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 Heritage_Sites (Site_Name VARCHAR(50), Country VARCHAR(50), Region VARCHAR(50)); INSERT INTO Heritage_Sites (Site_Name, Country, Region) VALUES ('Angkor Wat', 'Cambodia', 'Southeast Asia'), ('Borobudur', 'Indonesia', 'Southeast Asia'); | What are the names and locations of all heritage sites in Southeast Asia, organized by country? | SELECT Country, Site_Name, Region FROM Heritage_Sites WHERE Region = 'Southeast Asia' GROUP BY Country; | gretelai_synthetic_text_to_sql |
CREATE TABLE streams (song_name VARCHAR, platform VARCHAR, streams INT); | How many streams did the song 'Hound Dog' get on the music streaming platform? | SELECT SUM(streams) FROM streams WHERE song_name = 'Hound Dog'; | gretelai_synthetic_text_to_sql |
CREATE TABLE species_observations (expedition_id INT, species_count INT); | What is the maximum number of species observed in a single expedition? | SELECT MAX(species_count) FROM species_observations; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, username VARCHAR(255), role VARCHAR(255), followers INT, created_at TIMESTAMP, category VARCHAR(255)); | Which user gained the most followers in the "gaming" category in March 2022? | SELECT username FROM users WHERE category = 'gaming' AND created_at >= '2022-03-01' AND created_at < '2022-04-01' ORDER BY followers DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE bookings (id INT, hotel_id INT, otan_code TEXT, region TEXT, year INT, bookings INT); | What is the total number of bookings for online travel agencies in the 'APAC' region for the year 2022? | SELECT otan_code, SUM(bookings) FROM bookings WHERE region = 'APAC' AND year = 2022 GROUP BY otan_code; | gretelai_synthetic_text_to_sql |
CREATE TABLE Suppliers (SupplierID INT, SupplierName TEXT, Country TEXT);CREATE TABLE Products (ProductID INT, ProductName TEXT, Price DECIMAL, Local BOOLEAN, SupplierID INT); INSERT INTO Suppliers (SupplierID, SupplierName, Country) VALUES (1, 'SupplierA', 'USA'), (2, 'SupplierB', 'Canada'), (3, 'SupplierC', 'France'), (4, 'SupplierD', 'UK'), (5, 'SupplierE', 'Germany'), (6, 'SupplierF', 'Japan'), (7, 'SupplierG', 'Australia'); INSERT INTO Products (ProductID, ProductName, Price, Local, SupplierID) VALUES (1, 'Product1', 15.99, false, 1), (2, 'Product2', 12.49, true, 1), (3, 'Product3', 20.99, true, 2), (4, 'Product4', 10.99, true, 3), (5, 'Product5', 8.99, false, 4), (6, 'Product6', 25.99, true, 4), (7, 'Product7', 18.99, false, 5), (8, 'Product8', 9.99, true, 5), (9, 'Product9', 12.99, true, 6), (10, 'Product10', 14.99, true, 6), (11, 'Product11', 15.99, true, 7), (12, 'Product12', 20.99, true, 7); | What is the maximum price of locally sourced products sold by suppliers in Australia? | SELECT MAX(Price) FROM Products JOIN Suppliers ON Products.SupplierID = Suppliers.SupplierID WHERE Local = true AND Country = 'Australia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE customers (customer VARCHAR(20), purchases INT); INSERT INTO customers (customer, purchases) VALUES ('Customer D', 12), ('Customer E', 8), ('Customer F', 20); CREATE TABLE denim_sales (customer VARCHAR(20), denim INT); INSERT INTO denim_sales (customer, denim) VALUES ('Customer D', 6), ('Customer E', 5), ('Customer F', 10); | Who is the top customer for sustainable denim? | SELECT customer, purchases FROM (SELECT customer, SUM(denim) AS