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 volunteers (id INT, name VARCHAR(255), program VARCHAR(255), volunteer_date DATE); CREATE TABLE all_programs (id INT, name VARCHAR(255), focus_area VARCHAR(255)); | How many unique volunteers have there been in each program in the past year? | SELECT program, COUNT(DISTINCT id) FROM volunteers JOIN all_programs ON volunteers.program = all_programs.name WHERE volunteer_date >= DATEADD(year, -1, GETDATE()) GROUP BY program; | gretelai_synthetic_text_to_sql |
CREATE TABLE fields (field_id INT, field_name TEXT, location TEXT); | Insert a new record into the 'fields' table for a field named 'Offshore Field X' located in the Gulf of Mexico. | INSERT INTO fields (field_name, location) VALUES ('Offshore Field X', 'Gulf of Mexico'); | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_offset_projects (id INT PRIMARY KEY, project_name VARCHAR(100), location VARCHAR(50)); | Add a new carbon offset project called 'Peatland Restoration' to the 'carbon_offset_projects' table | INSERT INTO carbon_offset_projects (project_name, location) VALUES ('Peatland Restoration', 'Boreal Forest'); | gretelai_synthetic_text_to_sql |
CREATE SCHEMA space; USE space; CREATE TABLE spacecraft (name VARCHAR(50), destination VARCHAR(50), visits INT); INSERT INTO spacecraft (name, destination, visits) VALUES ('Mariner 4', 'Mars', 1), ('Mariner 6', 'Mars', 1), ('Mariner 7', 'Mars', 1), ('Viking 1', 'Mars', 1), ('Viking 2', 'Mars', 1), ('Mars Global Surveyor', 'Mars', 1), ('Mars Pathfinder', 'Mars', 1), ('Mars Reconnaissance Orbiter', 'Mars', 1), ('Mars Science Laboratory', 'Mars', 1), ('Mars Exploration Rover', 'Mars', 2); | What is the total number of spacecraft that have visited Mars? | SELECT COUNT(name) FROM space.spacecraft WHERE destination = 'Mars'; | gretelai_synthetic_text_to_sql |
CREATE TABLE news_articles (id INT, title VARCHAR(100), section VARCHAR(50), rating INT); INSERT INTO news_articles (id, title, section, rating) VALUES (1, 'Article 1', 'technology', 4), (2, 'Article 2', 'politics', 5), (3, 'Article 3', 'sports', 3), (4, 'Article 4', 'international', 7); CREATE TABLE news_ratings (article_id INT, rating INT); INSERT INTO news_ratings (article_id, rating) VALUES (1, 4), (2, 5), (3, 3), (4, 7); | Which international news article has the highest rating? | SELECT title FROM news_articles WHERE id = (SELECT article_id FROM news_ratings WHERE rating = (SELECT MAX(rating) FROM news_ratings WHERE section = 'international')); | gretelai_synthetic_text_to_sql |
CREATE TABLE IndigenousCommunities (id INT PRIMARY KEY, community VARCHAR(255), location VARCHAR(255), population INT); INSERT INTO IndigenousCommunities (id, community, location, population) VALUES (1, 'Inuit', 'Canada', 60000); INSERT INTO IndigenousCommunities (id, community, location, population) VALUES (2, 'Sami', 'Norway', 80000); | Calculate the total number of indigenous communities in each Arctic country. | SELECT location, COUNT(DISTINCT community) as total_communities FROM IndigenousCommunities GROUP BY location; | gretelai_synthetic_text_to_sql |
CREATE TABLE wildlife_habitat (species VARCHAR(255), forest_type VARCHAR(255)); | Find the wildlife species that are present in both temperate and tropical forests. | SELECT species FROM wildlife_habitat WHERE forest_type IN ('temperate', 'tropical') GROUP BY species HAVING COUNT(DISTINCT forest_type) = 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE RuralInfrastructure (region TEXT, year INTEGER, project_status TEXT); INSERT INTO RuralInfrastructure (region, year, project_status) VALUES ('South Asia', 2019, 'completed'), ('South Asia', 2020, 'completed'), ('South Asia', 2021, 'completed'), ('South Asia', 2019, 'in progress'), ('South Asia', 2020, 'in progress'), ('South Asia', 2021, 'in progress'); | How many rural infrastructure projects were completed in South Asia in each year? | SELECT year, COUNT(*) FROM RuralInfrastructure WHERE region = 'South Asia' AND project_status = 'completed' GROUP BY year; | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, condition VARCHAR(50), region VARCHAR(50)); INSERT INTO patients (id, condition, region) VALUES (1, 'Anxiety', 'Europe'), (2, 'Depression', 'Europe'), (3, 'Bipolar Disorder', 'Europe'), (4, 'Anxiety', 'USA'); | What percentage of patients in Europe have anxiety as a primary condition? | SELECT (COUNT(*) * 100.0 / (SELECT COUNT(*) FROM patients WHERE region = 'Europe')) AS percentage FROM patients WHERE region = 'Europe' AND condition = 'Anxiety'; | gretelai_synthetic_text_to_sql |
CREATE TABLE date (date_id INT, date DATE); INSERT INTO date (date_id, date) VALUES (1, '2022-01-01'), (2, '2022-02-01'), (3, '2022-03-01'), (4, '2022-04-01'), (5, '2022-05-01'), (6, '2022-06-01'), (7, '2022-07-01'), (8, '2022-08-01'), (9, '2022-09-01'), (10, '2022-10-01'), (11, '2022-11-01'), (12, '2022-12-01'); CREATE TABLE water_usage (usage_id INT, date_id INT, water_usage_m3 FLOAT); INSERT INTO water_usage (usage_id, date_id, water_usage_m3) VALUES (1, 1, 1000), (2, 1, 1200), (3, 2, 1500), (4, 2, 1800), (5, 3, 2000), (6, 3, 2200), (7, 4, 1500), (8, 4, 1700), (9, 5, 1200), (10, 5, 1400), (11, 6, 1000), (12, 6, 1100), (13, 7, 1500), (14, 7, 1800), (15, 8, 2000), (16, 8, 2200), (17, 9, 1500), (18, 9, 1700), (19, 10, 1200), (20, 10, 1400), (21, 11, 1000), (22, 11, 1100), (23, 12, 1500), (24, 12, 1800); | What is the total water usage per month for the last year? | SELECT EXTRACT(MONTH FROM d.date) as month, AVG(w.water_usage_m3) as avg_water_usage_m3 FROM water_usage w JOIN date d ON w.date_id = d.date_id WHERE d.date BETWEEN '2021-01-01' AND '2022-12-31' GROUP BY EXTRACT(MONTH FROM d.date); | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, name TEXT, founder_gender TEXT); INSERT INTO companies (id, name, founder_gender) VALUES (1, 'Acme Inc', 'female'), (2, 'Beta Corp', 'male'); CREATE TABLE funding (company_id INT, amount INT); INSERT INTO funding (company_id, amount) VALUES (1, 500000), (2, 750000); | What is the total funding received by startups founded by women? | SELECT SUM(funding.amount) FROM companies INNER JOIN funding ON companies.id = funding.company_id WHERE companies.founder_gender = 'female'; | gretelai_synthetic_text_to_sql |
