context stringlengths 11 9.12k | question stringlengths 0 1.06k | SQL stringlengths 2 4.44k | source stringclasses 28 values |
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CREATE TABLE public.ambulances (id SERIAL PRIMARY KEY, city VARCHAR(255), num_ambulances INTEGER); INSERT INTO public.ambulances (city, num_ambulances) VALUES ('Los Angeles', 300), ('New York', 500), ('Chicago', 400); | What is the total number of ambulances in the city of Los Angeles? | SELECT num_ambulances FROM public.ambulances WHERE city = 'Los Angeles'; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers (id INT, service VARCHAR(10), region VARCHAR(10)); INSERT INTO subscribers (id, service, region) VALUES (1, 'broadband', 'West'), (2, 'mobile', 'West'); CREATE TABLE speeds (subscriber_id INT, connection_speed INT); INSERT INTO speeds (subscriber_id, connection_speed) VALUES (1, 550), (2, 450); | What is the minimum connection speed in Mbps for broadband customers in the West region? | SELECT MIN(connection_speed) FROM speeds JOIN subscribers ON speeds.subscriber_id = subscribers.id WHERE subscribers.service = 'broadband' AND subscribers.region = 'West'; | gretelai_synthetic_text_to_sql |
CREATE TABLE shipment_details (shipment_id INT, package_id INT, weight DECIMAL(5,2), destination_state TEXT); | What is the total weight of packages shipped to California from the 'shipment_details' table? | SELECT SUM(weight) FROM shipment_details WHERE destination_state = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE local_events (event_id INT, event_name TEXT, location TEXT, cause TEXT); INSERT INTO local_events (event_id, event_name, location, cause) VALUES (1, 'Festival of Diversity', 'India', 'Women''s Empowerment'), (2, 'Sustainable Fashion Show', 'Mexico', 'Sustainable Development'); | How many local events in India and Mexico support women's empowerment and sustainable development? | SELECT COUNT(*) FROM local_events WHERE location IN ('India', 'Mexico') AND cause IN ('Women''s Empowerment', 'Sustainable Development'); | gretelai_synthetic_text_to_sql |
CREATE TABLE bridges (bridge_id INT, bridge_name VARCHAR(50), location VARCHAR(50), length DECIMAL(10,2), construction_date DATE); | List all the bridges built before 2010, sorted by construction date. | SELECT * FROM bridges WHERE construction_date < '2010-01-01' ORDER BY construction_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE client_transactions (transaction_id INT, client_id INT, amount DECIMAL(10, 2), transaction_date DATE); INSERT INTO client_transactions (transaction_id, client_id, amount, transaction_date) VALUES (1, 1, 50.00, '2022-01-01'), (2, 1, 100.00, '2022-01-15'), (3, 2, 75.00, '2022-02-03'), (4, 3, 120.00, '2022-03-01'); CREATE TABLE clients (client_id INT, name VARCHAR(50), region VARCHAR(50)); INSERT INTO clients (client_id, name, region) VALUES (1, 'Thomas', 'Southeast'), (2, 'Patel', 'Northeast'), (3, 'Li', 'Southeast'); | What is the total transaction amount per month for clients in the Southeast region? | SELECT DATE_FORMAT(transaction_date, '%Y-%m') AS month, SUM(amount) FROM client_transactions ct JOIN clients cl ON ct.client_id = cl.client_id WHERE cl.region = 'Southeast' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id int, material varchar(20)); INSERT INTO products (product_id, material) VALUES (1, 'organic cotton'), (2, 'recycled polyester'), (3, 'organic cotton'), (4, 'recycled cotton'); | How many products are made from each type of material? | SELECT material, COUNT(*) FROM products GROUP BY material; | gretelai_synthetic_text_to_sql |
CREATE TABLE warehouses (id INT, name TEXT, region TEXT); INSERT INTO warehouses (id, name, region) VALUES (1, 'Warehouse I', 'EMEA'), (2, 'Warehouse J', 'APAC'); | Calculate the average weight of packages shipped from warehouses in the 'Americas' and 'APAC' regions | SELECT AVG(weight) FROM packages JOIN warehouses ON packages.warehouse_id = warehouses.id WHERE region IN ('Americas', 'APAC'); | gretelai_synthetic_text_to_sql |
CREATE TABLE physical_inactivity (age_group VARCHAR(10), pct_inactive FLOAT); INSERT INTO physical_inactivity (age_group, pct_inactive) VALUES ('0-9', 25), ('10-19', 30), ('20-29', 40), ('30-39', 45), ('40-49', 50); | What is the percentage of the population that is physically inactive, by age group? | SELECT age_group, (SUM(pct_inactive) / COUNT(age_group) * 100) as pct_inactive FROM physical_inactivity GROUP BY age_group; | gretelai_synthetic_text_to_sql |
CREATE TABLE animal_rehabilitation (animal_id INT, species VARCHAR(255), admission_date DATE); INSERT INTO animal_rehabilitation (animal_id, species, admission_date) VALUES (1, 'Tiger', '2020-01-01'), (2, 'Tiger', '2019-01-01'), (3, 'Elephant', '2020-01-01'); | How many animals of each species were admitted to the 'animal_rehabilitation' table in the year 2020? | SELECT species, COUNT(animal_id) as count_2020 FROM animal_rehabilitation WHERE YEAR(admission_date) = 2020 GROUP BY species; | gretelai_synthetic_text_to_sql |
CREATE TABLE bioprocess(id INT, investment VARCHAR(50), date DATE, amount DECIMAL(10,2)); INSERT INTO bioprocess VALUES (1, 'InvestmentA', '2021-04-15', 2000000.00), (2, 'InvestmentB', '2021-06-30', 1500000.00), (3, 'InvestmentC', '2021-02-28', 2500000.00); | What is the total investment in bioprocess engineering in H1 2021? | SELECT SUM(amount) FROM bioprocess WHERE date BETWEEN '2021-01-01' AND '2021-06-30'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ArtCollections (CollectionID INT PRIMARY KEY, CollectionName VARCHAR(50), ArtistID INT, FOREIGN KEY (ArtistID) REFERENCES Artists(ArtistID)); INSERT INTO ArtCollections (CollectionID, CollectionName, ArtistID) VALUES (1, 'Asian Art Collection', 1); | What is the name of artists who have contributed to the 'Asian Art Collection'? | SELECT Artists.ArtistName FROM Artists INNER JOIN ArtCollections ON Artists.ArtistID = ArtCollections.ArtistID WHERE ArtCollections.CollectionName = 'Asian Art Collection'; | gretelai_synthetic_text_to_sql |
CREATE TABLE unions (id INT, name VARCHAR(255), state VARCHAR(255)); CREATE TABLE union_industry (id INT, union_id INT, industry VARCHAR(255), workers INT); INSERT INTO unions (id, name, state) VALUES (1, 'TEAMSTERS', 'New York'); INSERT INTO union_industry (id, union_id, industry, workers) VALUES (1, 1, 'Transportation', 8000); | What is the average number of workers in each union by industry in New York? | SELECT ui.industry, AVG(ui.workers) as avg_workers FROM union_industry ui JOIN unions u ON ui.union_id = u.id WHERE u.state = 'New York' GROUP BY ui.industry; | gretelai_synthetic_text_to_sql |