denim_purchases FROM denim_sales GROUP BY customer) AS denim_purchases INNER JOIN customers ON denim_purchases.customer = customers.customer WHERE denim_purchases >= 5 ORDER BY denim_purchases DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE if not exists cities (city_id INT, name TEXT, country TEXT); INSERT INTO cities (city_id, name, country) VALUES (1, 'Rio de Janeiro', 'Brazil'); CREATE TABLE if not exists visit_logs (log_id INT, visitor_id INT, city_id INT, visit_date DATE); INSERT INTO visit_logs (log_id, visitor_id, city_id, visit_date) VALUES (1, 1, 1, '2022-01-01'), (2, 2, 1, '2022-01-15'), (3, 3, 1, '2022-01-30'); | What is the total number of tourists visiting Rio de Janeiro, Brazil, in the last 30 days? | SELECT COUNT(DISTINCT visitor_id) FROM visit_logs JOIN cities ON visit_logs.city_id = cities.city_id WHERE cities.name = 'Rio de Janeiro' AND visit_date >= (CURRENT_DATE - INTERVAL '30 days'); | gretelai_synthetic_text_to_sql |
CREATE TABLE countries (country_id INT, name VARCHAR(255)); CREATE TABLE initiatives (initiative_id INT, country_id INT, type VARCHAR(255)); | Count pollution control initiatives for each country. | SELECT c.name, COUNT(i.initiative_id) AS initiative_count FROM countries c JOIN initiatives i ON c.country_id = i.country_id GROUP BY c.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE safety_scores (model_id INT, region VARCHAR(50), safety FLOAT); INSERT INTO safety_scores (model_id, region, safety) VALUES (1, 'South Asia', 0.97), (2, 'Europe', 0.78), (3, 'South Asia', 0.92), (4, 'North America', 0.65), (5, 'South America', 0.98); | How many creative AI models have a safety score above 0.95 and were developed in South Asia? | SELECT COUNT(*) FROM safety_scores WHERE region = 'South Asia' AND safety > 0.95; | gretelai_synthetic_text_to_sql |
CREATE TABLE Transactions (TransactionID INT, CustomerID INT, Amount DECIMAL(10,2), TransactionDate DATE); INSERT INTO Transactions (TransactionID, CustomerID, Amount, TransactionDate) VALUES (1, 1, 100.00, '2022-02-01'); INSERT INTO Transactions (TransactionID, CustomerID, Amount, TransactionDate) VALUES (2, 1, 200.00, '2022-02-02'); INSERT INTO Transactions (TransactionID, CustomerID, Amount, TransactionDate) VALUES (3, 2, 50.00, '2022-02-01'); INSERT INTO Transactions (TransactionID, CustomerID, Amount, TransactionDate) VALUES (4, 2, 150.00, '2022-02-03'); CREATE TABLE Fraud (FraudID INT, TransactionID INT, IsFraud BIT, CustomerID INT); INSERT INTO Fraud (FraudID, TransactionID, IsFraud, CustomerID) VALUES (1, 1, 0, 1); INSERT INTO Fraud (FraudID, TransactionID, IsFraud, CustomerID) VALUES (2, 2, 1, 1); INSERT INTO Fraud (FraudID, TransactionID, IsFraud, CustomerID) VALUES (3, 3, 0, 2); INSERT INTO Fraud (FraudID, TransactionID, IsFraud, CustomerID) VALUES (4, 4, 0, 2); INSERT INTO Customers (CustomerID, FirstName, LastName, Age, Country) VALUES (1, 'Sanaa', 'Ali', 32, 'United States'); INSERT INTO Customers (CustomerID, FirstName, LastName, Age, Country) VALUES (2, 'Javier', 'Gonzalez', 47, 'Mexico'); | Count the number of transactions that are not marked as fraud for customers from the United States. | SELECT COUNT(*) FROM Transactions T INNER JOIN Fraud F ON T.TransactionID = F.TransactionID INNER JOIN Customers C ON T.CustomerID = C.CustomerID WHERE F.IsFraud = 0 AND C.Country = 'United States'; | gretelai_synthetic_text_to_sql |