CREATE TABLE timber_production (id INT, year INT, volume FLOAT); INSERT INTO timber_production (id, year, volume) VALUES (1, 2020, 1200.5), (2, 2021, 1500.7), (3, 2022, 1700.3); | How many timber production records were inserted in 2022? | SELECT COUNT(*) FROM timber_production WHERE year = 2022; | gretelai_synthetic_text_to_sql |
CREATE TABLE heritage_preservation (project_id INT, project_name TEXT, start_date DATE, end_date DATE, budget INT); | Insert new records into the heritage_preservation table for a new project. | INSERT INTO heritage_preservation (project_id, project_name, start_date, end_date, budget) VALUES (2001, 'Conservation of Indigenous Art', '2023-01-01', '2023-12-31', 500000); | gretelai_synthetic_text_to_sql |
CREATE TABLE SupportPrograms (programID INT, programName VARCHAR(50), enrollment INT); | What is the maximum number of students enrolled in a support program in the SupportPrograms table? | SELECT MAX(enrollment) FROM SupportPrograms; | gretelai_synthetic_text_to_sql |
CREATE TABLE dallas_emergency_response (id INT, incident_type TEXT, response_time INT); INSERT INTO dallas_emergency_response (id, incident_type, response_time) VALUES (1, 'Fire', 120), (2, 'Medical', 150), (3, 'Police', 180); | What is the average incident response time in Dallas? | SELECT AVG(response_time) FROM dallas_emergency_response WHERE incident_type = 'Police'; | gretelai_synthetic_text_to_sql |
CREATE TABLE CitizenFeedback (District VARCHAR(10), Quarter INT, Year INT, FeedbackCount INT); INSERT INTO CitizenFeedback VALUES ('District K', 3, 2021, 700), ('District K', 4, 2021, 800), ('District L', 3, 2021, 600), ('District L', 4, 2021, 700); | How many citizens provided feedback in District K and L in Q3 and Q4 of 2021? | SELECT SUM(FeedbackCount) FROM CitizenFeedback WHERE District IN ('District K', 'District L') AND Quarter IN (3, 4) AND Year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (species_name TEXT, conservation_status TEXT, habitat TEXT); INSERT INTO marine_species (species_name, conservation_status, habitat) VALUES ('Beluga Whale', 'Near Threatened', 'Arctic Ocean'), ('Greenland Shark', 'Least Concern', 'Atlantic and Arctic Oceans'), ('Polar Bear', 'Vulnerable', 'Arctic Ocean'); | List all marine species found in the Arctic Ocean | SELECT species_name FROM marine_species WHERE habitat = 'Arctic Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE inspection_scores (restaurant_name TEXT, location TEXT, score INTEGER); INSERT INTO inspection_scores (restaurant_name, location, score) VALUES ('Restaurant A', 'California', 90), ('Restaurant B', 'California', 85), ('Restaurant C', 'California', 95); | What is the maximum food safety score for restaurants in 'California'? | SELECT MAX(score) FROM inspection_scores WHERE location = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE FashionBrands (BrandID INT, BrandName VARCHAR(50), SustainableFabricsUsed INT); CREATE TABLE FabricUsage (BrandID INT, FabricType VARCHAR(50), QuantityUsed INT); | What is the total quantity of sustainable fabrics used by each fashion brand? | SELECT FB.BrandName, SUM(FU.QuantityUsed) AS TotalSustainableFabricsUsed FROM FashionBrands FB INNER JOIN FabricUsage FU ON FB.BrandID = FU.BrandID WHERE FB.SustainableFabricsUsed = 1 GROUP BY FB.BrandName; | gretelai_synthetic_text_to_sql |
CREATE TABLE canada_platforms (platform_id INT, platform_name VARCHAR(50), location VARCHAR(50), operational_status VARCHAR(15)); INSERT INTO canada_platforms VALUES (1, 'Suncor 1', 'Alberta', 'Active'); INSERT INTO canada_platforms VALUES (2, 'Imperial Oil 1', 'Alberta', 'Active'); CREATE TABLE oil_production (platform_id INT, year INT, month INT, production FLOAT); INSERT INTO oil_production VALUES (1, 2015, 1, 1200000); INSERT INTO oil_production VALUES (1, 2015, 2, 1300000); INSERT INTO oil_production VALUES (2, 2015, 1, 1000000); INSERT INTO oil_production VALUES (2, 2015, 2, 1100000); | What was the average crude oil production in Canada by month? | SELECT month, AVG(production) FROM oil_production GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE Organic_Cosmetics (product_id INT, product_name VARCHAR(255), category VARCHAR(255), price DECIMAL(10,2)); INSERT INTO Organic_Cosmetics (product_id, product_name, category, price) VALUES (1, 'Organic Cosmetic 1', 'Organic', 35.99), (2, 'Organic Cosmetic 2', 'Organic', 45.99), (3, 'Organic Cosmetic 3', 'Organic', 25.99), (4, 'Organic Cosmetic 4', 'Organic', 55.99); | List all cosmetics with a price greater than 40 USD from the organic line. | SELECT * FROM Organic_Cosmetics WHERE price > 40; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, DonorName TEXT, DonationAmount DECIMAL(10,2), FirstDonationDate DATE); INSERT INTO Donors (DonorID, DonorName, DonationAmount, FirstDonationDate) VALUES (1, 'Grace', 250.00, '2021-08-20'), (2, 'Harry', 550.00, '2022-02-10'); | What is the average donation amount for new and returning donors in H1 2022? | SELECT CASE WHEN FirstDonationDate BETWEEN '2022-01-01' AND '2022-06-30' THEN 'New Donor' ELSE 'Returning Donor' END as DonorType, AVG(DonationAmount) as AvgDonation FROM Donors WHERE DonationDate BETWEEN '2022-01-01' AND '2022-06-30' GROUP BY DonorType; | gretelai_synthetic_text_to_sql |
CREATE TABLE restorative_justice_program (id INT, age INT, completion_date DATE); | What is the average age of individuals who have completed a restorative justice program in the last year? | SELECT AVG(age) FROM restorative_justice_program WHERE completion_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR); | gretelai_synthetic_text_to_sql |
CREATE TABLE production (id INT, product_id INT, material VARCHAR(50), production_cost DECIMAL(5,2)); | What is the total production cost for each sustainable material? | SELECT material, SUM(production_cost) AS total_production_cost FROM production WHERE material IN ('organic_cotton', 'recycled_polyester', 'tencel', 'hemp', 'modal') GROUP BY material; | gretelai_synthetic_text_to_sql |
