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 Accommodations (ID INT PRIMARY KEY, Country VARCHAR(50), AccommodationType VARCHAR(50), Quantity INT); INSERT INTO Accommodations (ID, Country, AccommodationType, Quantity) VALUES (1, 'USA', 'Sign Language Interpretation', 300), (2, 'Canada', 'Wheelchair Ramp', 250), (3, 'Mexico', 'Assistive Listening Devices', 150), (4, 'Japan', 'Mobility Assistance', 200), (5, 'Germany', 'Sign Language Interpretation', 400), (6, 'Egypt', 'Wheelchair Ramp', 100); | What is the total number of accommodations provided, by accommodation type, for each country? | SELECT Country, AccommodationType, SUM(Quantity) as Total FROM Accommodations GROUP BY Country, AccommodationType; | gretelai_synthetic_text_to_sql |
CREATE TABLE department (name VARCHAR(255), id INT);CREATE TABLE professor (name VARCHAR(255), department_id INT, grant_amount DECIMAL(10,2), publication_year INT); | What is the minimum research grant amount awarded to a professor in the Chemistry department who has published at least one paper? | SELECT MIN(grant_amount) FROM professor WHERE department_id IN (SELECT id FROM department WHERE name = 'Chemistry') AND publication_year IS NOT NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE Suppliers (supplier_id INTEGER, supplier_name TEXT, safety_rating INTEGER); INSERT INTO Suppliers (supplier_id, supplier_name, safety_rating) VALUES (123, 'Acme Corp', 90), (234, 'Beta Inc', 85), (345, 'Gamma Ltd', 95), (456, 'Delta Co', 80), (567, 'Epsilon plc', 92); | What are the names and safety ratings for suppliers with a supplier ID between 300 and 500? | SELECT s.supplier_name, s.safety_rating FROM Suppliers s WHERE s.supplier_id BETWEEN 300 AND 500; | gretelai_synthetic_text_to_sql |
CREATE TABLE bus_trips (id INT, trip_date DATE, passengers INT); INSERT INTO bus_trips (id, trip_date, passengers) VALUES (1, '2022-01-01', 50), (2, '2022-01-01', 60), (3, '2022-02-01', 40); | What is the average number of passengers per bus trip, partitioned by month and ranked by the highest average? | SELECT AVG(passengers) OVER (PARTITION BY DATEPART(mm, trip_date) ORDER BY AVG(passengers) DESC) as avg_passengers, trip_date FROM bus_trips WHERE trip_date >= DATEADD(year, -1, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE defense_contracts (contract_id INT PRIMARY KEY, contracting_agency VARCHAR(255), contract_status VARCHAR(255), contract_amount DECIMAL(10,2)); | Update the 'contract_amount' field in the 'defense_contracts' table for records where 'contracting_agency' is 'Department of the Navy' and 'contract_status' is 'active' by setting the 'contract_amount' to 'contract_amount' + 0.10 * 'contract_amount' | UPDATE defense_contracts SET contract_amount = contract_amount + 0.10 * contract_amount WHERE contracting_agency = 'Department of the Navy' AND contract_status = 'active'; | gretelai_synthetic_text_to_sql |
CREATE TABLE GarmentInventory (garment_id INT, size INT, quantity INT); INSERT INTO GarmentInventory VALUES (1, 8, 200), (2, 10, 150), (3, 12, 300); | What is the total number of size 8 and size 10 garments in stock? | SELECT SUM(quantity) FROM GarmentInventory WHERE size IN (8, 10); | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (patient_id INT, patient_name TEXT, condition TEXT, therapist_id INT, treatment TEXT); INSERT INTO patients (patient_id, patient_name, condition, therapist_id, treatment) VALUES (1, 'James Johnson', 'PTSD', 1, 'Meditation'); INSERT INTO patients (patient_id, patient_name, condition, therapist_id, treatment) VALUES (2, 'Sophia Lee', 'PTSD', 1, 'Medication'); CREATE TABLE therapists (therapist_id INT, therapist_name TEXT, state TEXT); INSERT INTO therapists (therapist_id, therapist_name, state) VALUES (1, 'Dr. Maria Rodriguez', 'California'); | How many patients have been treated with meditation for PTSD in California? | SELECT COUNT(*) FROM patients JOIN therapists ON patients.therapist_id = therapists.therapist_id WHERE patients.condition = 'PTSD' AND patients.treatment = 'Meditation' AND therapists.state = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (species_id INT, species_name VARCHAR(255), conservation_status VARCHAR(50)); CREATE TABLE conservation_efforts (effort_id INT, species_id INT, ocean VARCHAR(50), effort_description VARCHAR(255)); INSERT INTO marine_species (species_id, species_name, conservation_status) VALUES (1, 'Mediterranean Monk Seal', 'Endangered'), (2, 'Basking Shark', 'Vulnerable'); INSERT INTO conservation_efforts (effort_id, species_id, ocean, effort_description) VALUES (1, 1, 'Mediterranean', 'Habitat Protection'), (2, 2, 'Atlantic', 'Research and Monitoring'); | What are the conservation efforts for endangered marine species in the Mediterranean Sea? | SELECT conservation_efforts.effort_description FROM marine_species INNER JOIN conservation_efforts ON marine_species.species_id = conservation_efforts.species_id WHERE marine_species.conservation_status = 'Endangered' AND conservation_efforts.ocean = 'Mediterranean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE sustainable_fabric (id INT PRIMARY KEY, fabric VARCHAR(25), country_of_origin VARCHAR(20)); INSERT INTO sustainable_fabric (id, fabric, country_of_origin) VALUES (1, 'Organic Cotton', 'India'), (2, 'Tencel', 'Austria'), (3, 'Hemp', 'China'), (4, 'Recycled Polyester', 'Japan'); | Insert data into sustainable_fabric | INSERT INTO sustainable_fabric (id, fabric, country_of_origin) VALUES (1, 'Organic Cotton', 'India'), (2, 'Tencel', 'Austria'), (3, 'Hemp', 'China'), (4, 'Recycled Polyester', 'Japan'); | gretelai_synthetic_text_to_sql |
CREATE TABLE vessels (id VARCHAR(20), name VARCHAR(20)); INSERT INTO vessels (id, name) VALUES ('VES011', 'VESSEL011'), ('VES012', 'VESSEL012'); CREATE TABLE fuel_consumption (vessel_id VARCHAR(20), consumption_rate DECIMAL(5,2)); INSERT INTO fuel_consumption (vessel_id, consumption_rate) VALUES ('VES011', 4.5), ('VES011', 4.6), ('VES011', 4.4), ('VES012', 4.7), ('VES012', 4.8), ('VES012', 4.9); | What is the maximum fuel consumption rate for VESSEL011? | SELECT MAX(consumption_rate) FROM fuel_consumption WHERE vessel_id = 'VES011'; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers(id INT, city VARCHAR(20), last_data_usage_date DATE, monthly_data_usage DECIMAL(5,2)); INSERT INTO subscribers(id, city, last_data_usage_date, monthly_data_usage) VALUES (1, 'New York', '2022-01-15', 3.5), (2, 'New York', '2022-02-10', 4.2), (3, 'Chicago', '2022-03-05', 0.0); | List all cities with mobile subscribers who have not used any data in the last month. | SELECT city FROM subscribers WHERE monthly_data_usage = 0 AND last_data_usage_date < DATE_SUB(CURDATE(), INTERVAL 1 MONTH) GROUP BY city; | gretelai_synthetic_text_to_sql |