CREATE TABLE regions (id INT, name VARCHAR(255)); CREATE TABLE natural_disasters (id INT, region_id INT, year INT); INSERT INTO regions (id, name) VALUES (1, 'West Coast'); INSERT INTO natural_disasters (id, region_id, year) VALUES (1, 1, 2020); | How many natural disasters were recorded in the 'West Coast' region in 2020? | SELECT COUNT(*) FROM natural_disasters WHERE region_id = (SELECT id FROM regions WHERE name = 'West Coast') AND year = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE influencers (influencer_id INT, influencer_name VARCHAR(100), region VARCHAR(50)); CREATE TABLE media_literacy_scores (influencer_id INT, score INT); | Who are the top media literacy influencers in Asia? | SELECT influencer_name FROM influencers JOIN media_literacy_scores ON influencers.influencer_id = media_literacy_scores.influencer_id WHERE region = 'Asia' ORDER BY score DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE districts (id INT, name VARCHAR(255)); INSERT INTO districts (id, name) VALUES (1, 'School District 1'), (2, 'School District 2'); CREATE TABLE schools (id INT, name VARCHAR(255), district_id INT, student_population INT); INSERT INTO schools (id, name, district_id, student_population) VALUES (1, 'School 1', 1, 600), (2, 'School 2', 1, 450), (3, 'School 3', 2, 700); | What is the name and location of all schools in 'School District 1' that have a student population greater than 500? | SELECT name, district_id FROM schools WHERE district_id = (SELECT id FROM districts WHERE name = 'School District 1') AND student_population > 500; | gretelai_synthetic_text_to_sql |
CREATE TABLE Players (PlayerID INT, Age INT, GameType VARCHAR(10)); INSERT INTO Players (PlayerID, Age, GameType) VALUES (1, 25, 'VR'), (2, 30, 'Non-VR'), (3, 22, 'VR'); | What is the average age of players who play VR games? | SELECT AVG(Age) FROM Players WHERE GameType = 'VR'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Artwork (artwork_id INT, artwork_name VARCHAR(30), genre VARCHAR(20), rating INT); | What is the average rating of artworks in the 'Impressionism' genre, excluding artworks with a rating of 0? | SELECT AVG(Artwork.rating) FROM Artwork WHERE Artwork.genre = 'Impressionism' AND Artwork.rating > 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE ingredient_certifications (certification_id INT PRIMARY KEY, ingredient_id INT, certification_date DATE, certified_by TEXT); | Create a table to store cruelty-free certification records for ingredients | CREATE TABLE ingredient_certifications (certification_id INT PRIMARY KEY, ingredient_id INT, certification_date DATE, certified_by TEXT); | gretelai_synthetic_text_to_sql |
CREATE TABLE bills (id INT PRIMARY KEY, title VARCHAR(255), sponsor_id INT, status VARCHAR(255)); INSERT INTO bills (id, title, sponsor_id, status) VALUES (1, 'Public Space Enhancement Act', 1, 'Introduced'), (2, 'Affordable Housing Development Act', 2, 'Passed'); | Remove the bill with id 2 | DELETE FROM bills WHERE id = 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE ExcavationSites (site_id INT, site_name VARCHAR(50)); CREATE TABLE ExcavationTimeline (site_id INT, start_year INT, end_year INT); INSERT INTO ExcavationSites (site_id, site_name) VALUES (6, 'Petra'); INSERT INTO ExcavationTimeline (site_id, start_year, end_year) VALUES (6, 1929, 1934), (6, 1958, 1961), (6, 1993, 1998); | What was the total duration