CREATE TABLE AIEthicsPapers (id INT, paper_title VARCHAR(50), author_name VARCHAR(50), affiliation VARCHAR(50), publication_date DATE, num_citations INT); INSERT INTO AIEthicsPapers (id, paper_title, author_name, affiliation, publication_date, num_citations) VALUES (1, 'AI Ethics in Africa: A Review', 'John Doe', 'University of Cape Town', '2023-01-01', 20), (2, 'Exploring Bias in AI Algorithms', 'Jane Smith', 'University of Nairobi', '2023-02-01', 30), (3, 'AI Ethics and Human Rights in Africa', 'Olu Ade', 'University of Lagos', '2023-03-01', 15), (4, 'The Role of AI in African Development', 'James Njenga', 'University of Addis Ababa', '2023-04-01', 25), (5, 'AI Ethics in African Healthcare', 'Fatima Kaba', 'University of Cairo', '2023-05-01', 40); | How many AI ethics research papers were published in the past year by authors affiliated with universities in Africa, and what is the minimum number of citations for a single paper? | SELECT affiliation, COUNT(*) as paper_count FROM AIEthicsPapers WHERE affiliation IN (SELECT affiliation FROM AIEthicsPapers WHERE publication_date >= '2022-01-01' AND author_name IN (SELECT author_name FROM AIEthicsPapers WHERE affiliation LIKE '%Africa%')) GROUP BY affiliation; SELECT MIN(num_citations) as min_citations FROM AIEthicsPapers WHERE publication_date >= '2022-01-01' AND author_name IN (SELECT author_name FROM AIEthicsPapers WHERE affiliation LIKE '%Africa%'); | gretelai_synthetic_text_to_sql |
CREATE TABLE mental_health (patient_id INT, gender VARCHAR(10), condition VARCHAR(50)); INSERT INTO mental_health (patient_id, gender, condition) VALUES (1, 'Male', 'Depression'), (2, 'Female', 'Anxiety'), (3, 'Non-binary', 'Bipolar'), (4, 'Male', 'PTSD'), (5, 'Female', 'Depression'), (6, 'Non-binary', 'Anxiety'), (7, 'Male', 'Bipolar'), (8, 'Female', 'PTSD'); | What is the distribution of mental health conditions among different genders? | SELECT gender, condition, COUNT(*) as count FROM mental_health GROUP BY gender, condition; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_mammals (mammal_id INT, mammal_name VARCHAR(255), PRIMARY KEY(mammal_id)); INSERT INTO marine_mammals (mammal_id, mammal_name) VALUES (1, 'Polar Bear'); CREATE TABLE population_trends (population_id INT, mammal_id INT, region VARCHAR(255), population_status VARCHAR(255), PRIMARY KEY(population_id, mammal_id), FOREIGN KEY (mammal_id) REFERENCES marine_mammals(mammal_id)); INSERT INTO population_trends (population_id, mammal_id, region, population_status) VALUES (1, 1, 'Arctic Ocean', 'Decreasing'); | List all marine mammal species and their population trends in the Arctic Ocean. | SELECT marine_mammals.mammal_name, population_trends.population_status FROM marine_mammals INNER JOIN population_trends ON marine_mammals.mammal_id = population_trends.mammal_id WHERE population_trends.region = 'Arctic Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE IslandSite (site VARCHAR(50), date DATE, artifacts INT); INSERT INTO IslandSite (site, date, artifacts) VALUES ('IslandSite1', '2019-01-01', 5), ('IslandSite1', '2019-01-02', 7); INSERT INTO IslandSite (site, date, artifacts) VALUES ('IslandSite2', '2019-01-01', 3), ('IslandSite2', '2019-01-02', 4); | What was the total number of artifacts found in 'IslandSite1' and 'IslandSite2' in '2019'? | SELECT SUM(artifacts) FROM IslandSite WHERE site IN ('IslandSite1', 'IslandSite2') AND date LIKE '2019-%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE countries (country_name VARCHAR(50), eco_tourism_activities INT); INSERT INTO countries (country_name, eco_tourism_activities) VALUES ('Costa Rica', 100), ('Nepal', 80), ('Bhutan', 60), ('New Zealand', 120); | Rank countries by the number of eco-tourism activities offered, highest first. | SELECT country_name, ROW_NUMBER() OVER(ORDER BY eco_tourism_activities DESC) as rank FROM countries; | gretelai_synthetic_text_to_sql |
CREATE TABLE Tours (id INT, country TEXT, type TEXT, participants INT); INSERT INTO Tours (id, country, type, participants) VALUES (1, 'South Africa', 'Eco-friendly', 200), (2, 'South Africa', 'Regular', 300), (3, 'South Africa', 'Eco-friendly', 250); | What is the total number of eco-friendly tours in South Africa? | SELECT SUM(participants) FROM Tours WHERE country = 'South Africa' AND type = 'Eco-friendly'; | gretelai_synthetic_text_to_sql |
CREATE TABLE movies (title VARCHAR(255), rating INT, director VARCHAR(50)); INSERT INTO movies (title, rating, director) VALUES ('Movie1', 8, 'DirectorA'), ('Movie2', 7, 'DirectorB'), ('Movie3', 9, 'DirectorA'), ('Movie4', 6, 'DirectorB'); | What is the average movie rating for each director? | SELECT director, AVG(rating) as avg_rating FROM movies GROUP BY director; | gretelai_synthetic_text_to_sql |
CREATE TABLE MentalHealthParityRegulations (State VARCHAR(20), Year INT, Regulation VARCHAR(100)); INSERT INTO MentalHealthParityRegulations (State, Year, Regulation) VALUES ('New York', 2016, 'Regulation 1'), ('New York', 2018, 'Regulation 2'), ('Florida', 2017, 'Regulation A'), ('Florida', 2019, 'Regulation B'); | What is the number of mental health parity regulations implemented in New York and Florida since 2015? | SELECT * FROM MentalHealthParityRegulations WHERE State IN ('New York', 'Florida') AND Year >= 2015; | gretelai_synthetic_text_to_sql |
CREATE TABLE vehicle_stats (id INT, vehicle_make VARCHAR(50), mpg INT, is_domestic BOOLEAN); INSERT INTO vehicle_stats (id, vehicle_make, mpg, is_domestic) VALUES (1, 'Toyota', 32, false), (2, 'Honda', 35, false), (3, 'Ford', 28, true), (4, 'Chevy', 25, true), (5, 'Tesla', null, true); | Calculate the average miles per gallon for domestic vehicles | SELECT AVG(mpg) as avg_mpg FROM vehicle_stats WHERE is_domestic = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE Water_Distribution (project_id INT, project_name VARCHAR(100), total_cost FLOAT); INSERT INTO Water_Distribution (project_id, project_name, total_cost) VALUES (1, 'Water Treatment Plant', 5000000.00), (2, 'Pipe Replacement', 2000000.00), (4, 'Water Main Installation', 4000000.00); | What is the number of projects in the 'Water_Distribution' table that have a total cost greater than $3,000,000.00? | SELECT COUNT(*) FROM Water_Distribution WHERE total_cost > 3000000.00; | gretelai_synthetic_text_to_sql |
CREATE TABLE HealthEquityMetrics (ID INT, CommunityHealthWorker VARCHAR(50), Score INT); INSERT INTO HealthEquityMetrics (ID, CommunityHealthWorker, Score) VALUES (1, 'John Doe', 95), (2, 'Jane Smith', 88); | What is the health equity metric performance for each community health worker? | SELECT CommunityHealthWorker, Score, RANK() OVER (PARTITION BY Score ORDER BY CommunityHealthWorker) as Rank FROM HealthEquityMetrics; | gretelai_synthetic_text_to_sql |