CREATE TABLE Programs (ProgramID INT, ProgramName VARCHAR(50)); INSERT INTO Programs (ProgramID, ProgramName) VALUES (1, 'Education'), (2, 'Health'), (3, 'Environment'); CREATE TABLE Donations (DonationID INT, ProgramID INT); INSERT INTO Donations (DonationID, ProgramID) VALUES (1, 1), (2, 1), (3, 2); | Which programs do not have any donations? | SELECT ProgramID, ProgramName FROM Programs WHERE ProgramID NOT IN (SELECT ProgramID FROM Donations); | gretelai_synthetic_text_to_sql |
CREATE TABLE mobile_subscribers (subscriber_id INT, subscription_type VARCHAR(50)); INSERT INTO mobile_subscribers (subscriber_id, subscription_type) VALUES (1, 'Postpaid'), (2, 'Prepaid'); | What is the total number of mobile subscribers for each mobile subscription type? | SELECT subscription_type, COUNT(*) FROM mobile_subscribers GROUP BY subscription_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE nutrition (country VARCHAR(255), calories INT, meal_time TIME); INSERT INTO nutrition (country, calories, meal_time) VALUES ('USA', 800, 'Breakfast'), ('USA', 1200, 'Lunch'), ('USA', 500, 'Dinner'); | What is the difference in calorie intake between the earliest and latest meal times in the 'nutrition' table? | SELECT MAX(meal_time_calories) - MIN(meal_time_calories) as calorie_difference FROM (SELECT meal_time, SUM(calories) as meal_time_calories FROM nutrition GROUP BY meal_time) as subquery; | gretelai_synthetic_text_to_sql |
CREATE TABLE Vessels (Id INT, Name VARCHAR(50)); CREATE TABLE Cargo (VesselId INT, Weight FLOAT); INSERT INTO Vessels (Id, Name) VALUES (1, 'Vessel1'), (2, 'Vessel2'), (3, 'Vessel3'); INSERT INTO Cargo (VesselId, Weight) VALUES (1, 15000), (1, 12000), (2, 18000), (3, 20000), (3, 25000); | Find the vessel with the highest total cargo weight | SELECT Vessels.Name, SUM(Cargo.Weight) AS TotalCargoWeight FROM Vessels JOIN Cargo ON Vessels.Id = Cargo.VesselId GROUP BY Vessels.Id ORDER BY TotalCargoWeight DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE CountryDefenseDiplomacy (id INT, country VARCHAR(50), num_operations INT); | What is the minimum number of defense diplomacy operations participated in by each country? | SELECT country, MIN(num_operations) FROM CountryDefenseDiplomacy GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE ticket_sales (id INT PRIMARY KEY, team VARCHAR(50), event_date DATE, tickets_sold INT, total_sales DECIMAL(10,2)); | Insert ticket sales records into the "ticket_sales" table for the event held in Dallas | INSERT INTO ticket_sales (id, team, event_date, tickets_sold, total_sales) VALUES (1, 'Cowboys', '2022-08-15', 2500, 75000.00); | gretelai_synthetic_text_to_sql |
CREATE TABLE Funding_Allocation (id INT, project VARCHAR(30), funding FLOAT); | Increase the 'funding' for a specific project by 10% in the 'Funding_Allocation' table. | UPDATE Funding_Allocation SET funding = funding * 1.10 WHERE project = 'Arctic Biodiversity Monitoring'; | gretelai_synthetic_text_to_sql |
CREATE TABLE education_budget (state VARCHAR(20), school_district VARCHAR(20), budget INT); INSERT INTO education_budget (state, school_district, budget) VALUES ('Texas', 'Dallas ISD', 4000000); INSERT INTO education_budget (state, school_district, budget) VALUES ('Texas', 'Houston ISD', 6000000); INSERT INTO education_budget (state, school_district, budget) VALUES ('Texas', 'Austin ISD', 5000000); INSERT INTO education_budget (state, school_district, budget) VALUES ('Florida', 'Miami-Dade County', 7000000); | What is the total budget allocated for education in the state of Texas, excluding school districts with a budget over 5 million? | SELECT SUM(budget) FROM education_budget WHERE state = 'Texas' AND school_district NOT IN (SELECT school_district FROM education_budget WHERE state = 'Texas' GROUP BY school_district HAVING SUM(budget) > 5000000); | gretelai_synthetic_text_to_sql |
CREATE TABLE cases (age_group VARCHAR(10), num_cases INT); INSERT INTO cases (age_group, num_cases) VALUES ('0-9', 1500), ('10-19', 2000), ('20-29', 3000), ('30-39', 2500), ('40-49', 2200); | What is the total number of infectious disease cases, by age group? | SELECT age_group, SUM(num_cases) as total_cases FROM cases GROUP BY age_group; | gretelai_synthetic_text_to_sql |
CREATE TABLE farmer_support_program (id INT PRIMARY KEY, first_name VARCHAR(50), last_name VARCHAR(50), age INT, gender VARCHAR(10), location VARCHAR(50), support_granted INT); | What's the total number of farmers who received support in the 'farmer_support_program' table? | SELECT SUM(support_granted) FROM farmer_support_program WHERE support_granted = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE Events (event_id INT, event_name VARCHAR(255), attendees INT); INSERT INTO Events (event_id, event_name, attendees) VALUES (1, 'Music Festival', 800), (2, 'Art Exhibition', 500); CREATE TABLE Attendee_Demographics (attendee_id INT, attendee_race VARCHAR(255), event_id INT); INSERT INTO Attendee_Demographics (attendee_id, attendee_race, event_id) VALUES (1, 'Hispanic', 1), (2, 'African American', 1), (3, 'Asian', 2); | How many visitors identified as BIPOC attended the 'Music Festival' event? | SELECT COUNT(*) FROM Attendee_Demographics AD JOIN Events E ON AD.event_id = E.event_id WHERE E.event_name = 'Music Festival' AND AD.attendee_race IN ('Hispanic', 'African American', 'Asian'); | gretelai_synthetic_text_to_sql |
CREATE TABLE fares (id INT, route_id INT, fare FLOAT, distance FLOAT); INSERT INTO fares (id, route_id, fare, distance) VALUES (3002, 102, 4.0, 40.0), (3003, 103, 3.0, 35.0); | What is the average fare per kilometer for route 102 and 103? | SELECT route_id, AVG(fare / distance) as avg_fare_per_km FROM fares GROUP BY route_id HAVING route_id IN (102, 103); | gretelai_synthetic_text_to_sql |
CREATE TABLE water_usage (id INT PRIMARY KEY, year INT, location VARCHAR(50), usage FLOAT); INSERT INTO water_usage (id, year, location, usage) VALUES (1, 2018, 'Jacksonville', 1234.56), (2, 2018, 'Austin', 3567.89), (3, 2018, 'Albuquerque', 1890.12), (4, 2018, 'Atlanta', 987.65), (5, 2018, 'Baltimore', 1567.89); | Find the number of times water usage exceeded 2000 cubic meters for each location in the year 2018 | SELECT location, COUNT(*) FROM water_usage WHERE year = 2018 AND usage > 2000 GROUP BY location; | gretelai_synthetic_text_to_sql |