CREATE TABLE recycling_rates (region VARCHAR(10), year INT, rate DECIMAL(3,2)); INSERT INTO recycling_rates (region, year, rate) VALUES ('North', 2018, 0.55), ('North', 2019, 0.58), ('North', 2020, 0.61), ('South', 2018, 0.60), ('South', 2019, 0.63), ('South', 2020, 0.66), ('East', 2018, 0.65), ('East', 2019, 0.68), ('East', 2020, 0.71), ('West', 2018, 0.70), ('West', 2019, 0.73), ('West', 2020, 0.76); | What is the recycling rate for the 'South' region in 2019? | SELECT rate FROM recycling_rates WHERE region = 'South' AND year = 2019; | gretelai_synthetic_text_to_sql |
CREATE TABLE PT_Usage (id INT, system_type VARCHAR(20), country VARCHAR(50), users INT, market_share FLOAT); INSERT INTO PT_Usage (id, system_type, country, users, market_share) VALUES (1, 'Tokyo Metro', 'Japan', 2500000, 0.35), (2, 'Osaka Municipal Subway', 'Japan', 900000, 0.12), (3, 'Nagoya Municipal Subway', 'Japan', 650000, 0.09); | What is the market share of public transportation systems in Japan? | SELECT AVG(market_share) as avg_market_share FROM PT_Usage WHERE country = 'Japan'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_protected_areas (area_id INT, name VARCHAR(50), depth FLOAT, ocean VARCHAR(10)); INSERT INTO marine_protected_areas (area_id, name, depth, ocean) VALUES (1, 'Great Barrier Reef', 34, 'Pacific'), (2, 'Galapagos Islands', 170, 'Pacific'), (3, 'Azores', 500, 'Atlantic'); | Delete the marine protected area with the minimum depth | DELETE FROM marine_protected_areas WHERE depth = (SELECT MIN(depth) FROM marine_protected_areas); | gretelai_synthetic_text_to_sql |
CREATE TABLE papers (paper_id INT, title VARCHAR(100), author_id INT, published_date DATE, category VARCHAR(50)); INSERT INTO papers (paper_id, title, author_id, published_date, category) VALUES (1, 'Fairness in AI', 1, '2021-06-01', 'Algorithmic Fairness'); INSERT INTO papers (paper_id, title, author_id, published_date, category) VALUES (2, 'AI Safety Challenges', 2, '2021-07-15', 'AI Safety'); INSERT INTO papers (paper_id, title, author_id, published_date, category) VALUES (3, 'Interpretable AI Models', 1, '2020-12-20', 'Explainable AI'); INSERT INTO papers (paper_id, title, author_id, published_date, category) VALUES (4, 'Neural Symbolic Machine Learning', 3, '2022-02-16', 'Creative AI Applications'); | Delete the papers related to 'Algorithmic Fairness' category. | DELETE FROM papers WHERE category = 'Algorithmic Fairness'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ai_papers (paper_id INT, title VARCHAR(100), publication_year INT, author_id INT, num_citations INT); | Identify the top 3 AI research papers in terms of citations, published in the last 2 years, along with their authors and the number of citations they have received. | SELECT title, author_id, num_citations FROM ai_papers WHERE publication_year >= YEAR(CURRENT_DATE) - 2 GROUP BY paper_id ORDER BY num_citations DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE sustainable_certifications (certification_id INT, destination TEXT, certification_type TEXT, certification_date DATE); INSERT INTO sustainable_certifications (certification_id, destination, certification_type, certification_date) VALUES (1, 'Bali', 'Green Globe', '2022-01-01'), (2, 'Paris', 'EarthCheck', '2022-02-01'), (3, 'Bali', 'Green Key', '2022-03-01'); | List all destinations with more than 1 sustainable certification, ordered by the number of certifications in descending order. | SELECT destination FROM sustainable_certifications GROUP BY destination HAVING COUNT(*) > 1 ORDER BY COUNT(*) DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, name TEXT, region TEXT, num_founders INT, funding FLOAT); INSERT INTO companies (id, name, region, num_founders, funding) VALUES (1, 'Startup A', 'west_coast', 2, 5000000), (2, 'Startup B', 'east_coast', 1, 3000000), (3, 'Startup C', 'west_coast', 3, 7000000), (4, 'Startup D', 'east_coast', 1, 8000000); | Calculate the total funding for startups that have more than one founder | SELECT SUM(funding) FROM companies WHERE num_founders > 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_consumption (city VARCHAR(50), consumption FLOAT, month INT, year INT); INSERT INTO water_consumption (city, consumption, month, year) VALUES ('New York', 120.2, 1, 2021), ('New York', 130.5, 2, 2021), ('New York', 100.8, 3, 2021); | Determine the month with the lowest water consumption for the city of New York. | SELECT month, MIN(consumption) FROM water_consumption WHERE city = 'New York' AND year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE restaurant_revenue (menu_category VARCHAR(50), transaction_date DATE, revenue NUMERIC(10,2)); INSERT INTO restaurant_revenue (menu_category, transaction_date, revenue) VALUES ('Appetizers', '2023-03-01', 1500.00), ('Entrees', '2023-03-03', 2500.00), ('Desserts', '2023-03-02', 1200.00); | Find the top 3 menu categories with the highest revenue in the last 7 days. | SELECT menu_category, SUM(revenue) AS total_revenue FROM restaurant_revenue WHERE transaction_date >= CURRENT_DATE - INTERVAL '7 days' GROUP BY menu_category ORDER BY total_revenue DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE readers (id INT, age INT, gender VARCHAR(10), country VARCHAR(50), news_preference VARCHAR(50)); INSERT INTO readers (id, age, gender, country, news_preference) VALUES (1, 30, 'Male', 'India', 'Technology'), (2, 40, 'Female', 'India', 'Technology'); | What is the average age of readers who prefer technology news in India, partitioned by gender? | SELECT AVG(age) avg_age, gender FROM readers WHERE country = 'India' AND news_preference = 'Technology' GROUP BY gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE social_media (user_id INT, post_id INT, post_date DATE); | Count the number of users who have made a post on January 1, 2022 in the 'social_media' table. | SELECT COUNT(*) FROM social_media WHERE post_date = '2022-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Clients (id INT, name VARCHAR(50), attorney_id INT, paid DECIMAL(5,2)); CREATE TABLE Bills (id INT, client_id INT, amount DECIMAL(5,2)); INSERT INTO Clients (id, name, attorney_id, paid) VALUES (1, 'Client1', 1, 600.00), (2, 'Client2', 1, NULL), (3, 'Client3', 2, 1000.00); INSERT INTO Bills (id, client_id, amount) VALUES (1, 1, 500.00), (2, 2, 700.00), (3, 3, 1200.00); | What are the names of