CREATE TABLE Audience (AudienceID INT, AudienceName VARCHAR(50)); CREATE TABLE AudienceAttendance (EventID INT, AudienceID INT); INSERT INTO Audience (AudienceID, AudienceName) VALUES (1, 'Alice'), (2, 'Bob'), (3, 'Charlie'); INSERT INTO AudienceAttendance (EventID, AudienceID) VALUES (1, 1), (1, 2), (2, 1), (2, 3); | How many unique audience members attended events in 2021? | SELECT COUNT(DISTINCT a.AudienceID) as NumUniqueAudienceMembers FROM Audience a INNER JOIN AudienceAttendance aa ON a.AudienceID = aa.AudienceID INNER JOIN Events e ON aa.EventID = e.EventID WHERE e.EventDate >= '2021-01-01' AND e.EventDate < '2022-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE volunteers (id INT PRIMARY KEY, name VARCHAR(255), email VARCHAR(255), hours_per_week FLOAT); | Delete the record for Maria Garcia from the 'volunteers' table | DELETE FROM volunteers WHERE name = 'Maria Garcia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, name VARCHAR(50), ethnicity VARCHAR(50), mental_health_parity BOOLEAN); INSERT INTO patients (id, name, ethnicity, mental_health_parity) VALUES (1, 'Alice', 'Caucasian', true), (2, 'Brian', 'African American', false); CREATE TABLE interpreter_services (id INT, patient_id INT, interpreter_language VARCHAR(50), date DATE); INSERT INTO interpreter_services (id, patient_id, interpreter_language, date) VALUES (1, 1, 'Spanish', '2022-01-02'), (2, 3, 'Mandarin', '2022-03-01'); | List patients who have used interpreter services but do not have mental health parity. | SELECT patients.name FROM patients WHERE mental_health_parity = false INTERSECT SELECT patients.name FROM patients INNER JOIN interpreter_services ON patients.id = interpreter_services.patient_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE recycling_rates(year INT, state VARCHAR(255), plastic_recycling FLOAT, paper_recycling FLOAT, glass_recycling FLOAT); INSERT INTO recycling_rates VALUES (2020, 'California', 0.6, 0.7, 0.5), (2020, 'Texas', 0.5, 0.6, 0.4); | What is the maximum recycling rate for plastic in 2020 for each state? | SELECT MAX(plastic_recycling) AS max_plastic_recycling, state FROM recycling_rates WHERE year = 2020 GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE vessels (id INT, name TEXT, type TEXT, speed FLOAT, gps_position TEXT); CREATE TABLE gps_positions (id INT, latitude FLOAT, longitude FLOAT, country TEXT, month INT); | What is the average speed of vessels in the Arctic, grouped by month and vessel type? | SELECT v.type, AVG(v.speed), g.month FROM vessels v JOIN gps_positions g ON v.gps_position = g.id WHERE g.country = 'Arctic' GROUP BY v.type, g.month; | gretelai_synthetic_text_to_sql |
CREATE TABLE Spending (id INT, country TEXT, year INT, spending FLOAT); INSERT INTO Spending (id, country, year, spending) VALUES (1, 'Indonesia', 2018, 1000), (2, 'Indonesia', 2019, 1200), (3, 'Indonesia', 2020, 800); | What is the average tourist spending in Indonesia? | SELECT AVG(spending) FROM Spending WHERE country = 'Indonesia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_protected_areas (area_name TEXT, ocean_basin TEXT, depth FLOAT); INSERT INTO marine_protected_areas (area_name, ocean_basin, depth) VALUES ('Galapagos Islands', 'Pacific', 2000.0), ('Great Barrier Reef', 'Pacific', 1000.0), ('Palau National Marine Sanctuary', 'Pacific', 5000.0), ('Northwest Atlantic Marine National Monument', 'Atlantic', 1500.0); | List all marine protected areas in the Atlantic Ocean and their depths. | SELECT area_name, depth FROM marine_protected_areas WHERE ocean_basin = 'Atlantic'; | gretelai_synthetic_text_to_sql |
CREATE TABLE investments_esg (id INT, sector VARCHAR(255), esg_factor VARCHAR(255), investment_amount INT); INSERT INTO investments_esg (id, sector, esg_factor, investment_amount) VALUES (1, 'Energy', 'E', 500000), (2, 'Energy', 'S', 350000), (3, 'Energy', 'G', 450000); | What is the total investment in the Energy sector, broken down by ESG factors? | SELECT sector, esg_factor, SUM(investment_amount) FROM investments_esg WHERE sector = 'Energy' GROUP BY sector, esg_factor; | gretelai_synthetic_text_to_sql |
CREATE TABLE multimodal_mobility (id INT, city VARCHAR(50), mode VARCHAR(50), users INT); | Delete records from the 'multimodal_mobility' table where the 'mode' is 'Bus' | DELETE FROM multimodal_mobility WHERE mode = 'Bus'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Members (ID INT, Gender VARCHAR(10), Age INT, Activity VARCHAR(20)); INSERT INTO Members (ID, Gender, Age, Activity) VALUES (1, 'Male', 35, 'Yoga'); | What's the average age of male members who do yoga? | SELECT AVG(Age) FROM Members WHERE Gender = 'Male' AND Activity = 'Yoga'; | gretelai_synthetic_text_to_sql |
CREATE TABLE games (game_id INT, game_genre VARCHAR(255), num_players INT); | How many games were played in the 'Strategy' genre that have more than 1000 players? | SELECT COUNT(game_id) FROM games WHERE game_genre = 'Strategy' HAVING num_players > 1000; | gretelai_synthetic_text_to_sql |
CREATE TABLE threat_intelligence (report_id INT, report_date DATE, region TEXT); INSERT INTO threat_intelligence (report_id, report_date, region) VALUES (1, '2022-01-01', 'Northeast'), (2, '2022-02-15', 'Midwest'); | Identify the number of threat intelligence reports generated in the last 6 months by region | SELECT region, COUNT(report_id) FROM threat_intelligence WHERE report_date >= DATE_SUB(CURRENT_DATE, INTERVAL 6 MONTH) GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE stations (station_id INTEGER, name TEXT, latitude REAL, longitude REAL); INSERT INTO stations (station_id, name, latitude, longitude) VALUES (1, 'Downtown', 40.7128, -74.0060); | List all unique station names and their corresponding latitudes and longitudes from the stations table | SELECT DISTINCT name, latitude, longitude FROM stations; | gretelai_synthetic_text_to_sql |