CREATE TABLE routes (route_id INT, route_name VARCHAR(255)); INSERT INTO routes (route_id, route_name) VALUES (1, 'Green Line'), (2, 'Blue Line'), (3, 'Orange Line'); CREATE TABLE fares (route_id INT, payment_type VARCHAR(255)); INSERT INTO fares (route_id, payment_type) VALUES (1, 'credit_card'), (1, 'cash'), (2, 'credit_card'), (3, 'mobile_payment'), (3, 'cash'); | What are the unique payment types for each route? | SELECT r.route_name, f.payment_type FROM routes r JOIN fares f ON r.route_id = f.route_id GROUP BY r.route_name, f.payment_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE safety_ai.ai_applications (ai_application_id INT PRIMARY KEY, ai_algorithm_id INT, application_name VARCHAR(255), fairness_score FLOAT); INSERT INTO safety_ai.ai_applications (ai_application_id, ai_algorithm_id, application_name, fairness_score) VALUES (1, 1, 'AI-generated art', 0.8), (2, 1, 'AI-generated music', 0.75), (3, 2, 'AI-powered chatbot', 0.9), (4, 3, 'AI-powered self-driving car', 0.6); CREATE TABLE safety_ai.ai_algorithms (ai_algorithm_id INT PRIMARY KEY, ai_algorithm VARCHAR(255), fairness_score FLOAT); INSERT INTO safety_ai.ai_algorithms (ai_algorithm_id, ai_algorithm, fairness_score) VALUES (1, 'Generative Adversarial Networks', 0.75), (2, 'Transformers', 0.85), (3, 'Deep Reinforcement Learning', 0.65); | What is the average fairness score for each AI application in the 'safety_ai' database, segmented by algorithm type? | SELECT f.ai_algorithm, AVG(a.fairness_score) as avg_fairness_score FROM safety_ai.ai_applications a JOIN safety_ai.ai_algorithms f ON a.ai_algorithm_id = f.ai_algorithm_id GROUP BY f.ai_algorithm; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA renewables; CREATE TABLE wind_farms (name VARCHAR(50), capacity INT); INSERT INTO wind_farms (name, capacity) VALUES ('Farm1', 100), ('Farm2', 150); | Find the total capacity (MW) of wind farms in the 'renewables' schema | SELECT SUM(capacity) FROM renewables.wind_farms; | gretelai_synthetic_text_to_sql |
CREATE TABLE Spacecraft (SpacecraftID INT, SpacecraftName VARCHAR(50), Manufacturer VARCHAR(50), Mission VARCHAR(50)); | What are the names of the spacecraft that have flown to Mars but were not manufactured by NASA or SpaceX? | SELECT SpacecraftName FROM Spacecraft WHERE Manufacturer NOT IN ('NASA', 'SpaceX') AND Mission LIKE '%Mars%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE pipelines (pipeline_id INT, pipeline_name TEXT, start_location TEXT, end_location TEXT); INSERT INTO pipelines (pipeline_id, pipeline_name, start_location, end_location) VALUES (1, 'Pipeline A', 'North Sea', 'Europe'), (2, 'Pipeline B', 'Atlantic', 'North America'); CREATE TABLE pipeline_segments (pipeline_id INT, segment_id INT, location TEXT); INSERT INTO pipeline_segments (pipeline_id, segment_id, location) VALUES (1, 1, 'North Sea'), (1, 2, 'Europe'), (2, 1, 'Atlantic'), (2, 2, 'North America'); | List all pipelines that intersect with platforms in the North Sea | SELECT p.pipeline_name FROM pipelines p JOIN pipeline_segments ps ON p.pipeline_id = ps.pipeline_id WHERE ps.location = 'North Sea'; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (id INT, name VARCHAR(255), category VARCHAR(255), price DECIMAL(5,2), cruelty_free BOOLEAN); INSERT INTO products (id, name, category, price, cruelty_free) VALUES (1, 'Lipstick', 'makeup', 12.99, true), (2, 'Mascara', 'makeup', 14.99, true); | Insert new cruelty-free makeup products in the 'natural' category. | INSERT INTO products (name, category, price, cruelty_free) VALUES ('Eyeshadow', 'natural', 9.99, true), ('Blush', 'natural', 7.99, true); | gretelai_synthetic_text_to_sql |
CREATE TABLE public_ferries(id INT, ferry_number INT, city VARCHAR(20), max_seating_capacity INT); | What is the maximum seating capacity of public ferries in Hong Kong? | SELECT MAX(max_seating_capacity) FROM public_ferries WHERE city = 'Hong Kong'; | gretelai_synthetic_text_to_sql |
CREATE TABLE smart_city_tech (tech_id INT, tech_name VARCHAR(30), city VARCHAR(20), cost DECIMAL(10,2)); INSERT INTO smart_city_tech (tech_id, tech_name, city, cost) VALUES (1, 'Smart Grids', 'New York', 7000000.00), (2, 'Smart Lighting', 'Los Angeles', 4000000.00), (3, 'Smart Traffic Management', 'Chicago', 6000000.00); | List all smart city technology adoptions in the city of New York and their respective costs. | SELECT tech_name, cost FROM smart_city_tech WHERE city = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE basketball_players (player_id INT, player_name VARCHAR(50), assists INT); INSERT INTO basketball_players (player_id, player_name, assists) VALUES (1, 'LeBron James', 325), (2, 'Stephen Curry', 287), (3, 'Nikola Jokic', 378), (4, 'James Harden', 354), (5, 'Luka Doncic', 365); | What is the total number of assists by each basketball player in the 2022 season? | SELECT player_name, SUM(assists) as total_assists FROM basketball_players GROUP BY player_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE IncidentResolution (id INT, incident_month DATE, resolution_days INT); INSERT INTO IncidentResolution (id, incident_month, resolution_days) VALUES (1, '2022-02-01', 10), (2, '2022-02-15', 15), (3, '2022-03-01', 5); | What is the average number of days to resolve security incidents in the last month? | SELECT AVG(IncidentResolution.resolution_days) AS Average_Resolution_Days FROM IncidentResolution WHERE IncidentResolution.incident_month >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (donor_id INT PRIMARY KEY, donation_amount DECIMAL(10, 2), donation_date DATE, first_donation_date DATE); INSERT INTO donors (donor_id, donation_amount, donation_date, first_donation_date) VALUES (1, 250, '2020-01-01', '2020-01-01'), (2, 750, '2020-01-03', '2019-01-01'), (3, 900, '2020-02-05', '2020-02-05'); | What is the total amount donated by new donors (those who have donated for the first time) in the year 2020? | SELECT SUM(donation_amount) FROM donors WHERE YEAR(donation_date) = 2020 AND YEAR(first_donation_date) = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, product_name VARCHAR(50), category VARCHAR(50)); INSERT INTO products VALUES (1, 'Sativa Flower', 'Flower'), (2, 'Indica Flower', 'Flower'), (3, 'Hybrid Flower', 'Flower'), (4, 'Cannabis Oil', 'Concentrates'), (5, 'Edibles', 'Edibles'); CREATE TABLE sales (sale_id INT, product_id INT, sale_date DATE, revenue DECIMAL(10,2)); INSERT INTO sales VALUES (1, 1, '2022-01-02', 35.99), (2, 3, '2022-01-05', 44.50), (3, 4, '2022-01-10', 78.00), (4, 2, '2022-02-14', 29.99), (5, 5, '2022-03-20', 14.99); | What was the total revenue for each product category in Q1 2022? | SELECT category, SUM(revenue) as total_revenue FROM sales JOIN products ON sales.product_id = products.product_id WHERE sale_date >= '2022-01-01' AND sale_date < '2022-04-01' GROUP BY category; | gretelai_synthetic_text_to_sql |