clients who have not paid their bills? | SELECT Clients.name FROM Clients LEFT JOIN Bills ON Clients.id = Bills.client_id WHERE Clients.paid IS NULL OR Bills.amount - Clients.paid > 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE OceanFloorMapping (location TEXT, depth INTEGER, map_date DATE); INSERT INTO OceanFloorMapping (location, depth, map_date) VALUES ('Pacific Ocean', 6000, '2022-01-01'); | What is the maximum depth mapped in the Pacific Ocean? | SELECT OceanFloorMapping.location, MAX(depth) FROM OceanFloorMapping WHERE location = 'Pacific Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE market_access (strategy VARCHAR(255), success_rate FLOAT); INSERT INTO market_access (strategy, success_rate) VALUES ('Direct to consumer', 0.75), ('Physician recommendation', 0.85), ('Pharmacy sales', 0.65); | List the market access strategies and their respective success rates. | SELECT strategy, success_rate FROM market_access; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (id INT, cause VARCHAR(50), donation DECIMAL(10, 2), donation_date DATE); | What is the total donation amount for each cause in the first quarter of 2022? | SELECT cause, SUM(donation) FROM donations WHERE donation_date >= '2022-01-01' AND donation_date < '2022-04-01' GROUP BY cause; | gretelai_synthetic_text_to_sql |
CREATE TABLE billing (attorney_id INT, client_id INT, hours FLOAT, rate FLOAT); INSERT INTO billing (attorney_id, client_id, hours, rate) VALUES (1, 101, 10, 300), (2, 102, 8, 350), (3, 103, 12, 250); | List clients and their total billing hours in the 'billing' table? | SELECT client_id, SUM(hours) FROM billing GROUP BY client_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE employees (id INT, name VARCHAR(50), department VARCHAR(50), role VARCHAR(50)); INSERT INTO employees (id, name, department, role) VALUES (1, 'John Doe', 'hr', 'employee'), (2, 'Jane Smith', 'hr', 'manager'), (3, 'Bob Johnson', 'operations', 'employee'), (4, 'Alice', 'it', 'employee'); | Update the role of employee with id 3 to 'senior employee'. | UPDATE employees SET role = 'senior employee' WHERE id = 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Max_Altitude (rocket VARCHAR(50), altitude INT); INSERT INTO Max_Altitude (rocket, altitude) VALUES ('Falcon Heavy', 20000000), ('Falcon 9', 15000000); | What is the maximum altitude reached by SpaceX's Falcon Heavy rocket? | SELECT altitude FROM Max_Altitude WHERE rocket = 'Falcon Heavy'; | gretelai_synthetic_text_to_sql |
CREATE TABLE staff_categories (id INT, name VARCHAR(255)); CREATE TABLE staff (id INT, country_id INT, category_id INT, hired_date DATE); | What is the total number of disaster response and community development staff members in each country? | SELECT countries.name, COUNT(staff.id) FROM staff JOIN countries ON staff.country_id = countries.id WHERE staff.category_id IN (SELECT id FROM staff_categories WHERE name IN ('disaster response', 'community development')) GROUP BY staff.country_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE co_ownership (property_id INT, owner VARCHAR(255), percentage INT); INSERT INTO co_ownership (property_id, owner, percentage) VALUES (1, 'Alice', 50), (1, 'Bob', 50), (2, 'Carol', 75), (2, 'Dave', 25), (3, 'Eve', 60), (3, 'Frank', 40); | List the names and average co-owner percentages for all properties in the 'co_ownership' table where the co-owner percentage is greater than 50. | SELECT owner, AVG(percentage) FROM co_ownership WHERE percentage > 50 GROUP BY owner; | gretelai_synthetic_text_to_sql |
CREATE TABLE global_health (donor_id INTEGER, donation_amount INTEGER, organization_name TEXT); INSERT INTO global_health (donor_id, donation_amount, organization_name) VALUES (1, 5000, 'Malaria Consortium'), (2, 4000, 'Schistosomiasis Control Initiative'); | Which organizations have received donations in the 'global_health' sector? | SELECT DISTINCT organization_name FROM global_health WHERE organization_name LIKE '%global_health%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE heritage_sites (id INT, country VARCHAR(50), name VARCHAR(100), visitor_count INT); INSERT INTO heritage_sites (id, country, name, visitor_count) VALUES (1, 'Japan', 'Site A', 2000), (2, 'Japan', 'Site B', 3000), (3, 'Italy', 'Site C', 4000); | How many heritage sites are there in Japan and their average visitor count? | SELECT country, AVG(visitor_count) FROM heritage_sites WHERE country = 'Japan' GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE artifact_chichen_itza (artifact_id INTEGER, artifact_name TEXT, analysis_status TEXT); INSERT INTO artifact_chichen_itza (artifact_id, artifact_name, analysis_status) VALUES (1, 'Temple of Kukulcan', 'Analyzed'), (2, 'Great Ball Court', 'Not Analyzed'), (3, 'Platform of Venus', 'Analyzed'), (4, 'Observatory', 'Analyzed'), (5, 'Red House', 'Analyzed'), (6, 'Skull Platform', 'Not Analyzed'); | list all artifacts from site 'Chichen Itza' with their analysis status | SELECT * FROM artifact_chichen_itza WHERE artifact_name = 'Chichen Itza'; | gretelai_synthetic_text_to_sql |
CREATE TABLE orders (id INT, product_id INT, quantity INT, price DECIMAL(5,2)); CREATE TABLE products (id INT, name VARCHAR(50), natural BOOLEAN); | Calculate the total revenue from natural hair care products | SELECT SUM(orders.quantity * products.price) FROM orders JOIN products ON orders.product_id = products.id WHERE products.natural = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE Manufacturers (name VARCHAR(50), satellites INT); INSERT INTO Manufacturers (name, satellites) VALUES ('SpaceX', 200), ('Boeing', 100), ('Lockheed Martin', 75); | What is the total number of satellites deployed by each manufacturer? | SELECT name, SUM(satellites) FROM Manufacturers GROUP BY name; | gretelai_synthetic_text_to_sql |
CREATE TABLE policy_events (event_id INT, event_date DATE, event_topic VARCHAR(255)); | How many policy advocacy events were held in the last 12 months for mental health? | SELECT COUNT(*) FROM policy_events WHERE event_topic = 'Mental Health' AND event_date >= DATEADD(month, -12, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE Events (event_id INT, event_name VARCHAR(255), team VARCHAR(255), quarter VARCHAR(255), price DECIMAL(5,2)); INSERT INTO Events VALUES (1, 'Tournament 1', 'E-Sports', 'Q1', 25.00), (2, 'Tournament 2', 'E-Sports', 'Q1', 30.00); | What is the average ticket price for 'E-Sports' events in 'Q1'? | SELECT AVG(price) FROM Events WHERE team = 'E-Sports' AND quarter = 'Q1'; | gretelai_synthetic_text_to_sql |