of excavations at the 'Petra' site? | SELECT SUM(DATEDIFF(year, start_year, end_year)) FROM ExcavationTimeline WHERE site_id = (SELECT site_id FROM ExcavationSites WHERE site_name = 'Petra'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Students (student_id INT, name VARCHAR(50), visual_impairment BOOLEAN); CREATE TABLE Support_Programs (program_id INT, state VARCHAR(50), student_id INT); | How many students with visual impairments are enrolled in support programs in Texas and Florida? | SELECT COUNT(DISTINCT S.student_id) FROM Students S INNER JOIN Support_Programs SP ON S.student_id = SP.student_id WHERE S.visual_impairment = TRUE AND SP.state IN ('Texas', 'Florida'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Autonomous_Buses (id INT, route_number INT, fleet_number INT, in_service DATE, last_maintenance_date DATE); INSERT INTO Autonomous_Buses (id, route_number, fleet_number, in_service, last_maintenance_date) VALUES (3, 103, 2503, '2021-12-31', '2021-12-28'), (4, 104, 2504, '2021-12-30', '2021-12-27'); | Which routes have more than 2 autonomous buses that were in service before 2022-01-01? | SELECT route_number, COUNT(*) as total_buses FROM Autonomous_Buses WHERE in_service < '2022-01-01' GROUP BY route_number HAVING total_buses > 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_life (id INT, species VARCHAR(255), population INT, region VARCHAR(255)); INSERT INTO marine_life (id, species, population, region) VALUES (1, 'Salmon', 15000, 'pacific_ocean'); INSERT INTO marine_life (id, species, population, region) VALUES (2, 'Lionfish', 1200, 'atlantic_ocean'); INSERT INTO marine_life (id, species, population, region) VALUES (3, 'Starfish', 8000, 'pacific_ocean'); INSERT INTO marine_life (id, species, population, region) VALUES (4, 'Walrus', 3000, 'arctic_ocean'); INSERT INTO marine_life (id, species, population, region) VALUES (5, 'Seal', 2500, 'arctic_ocean'); | Display the species column and the total population for each species in the marine_life table, ordered by total population in descending order. | SELECT species, SUM(population) OVER (PARTITION BY species) as total_population FROM marine_life ORDER BY total_population DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, EmployeeName VARCHAR(50), Department VARCHAR(50), DiversityTraining VARCHAR(10)); INSERT INTO Employees (EmployeeID, EmployeeName, Department, DiversityTraining) VALUES (1, 'John Doe', 'IT', 'Completed'), (2, 'Jane Smith', 'IT', 'In Progress'), (3, 'Mike Johnson', 'HR', 'Completed'), (4, 'Sara Brown', 'HR', 'Not Started'); | Determine the percentage of employees who have completed diversity and inclusion training, by department. | SELECT Department, PERCENT_RANK() OVER (PARTITION BY DiversityTraining ORDER BY COUNT(*) DESC) AS PercentageCompleted FROM Employees GROUP BY Department, DiversityTraining; | gretelai_synthetic_text_to_sql |
CREATE TABLE deepest_points (ocean TEXT, trench_name TEXT, depth INTEGER); INSERT INTO deepest_points (ocean, trench_name, depth) VALUES ('Pacific Ocean', 'Mariana Trench', 10994), ('Indian Ocean', 'Java Trench', 7290), ('Atlantic Ocean', 'Puerto Rico Trench', 8380); | Find the maximum depth of the Indian Ocean | SELECT MAX(depth) FROM deepest_points WHERE ocean = 'Indian Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE orders (id INT, order_value DECIMAL(10,2), device VARCHAR(20), country VARCHAR(50)); INSERT INTO orders (id, order_value, device, country) VALUES (1, 150.50, 'desktop', 'Spain'), (2, 75.20, 'mobile', 'Canada'), (3, 225.00, 'desktop', 'Spain'); | What is the minimum order value for purchases made using a desktop device in Spain? | SELECT MIN(order_value) FROM orders WHERE device = 'desktop' AND country = 'Spain'; | gretelai_synthetic_text_to_sql |