CREATE TABLE dishes (dish_id INT, name VARCHAR(50), fiber INT, serving_size INT); INSERT INTO dishes (dish_id, name, fiber, serving_size) VALUES (1, 'Quinoa Salad', 8, 200), (2, 'Lentil Soup', 12, 300), (3, 'Chickpea Curry', 10, 350); | What is the percentage of dishes that meet the daily recommended intake of fiber? | SELECT 100.0 * COUNT(*) / (SELECT COUNT(*) FROM dishes) AS percentage FROM dishes WHERE fiber >= (SELECT serving_size * 0.5); | gretelai_synthetic_text_to_sql |
CREATE TABLE defense_contracts (contract_id INT, vendor_state VARCHAR(2), contract_value DECIMAL(10,2), contract_date DATE); INSERT INTO defense_contracts VALUES (1, 'CA', 500000.00, '2020-01-05'), (2, 'CA', 600000.00, '2020-01-10'), (3, 'TX', 400000.00, '2020-01-15'); | What is the total value of defense contracts signed by vendors from California in Q1 2020? | SELECT SUM(contract_value) FROM defense_contracts WHERE vendor_state = 'CA' AND contract_date >= '2020-01-01' AND contract_date < '2020-04-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE labor_productivity (id INT, mine_id INT, state TEXT, employees INT, production INT); INSERT INTO labor_productivity (id, mine_id, state, employees, production) VALUES (1, 3, 'Texas', 50, 2000), (2, 3, 'Texas', 50, 2000), (3, 4, 'California', 75, 3000); | What is the average labor productivity per mine by state in the USA? | SELECT state, AVG(production/employees) as avg_productivity FROM labor_productivity GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, name VARCHAR(50), gender VARCHAR(10), age INT, location VARCHAR(50)); CREATE TABLE posts (id INT, user_id INT, content TEXT, timestamp TIMESTAMP); | What is the total number of posts created by users in 'California' between '2021-01-01' and '2021-03-31'? | SELECT COUNT(posts.id) AS total_posts FROM posts JOIN users ON posts.user_id = users.id WHERE users.location = 'California' AND posts.timestamp BETWEEN '2021-01-01' AND '2021-03-31'; | gretelai_synthetic_text_to_sql |
trends(id, industry, innovation_trend, trend_impact) | Add a new innovation trend for the industry 'technology' in the 'trends' table | INSERT INTO trends (id, industry, innovation_trend, trend_impact) VALUES (4, 'technology', 'AI in healthcare', 0.9); | gretelai_synthetic_text_to_sql |
CREATE TABLE Policy_Advocacy_Events (event_id INT, year INT, type VARCHAR(255)); INSERT INTO Policy_Advocacy_Events VALUES (1, 2021, 'Webinar'); | What is the number of policy advocacy events held in 2021? | SELECT COUNT(*) FROM Policy_Advocacy_Events WHERE year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE payment_methods (id INT, payment_method VARCHAR(50), donation_date DATE, donation_amount FLOAT); INSERT INTO payment_methods (id, payment_method, donation_date, donation_amount) VALUES (1, 'Credit Card', '2023-04-01', 50.0), (2, 'Debit Card', '2023-05-15', 100.0), (3, 'PayPal', '2023-06-30', 200.0); | What was the average donation amount by payment method in Q2 2023? | SELECT payment_method, AVG(donation_amount) FROM payment_methods WHERE donation_date BETWEEN '2023-04-01' AND '2023-06-30' GROUP BY payment_method; | gretelai_synthetic_text_to_sql |
CREATE TABLE OccupationGenderData (Occupation VARCHAR(255), Gender VARCHAR(10), AvgIncome DECIMAL(10,2)); INSERT INTO OccupationGenderData (Occupation, Gender, AvgIncome) VALUES ('Occupation A', 'Male', 50000.00), ('Occupation A', 'Female', 45000.00), ('Occupation B', 'Male', 60000.00), ('Occupation B', 'Female', 55000.00); CREATE TABLE OverallData (OverallAvgIncome DECIMAL(10,2)); INSERT INTO OverallData (OverallAvgIncome) VALUES (52500.00); | What is the average income by occupation and gender, and how does it compare to the overall average income? | SELECT Occupation, Gender, AvgIncome, AvgIncome * 100.0 / (SELECT OverallAvgIncome FROM OverallData) AS Percentage FROM OccupationGenderData; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotels (id INT PRIMARY KEY, name VARCHAR(255), country VARCHAR(255)); CREATE TABLE sustainable_practices (id INT PRIMARY KEY, hotel_id INT, practice VARCHAR(255)); INSERT INTO hotels (id, name, country) VALUES (1, 'Eco-Friendly Hotel', 'Sweden'); INSERT INTO hotels (id, name, country) VALUES (2, 'Sustainable Resort', 'Costa Rica'); INSERT INTO sustainable_practices (id, hotel_id, practice) VALUES (1, 1, 'Recycling program'); INSERT INTO sustainable_practices (id, hotel_id, practice) VALUES (2, 2, 'Solar power'); | Create a new view that shows the hotels and their sustainable practices | CREATE VIEW hotel_sustainable_practices AS SELECT hotels.name, sustainable_practices.practice FROM hotels INNER JOIN sustainable_practices ON hotels.id = sustainable_practices.hotel_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE transactions (id INT, tx_hash VARCHAR(50), tx_type VARCHAR(10), block_height INT, tx_time TIMESTAMP); INSERT INTO transactions (id, tx_hash, tx_type, block_height, tx_time) VALUES (1, '0x123...', 'transfer', 1000000, '2021-01-01 00:00:00'), (2, '0x456...', 'deploy', 1000001, '2021-01-02 00:00:00'); | What is the latest transaction time in the 'transactions' table? | SELECT MAX(tx_time) FROM transactions; | gretelai_synthetic_text_to_sql |
CREATE TABLE garment (id INT PRIMARY KEY, garment_name VARCHAR(255), quantity INT, price DECIMAL(5,2)); INSERT INTO garment (id, garment_name, quantity, price) VALUES (1, 'Rayon', 100, 15.00), (2, 'Silk', 0, 0), (3, 'Cotton', 200, 20.00); | Update the price of 'Silk' garments to $25.00 in the garment table. | UPDATE garment SET price = 25.00 WHERE garment_name = 'Silk'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Workers (id INT, industry VARCHAR(20), employment_status VARCHAR(20)); INSERT INTO Workers (id, industry, employment_status) VALUES (1, 'Manufacturing', 'Part-time'), (2, 'Retail', 'Full-time'), (3, 'Manufacturing', 'Full-time'); | How many workers in the 'Retail' industry have a 'Full-time' status? | SELECT COUNT(*) FROM Workers WHERE industry = 'Retail' AND employment_status = 'Full-time'; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, country VARCHAR(255), created_at TIMESTAMP); | Show the number of new users who signed up from India in the past week and the number of new users who signed up from India in the past month. | SELECT COUNT(*) as last_week, (SELECT COUNT(*) FROM users WHERE country = 'India' AND created_at > NOW() - INTERVAL '1 month') as last_month FROM users WHERE country = 'India' AND created_at > NOW() - INTERVAL '1 week'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Songs (id INT, title VARCHAR(100), artist VARCHAR(100), streams INT); CREATE TABLE Artists (id INT, name VARCHAR(100), country VARCHAR(100)); | What is the maximum number of streams for a song by an artist from Canada? | SELECT MAX(s.streams) FROM Songs s JOIN Artists a ON s.artist = a.name WHERE a.country = 'Canada'; | gretelai_synthetic_text_to_sql |