CREATE TABLE regions (id INT, name VARCHAR(50)); INSERT INTO regions (id, name) VALUES (1, 'RegionA'), (2, 'RegionB'), (3, 'RegionC'), (4, 'RegionD'); CREATE TABLE budget (id INT, region_id INT, department VARCHAR(50), amount INT); INSERT INTO budget (id, region_id, department, amount) VALUES (1, 1, 'Education', 500000), (2, 1, 'Health', 700000), (3, 2, 'Education', 300000), (4, 2, 'Health', 600000), (5, 3, 'Transportation', 900000), (6, 4, 'Transportation', 1200000); | What is the total budget allocated for transportation in 'RegionD'? | SELECT SUM(amount) FROM budget WHERE department = 'Transportation' AND region_id IN (SELECT id FROM regions WHERE name = 'RegionD'); | gretelai_synthetic_text_to_sql |
CREATE TABLE comm_history (id INT, ip_address VARCHAR(255), domain VARCHAR(255), communication_date DATE); INSERT INTO comm_history (id, ip_address, domain, communication_date) VALUES (1, '192.168.1.1', 'example.com', '2021-01-01'), (2, '192.168.1.2', 'example.com', '2021-01-01'), (3, '192.168.1.1', 'example.com', '2021-01-02'), (4, '192.168.1.3', 'example.com', '2021-01-02'); | How many unique IP addresses communicated with a specific domain in the last month? | SELECT COUNT(DISTINCT ip_address) as unique_ips FROM comm_history WHERE domain = 'example.com' AND communication_date >= DATEADD(day, -30, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE ethical_manufacturing (id INT AUTO_INCREMENT, company_name VARCHAR(50), location VARCHAR(50), ethical_certification VARCHAR(50), PRIMARY KEY(id)); | Show all records from the 'ethical_manufacturing' table | SELECT * FROM ethical_manufacturing; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers (user_id INT, service VARCHAR(50), subscription_date DATE); INSERT INTO subscribers (user_id, service, subscription_date) VALUES (1, 'Netflix', '2022-03-23'), (2, 'Disney+', '2022-03-18'); | Determine the number of users who started using a streaming service in the last month, by service. | SELECT service, COUNT(*) as new_subscribers FROM subscribers WHERE subscription_date >= DATEADD(month, -1, GETDATE()) GROUP BY service; | gretelai_synthetic_text_to_sql |
CREATE TABLE digital_assets (id INT, name VARCHAR(255), company VARCHAR(255), launch_date DATE, country VARCHAR(255)); INSERT INTO digital_assets (id, name, company, launch_date, country) VALUES (1, 'Asset 1', 'Company A', '2021-01-01', 'USA'), (2, 'Asset 2', 'Company B', '2021-02-15', 'Canada'); | What is the total number of digital assets launched by companies based in the United States and Canada? | SELECT COUNT(*) FROM digital_assets WHERE country IN ('USA', 'Canada'); | gretelai_synthetic_text_to_sql |
CREATE TABLE wells (well_id VARCHAR(10), well_location VARCHAR(20)); INSERT INTO wells (well_id, well_location) VALUES ('B02', 'Alaska'); CREATE TABLE production (well_id VARCHAR(10), production_count INT); INSERT INTO production (well_id, production_count) VALUES ('B02', 5000); | Update the production count for well 'B02' in 'Alaska' to 6500. | UPDATE production SET production_count = 6500 WHERE well_id = 'B02'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Incidents (facility VARCHAR(20), year INT, incidents INT); INSERT INTO Incidents (facility, year, incidents) VALUES ('Northern', 2021, 4), ('Northern', 2022, 2); | How many safety incidents were reported at the facility located in the Northern region in 2021? | SELECT incidents FROM Incidents WHERE facility = 'Northern' AND year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE vendors (id INT, name VARCHAR(50), country VARCHAR(50)); CREATE TABLE vendor_shipments (id INT, vendor_id INT, store_id INT, shipment_date DATE, quantity INT); CREATE TABLE stores (id INT, name VARCHAR(50), city VARCHAR(50), region VARCHAR(50)); | List all the vendors that have supplied products to a particular store in the last six months, along with the quantities of products supplied. | SELECT vendors.name, vendor_shipments.product_id, vendor_shipments.quantity FROM vendors JOIN vendor_shipments ON vendors.id = vendor_shipments.vendor_id JOIN stores ON vendor_shipments.store_id = stores.id WHERE stores.name = 'Specific Store Name' AND vendor_shipments.shipment_date >= DATE(NOW()) - INTERVAL 6 MONTH; | gretelai_synthetic_text_to_sql |
CREATE TABLE policyholders (id INT, name VARCHAR(255), state VARCHAR(255), policy_type VARCHAR(255), premium FLOAT); INSERT INTO policyholders (id, name, state, policy_type, premium) VALUES (1, 'John Doe', 'New York', 'Auto', 1200), (2, 'Jane Smith', 'California', 'Home', 2000), (3, 'Bob Johnson', 'California', 'Auto', 1500), (4, 'Alice Williams', 'California', 'Auto', 1800), (5, 'Charlie Brown', 'Texas', 'Home', 2500), (6, 'Lucy Van Pelt', 'Texas', 'Auto', 1000); | What is the number of policies issued for each policy type? | SELECT policy_type, COUNT(*) FROM policyholders GROUP BY policy_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE businesses (id INT, sector VARCHAR(255), employee_count INT); INSERT INTO businesses (id, sector, employee_count) VALUES (1, 'technology', 150), (2, 'finance', 50), (3, 'retail', 200); CREATE TABLE ad_spend (business_id INT, amount DECIMAL(10,2)); INSERT INTO ad_spend (business_id, amount) VALUES (1, 5000.00), (1, 6000.00), (2, 3000.00), (3, 4000.00); | What is the average ad spend for businesses in the technology sector with more than 100 employees? | SELECT AVG(amount) FROM ad_spend INNER JOIN businesses ON ad_spend.business_id = businesses.id WHERE businesses.sector = 'technology' AND businesses.employee_count > 100; | gretelai_synthetic_text_to_sql |
CREATE TABLE PatientConditions (PatientID INT, Age INT, Condition VARCHAR(50)); | What is the most common mental health condition among patients aged 18-24? | SELECT Condition, COUNT(*) FROM PatientConditions WHERE Age BETWEEN 18 AND 24 GROUP BY Condition ORDER BY COUNT(*) DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE Cities (City VARCHAR(255), WaitingTime INT); INSERT INTO Cities (City, WaitingTime) VALUES ('Calgary', 10), ('Vancouver', 15), ('Toronto', 20), ('Montreal', 25); | What is the average waiting time for public transportation in each city, ordered by the average waiting time in ascending order? | SELECT City, AVG(WaitingTime) AS AvgWaitingTime FROM Cities GROUP BY City ORDER BY AvgWaitingTime ASC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Artworks (artwork_id INT, movement VARCHAR(255), sale_year INT, revenue DECIMAL(10, 2)); | What was the total revenue for all artworks sold by the 'Impressionist' movement in the year 2010? | SELECT SUM(revenue) FROM Artworks WHERE movement = 'Impressionist' AND sale_year = 2010; | gretelai_synthetic_text_to_sql |