CREATE TABLE Song (SongID INT, Title VARCHAR(50), GenreID INT, Revenue INT); | What is the minimum revenue for a song in the Hip-Hop genre? | SELECT MIN(Song.Revenue) as MinRevenue FROM Song WHERE Song.GenreID = (SELECT GenreID FROM Genre WHERE Name='Hip-Hop'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Esports_Events (Event_ID INT, Event_Name VARCHAR(20), Viewers INT); INSERT INTO Esports_Events (Event_ID, Event_Name, Viewers) VALUES (1, 'Event 1', 10000), (2, 'Event 2', 12000), (3, 'Event 3', 15000); | What is the name of the esports event with the highest number of viewers? | SELECT Event_Name, MAX(Viewers) FROM Esports_Events; | gretelai_synthetic_text_to_sql |
CREATE TABLE model (model_id INT, name VARCHAR(50), organization_id INT, explainability_score INT, fairness_score INT); INSERT INTO model VALUES (1, 'ModelA', 1, 8, 9), (2, 'ModelB', 2, 7, 8), (3, 'ModelC', 3, 6, 9), (4, 'ModelD', 1, 9, 8), (5, 'ModelE', 3, 5, 7); CREATE TABLE organization (organization_id INT, name VARCHAR(50), type VARCHAR(20)); INSERT INTO organization VALUES (1, 'TechCo', 'for-profit'), (2, 'AI Inc.', 'non-profit'), (3, 'Alpha Corp.', 'for-profit'); | List the names and fairness scores of all explainable AI models created by non-profit organizations. | SELECT model.name, model.fairness_score FROM model JOIN organization ON model.organization_id = organization.organization_id WHERE organization.type = 'non-profit' AND model.explainability_score >= 7; | gretelai_synthetic_text_to_sql |
CREATE TABLE HospitalBeds (HospitalID int, Beds int, Rural bool); INSERT INTO HospitalBeds (HospitalID, Beds, Rural) VALUES (1, 50, true); | What is the average number of hospital beds in rural areas of China? | SELECT AVG(Beds) FROM HospitalBeds WHERE Rural = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (id INT, name TEXT, country TEXT, donation_count INT, amount_donated DECIMAL(10,2)); | What is the average donation size for donors from India? | SELECT AVG(amount_donated / donation_count) FROM donors WHERE country = 'India'; | gretelai_synthetic_text_to_sql |
CREATE TABLE sizes (id INT, size VARCHAR(10)); INSERT INTO sizes (id, size) VALUES (1, 'XS'), (2, 'S'), (3, 'M'), (4, 'L'), (5, 'XL'); CREATE TABLE inventory (id INT, item_name VARCHAR(20), size_id INT); INSERT INTO inventory (id, item_name, size_id) VALUES (1, 't-shirt', 1), (2, 'blouse', 3), (3, 'jeans', 4); | Count the number of items in each size category | SELECT sizes.size, COUNT(inventory.id) FROM sizes JOIN inventory ON inventory.size_id = sizes.id GROUP BY sizes.size; | gretelai_synthetic_text_to_sql |
CREATE TABLE drug_approval (drug_name VARCHAR(255), approval_year INT, country VARCHAR(255)); INSERT INTO drug_approval (drug_name, approval_year, country) VALUES ('DrugA', 2019, 'USA'), ('DrugB', 2020, 'Canada'), ('DrugC', NULL, 'Germany'), ('DrugD', NULL, NULL); | What are the names of the drugs that were not approved in any country? | SELECT drug_name FROM drug_approval WHERE approval_year IS NULL AND country IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE ancient_civilizations (artifact_id INT, weight FLOAT, culture VARCHAR(255)); | What is the average weight of artifacts from the 'ancient_civilizations'? | SELECT AVG(weight) FROM ancient_civilizations; | gretelai_synthetic_text_to_sql |
CREATE TABLE volunteers (vol_id INT, org_id INT, hours_contributed INT, volunteer_name TEXT);CREATE TABLE organizations (org_id INT, org_name TEXT); INSERT INTO organizations VALUES (1, 'Habitat for Humanity'); INSERT INTO organizations VALUES (2, 'Red Cross'); INSERT INTO volunteers VALUES (1, 1, 10, 'John Doe'); INSERT INTO volunteers VALUES (2, 1, 15, 'Jane Smith'); INSERT INTO volunteers VALUES (3, 2, 20, 'Mary Johnson'); | What is the average number of hours contributed per volunteer, for each organization? | SELECT organizations.org_name, AVG(volunteers.hours_contributed) AS avg_hours_per_volunteer FROM organizations INNER JOIN volunteers ON organizations.org_id = volunteers.org_id GROUP BY organizations.org_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE employees (id INT, name TEXT, department TEXT, age INT); INSERT INTO employees (id, name, department, age) VALUES (1, 'John Doe', 'mining_operations', 35); INSERT INTO employees (id, name, department, age) VALUES (2, 'Jane Smith', 'geology', 28); | Find the average age of employees in the 'mining_operations' department. | SELECT AVG(age) FROM employees WHERE department = 'mining_operations'; | gretelai_synthetic_text_to_sql |
CREATE TABLE PolicyData (PolicyID INT, PolicyholderID INT, IssueDate DATE); INSERT INTO PolicyData (PolicyID, PolicyholderID, IssueDate) VALUES (1, 1, '2021-01-01'); INSERT INTO PolicyData (PolicyID, PolicyholderID, IssueDate) VALUES (2, 2, '2021-02-15'); CREATE TABLE ClaimData (ClaimID INT, PolicyID INT, ClaimDate DATE); INSERT INTO ClaimData (ClaimID, PolicyID, ClaimDate) VALUES (1, 1, '2021-03-10'); INSERT INTO ClaimData (ClaimID, PolicyID, ClaimDate) VALUES (2, 2, '2021-04-20'); | What is the total number of policies and claims processed in '2021' for policyholders living in 'NY'? | SELECT COUNT(DISTINCT PolicyData.PolicyID) AS Policies, COUNT(DISTINCT ClaimData.ClaimID) AS Claims FROM PolicyData JOIN ClaimData ON PolicyData.PolicyID = ClaimData.PolicyID WHERE YEAR(PolicyData.IssueDate) = 2021 AND PolicyData.PolicyholderID IN (SELECT PolicyholderID FROM Policyholders WHERE State = 'NY'); | gretelai_synthetic_text_to_sql |
CREATE TABLE sales (sale_id INT, product_id INT, sale_amount DECIMAL, sale_date DATE); CREATE TABLE products (product_id INT, product_name TEXT, category TEXT); INSERT INTO sales (sale_id, product_id, sale_amount, sale_date) VALUES (1, 1, 50.00, '2022-01-01'), (2, 1, 40.00, '2022-01-15'), (3, 2, 30.00, '2022-01-30'), (4, 3, 20.00, '2022-02-10'), (5, 3, 25.00, '2022-02-25'), (6, 4, 60.00, '2022-03-05'), (7, 1, 70.00, '2022-03-15'), (8, 5, 10.00, '2022-03-30'), (9, 6, 50.00, '2022-04-05'), (10, 7, 35.00, '2022-04-10'); INSERT INTO products (product_id, product_name, category) VALUES (1, 'Product 1', 'Natural'), (2, 'Product 2', 'Organic'), (3, 'Product 3', 'Natural'), (4, 'Product 4', 'Clean Beauty'), (5, 'Product 5', 'Skin Care'), (6, 'Product 6', 'Makeup'), (7, 'Product 7', 'Natural'); | Determine the percentage of total sales from the 'Natural' category during the past quarter. | SELECT 100.0 * SUM(sale_amount) / (SELECT SUM(sale_amount) FROM sales WHERE sale_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) AND CURRENT_DATE) AS pct_natural_sales FROM sales JOIN products ON sales.product_id = products.product_id WHERE products.category = 'Natural'; | gretelai_synthetic_text_to_sql |