CREATE TABLE players (id INT PRIMARY KEY, name VARCHAR(50), age INT, country VARCHAR(50)); | Insert a new player, 'Leila Zhang', aged 28 from China | INSERT INTO players (name, age, country) VALUES ('Leila Zhang', 28, 'China'); | gretelai_synthetic_text_to_sql |
CREATE TABLE digital_divide_asia (country VARCHAR(20), population INT, affected INT); INSERT INTO digital_divide_asia (country, population, affected) VALUES ('China', 1439323776, 197243372), ('India', 1380004385, 191680581), ('Indonesia', 273523615, 39032361); | What is the average number of people affected by the digital divide in Asia? | SELECT AVG(affected) FROM digital_divide_asia WHERE country = 'Asia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE mobile_data_usage (customer_id INT, data_usage FLOAT); INSERT INTO mobile_data_usage (customer_id, data_usage) VALUES (1, 3.0), (2, 4.5), (3, 1.9), (4, 3.1); | What is the total number of mobile customers in the telecom company's database who are using exactly 3GB of data per month? | SELECT COUNT(*) FROM mobile_data_usage WHERE data_usage = 3.0; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_name VARCHAR(50), vendor VARCHAR(50)); CREATE TABLE vulnerabilities (product_name VARCHAR(50), published DATE, cvss_score FLOAT); INSERT INTO products (product_name, vendor) VALUES ('Windows 10', 'Microsoft'), ('Office 365', 'Microsoft'), ('iPhone', 'Apple'), ('macOS', 'Apple'); INSERT INTO vulnerabilities (product_name, published, cvss_score) VALUES ('Windows 10', '2021-10-01', 7.5), ('Office 365', '2022-02-15', 6.2), ('iPhone', '2021-07-12', 8.1), ('macOS', '2022-03-20', 7.8); | Get the number of cybersecurity vulnerabilities for each product in the last year | SELECT products.product_name, COUNT(*) as vulnerability_count FROM products INNER JOIN vulnerabilities ON products.product_name = vulnerabilities.product_name WHERE vulnerabilities.published >= DATE(NOW()) - INTERVAL 1 YEAR GROUP BY products.product_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE therapy (therapy_id INT, patient_id INT, therapist_id INT, therapy_date DATE, city TEXT); INSERT INTO therapy (therapy_id, patient_id, therapist_id, therapy_date, city) VALUES (1, 1, 101, '2018-01-02', 'Paris'); | How many patients started therapy in Paris each quarter of 2021? | SELECT DATE_TRUNC('quarter', therapy_date) as quarter, COUNT(DISTINCT patient_id) as num_patients FROM therapy WHERE city = 'Paris' AND EXTRACT(YEAR FROM therapy_date) = 2021 GROUP BY quarter ORDER BY quarter; | 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 total number 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? | SELECT COUNT(DISTINCT s.user_id) as num_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 projects (project_id INT, project_name VARCHAR(50), budget DECIMAL(10, 2), area VARCHAR(50)); INSERT INTO projects (project_id, project_name, budget, area) VALUES (1, 'ProjectQ', 6000000.00, 'Urban'), (2, 'ProjectR', 12000000.00, 'Urban'), (3, 'ProjectS', 18000000.00, 'Urban'); | What is the average budget for public transportation projects in the "projects" table for projects with a budget between $5 million and $15 million? | SELECT AVG(budget) FROM projects WHERE budget BETWEEN 5000000.00 AND 15000000.00; | gretelai_synthetic_text_to_sql |
CREATE TABLE safety_protocols (id INT PRIMARY KEY, chemical_name VARCHAR(255), safety_protocol VARCHAR(255), date_implemented DATE); INSERT INTO safety_protocols (id, chemical_name, safety_protocol, date_implemented) VALUES (1, 'Ammonia', 'Always wear safety goggles when handling', '2022-01-01'); | Update the safety protocol for 'Ammonia' in the "safety_protocols" table | UPDATE safety_protocols SET safety_protocol = 'Always wear safety goggles and gloves when handling' WHERE chemical_name = 'Ammonia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ProductTransparency (product_id INT, recycled_materials BOOLEAN); INSERT INTO ProductTransparency (product_id, recycled_materials) VALUES (1, TRUE), (2, FALSE), (3, TRUE); CREATE TABLE Products (product_id INT, quantity INT); INSERT INTO Products (product_id, quantity) VALUES (1, 10), (2, 20), (3, 30); | Find the total quantity of products made from recycled materials. | SELECT SUM(quantity) FROM Products INNER JOIN ProductTransparency ON Products.product_id = ProductTransparency.product_id WHERE ProductTransparency.recycled_materials = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE genetics_research (id INT, project_name VARCHAR(50), lead_name VARCHAR(50), lead_email VARCHAR(50), location VARCHAR(50)); INSERT INTO genetics_research (id, project_name, lead_name, lead_email, location) VALUES (1, 'Genome Mapping', 'Jose Silva', 'jose.silva@email.com.br', 'Brazil'); INSERT INTO genetics_research (id, project_name, lead_name, lead_email, location) VALUES (2, 'Protein Sequencing', 'Ana Paula Santos', 'ana.paula.santos@email.com.br', 'Brazil'); | Who is the lead researcher for the genetic research project 'Genome Mapping' in Brazil? | SELECT lead_name FROM genetics_research WHERE project_name = 'Genome Mapping' AND location = 'Brazil'; | gretelai_synthetic_text_to_sql |
CREATE TABLE investment_products (id INT, name VARCHAR(50), asset_class VARCHAR(50)); INSERT INTO investment_products (id, name, asset_class) VALUES (1, 'Stock A', 'Equities'), (2, 'Bond B', 'Fixed Income'), (3, 'Mutual Fund C', 'Equities'), (4, 'ETF D', 'Commodities'); | List all the unique investment products and their associated asset classes. | SELECT DISTINCT name, asset_class FROM investment_products; | gretelai_synthetic_text_to_sql |