CREATE TABLE shelters (shelter_id INT, shelter_name VARCHAR(255), location VARCHAR(255), sector VARCHAR(255)); INSERT INTO shelters (shelter_id, shelter_name, location, sector) VALUES (1, 'Shelter A', 'City A', 'Education'); | What is the total number of shelters in 'disaster_response' schema and their types? | SELECT SUM(shelter_id) as total_shelters, sector FROM shelters GROUP BY sector; | gretelai_synthetic_text_to_sql |
CREATE TABLE CityGreenBuildings (city TEXT, building_count INT); INSERT INTO CityGreenBuildings (city, building_count) VALUES ('CityA', 200), ('CityB', 300), ('CityC', 400); | What is the total number of green buildings in the 'GreenBuildings' table for each city? | SELECT city, SUM(building_count) FROM CityGreenBuildings GROUP BY city; | gretelai_synthetic_text_to_sql |
CREATE TABLE safety_protocols (id INT, implemented_date DATE); INSERT INTO safety_protocols (id, implemented_date) VALUES (1, '2021-10-01'), (2, '2021-12-15'), (3, '2021-09-30'); | Which safety protocols were implemented in the last quarter of 2021? | SELECT * FROM safety_protocols WHERE implemented_date >= '2021-10-01' AND implemented_date < '2022-01-01' | gretelai_synthetic_text_to_sql |
CREATE TABLE Artists (ArtistID INT, ArtistName VARCHAR(100), Nationality VARCHAR(50)); INSERT INTO Artists (ArtistID, ArtistName, Nationality) VALUES (1, 'Pablo Picasso', 'Spanish'); INSERT INTO Artists (ArtistID, ArtistName, Nationality) VALUES (2, 'Georges Braque', 'French'); INSERT INTO Artists (ArtistID, ArtistName, Nationality) VALUES (3, 'Vincent Van Gogh', 'Dutch'); CREATE TABLE ArtWorks (ArtworkID INT, Title VARCHAR(100), YearCreated INT, Category VARCHAR(50), ArtistID INT); INSERT INTO ArtWorks (ArtworkID, Title, YearCreated, Category, ArtistID) VALUES (1, 'Guernica', 1937, 'Modern Art', 1); INSERT INTO ArtWorks (ArtworkID, Title, YearCreated, Category, ArtistID) VALUES (2, 'Woman with a Guitar', 1913, 'Cubism', 2); INSERT INTO ArtWorks (ArtworkID, Title, YearCreated, Category, ArtistID) VALUES (3, 'Starry Night', 1889, 'Post-Impressionism', 3); | Who are the painters that created works in the Cubism style? | SELECT A.ArtistName FROM Artists A JOIN ArtWorks AW ON A.ArtistID = AW.ArtistID WHERE AW.Category = 'Cubism'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (DonationID INT, DonorID INT, DonationAmount DECIMAL(10,2), DonationDate DATE); | What is the average donation amount per day? | SELECT AVG(D.DonationAmount) FROM Donations D; | gretelai_synthetic_text_to_sql |
CREATE TABLE disability_types (disability_id INT, disability_type VARCHAR(50), state VARCHAR(50), frequency INT); INSERT INTO disability_types (disability_id, disability_type, state, frequency) VALUES (1, 'Mobility', 'Texas', 3000), (2, 'Vision', 'Texas', 2000), (3, 'Hearing', 'Texas', 1500); | What is the third most common disability type in 'Texas'? | SELECT disability_type FROM (SELECT disability_type, ROW_NUMBER() OVER (PARTITION BY state ORDER BY frequency DESC) as rn FROM disability_types WHERE state = 'Texas') t WHERE rn = 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE vessels (id VARCHAR(20), name VARCHAR(20)); INSERT INTO vessels (id, name) VALUES ('VES001', 'VESSEL001'), ('VES003', 'VESSEL003'); CREATE TABLE safety_incidents (id INT, vessel_id VARCHAR(20), incident_type VARCHAR(50)); INSERT INTO safety_incidents (id, vessel_id, incident_type) VALUES (1, 'VES001', 'Collision'), (2, 'VES003', 'Fire'), (3, 'VES003', 'Grounding'); | List safety incidents for VESSEL003 | SELECT incident_type FROM safety_incidents WHERE vessel_id = 'VES003'; | gretelai_synthetic_text_to_sql |
CREATE TABLE deep_sea_expeditions (expedition_id INT, organization VARCHAR(255), year INT); INSERT INTO deep_sea_expeditions (expedition_id, organization, year) VALUES (1, 'NOAA', 2018), (2, 'WHOI', 2019), (3, 'NASA', 2020), (4, 'NOAA', 2021), (5, 'WHOI', 2021); | What is the number of deep-sea expeditions conducted by each organization in the last 5 years, grouped by the year the expedition was conducted? | SELECT year, organization, COUNT(*) as expeditions_in_last_5_years FROM deep_sea_expeditions WHERE year >= 2017 GROUP BY year, organization; | gretelai_synthetic_text_to_sql |
CREATE TABLE teacher_pd (teacher_id INT, department VARCHAR(10), budget DECIMAL(5,2), gender VARCHAR(10)); INSERT INTO teacher_pd (teacher_id, department, budget, gender) VALUES (1, 'Math', 500.00, 'Female'), (1, 'English', 600.00, 'Female'), (2, 'Math', 550.00, 'Male'), (2, 'English', 650.00, 'Male'), (3, 'Math', 450.00, 'Non-binary'), (3, 'English', 550.00, 'Non-binary'); | What is the average professional development budget per teacher for each gender? | SELECT gender, AVG(budget) as avg_budget FROM teacher_pd GROUP BY gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE movies_revenue (movie_id INT, title VARCHAR(255), release_year INT, revenue INT); INSERT INTO movies_revenue (movie_id, title, release_year, revenue) VALUES (1, 'Inception', 2010, 825), (2, 'Avatar', 2009, 2788), (3, 'Parasite', 2019, 258), (4, 'The Lion King', 2019, 1657), (5, 'Mulan', 2020, 60), (6, 'Wonder Woman 1984', 2020, 169); | What is the total revenue of movies released in 2020? | SELECT SUM(revenue) as total_revenue FROM movies_revenue WHERE release_year = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE garments (id INT, name VARCHAR(100), price DECIMAL(5,2), category VARCHAR(50)); | Insert a new garment into the garments table with the following details: ID 5, name 'Cotton Shirt', price 20.50, category 'Tops' | INSERT INTO garments (id, name, price, category) VALUES (5, 'Cotton Shirt', 20.50, 'Tops'); | gretelai_synthetic_text_to_sql |
CREATE TABLE suppliers (id INT, name VARCHAR(255), location VARCHAR(255), sustainable_practices BOOLEAN); CREATE TABLE garments (id INT, name VARCHAR(255), category VARCHAR(255), price DECIMAL(5,2), quantity INT, supplier_id INT); CREATE TABLE manufacturing_costs (id INT, garment_id INT, labor_cost DECIMAL(5,2), material_cost DECIMAL(5,2), manufacturing_time INT); INSERT INTO suppliers (id, name, location, sustainable_practices) VALUES (4, 'Supplier D', 'Africa', true); INSERT INTO garments (id, name, category, price, quantity, supplier_id) VALUES (4, 'Garment W', 'Accessories', 15.99, 35, 4); INSERT INTO manufacturing_costs (id, garment_id, labor_cost, material_cost, manufacturing_time) VALUES (4, 4, 12.50, 11.25, 30); | What is the average labor cost for manufacturing in Africa? | SELECT AVG(manufacturing_costs.labor_cost) FROM manufacturing_costs JOIN suppliers ON manufacturing_costs.supplier_id = suppliers.id WHERE suppliers.location = 'Africa'; | gretelai_synthetic_text_to_sql |