CREATE TABLE paris_sustainable_hotels(id INT, name TEXT, sustainable BOOLEAN, revenue FLOAT); INSERT INTO paris_sustainable_hotels(id, name, sustainable, revenue) VALUES (1, 'EcoHotel Paris', true, 12000.0), (2, 'Paris Green Suites', true, 15000.0), (3, 'Paris Urban Hotel', false, 10000.0); | What is the average revenue per sustainable hotel in Paris? | SELECT AVG(revenue) FROM paris_sustainable_hotels WHERE sustainable = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE nfl_players (player_id INT, player_name VARCHAR(255)); INSERT INTO nfl_players VALUES (1, 'Player1'), (2, 'Player2'), (3, 'Player3'), (4, 'Player4'); CREATE TABLE nfl_stats (game_id INT, player_id INT, running_distance DECIMAL(10,2)); INSERT INTO nfl_stats VALUES (1, 1, 85.67), (1, 2, 76.34), (2, 1, 91.23), (2, 3, 65.54), (3, 2, 89.21), (3, 4, 72.10); | What is the average running distance per game for each player in the 2022 NFL season? | SELECT p.player_name, AVG(s.running_distance) AS avg_running_distance FROM nfl_players p JOIN nfl_stats s ON p.player_id = s.player_id GROUP BY p.player_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE Workouts (WorkoutID INT, Duration INT, MemberID INT, Location VARCHAR(50)); INSERT INTO Workouts (WorkoutID, Duration, MemberID, Location) VALUES (1, 60, 1, 'California'); INSERT INTO Workouts (WorkoutID, Duration, MemberID, Location) VALUES (2, 90, 2, 'New York'); | What is the total duration of outdoor workouts for members living in California? | SELECT SUM(Workouts.Duration) FROM Workouts WHERE Workouts.Location = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE species (id INT, name VARCHAR(50), population INT, conservation_status VARCHAR(20)); INSERT INTO species (id, name, population, conservation_status) VALUES (1, 'Polar Bear', 26500, 'Vulnerable'); CREATE TABLE species_research (id INT, species_id INT, year INT, location VARCHAR(50), observations INT); INSERT INTO species_research (id, species_id, year, location, observations) VALUES (1, 1, 2015, 'Arctic', 350); CREATE TABLE location (id INT, name VARCHAR(50)); INSERT INTO location (id, name) VALUES (1, 'Canada'); | What species have been studied in Canada? | SELECT s.name FROM species s JOIN species_research r ON s.id = s.species_id JOIN location l ON r.location = l.name WHERE l.name = 'Canada'; | gretelai_synthetic_text_to_sql |
CREATE TABLE DisabilitySupportPrograms (ID INT, Disability VARCHAR(50), Program VARCHAR(50), Budget INT); INSERT INTO DisabilitySupportPrograms (ID, Disability, Program, Budget) VALUES (1, 'Visual Impairment', 'Braille Materials', 10000); INSERT INTO DisabilitySupportPrograms (ID, Disability, Program, Budget) VALUES (2, 'Hearing Impairment', 'Sign Language Interpreter', 15000); INSERT INTO DisabilitySupportPrograms (ID, Disability, Program, Budget) VALUES (3, 'Visual Impairment', 'Assistive Technology', 12000); INSERT INTO DisabilitySupportPrograms (ID, Disability, Program, Budget) VALUES (4, 'Autism', 'Behavioral Therapy', 8000); | What is the minimum budget allocated for disability support programs per disability type? | SELECT Disability, MIN(Budget) as MinBudget FROM DisabilitySupportPrograms GROUP BY Disability; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (id INT, donor_id INT, ngo_identity VARCHAR(255), category VARCHAR(255), amount DECIMAL(10, 2), donation_date DATE); INSERT INTO Donations (id, donor_id, ngo_identity, category, amount, donation_date) VALUES (1, 1001, 'LGBTQ+', 'Education', 5000, '2021-05-05'), (2, 1002, 'Allies', 'Environment', 3000, '2021-04-15'), (3, 1003, 'LGBTQ+', 'Arts', 7000, '2021-07-30'), (4, 1004, 'Allies', 'Education', 4000, '2021-03-25'), (5, 1005, 'LGBTQ+', 'Education', 8000, '2021-06-10'); | How many donations were made to LGBTQ+ organizations in the Education sector in Q2 2021? | SELECT COUNT(*) as total_donations FROM Donations WHERE donation_date BETWEEN '2021-04-01' AND '2021-06-30' AND ngo_identity = 'LGBTQ+' AND category = 'Education'; | gretelai_synthetic_text_to_sql |
CREATE TABLE climate_finance_recipients (year INT, community VARCHAR(255), amount FLOAT); INSERT INTO climate_finance_recipients VALUES (2020, 'First Nations', 600000); | Which Indigenous communities received climate finance over 500,000 in 2020? | SELECT community FROM climate_finance_recipients WHERE year = 2020 AND amount > 500000; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, Name VARCHAR(50), Salary DECIMAL(10, 2), Department VARCHAR(50)); INSERT INTO Employees (EmployeeID, Name, Salary, Department) VALUES (1, 'John Doe', 50000, 'HR'), (2, 'Jane Smith', 55000, 'IT'), (3, 'Mike Johnson', 60000, 'IT'), (4, 'Sara Doe', 45000, 'LA'); | Display the names and salaries of all employees in the 'IT' department, ordered by salary. | SELECT Name, Salary FROM Employees WHERE Department = 'IT' ORDER BY Salary; | gretelai_synthetic_text_to_sql |
CREATE TABLE SkincareSales (productID INT, productName VARCHAR(50), region VARCHAR(50), revenue DECIMAL(10,2)); INSERT INTO SkincareSales (productID, productName, region, revenue) VALUES (1, 'Nourishing Cream', 'Europe', 5000.00), (2, 'Soothing Lotion', 'Europe', 7000.00), (3, 'Regenerating Serum', 'Europe', 8000.00); CREATE TABLE ProductIngredients (productID INT, ingredient VARCHAR(50), organic BOOLEAN); INSERT INTO ProductIngredients (productID, ingredient, organic) VALUES (1, 'Aloe Vera', true), (2, 'Chamomile', true), (3, 'Retinol', false); | What is the total sales revenue of organic skincare products in the European market? | SELECT SUM(revenue) FROM SkincareSales INNER JOIN ProductIngredients ON SkincareSales.productID = ProductIngredients.productID WHERE organic = true AND region = 'Europe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE WeatherData (location VARCHAR(255), date DATE, temperature FLOAT); INSERT INTO WeatherData (location, date, temperature) VALUES ('Svalbard', '2020-01-01', -5.0); INSERT INTO WeatherData (location, date, temperature) VALUES ('Svalbard', '2020-01-02', -6.5); | What is the average temperature recorded in Svalbard during 2020? | SELECT AVG(temperature) FROM WeatherData WHERE location = 'Svalbard' AND YEAR(date) = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE ArtPieces (id INT, region VARCHAR(20), year INT, type VARCHAR(20), price FLOAT); INSERT INTO ArtPieces (id, region, year, type, price) VALUES (1, 'Pacific', 2021, 'VisualArt', 5000); INSERT INTO ArtPieces (id, region, year, type, price) VALUES (2, 'Pacific', 2021, 'Sculpture', 8000); | How many visual art pieces were sold in the Pacific region in 2021? | SELECT SUM(price) FROM ArtPieces WHERE region = 'Pacific' AND year = 2021 AND type = 'VisualArt'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Journeys(journey_id INT, journey_date DATE, mode_of_transport VARCHAR(20)); INSERT INTO Journeys(journey_id, journey_date, mode_of_transport) VALUES (1, '2022-06-01', 'Light Rail'), (2, '2022-06-02', 'Light Rail'), (3, '2022-07-01', 'Light Rail'); | What is the total number of journeys for 'Light Rail' mode of transport in 'Summer' season? | SELECT COUNT(*) FROM Journeys WHERE mode_of_transport = 'Light Rail' AND EXTRACT(MONTH FROM journey_date) BETWEEN 6 AND 8; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (id INT, donor VARCHAR(50), cause VARCHAR(50), amount DECIMAL(10, 2), donation_date DATE); INSERT INTO donations (id, donor, cause, amount, donation_date) VALUES (1, 'John Doe', 'Education', 500, '2022-04-01'), (2, 'Jane Smith', 'Health', 300, '2022-04-15'), (3, 'Alice Johnson', 'Environment', 700, '2022-05-05'); | What is the average donation amount by month in 2022? | SELECT EXTRACT(MONTH FROM donation_date) as month, AVG(amount) as avg_donation FROM donations WHERE donation_date BETWEEN '2022-01-01' AND '2022-12-31' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE cultural_events (event_id INT, name VARCHAR(50), city VARCHAR(50)); CREATE TABLE donors (donor_id INT, name VARCHAR(50), event_id INT, amount DECIMAL(10,2)); INSERT INTO cultural_events (event_id, name, city) VALUES (1, 'Theatre Festival', 'London'); | Insert a new record of a donor who contributed to a cultural event in London. | INSERT INTO donors (donor_id, name, event_id, amount) VALUES (1, 'Alex Johnson', 1, 500.00); | gretelai_synthetic_text_to_sql |
CREATE TABLE RenewableEnergyProjects (id INT, name VARCHAR(100), location VARCHAR(100), type VARCHAR(50), capacity FLOAT); | List the top 3 renewable energy projects with the highest capacity in the 'RenewableEnergyProjects' table. | SELECT name, capacity FROM RenewableEnergyProjects ORDER BY capacity DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Volunteers (VolunteerID INT PRIMARY KEY, FirstName VARCHAR(50), LastName VARCHAR(50), Email VARCHAR(100)); | Update the email address of a volunteer in the 'Volunteers' table | UPDATE Volunteers SET Email = 'new.email@example.com' WHERE VolunteerID = 201; | gretelai_synthetic_text_to_sql |
CREATE TABLE tour_details (tour_id INT, hotel_id INT, region VARCHAR(20), tour_date DATE); | Insert a new virtual tour record for a hotel in the 'Asia' region on 2023-03-15. | INSERT INTO tour_details (hotel_id, region, tour_date) VALUES (102, 'Asia', '2023-03-15'); | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, name VARCHAR(50), posts_count INT, followers INT); CREATE TABLE posts (id INT, user_id INT, post_text VARCHAR(255)); | How many users in the social_media schema have posted at least once and have more than 100 followers? | SELECT COUNT(DISTINCT users.id) FROM users JOIN posts ON users.id = posts.user_id WHERE posts_count > 0 AND followers > 100; | gretelai_synthetic_text_to_sql |
CREATE TABLE revenue (restaurant_id INT, revenue_date DATE, total_revenue DECIMAL(10,2)); | Insert a new record for restaurant revenue | INSERT INTO revenue (restaurant_id, revenue_date, total_revenue) VALUES (987, '2022-03-15', 6000.00); | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT); CREATE TABLE posts (id INT, user_id INT, hashtags TEXT); | What is the count of distinct users who have interacted with content related to the hashtag "#technology" in the last month? | SELECT COUNT(DISTINCT users.id) FROM users INNER JOIN posts ON users.id = posts.user_id WHERE FIND_IN_SET('technology', posts.hashtags) > 0 AND posts.created_at >= DATE_SUB(NOW(), INTERVAL 1 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE rd_expenditures (quarter TEXT, drug_name TEXT, amount INT); CREATE TABLE drug_categories (drug_name TEXT, drug_category TEXT); INSERT INTO rd_expenditures (quarter, drug_name, amount) VALUES ('Q1', 'DrugA', 300000), ('Q2', 'DrugA', 350000), ('Q3', 'DrugA', 400000), ('Q4', 'DrugA', 450000), ('Q1', 'DrugB', 500000), ('Q2', 'DrugB', 550000), ('Q3', 'DrugB', 600000), ('Q4', 'DrugB', 650000); INSERT INTO drug_categories (drug_name, drug_category) VALUES ('DrugA', 'Antihypertensive'), ('DrugB', 'Antidiabetic'); | What are the total R&D expenditures per quarter for each drug category in the 'rd_expenditures' and 'drug_categories' tables? | SELECT c.drug_category, r.quarter, SUM(r.amount) as total_expenditure FROM rd_expenditures r JOIN drug_categories c ON r.drug_name = c.drug_name GROUP BY c.drug_category, r.quarter; | gretelai_synthetic_text_to_sql |
CREATE TABLE hydro_energy (id INT, region VARCHAR(50), year INT, production FLOAT); | Delete the hydroelectric energy production record for Ontario in 2020 | DELETE FROM hydro_energy WHERE region = 'Ontario' AND year = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE ocean_acidification_levels (location TEXT, acidification_level REAL, measurement_date DATE); CREATE TABLE atlantic_region (region_name TEXT, region_description TEXT); | What is the maximum ocean acidification level recorded in the Atlantic region in the last decade?" | SELECT MAX(oal.acidification_level) FROM ocean_acidification_levels oal INNER JOIN atlantic_region ar ON oal.location LIKE '%Atlantic%' AND oal.measurement_date >= (CURRENT_DATE - INTERVAL '10 years'); | gretelai_synthetic_text_to_sql |
CREATE TABLE sales_associates (id INT, name VARCHAR(50), is_union_member BOOLEAN); INSERT INTO sales_associates (id, name, is_union_member) VALUES (1, 'Nina', false), (2, 'Noah', false), (3, 'Nicole', true); | What is the total number of employees who are not members of a union in the 'retail_database' database? | SELECT COUNT(*) FROM sales_associates WHERE is_union_member = false; | gretelai_synthetic_text_to_sql |
CREATE TABLE open_pedagogy_age (student_id INT, age INT, total_open_pedagogy_hours INT); INSERT INTO open_pedagogy_age (student_id, age, total_open_pedagogy_hours) VALUES (1, 18, 30), (2, 21, 45), (3, 22, 60); | What is the total number of hours spent on open pedagogy projects by students in each age group? | SELECT FLOOR(age / 10) * 10 AS age_group, SUM(total_open_pedagogy_hours) FROM open_pedagogy_age GROUP BY age_group; | gretelai_synthetic_text_to_sql |
