAR(50), cs_city VARCHAR(50), cs_count INT); | Calculate the total number of EV charging stations in Berlin | SELECT SUM(cs_count) AS total_cs_count FROM charging_stations WHERE cs_city = 'Berlin' AND cs_type = 'EV'; | gretelai_synthetic_text_to_sql |
CREATE TABLE cause (id INT PRIMARY KEY, name VARCHAR(255));CREATE TABLE donation (id INT PRIMARY KEY, cause_id INT, donor_id INT); | Which causes have the most unique donors? | SELECT c.name, COUNT(DISTINCT d.donor_id) AS total_donors FROM cause c JOIN donation d ON c.id = d.cause_id GROUP BY c.id ORDER BY total_donors DESC LIMIT 10; | gretelai_synthetic_text_to_sql |
CREATE TABLE players (player_name VARCHAR(255), sport VARCHAR(255)); INSERT INTO players (player_name, sport) VALUES ('Federer', 'Tennis'); INSERT INTO players (player_name, sport) VALUES ('Nadal', 'Tennis'); CREATE TABLE wins (player_name VARCHAR(255), match_id INT); INSERT INTO wins (player_name, match_id) VALUES ('Federer', 1); INSERT INTO wins (player_name, match_id) VALUES ('Federer', 2); INSERT INTO wins (player_name, match_id) VALUES ('Nadal', 3); INSERT INTO wins (player_name, match_id) VALUES ('Nadal', 4); | Show tennis players who have won more than 10 matches | SELECT player_name FROM (SELECT player_name, COUNT(*) as wins FROM wins GROUP BY player_name) AS subquery WHERE wins > 10; | gretelai_synthetic_text_to_sql |
CREATE TABLE npos (id INT, name VARCHAR(50), sector VARCHAR(50), country VARCHAR(50), total_donations FLOAT); INSERT INTO npos (id, name, sector, country, total_donations) VALUES (1, 'UNESCO', 'Education', 'Nigeria', 100000), (2, 'Save the Children', 'Education', 'Kenya', 200000); | What is the total amount donated to education-focused NPOs in Africa in the last 2 years? | SELECT SUM(total_donations) FROM npos WHERE sector = 'Education' AND country IN ('Nigeria', 'Kenya', 'South Africa', 'Egypt', 'Algeria') AND total_donations BETWEEN '2020-01-01' AND '2021-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE schools (id INT, name VARCHAR(50), division VARCHAR(50), age INT, enrollment FLOAT); INSERT INTO schools (id, name, division, age, enrollment) VALUES (1, 'School A', 'Education', 10, 500), (2, 'School B', 'Education', 15, 700), (3, 'School C', 'Education', 12, 600); | What is the average age of all schools and their current enrollment levels in the education division? | SELECT AVG(age), enrollment FROM schools WHERE division = 'Education' GROUP BY enrollment; | gretelai_synthetic_text_to_sql |
CREATE VIEW Eco_Friendly_Products AS SELECT product_id, product_name, environmental_impact_score FROM Products; INSERT INTO Products (product_id, product_name, transportation_emissions, production_emissions, packaging_emissions, labor_conditions_score, environmental_impact_score) VALUES (1101, 'Jacket', 1, 2, 1, 5, 2); INSERT INTO Products (product_id, product_name, transportation_emissions, production_emissions, packaging_emissions, labor_conditions_score, environmental_impact_score) VALUES (1102, 'Backpack', 2, 3, 2, 6, 1); INSERT INTO Products (product_id, product_name, transportation_emissions, production_emissions, packaging_emissions, labor_conditions_score, environmental_impact_score) VALUES (1103, 'Hat', 3, 4, 3, 7, 0); | What is the maximum environmental impact score for products in the Eco_Friendly_Products view? | SELECT MAX(environmental_impact_score) FROM Eco_Friendly_Products; | gretelai_synthetic_text_to_sql |
CREATE TABLE cosmetics (product_id INT, product_name VARCHAR(100), subcategory VARCHAR(50), vegan BOOLEAN); INSERT INTO cosmetics (product_id, product_name, subcategory, vegan) VALUES (1, 'Lipstick', 'Matte', true), (2, 'Foundation', 'Liquid', false); | What is the percentage of vegan cosmetics by subcategory? | SELECT subcategory, COUNT(*) FILTER (WHERE vegan = true) * 100.0 / COUNT(*) AS percentage_vegan_cosmetics FROM cosmetics WHERE category = 'Cosmetics' GROUP BY subcategory; | gretelai_synthetic_text_to_sql |