CREATE TABLE teacher_pd (teacher_id INT, course_name VARCHAR(50), location VARCHAR(20)); INSERT INTO teacher_pd (teacher_id, course_name, location) VALUES (101, 'Python for Educators', 'New York'), (102, 'Data Science for Teachers', 'Chicago'), (103, 'Open Pedagogy', 'New York'); | List the unique professional development courses attended by teachers in 'New York'? | SELECT DISTINCT course_name FROM teacher_pd WHERE location = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE solar_farms (id INT, state VARCHAR(20), capacity FLOAT); INSERT INTO solar_farms (id, state, capacity) VALUES (1, 'Arizona', 120.5), (2, 'Nevada', 150.2), (3, 'Arizona', 180.1), (4, 'Oregon', 200.5); | What is the total installed capacity of solar farms in 'Arizona'? | SELECT SUM(capacity) FROM solar_farms WHERE state = 'Arizona'; | gretelai_synthetic_text_to_sql |
CREATE TABLE GreenBuildings (id INT, name VARCHAR(100), location VARCHAR(100), energy_consumption FLOAT); | List the top 5 cities with the highest number of green buildings in the 'GreenBuildings' table. | SELECT location, COUNT(*) as building_count FROM GreenBuildings GROUP BY location ORDER BY building_count DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE deep_sea_trenches (trench_name TEXT, location TEXT, max_depth FLOAT); INSERT INTO deep_sea_trenches (trench_name, location, max_depth) VALUES ('Trench 1', 'Indian Ocean', 7600.0), ('Trench 2', 'Pacific Ocean', 8601.0), ('Trench 3', 'Indian Ocean', 8000.0); | List the names and maximum depths of all deep-sea trenches in the Indian ocean. | SELECT trench_name, max_depth FROM deep_sea_trenches WHERE location = 'Indian Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE city_environmental_budget (city VARCHAR(255), fiscal_year INT, budget DECIMAL(10,2)); INSERT INTO city_environmental_budget (city, fiscal_year, budget) VALUES ('New York', 2023, 12000000.00), ('Los Angeles', 2023, 10000000.00), ('Chicago', 2023, 15000000.00), ('Houston', 2023, 8000000.00), ('Miami', 2023, 9000000.00); | Identify the top 3 cities with the highest budget allocated for environmental services, for the fiscal year 2023, and their respective budgets. | SELECT city, budget FROM (SELECT city, budget, ROW_NUMBER() OVER (ORDER BY budget DESC) as rank FROM city_environmental_budget WHERE fiscal_year = 2023 AND service = 'Environmental') as ranked_cities WHERE rank <= 3 | gretelai_synthetic_text_to_sql |
CREATE TABLE labor_costs (project_id INT, labor_cost DECIMAL(10, 2)); | What was the total construction labor cost for a specific project with project_id = 123? | SELECT SUM(labor_cost) FROM labor_costs WHERE project_id = 123; | gretelai_synthetic_text_to_sql |
CREATE TABLE VESSEL_CARGO (ID INT, VESSEL_ID INT, CARGO_TYPE VARCHAR(50), WEIGHT INT); INSERT INTO VESSEL_CARGO VALUES (1, 1, 'Container', 2500); INSERT INTO VESSEL_CARGO VALUES (2, 1, 'Bulk', 50000); INSERT INTO VESSEL_CARGO VALUES (3, 2, 'Container', 3000); | Show the average cargo weight per vessel, ranked in descending order. | SELECT V.NAME, AVG(VC.WEIGHT) AS AVG_WEIGHT, ROW_NUMBER() OVER(ORDER BY AVG(VC.WEIGHT) DESC) AS RANK FROM VESSEL_CARGO VC JOIN VESSELS V ON VC.VESSEL_ID = V.ID GROUP BY V.ID, V.NAME | gretelai_synthetic_text_to_sql |
CREATE TABLE authors (author_id INT, name VARCHAR(255), nationality VARCHAR(100)); | Insert a new record in the 'authors' table | INSERT INTO authors (author_id, name, nationality) VALUES (1, 'Chimamanda Ngozi Adichie', 'Nigerian'); | gretelai_synthetic_text_to_sql |
CREATE TABLE covid_cases (county TEXT, population INT, cases INT); INSERT INTO covid_cases (county, population, cases) VALUES ('County A', 500000, 5000), ('County B', 750000, 8000), ('County C', 600000, 6500), ('County D', 450000, 4000); | What is the number of COVID-19 cases per 100,000 population for each county in the covid_cases table? | SELECT county, (cases * 100000) / population AS cases_per_100k FROM covid_cases; | gretelai_synthetic_text_to_sql |
CREATE TABLE volunteers (id INT, region VARCHAR(50), hours INT); INSERT INTO volunteers (id, region, hours) VALUES (1, 'Northeast', 500), (2, 'Southeast', 700), (3, 'Midwest', 600), (4, 'West', 800); | Which regions have the highest volunteer hours? | SELECT region, MAX(hours) as max_hours FROM volunteers GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE startups (id INT, name TEXT, location TEXT, founder_gender TEXT, funding_amount INT); INSERT INTO startups (id, name, location, founder_gender, funding_amount) VALUES (1, 'Startup A', 'USA', 'female', 3000000); INSERT INTO startups (id, name, location, founder_gender, funding_amount) VALUES (2, 'Startup B', 'Canada', 'non-binary', 5000000); INSERT INTO startups (id, name, location, founder_gender, funding_amount) VALUES (3, 'Startup C', 'USA', 'female', 4000000); | What is the average funding amount for startups founded by people from historically marginalized gender identities? | SELECT AVG(funding_amount) FROM startups WHERE founder_gender IN ('female', 'non-binary'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, Gender VARCHAR(20), Department VARCHAR(30), Salary INT); INSERT INTO Employees (EmployeeID, Gender, Department, Salary) VALUES (1, 'Non-binary', 'IT', 60000), (2, 'Transgender', 'HR', 65000), (3, 'Non-binary', 'Finance', 70000), (4, 'Transgender', 'Marketing', 62000); | What is the average salary of non-binary and transgender employees, partitioned by department? | SELECT Department, AVG(CASE WHEN Gender = 'Non-binary' THEN Salary ELSE NULL END) AS Avg_Nonbinary_Salary, AVG(CASE WHEN Gender = 'Transgender' THEN Salary ELSE NULL END) AS Avg_Transgender_Salary FROM Employees GROUP BY Department; | gretelai_synthetic_text_to_sql |
CREATE TABLE songs (song_id INT, genre VARCHAR(20), album VARCHAR(30), artist VARCHAR(30), length FLOAT, release_year INT); CREATE TABLE genres (genre VARCHAR(20)); INSERT INTO genres (genre) VALUES ('pop'), ('rock'), ('jazz'), ('hip-hop'); ALTER TABLE songs ADD CONSTRAINT fk_genre FOREIGN KEY (genre) REFERENCES genres(genre); | What is the average length of songs in the jazz genre released in the 2000s? | SELECT AVG(length) as avg_length FROM songs WHERE genre = (SELECT genre FROM genres WHERE genre = 'jazz') AND release_year BETWEEN 2000 AND 2009; | gretelai_synthetic_text_to_sql |