CREATE TABLE wells_canada (id INT, well_name VARCHAR(50), location VARCHAR(50), company VARCHAR(50), num_drills INT, drill_date DATE, is_private BOOLEAN, province VARCHAR(50)); INSERT INTO wells_canada VALUES (7, 'Well V', 'Alberta', 'Canadian Oil', 5, '2020-06-01', true, 'Alberta'); INSERT INTO wells_canada VALUES (8, 'Well W', 'British Columbia', 'Canadian Gas', 7, '2019-12-15', true, 'British Columbia'); | Identify the number of wells drilled in each province of Canada for privately-owned companies between 2019 and 2021 | SELECT province, SUM(num_drills) FROM wells_canada WHERE is_private = true AND drill_date BETWEEN '2019-01-01' AND '2021-12-31' GROUP BY province; | gretelai_synthetic_text_to_sql |
CREATE TABLE forests (id INT, name TEXT, area FLOAT, region TEXT, carbon_sequestration FLOAT); INSERT INTO forests (id, name, area, region, carbon_sequestration) VALUES (1, 'Arctic Tundra', 123456.7, 'Arctic', 123.4), (2, 'Svalbard', 23456.7, 'Arctic', 234.5); | What is the average carbon sequestration of forests in the 'Arctic' region? | SELECT AVG(carbon_sequestration) FROM forests WHERE region = 'Arctic'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID int, DonorName varchar(100), Country varchar(50), DonationDate date); INSERT INTO Donors (DonorID, DonorName, Country, DonationDate) VALUES (1, 'John Doe', 'USA', '2022-01-01'), (2, 'Jane Smith', 'Canada', '2021-01-01'), (3, 'Ali Khan', 'Pakistan', '2022-03-01'), (4, 'Han Lee', 'South Korea', '2022-04-01'); | How many new donors from Asia joined in 2022? | SELECT COUNT(*) FROM Donors WHERE YEAR(DonationDate) = 2022 AND Country IN ('Afghanistan', 'Bahrain', 'Bangladesh', 'Bhutan', 'Brunei', 'Cambodia', 'China', 'Cyprus', 'East Timor', 'India', 'Indonesia', 'Iran', 'Iraq', 'Israel', 'Japan', 'Jordan', 'Kazakhstan', 'Kuwait', 'Kyrgyzstan', 'Laos', 'Lebanon', 'Malaysia', 'Maldives', 'Mongolia', 'Myanmar', 'Nepal', 'North Korea', 'Oman', 'Pakistan', 'Philippines', 'Qatar', 'Russia', 'Saudi Arabia', 'Singapore', 'South Korea', 'Sri Lanka', 'Syria', 'Tajikistan', 'Thailand', 'Turkey', 'Turkmenistan', 'United Arab Emirates', 'Uzbekistan', 'Vietnam', 'Yemen'); | gretelai_synthetic_text_to_sql |
CREATE TABLE ships (ship_id INT, ship_name VARCHAR(255), registration_date DATE, fleet_id INT); INSERT INTO ships VALUES (1, 'Sea Giant', '2010-03-23', 1), (2, 'Poseidon', '2012-09-08', 1); CREATE TABLE fleets (fleet_id INT, fleet_name VARCHAR(255)); INSERT INTO fleets VALUES (1, 'Sea Fleet'); CREATE TABLE cargo (cargo_id INT, ship_id INT, weight FLOAT, handling_date DATE); INSERT INTO cargo VALUES (1, 1, 5000, '2022-01-01'), (2, 1, 2000, '2022-02-01'), (3, 2, 4000, '2022-12-31'); | List all ships in 'Sea Fleet' with their total cargo weight in 2022 | SELECT s.ship_name, SUM(c.weight) as total_weight FROM ships s JOIN cargo c ON s.ship_id = c.ship_id WHERE s.fleet_id = 1 AND YEAR(c.handling_date) = 2022 GROUP BY s.ship_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE policy (policy_id INT, policy_holder