CREATE TABLE lolgames (game_id INT, champion VARCHAR(50), killer_champion VARCHAR(50)); INSERT INTO lolgames (game_id, champion, killer_champion) VALUES (1, 'Ashe', 'Yasuo'); | Find the most common cause of death for each champion in LoL | SELECT champion, killer_champion, COUNT(*) as num_deaths, RANK() OVER (PARTITION BY champion ORDER BY COUNT(*) DESC) as rank FROM lolgames GROUP BY champion, killer_champion | gretelai_synthetic_text_to_sql |
CREATE TABLE Attorneys (id INT, name VARCHAR(50), LGBTQ BOOLEAN); CREATE TABLE Cases (id INT, attorney_id INT, precedent VARCHAR(100)); INSERT INTO Attorneys (id, name, LGBTQ) VALUES (1, 'Attorney1', FALSE), (2, 'Attorney2', TRUE), (3, 'Attorney3', FALSE); INSERT INTO Cases (id, attorney_id, precedent) VALUES (1, 1, 'Precedent1'), (2, 1, 'Precedent2'), (3, 2, 'Precedent3'), (4, 3, 'Precedent4'); | What are the legal precedents cited in cases handled by attorneys who identify as LGBTQ+? | SELECT Cases.precedent FROM Cases INNER JOIN Attorneys ON Cases.attorney_id = Attorneys.id WHERE Attorneys.LGBTQ = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE rural_clinics (clinic_id INT); INSERT INTO rural_clinics (clinic_id) VALUES (1), (2); CREATE TABLE urban_clinics (clinic_id INT); INSERT INTO urban_clinics (clinic_id) VALUES (1), (2); CREATE TABLE rural_hospitals (hospital_id INT); INSERT INTO rural_hospitals (hospital_id) VALUES (1), (2); CREATE TABLE urban_hospitals (hospital_id INT); INSERT INTO urban_hospitals (hospital_id) VALUES (1), (2); | Show the total number of rural clinics and hospitals, as well as the total number of urban clinics and hospitals, in a single query. | SELECT 'Rural Clinics' AS location, COUNT(*) AS total_facilities FROM rural_clinics UNION SELECT 'Urban Clinics', COUNT(*) FROM urban_clinics UNION SELECT 'Rural Hospitals', COUNT(*) FROM rural_hospitals UNION SELECT 'Urban Hospitals', COUNT(*) FROM urban_hospitals; | gretelai_synthetic_text_to_sql |
CREATE TABLE Europium_Production (Year INT, Quarter INT, Quantity INT); INSERT INTO Europium_Production (Year, Quarter, Quantity) VALUES (2018, 1, 150), (2018, 2, 175), (2018, 3, 200), (2018, 4, 225), (2019, 1, 250), (2019, 2, 275), (2019, 3, 300), (2019, 4, 325); | Determine the year with the highest Europium production. | SELECT Year, MAX(Quantity) FROM Europium_Production GROUP BY Year ORDER BY MAX(Quantity) DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (id INT, name VARCHAR(255), organic BOOLEAN, weight FLOAT, supplier_id INT); | Calculate the average weight of organic and non-organic products supplied by each supplier. | SELECT s.name, AVG(p.weight) as avg_weight, p.organic FROM suppliers s INNER JOIN products p ON s.id = p.supplier_id GROUP BY s.name, p.organic; | gretelai_synthetic_text_to_sql |
CREATE TABLE safety_records (id INT, vessel_id INT, incident_date DATE, description VARCHAR(100)); | How many incidents are recorded in the 'safety_records' table? | SELECT COUNT(*) FROM safety_records; | gretelai_synthetic_text_to_sql |
CREATE TABLE sustainable_practices (practice_id INT, description TEXT, category VARCHAR(20)); | Add a new record to the "sustainable_practices" table with an ID of 7, a description of 'Reducing food waste through composting', and a category of 'Waste' | INSERT INTO sustainable_practices (practice_id, description, category) VALUES (7, 'Reducing food waste through composting', 'Waste'); | gretelai_synthetic_text_to_sql |
CREATE TABLE snapchat_stories (story_id INT, user_id INT, story_date DATE);CREATE TABLE users (user_id INT, state VARCHAR(50), registration_date DATE);CREATE TABLE state_populations (state VARCHAR(50), population INT); | What is the percentage of users who have posted a story on Snapchat in the past week and who are located in a state with a population of over 10 million, out of all users located in a state with a population of over 10 million? | SELECT 100.0 * COUNT(DISTINCT s.user_id) / (SELECT COUNT(DISTINCT u.user_id) FROM users u JOIN state_populations sp ON u.state = sp.state WHERE sp.population > 10000000) as pct_users FROM snapchat_stories s JOIN users u ON s.user_id = u.user_id JOIN state_populations sp ON u.state = sp.state WHERE s.story_date >= DATE(NOW()) - INTERVAL 1 WEEK AND sp.population > 10000000; | gretelai_synthetic_text_to_sql |
CREATE TABLE seasons (season_id INT, player TEXT, team TEXT, home_runs INT); | What is the average number of home runs hit by a player in a single MLB season? | SELECT AVG(home_runs) FROM seasons; | gretelai_synthetic_text_to_sql |
CREATE TABLE recycling_rates_material(material VARCHAR(50), year INT, rate FLOAT); INSERT INTO recycling_rates_material(material, year, rate) VALUES('Plastic', 2018, 0.25), ('Plastic', 2019, 0.3), ('Plastic', 2020, 0.35), ('Paper', 2018, 0.5), ('Paper', 2019, 0.55), ('Paper', 2020, 0.6); | What is the recycling rate trend for Plastic and Paper from 2018 to 2020? | SELECT material, year, rate FROM recycling_rates_material WHERE material IN ('Plastic', 'Paper') ORDER BY year; | gretelai_synthetic_text_to_sql |
CREATE TABLE evacuations (evacuation_id INT, state VARCHAR(50), mission_status VARCHAR(10)); INSERT INTO evacuations (evacuation_id, state, mission_status) VALUES (1, 'State A', 'successful'), (2, 'State A', 'failed'), (3, 'State B', 'successful'), (4, 'State C', 'failed'), (5, 'State A', 'successful'), (6, 'State B', 'failed'); CREATE TABLE states (state_id INT, name VARCHAR(50)); INSERT INTO states (state_id, name) VALUES (1, 'State A'), (2, 'State B'), (3, 'State C'); | What is the total number of successful and failed evacuation missions in each state? | SELECT s.name, SUM(CASE WHEN e.mission_status = 'successful' THEN 1 ELSE 0 END) AS num_successful, SUM(CASE WHEN e.mission_status = 'failed' THEN 1 ELSE 0 END) AS num_failed FROM evacuations e JOIN states s ON e.state = s.name GROUP BY s.name | gretelai_synthetic_text_to_sql |
CREATE TABLE languages (id INT, language VARCHAR(255), native_speakers INT, country VARCHAR(255)); INSERT INTO languages (id, language, native_speakers, country) VALUES (1, 'Mandarin', 1100000, 'China'), (2, 'Quechua', 800000, 'Peru'); | How many languages have more than 1000 native speakers? | SELECT COUNT(*) FROM languages WHERE native_speakers > 1000; | gretelai_synthetic_text_to_sql |