CREATE TABLE threat_intel (report_id INT, report_date DATE, region TEXT); INSERT INTO threat_intel (report_id, report_date, region) VALUES (1, '2020-01-01', 'Asia-Pacific'), (2, '2020-02-15', 'Europe'); | How many threat intelligence reports were generated for the Asia-Pacific region in 2020? | SELECT COUNT(*) FROM threat_intel WHERE region = 'Asia-Pacific' AND report_date >= '2020-01-01' AND report_date < '2021-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_protected_areas (area_name VARCHAR(255), ocean VARCHAR(255)); CREATE TABLE oceans (ocean_name VARCHAR(255), ocean_id INTEGER); | What is the total number of marine protected areas in the Pacific Ocean? | SELECT COUNT(area_name) FROM marine_protected_areas WHERE ocean = 'Pacific Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE budget (state VARCHAR(20), service VARCHAR(20), amount INT); INSERT INTO budget (state, service, amount) VALUES ('Florida', 'Education', 40000), ('Florida', 'Healthcare', 60000), ('Florida', 'Transportation', 30000); | What is the total budget allocated for all services in 'Florida'? | SELECT SUM(amount) FROM budget WHERE state = 'Florida'; | gretelai_synthetic_text_to_sql |
CREATE TABLE train_routes (id INT, route_name VARCHAR(255), fare DECIMAL(5, 2)); INSERT INTO train_routes (id, route_name, fare) VALUES (1, 'Route A', 2.75), (2, 'Route B', 3.50), (3, 'Route C', 2.25); | Identify train routes in the NYC subway system with fares higher than Route A but lower than Route C. | SELECT route_name, fare FROM train_routes WHERE fare > 2.75 AND fare < 2.25; | gretelai_synthetic_text_to_sql |
CREATE TABLE sales (garment VARCHAR(50), category VARCHAR(50), sale_date DATE); INSERT INTO sales (garment, category, sale_date) VALUES ('Shirt', 'Tops', '2021-01-05'), ('Pants', 'Bottoms', '2021-01-05'), ('Dress', 'Tops', '2021-01-10'), ('Shirt', 'Tops', '2022-01-05'), ('Pants', 'Bottoms', '2022-01-05'), ('Dress', 'Tops', '2022-01-10'); | Find the first and last sale dates for each garment, partitioned by category and ordered by date. | SELECT garment, category, MIN(sale_date) OVER (PARTITION BY garment) as first_sale_date, MAX(sale_date) OVER (PARTITION BY garment) as last_sale_date FROM sales; | gretelai_synthetic_text_to_sql |
CREATE TABLE montreal.metro_fares (id INT, trip_type VARCHAR, fare DECIMAL); INSERT INTO montreal.metro_fares (id, trip_type, fare) VALUES (1, 'single', 3.5), (2, 'round', 6.5), (3, 'weekly', 25); | What is the maximum fare for a single trip on the 'montreal' schema's metro system? | SELECT MAX(fare) FROM montreal.metro_fares WHERE trip_type = 'single'; | gretelai_synthetic_text_to_sql |
CREATE TABLE charging_stations (id INT, station_name VARCHAR(255), station_type VARCHAR(255), location VARCHAR(255)); | Update 'vehicle_type' to 'EV' for records in the 'charging_stations' table where 'station_type' is 'fast_charger' | UPDATE charging_stations SET vehicle_type = 'EV' WHERE station_type = 'fast_charger'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Species (id INT PRIMARY KEY, species_name VARCHAR(50), population INT, region VARCHAR(50)); INSERT INTO Species (id, species_name, population, region) VALUES (1, 'Polar Bear', 25000, 'Arctic'), (2, 'Beluga Whale', 15000, 'Arctic'); | What is the population of the Beluga Whale in the Arctic? | SELECT species_name, population FROM Species WHERE species_name = 'Beluga Whale' AND region = 'Arctic'; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, name VARCHAR(50), location VARCHAR(50), join_date DATE); CREATE TABLE posts (id INT, user_id INT, post_date DATE); INSERT INTO users (id, name, location, join_date) VALUES (1, 'Alice', 'Canada', '2021-01-01'); INSERT INTO users (id, name, location, join_date) VALUES (2, 'Bob', 'USA', '2020-01-01'); INSERT INTO posts (id, user_id, post_date) VALUES (1, 1, '2021-01-01'); INSERT INTO posts (id, user_id, post_date) VALUES (2, 1, '2021-01-02'); INSERT INTO posts (id, user_id, post_date) VALUES (3, 2, '2021-01-03'); | How many users are there in each country, and what is the total number of posts for users in each country who joined in 2021? | SELECT u.location, COUNT(DISTINCT u.id) as user_count, COUNT(p.id) as post_count FROM users u JOIN posts p ON u.id = p.user_id WHERE u.join_date >= '2021-01-01' GROUP BY u.location; | gretelai_synthetic_text_to_sql |
CREATE TABLE company (id INT, name TEXT, founder_race TEXT, funding_amount INT); INSERT INTO company (id, name, founder_race, funding_amount) VALUES (1, 'Kappa Inc', 'Latinx', 1500000); INSERT INTO company (id, name, founder_race, funding_amount) VALUES (2, 'Lambda Corp', 'Asian', 2000000); INSERT INTO company (id, name, founder_race, funding_amount) VALUES (3, 'Mu Inc', 'Latinx', 1200000); INSERT INTO company (id, name, founder_race, funding_amount) VALUES (4, 'Nu Corp', 'Caucasian', 2500000); | What is the maximum funding amount received by companies founded by Latinx entrepreneurs? | SELECT MAX(funding_amount) FROM company WHERE founder_race = 'Latinx'; | gretelai_synthetic_text_to_sql |
CREATE TABLE product_vulnerabilities (product_id INT, vulnerability_id INT, risk_score INT, detection_date DATE); INSERT INTO product_vulnerabilities (product_id, vulnerability_id, risk_score, detection_date) VALUES (1, 1001, 7, '2022-01-05'); INSERT INTO product_vulnerabilities (product_id, vulnerability_id, risk_score, detection_date) VALUES (1, 1002, 5, '2022-01-10'); INSERT INTO product_vulnerabilities (product_id, vulnerability_id, risk_score, detection_date) VALUES (2, 1003, 8, '2022-01-15'); | What is the average risk score of vulnerabilities for each product in the last month? | SELECT product_id, AVG(risk_score) as avg_risk_score FROM product_vulnerabilities WHERE detection_date >= DATEADD(month, -1, CURRENT_DATE) GROUP BY product_id ORDER BY avg_risk_score DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE MentalHealthParity (id INT, patientID INT, condition VARCHAR(50), treatment VARCHAR(50), cost DECIMAL(5,2)); INSERT INTO MentalHealthParity (id, patientID, condition, treatment, cost) VALUES (1, 1001, 'Anxiety', 'Counseling', 80.00), (2, 1002, 'Depression', 'Medication', 100.00); | What is the total cost of mental health treatments for patients with depression? | SELECT patientID, SUM(cost) as 'TotalCost' FROM MentalHealthParity WHERE condition = 