CREATE TABLE transactions (transaction_id INT, transaction_date DATE, transaction_category VARCHAR(255), transaction_value DECIMAL(10,2)); INSERT INTO transactions (transaction_id, transaction_date, transaction_category, transaction_value) VALUES (1, '2021-03-02', 'Food', 50.00), (2, '2021-03-05', 'Electronics', 300.00), (3, '2021-03-10', 'Clothing', 150.00); | What is the total transaction value for each hour of the day for the month of March 2021? | SELECT HOUR(transaction_date) as hour_of_day, SUM(transaction_value) as total_value FROM transactions WHERE transaction_date BETWEEN '2021-03-01' AND '2021-03-31' GROUP BY hour_of_day; | gretelai_synthetic_text_to_sql |
CREATE TABLE spacecraft (id INT, name VARCHAR(50), manufacturer VARCHAR(50), launch_year INT);INSERT INTO spacecraft (id, name, manufacturer, launch_year) VALUES (1, 'Dragon', 'SpaceX', 2010), (2, 'Falcon', 'SpaceX', 2006), (3, 'Crew', 'SpaceX', 2020); | Count the number of spacecraft manufactured by SpaceX before 2015 | SELECT COUNT(*) FROM spacecraft WHERE manufacturer = 'SpaceX' AND launch_year < 2015; | gretelai_synthetic_text_to_sql |
CREATE TABLE Road_Projects (project_id int, project_name varchar(255), location varchar(255), cost decimal(10,2)); | Find the top 3 most expensive road projects | SELECT project_id, project_name, location, cost FROM Road_Projects ORDER BY cost DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE news_articles (article_id INT, author_name VARCHAR(50), title VARCHAR(100), published_date DATE); | Find the number of articles published by each author in the 'news_articles' table | SELECT author_name, COUNT(article_id) as article_count FROM news_articles GROUP BY author_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_protected_areas (name VARCHAR(255), location VARCHAR(255), depth FLOAT); INSERT INTO marine_protected_areas (name, location, depth) VALUES ('MPA 1', 'Indian', 150.7); INSERT INTO marine_protected_areas (name, location, depth) VALUES ('MPA 2', 'Atlantic', 200.3); | What is the maximum depth of any marine protected area in the Indian region? | SELECT MAX(depth) FROM marine_protected_areas WHERE location = 'Indian'; | gretelai_synthetic_text_to_sql |
CREATE TABLE posts (id INT, content TEXT, likes INT, created_at TIMESTAMP, user_location VARCHAR(255)); CREATE VIEW user_country AS SELECT user_location, COUNT(DISTINCT id) AS num_users FROM users GROUP BY user_location; | List the top 3 countries with the most user engagement on posts related to "sports" in 2021. | SELECT user_country.user_location, SUM(posts.likes) AS total_likes FROM posts JOIN user_country ON posts.user_location = user_country.user_location WHERE posts.content LIKE '%sports%' AND YEAR(posts.created_at) = 2021 GROUP BY user_country.user_location ORDER BY total_likes DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE offenses (offender_id INT, offense_date DATE, crime VARCHAR(20)); INSERT INTO offenses (offender_id, offense_date, crime) VALUES (1, '2018-01-01', 'Murder'), (1, '2019-01-01', 'Robbery'), (2, '2017-01-01', 'Assault'); | What is the earliest offense date and corresponding crime type for each offender? | SELECT offender_id, MIN(offense_date) OVER (PARTITION BY offender_id) AS min_offense_date, FIRST_VALUE(crime) OVER (PARTITION BY offender_id ORDER BY offense_date) AS first_crime FROM offenses; | gretelai_synthetic_text_to_sql |
CREATE TABLE meetings (id INT, dept VARCHAR(255), meeting_date DATE); INSERT INTO meetings (id, dept, meeting_date) VALUES (1, 'Urban Development', '2022-03-01'), (2, 'Urban Development', '2022-05-15'), (3, 'Transportation', '2022-03-04'); | Report the number of public meetings in the 'Urban Development' department in the first half of 2022, grouped by the week they were held. | SELECT WEEKOFYEAR(meeting_date) AS week, COUNT(*) AS num_meetings FROM meetings WHERE dept = 'Urban Development' AND meeting_date BETWEEN '2022-01-01' AND '2022-06-30' GROUP BY week | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID int, DonorName varchar(50), Country varchar(50)); INSERT INTO Donors (DonorID, DonorName, Country) VALUES (1, 'John Doe', 'USA'), (2, 'Jane Smith', 'Canada'); CREATE TABLE Donations (DonationID int, DonorID int, DonationAmount decimal(10,2)); INSERT INTO Donations (DonationID, DonorID, DonationAmount) VALUES (1, 2, 100), (2, 2, 200), (3, 1, 50); | What is the average donation amount from donors in each country? | SELECT Country, AVG(DonationAmount) FROM Donations JOIN Donors ON Donations.DonorID = Donors.DonorID GROUP BY Country; | gretelai_synthetic_text_to_sql |
CREATE TABLE SmartContracts (ContractID INT, LastUpdate DATETIME); | Delete smart contracts from the 'SmartContracts' table that have not been updated in the past year from the current date. | DELETE FROM SmartContracts WHERE LastUpdate < DATEADD(year, -1, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE timber_production (production_id INT, year INT, volume FLOAT); | List all the timber_production data for a specific year, such as 2020? | SELECT * FROM timber_production WHERE year = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE DefenseProjects (ProjectID INT, Contractor VARCHAR(50), Region VARCHAR(50), StartDate DATE, EndDate DATE); INSERT INTO DefenseProjects (ProjectID, Contractor, Region, StartDate, EndDate) VALUES (1, 'Raytheon', 'Asia-Pacific', '2018-04-01', '2019-03-31'), (2, 'Boeing', 'Europe', '2019-01-01', '2020-12-31'), (3, 'Raytheon', 'Asia-Pacific', '2020-01-01', '2021-12-31'); | How many defense projects did Raytheon undertake in the Asia-Pacific region between 2018 and 2020? | SELECT COUNT(*) FROM DefenseProjects WHERE Contractor = 'Raytheon' AND Region = 'Asia-Pacific' AND StartDate <= '2020-12-31' AND EndDate >= '2018-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE vessel_performance (id INT, vessel_name VARCHAR(50), average_speed DECIMAL(5,2)); | Which vessels in the 'vessel_performance' table have an average speed below 10 knots? | SELECT vessel_name FROM vessel_performance WHERE average_speed < 10; | gretelai_synthetic_text_to_sql |
CREATE TABLE VR_Games (Game_ID INT, Release_Year INT, Game_Category VARCHAR(20)); INSERT INTO VR_Games (Game_ID, Release_Year, Game_Category) VALUES (1, 2022, 'VR'); | How many virtual reality (VR) games have been released in 2022 and 2023 from the 'VR_Games' table? | SELECT COUNT(*) FROM VR_Games WHERE Release_Year IN (2022, 2023) AND Game_Category = 'VR'; | gretelai_synthetic_text_to_sql |
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