CREATE TABLE rural_clinic_5 (patient_id INT, age INT, gender VARCHAR(10)); INSERT INTO rural_clinic_5 (patient_id, age, gender) VALUES (1, 35, 'Male'), (2, 50, 'Female'), (3, 42, 'Male'), (4, 60, 'Male'), (5, 30, 'Female'), (6, 45, 'Female'), (7, 40, 'Male'); | What is the number of male patients in the 'rural_clinic_5' table? | SELECT COUNT(*) FROM rural_clinic_5 WHERE gender = 'Male'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Weather (location VARCHAR(50), rainfall INT, timestamp TIMESTAMP); | What is the total rainfall in Oregon in the past week? | SELECT SUM(rainfall) FROM Weather WHERE location = 'Oregon' AND timestamp > NOW() - INTERVAL '1 week'; | gretelai_synthetic_text_to_sql |
CREATE TABLE species (species_id INT, species_name VARCHAR(50)); CREATE TABLE species_observations (observation_id INT, species_id INT, observation_date DATE); INSERT INTO species (species_id, species_name) VALUES (1, 'Polar Bear'), (2, 'Arctic Fox'), (3, 'Arctic Char'); INSERT INTO species_observations (observation_id, species_id, observation_date) VALUES (1, 1, '2017-01-01'), (2, 1, '2018-02-10'), (3, 2, '2019-03-15'), (4, 3, '2020-04-01'); | Delete all species observation records that are older than 5 years. | DELETE FROM species_observations WHERE observation_date < (CURRENT_DATE - INTERVAL '5 years'); | gretelai_synthetic_text_to_sql |
CREATE TABLE permits (id INT PRIMARY KEY, project_id INT, issue_date DATE, expiry_date DATE); INSERT INTO permits (id, project_id, issue_date, expiry_date) VALUES (1, 1, '2020-01-10', '2021-01-10'); INSERT INTO permits (id, project_id, issue_date, expiry_date) VALUES (2, 2, '2021-02-15', '2022-02-15'); | Which projects have had more than one building permit issued? | (SELECT project_id FROM permits GROUP BY project_id HAVING COUNT(*) > 1) | gretelai_synthetic_text_to_sql |
CREATE TABLE properties (id INT, city VARCHAR(50), state VARCHAR(2), build_date DATE, co_owners INT); INSERT INTO properties (id, city, state, build_date, co_owners) VALUES (1, 'Los Angeles', 'CA', '1999-01-01', 2), (2, 'San Diego', 'CA', '2005-01-01', 1), (3, 'Houston', 'TX', '1985-01-01', 3); | List the number of properties in each state that were built before 2000 and have more than one co-owner. | SELECT state, COUNT(*) FROM properties WHERE build_date < '2000-01-01' AND co_owners > 1 GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE investigative_journalism (article_id INT, author VARCHAR(50), title VARCHAR(100), published_date DATE, category VARCHAR(30), word_count INT, author_gender VARCHAR(10)); INSERT INTO investigative_journalism (article_id, author, title, published_date, category, word_count, author_gender) VALUES (1, 'Carlos Alvarez', 'Article 1', '2021-01-01', 'Crime', 1500, 'Male'); | What is the total number of articles in the 'investigative_journalism' table for each author's gender? | SELECT author_gender, COUNT(article_id) AS total_articles FROM investigative_journalism GROUP BY author_gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE veteran_employment (veteran_id INT, job_title VARCHAR(30), hire_date DATE, salary FLOAT); | Insert a new record into the 'veteran_employment' table for a veteran hired as a 'software engineer' on 2022-03-15 with a salary of $80,000 | INSERT INTO veteran_employment (veteran_id, job_title, hire_date, salary) VALUES (1, 'software engineer', '2022-03-15', 80000); | gretelai_synthetic_text_to_sql |
CREATE TABLE satellite (id INT, name VARCHAR(255), launch_site_id INT, country_id INT, launch_date DATE); INSERT INTO satellite (id, name, launch_site_id, country_id, launch_date) VALUES (1, 'Sentinel-3B', 1, 1, '2018-04-25'), (2, 'Telstar 18V', 2, 3, '2018-09-11'), (3, 'Galileo FOC FM-11', 3, 2, '2018-06-27'); CREATE TABLE launch_site (id INT, name VARCHAR(255)); INSERT INTO launch_site (id, name) VALUES (1, 'ESA Spaceport'), (2, 'Cape Canaveral'), (3, 'Kourou'); CREATE TABLE country (id INT, name VARCHAR(255)); INSERT INTO country (id, name) VALUES (1, 'France'), (2, 'Germany'), (3, 'USA'); | List all satellites with their launch sites and the country responsible for the launches in 2018. | SELECT s.name, ls.name as launch_site, c.name as country FROM satellite s INNER JOIN launch_site ls ON s.launch_site_id = ls.id INNER JOIN country c ON s.country_id = c.id WHERE YEAR(s.launch_date) = 2018; | gretelai_synthetic_text_to_sql |
CREATE TABLE Deliveries (id INT, delivery_date DATETIME, delivery_country VARCHAR(50)); INSERT INTO Deliveries (id, delivery_date, delivery_country) VALUES (1, '2022-01-01', 'Japan'), (2, '2022-01-02', 'China'), (3, '2022-01-03', 'South Korea'); | What are the average delivery times for each country in Asia? | SELECT delivery_country, AVG(DATEDIFF('2022-01-04', delivery_date)) avg_delivery_time FROM Deliveries WHERE delivery_country IN ('Japan', 'China', 'South Korea') GROUP BY delivery_country; | gretelai_synthetic_text_to_sql |
CREATE TABLE sales(product_id INT, category VARCHAR(255), amount DECIMAL(10,2), sale_date DATE); INSERT INTO sales(product_id, category, amount, sale_date) VALUES (1, 'Analgesics', 1500, '2021-01-01'), (2, 'Antidepressants', 2000, '2021-01-05'), (3, 'Antibiotics', 1200, '2021-01-10'); | What are the total sales for each product category in Q1 2021? | SELECT category, SUM(amount) as total_sales FROM sales WHERE sale_date BETWEEN '2021-01-01' AND '2021-03-31' GROUP BY category; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, DonorName VARCHAR(50), DonationAmount DECIMAL(10,2), CauseID INT);CREATE TABLE Causes (CauseID INT, CauseName VARCHAR(50)); | What is the average donation per donor for each cause? | SELECT C.CauseName, AVG(D.DonationAmount) FROM Donors D JOIN Causes C ON D.CauseID = C.CauseID GROUP BY C.CauseName; | gretelai_synthetic_text_to_sql |
CREATE TABLE SustainableUrbanismByYear (id INT PRIMARY KEY, city VARCHAR(50), state VARCHAR(50), initiative VARCHAR(100), year INT, date DATE); | Alter the SustainableUrbanismByYear table to include a date column | ALTER TABLE SustainableUrbanismByYear ADD COLUMN date DATE; | gretelai_synthetic_text_to_sql |
CREATE TABLE if not exists VehicleSafetyRating (Id int, Vehicle varchar(100), Country varchar(50), SafetyRating float); INSERT INTO VehicleSafetyRating (Id, Vehicle, Country, SafetyRating) VALUES (1, 'Tesla Model 3', 'USA', 5.3), (2, 'Tesla Model S', 'USA', 5.4), (3, 'Nissan Leaf', 'Japan', 4.8), (4, 'BMW i3', 'Germany', 4.9), (5, 'Renault Zoe', 'France', 4.6), (6, 'BYD e6', 'China', 4.4); | Find the average safety rating of the top 2 vehicles in each country? | SELECT Country, AVG(SafetyRating) FROM (SELECT Country, SafetyRating FROM VehicleSafetyRating GROUP BY Country ORDER BY AVG(SafetyRating) DESC LIMIT 2) AS Subquery; | gretelai_synthetic_text_to_sql |
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