'Depression'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Bridges (id INT, name TEXT, state TEXT, constructionDate DATE); | How many bridges were built in the last 5 years in the state of California? | SELECT COUNT(*) FROM Bridges WHERE state = 'California' AND constructionDate >= DATE_SUB(CURRENT_DATE, INTERVAL 5 YEAR); | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, name TEXT, age INT, condition TEXT, state TEXT); INSERT INTO patients (id, name, age, condition, state) VALUES (1, 'John Doe', 35, 'Depression', 'NY'), (2, 'Jane Smith', 40, 'Anxiety', 'NY'); | What is the most common mental health condition among patients from New York? | SELECT condition, COUNT(*) AS count FROM patients WHERE state = 'NY' GROUP BY condition ORDER BY count DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE quality_control (id INT, test_type VARCHAR(255), test_result VARCHAR(255), defect_count INT, shift VARCHAR(255)); | Insert a new record into the 'quality_control' table with id 201, 'test_type' 'Visual Inspection', 'test_result' 'Passed', 'defect_count' 0, and 'shift' 'Morning' | INSERT INTO quality_control (id, test_type, test_result, defect_count, shift) VALUES (201, 'Visual Inspection', 'Passed', 0, 'Morning'); | gretelai_synthetic_text_to_sql |
CREATE TABLE athletes (id INT, name VARCHAR(100), position VARCHAR(50), age INT, world_cup_2018 BOOLEAN); | What is the average age of athletes who played in the FIFA World Cup 2018, grouped by their position? | SELECT position, AVG(age) as avg_age FROM athletes WHERE world_cup_2018 = true GROUP BY position; | gretelai_synthetic_text_to_sql |
CREATE TABLE dishes (dish_id INT, name VARCHAR(255), calories INT, cuisine_type VARCHAR(255)); INSERT INTO dishes (dish_id, name, calories, cuisine_type) VALUES (1, 'Pizza', 300, 'Italian'), (2, 'Pasta', 400, 'Italian'), (3, 'Salad', 200, 'Salad'), (4, 'Burger', 500, 'American'), (5, 'Sushi', 250, 'Japanese'), (6, 'Curry', 350, 'Indian'); | Find the bottom 2 cuisine types with the lowest average calories per dish, excluding the 'Salad' type. | SELECT cuisine_type, AVG(calories) AS avg_calories FROM dishes WHERE cuisine_type != 'Salad' GROUP BY cuisine_type ORDER BY avg_calories LIMIT 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE socially_responsible_loans (id INT, value DECIMAL(10, 2), date DATE); INSERT INTO socially_responsible_loans (id, value, date) VALUES (1, 5000, '2022-04-01'); INSERT INTO socially_responsible_loans (id, value, date) VALUES (2, 7000, '2022-04-15'); | What is the average transaction value for socially responsible loans in Q2 2022? | SELECT AVG(value) FROM socially_responsible_loans WHERE date BETWEEN '2022-04-01' AND '2022-06-30'; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, segment VARCHAR(20), price DECIMAL(5,2)); INSERT INTO products (product_id, segment, price) VALUES (1, 'Natural', 15.99), (2, 'Organic', 20.99), (3, 'Natural', 12.49); | What is the most expensive product in the Organic segment? | SELECT segment, MAX(price) FROM products WHERE segment = 'Organic' GROUP BY segment; | gretelai_synthetic_text_to_sql |
CREATE TABLE BusStations (id INT, borough VARCHAR(255), station_name VARCHAR(255)); CREATE TABLE TrainStations (id INT, district VARCHAR(255), station_name VARCHAR(255)); | Show the number of bus and train stations in each borough or district. | SELECT 'Bus' as transportation, borough, COUNT(*) as station_count FROM BusStations GROUP BY borough UNION ALL SELECT 'Train', district, COUNT(*) FROM TrainStations GROUP BY district; | gretelai_synthetic_text_to_sql |
CREATE TABLE WasteData (WasteID INT, Material VARCHAR(255), Quantity DECIMAL(10,2), GenerationDate DATE); INSERT INTO WasteData (WasteID, Material, Quantity, GenerationDate) VALUES (1, 'Plastic', 1200, '2021-01-01'), (2, 'Glass', 3000, '2021-01-03'), (3, 'Paper', 4500, '2021-01-05'); | What is the total waste generation in gram for each material type in the first quarter of 2021, grouped by material type, and only showing those with a total generation greater than 5000 grams? | SELECT Material, SUM(Quantity) AS TotalWaste FROM WasteData WHERE GenerationDate BETWEEN '2021-01-01' AND '2021-03-31' GROUP BY Material HAVING SUM(Quantity) > 5000; | gretelai_synthetic_text_to_sql |
CREATE TABLE Company (id INT, name VARCHAR(50), industry VARCHAR(50), founding_year INT); INSERT INTO Company (id, name, industry, founding_year) VALUES (1, 'Acme Inc', 'Tech', 2010); INSERT INTO Company (id, name, industry, founding_year) VALUES (2, 'Bravo Corp', 'Finance', 2005); CREATE TABLE Diversity (id INT, company_id INT, gender VARCHAR(10), minority VARCHAR(50), percentage_representation DECIMAL(4,2)); INSERT INTO Diversity (id, company_id, gender, minority, percentage_representation) VALUES (1, 1, 'Male', 'Non-minority', 0.65); INSERT INTO Diversity (id, company_id, gender, minority, percentage_representation) VALUES (2, 1, 'Female', 'Minority', 0.35); | What is the representation percentage of each gender and minority group per company? | SELECT company_id, gender, minority, SUM(percentage_representation) as total_percentage FROM Diversity GROUP BY company_id, gender, minority; | gretelai_synthetic_text_to_sql |
CREATE TABLE company (id INT, name TEXT, country TEXT, founding_date DATE, founder_race TEXT); INSERT INTO company (id, name, country, founding_date, founder_race) VALUES (1, 'Delta Startups', 'Canada', '2018-01-01', 'South Asian'); INSERT INTO company (id, name, country, founding_date, founder_race) VALUES (2, 'Epsilon Enterprises', 'Canada', '2020-01-01', 'Caucasian'); | What percentage of companies were founded by underrepresented racial or ethnic groups in Canada? | SELECT (COUNT(*) * 100.0 / (SELECT COUNT(*) FROM company)) FROM company WHERE founder_race IN ('Black', 'Hispanic', 'Indigenous', 'South Asian', 'Middle Eastern') AND country = 'Canada'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Beverages (id INT, is_fair_trade BOOLEAN, category VARCHAR(20), serving_size INT); INSERT INTO Beverages (id, is_fair_trade, category, serving_size) VALUES (1, true, 'coffee', 8), (2, false, 'coffee', 12), (3, true, 'tea', 16); | What is the minimum serving size for fair-trade coffee? | SELECT MIN(serving_size) FROM Beverages WHERE is_fair_trade = true AND category = 'coffee'; | gretelai_synthetic_text_to_sql |