CREATE TABLE property_sizes (id INT, size INT, property_id INT, measurement_time TIMESTAMP); INSERT INTO property_sizes (id, size, property_id, measurement_time) VALUES (1, 1500, 1, '2022-01-01 00:00:00'), (2, 1600, 1, '2022-02-01 00:00:00'), (3, 1800, 2, '2022-01-01 00:00:00'); | What is the change in property size for each property in the USA over time? | SELECT property_id, size, measurement_time, LEAD(size) OVER (PARTITION BY property_id ORDER BY measurement_time) - size as size_change FROM property_sizes WHERE country = 'USA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Auto_Shows (id INT, manufacturer VARCHAR(50), show_name VARCHAR(50), year INT); CREATE TABLE Manufacturers (id INT, name VARCHAR(50)); | What is the total number of auto shows attended by a specific manufacturer? | SELECT COUNT(DISTINCT show_name) FROM Auto_Shows JOIN Manufacturers ON Auto_Shows.manufacturer = Manufacturers.name WHERE Manufacturers.name = 'Tesla'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ocean_acidity (date DATE, location TEXT, acidity FLOAT); CREATE TABLE sea_surface_temperature (date DATE, location TEXT, temperature FLOAT); | What is the maximum ocean acidity level and the average sea surface temperature for each month in the Pacific Ocean over the past decade? | SELECT MONTH(ocean_acidity.date) AS month, MAX(ocean_acidity.acidity) AS max_acidity, AVG(sea_surface_temperature.temperature) AS avg_temperature FROM ocean_acidity INNER JOIN sea_surface_temperature ON ocean_acidity.date = sea_surface_temperature.date WHERE ocean_acidity.location = 'Pacific Ocean' AND sea_surface_temperature.location = 'Pacific Ocean' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE habitat_preservation (id INT, animal_name VARCHAR(255), preserve_name VARCHAR(255)); | What is the total number of animals in the habitat_preservation table that have been relocated to a specific preserve? | SELECT COUNT(animal_name) FROM habitat_preservation WHERE preserve_name = 'Yellowstone National Park'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (org_name TEXT, donation_amount INTEGER, donation_date DATE); INSERT INTO Donations (org_name, donation_amount, donation_date) VALUES ('Organization A', 5000, '2020-01-01'); INSERT INTO Donations (org_name, donation_amount, donation_date) VALUES ('Organization B', 7000, '2020-02-15'); | What was the total amount of donations received by each organization in 2020? | SELECT org_name, SUM(donation_amount) FROM Donations WHERE donation_date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY org_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE revenues (line VARCHAR(10), revenue FLOAT); INSERT INTO revenues (line, revenue) VALUES ('red', 15000.00), ('blue', 20000.00), ('green', 12000.00); | What is the total revenue for each line? | SELECT line, SUM(revenue) FROM revenues GROUP BY line; | gretelai_synthetic_text_to_sql |
CREATE TABLE content (id INT, title VARCHAR(50), location VARCHAR(50), literacy_score INT); INSERT INTO content (id, title, location, literacy_score) VALUES (1, 'Article 1', 'Asia', 65), (2, 'Article 2', 'Europe', 75), (3, 'News 1', 'Asia', 80); | What is the average media literacy score for content published in 'Asia'? | SELECT AVG(literacy_score) FROM content WHERE location = 'Asia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE fan_attendance (id INT, fan_id INT, team VARCHAR(50), conference VARCHAR(50), game_date DATE); | How many unique fans attended games of teams in the eastern_conference in the fan_attendance table? | SELECT COUNT(DISTINCT fan_id) FROM fan_attendance WHERE conference = 'eastern_conference'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Concerts (id INT, title VARCHAR(255), location VARCHAR(255), viewers INT); | Find the average viewership for concerts held in Asia. | SELECT AVG(viewers) FROM Concerts WHERE location LIKE '%Asia%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE communication_campaign (campaign_id INT, campaign_name TEXT, sector TEXT); INSERT INTO communication_campaign (campaign_id, campaign_name, sector) VALUES (1, 'European Climate Communication Initiative', 'Public'); | What is the total number of climate communication campaigns targeting the public sector in Europe? | SELECT COUNT(*) FROM communication_campaign WHERE sector = 'Public' AND region = 'Europe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE planets (id INT PRIMARY KEY, name VARCHAR(50), distance_to_sun FLOAT); INSERT INTO planets (id, name, distance_to_sun) VALUES (1, 'Mercury', 0.39), (2, 'Venus', 0.72), (3, 'Earth', 1), (4, 'Mars', 1.52); | What is the name of the planet with id 3? | SELECT name FROM planets WHERE id = 3; | 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.