CREATE TABLE transactions (customer_id INT, transaction_amount DECIMAL(10,2), country VARCHAR(50)); INSERT INTO transactions (customer_id, transaction_amount, country) VALUES (1, 120.50, 'Mexico'), (2, 75.30, 'Mexico'), (3, 50.00, 'Mexico'), (4, 150.00, 'Mexico'); | List all customers and their transaction amounts who have made a transaction over 100 in Mexico. | SELECT customer_id, transaction_amount FROM transactions WHERE country = 'Mexico' AND transaction_amount > 100; | gretelai_synthetic_text_to_sql |
CREATE TABLE donor_type (id INT, type VARCHAR(20)); INSERT INTO donor_type (id, type) VALUES (1, 'Individual'), (2, 'Corporate'), (3, 'Foundation'); CREATE TABLE donations (id INT, donor_id INT, amount DECIMAL(10,2)); | What is the total donation amount per donor type? | SELECT dt.type, SUM(d.amount) as total_donation FROM donations d JOIN donor_type dt ON d.donor_id = dt.id GROUP BY dt.type; | gretelai_synthetic_text_to_sql |
CREATE TABLE routes (line VARCHAR(10), station VARCHAR(20)); INSERT INTO routes (line, station) VALUES ('Red', 'Station X'), ('Red', 'Station Y'), ('Red', 'Station Z'); CREATE TABLE fares (route VARCHAR(10), revenue DECIMAL(10, 2)); INSERT INTO fares (route, revenue) VALUES ('Red', 2000), ('Red', 2500), ('Red', 3000); | Delete the 'Red' line's data from the 'fares' and 'routes' tables. | DELETE FROM routes WHERE line = 'Red'; DELETE FROM fares WHERE route IN (SELECT line FROM routes WHERE line = 'Red'); | gretelai_synthetic_text_to_sql |
CREATE TABLE CommunityMediation (CenterID INT, CenterName VARCHAR(50), CaseID INT); INSERT INTO CommunityMediation (CenterID, CenterName, CaseID) VALUES (1, 'Boston Community Mediation', 100), (2, 'Chicago Community Justice Center', 150), (3, 'Seattle Neighborhood Mediation', 120), (4, 'Denver Community Mediation', 80); | What is the number of cases handled by each community mediation center, ordered by the total number of cases, descending? | SELECT CenterName, COUNT(*) AS TotalCases FROM CommunityMediation GROUP BY CenterName ORDER BY TotalCases DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Production (ProductionID INT, WellID INT, ProductionDate DATE, ProductionRate FLOAT, Country VARCHAR(50)); INSERT INTO Production (ProductionID, WellID, ProductionDate, ProductionRate, Country) VALUES (1, 1, '2021-01-01', 500, 'USA'), (2, 2, '2021-01-15', 600, 'Canada'), (3, 3, '2022-02-01', 700, 'Mexico'); | What is the total production for each country in the last year? | SELECT Country, SUM(ProductionRate) AS TotalProduction FROM Production WHERE ProductionDate >= DATEADD(year, -1, GETDATE()) GROUP BY Country; | gretelai_synthetic_text_to_sql |
CREATE TABLE YogaHeartRate (MemberID INT, YogaHeartRate INT); CREATE TABLE CyclingHeartRate (MemberID INT, CyclingHeartRate INT); INSERT INTO YogaHeartRate (MemberID) VALUES (1), (2); INSERT INTO CyclingHeartRate (MemberID) VALUES (1, 60), (2, 50); | Find the number of members who have a higher heart rate during cycling than during yoga. | SELECT COUNT(*) FROM (SELECT MemberID, CyclingHeartRate, YogaHeartRate FROM CyclingHeartRate JOIN YogaHeartRate ON CyclingHeartRate.MemberID = YogaHeartRate.MemberID) WHERE CyclingHeartRate > YogaHeartRate; | gretelai_synthetic_text_to_sql |
CREATE TABLE Citizens (citizen_id INT, name VARCHAR(50), age INT, city VARCHAR(50)); | Insert a new record of a new citizen in the 'Citizens' table | INSERT INTO Citizens (citizen_id, name, age, city) VALUES (1, 'Alex Garcia', 34, 'Los Angeles'); | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (id INT, species_name VARCHAR(255), ocean VARCHAR(255), depth INT); INSERT INTO marine_species (id, species_name, ocean, depth) VALUES (1, 'Southern Ocean Squid', 'Southern', 3000); INSERT INTO marine_species (id, species_name, ocean, depth) VALUES (2, 'Southern Ocean Crab', 'Southern', 2500); | How many marine species were observed in the Southern ocean with a depth greater than 2000 meters? | SELECT COUNT(*) FROM marine_species WHERE ocean = 'Southern' AND depth > 2000; | gretelai_synthetic_text_to_sql |
CREATE TABLE education_programs (id INT, program_name VARCHAR(255), community_type VARCHAR(255), num_participants INT); INSERT INTO education_programs (id, program_name, community_type, num_participants) VALUES (1, 'Wildlife Awareness', 'Indigenous', 500), (2, 'Conservation Workshops', 'Urban', 300), (3, 'Nature Camps', 'Rural', 400); | List community education programs in Indigenous communities and the number of participants | SELECT program_name, community_type, num_participants FROM education_programs WHERE community_type = 'Indigenous'; | gretelai_synthetic_text_to_sql |
CREATE TABLE sales (id INT, region TEXT, product_id INT, is_gluten_free BOOLEAN, revenue INT); INSERT INTO sales (id, region, product_id, is_gluten_free, revenue) VALUES (1, 'Northeast', 1, true, 200), (2, 'Northeast', 2, false, 150), (3, 'Southeast', 3, true, 250), (4, 'Southeast', 4, false, 180), (5, 'Midwest', 5, true, 180), (6, 'Midwest', 6, false, 120), (7, 'Southwest', 7, true, 300), (8, 'Southwest', 8, false, 200); | What is the distribution of gluten-free product sales by region? | SELECT region, is_gluten_free, AVG(revenue) FROM sales GROUP BY region, is_gluten_free; | gretelai_synthetic_text_to_sql |
CREATE TABLE security_incidents (id INT, incident_date DATE, region VARCHAR(255), incident_type VARCHAR(255), threat_actor VARCHAR(255)); INSERT INTO security_incidents (id, incident_date, region, incident_type, threat_actor) VALUES (1, '2022-01-05', 'JP', 'Phishing', 'Threat Actor 1'), (2, '2022-02-10', 'JP', 'Malware', 'Threat Actor 2'), (3, '2022-03-15', 'JP', 'SQL Injection', 'Threat Actor 1'), (4, '2022-04-20', 'JP', 'Cross-site Scripting', 'Threat Actor 3'), (5, '2022-05-25', 'JP', 'DoS/DDoS', 'Threat Actor 2'); | What is the total number of security incidents caused by each threat actor in the JP region? | SELECT threat_actor, COUNT(*) as incidents_per_threat_actor FROM security_incidents WHERE region = 'JP' GROUP BY threat_actor; | gretelai_synthetic_text_to_sql |
CREATE TABLE inventory (item_code varchar(5), warehouse_id varchar(5), quantity int); INSERT INTO inventory (item_code, warehouse_id, quantity) VALUES ('D01', 'LHR', 800), ('D01', 'MAD', 900); | What is the quantity of item 'D01' in all warehouses? | SELECT SUM(quantity) FROM inventory WHERE item_code = 'D01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE dishes (id INT, name TEXT, vegan BOOLEAN, calories INT); INSERT INTO dishes (id, name, vegan, calories) VALUES (1, 'Quinoa Salad', TRUE, 350), (2, 'Pizza Margherita', FALSE, 500); | Retrieve all records from 'dishes' table with a calorie count less than 400 | SELECT * FROM dishes WHERE calories < 400; | gretelai_synthetic_text_to_sql |
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