VARCHAR(50), coverage_amount INT); CREATE TABLE claim (claim_id INT, policy_id INT, claim_amount INT, claim_date DATE); INSERT INTO policy (policy_id, policy_holder, coverage_amount) VALUES (1, 'John Doe', 400000), (2, 'Jane Smith', 600000), (3, 'Mary Johnson', 350000); INSERT INTO claim (claim_id, policy_id, claim_amount, claim_date) VALUES (1, 1, 5000, '2021-01-01'), (2, 1, 3000, '2021-02-01'), (3, 2, 7000, '2021-03-01'), (4, 3, 4000, '2021-04-01'); | Delete policy records for policyholders living in 'California' | DELETE FROM policy WHERE policy_holder IN (SELECT policy_holder FROM policy JOIN (SELECT 'California' AS state_name UNION ALL SELECT 'CA') AS ca ON policy_holder LIKE '%CA%'); | gretelai_synthetic_text_to_sql |
CREATE TABLE Esports_Events (id INT, name VARCHAR(50), event_date DATE); INSERT INTO Esports_Events (id, name, event_date) VALUES (1, 'Dreamhack', '2022-01-01'), (2, 'ESL One', '2021-01-01'), (3, 'IEM', '2022-03-01'); | Count the number of esports events in 2022 | SELECT COUNT(*) FROM Esports_Events WHERE event_date BETWEEN '2022-01-01' AND '2022-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE FerryFares (FareID INT, RouteID INT, Fare FLOAT); | What is the maximum fare for a ferry ride? | SELECT MAX(Fare) FROM FerryFares WHERE RouteID = 123; | gretelai_synthetic_text_to_sql |
CREATE TABLE consumer_preference (id INT PRIMARY KEY, consumer_id INT, product_id INT, preference_score INT, category VARCHAR(100));CREATE TABLE product (id INT PRIMARY KEY, name VARCHAR(100));CREATE TABLE consumer (id INT PRIMARY KEY, name VARCHAR(100), age INT, gender VARCHAR(100));CREATE VIEW avg_preference_score_by_category AS SELECT category, AVG(preference_score) as avg_preference_score FROM consumer_preference GROUP BY category; | List the names of products that have a preference score above the average preference score for products in the same category. | SELECT p.name FROM product p JOIN consumer_preference cp ON p.id = cp.product_id JOIN avg_preference_score_by_category aps ON cp.category = aps.category WHERE cp.preference_score > aps.avg_preference_score; | gretelai_synthetic_text_to_sql |
CREATE TABLE climate_projects (id INT, project_name VARCHAR(20), project_location VARCHAR(20), project_type VARCHAR(20)); INSERT INTO climate_projects (id, project_name, project_location, project_type) VALUES (1, 'Adaptation Project 1', 'Pacific Islands', 'Climate Adaptation'), (2, 'Mitigation Project 1', 'Europe', 'Climate Mitigation'), (3, 'Adaptation Project 2', 'Pacific Islands', 'Climate Adaptation'); | Delete all records related to climate adaptation projects in the Pacific Islands from the climate_projects table. | DELETE FROM climate_projects WHERE project_location = 'Pacific Islands' AND project_type = 'Climate Adaptation'; | gretelai_synthetic_text_to_sql |
CREATE TABLE fish_farms (id INT, name TEXT, location TEXT, temperature FLOAT); INSERT INTO fish_farms (id, name, location, temperature) VALUES (1, 'Farm A', 'South Pacific Ocean', 22.5), (2, 'Farm B', 'North Pacific Ocean', 18.0); | What is the average temperature (°C) for fish farms located in the South Pacific Ocean? | SELECT AVG(temperature) FROM fish_farms WHERE location = 'South Pacific Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE meals (id INT, name TEXT, restaurant_type TEXT); INSERT INTO meals (id, name, restaurant_type) VALUES (1, 'Filet Mignon', 'fine dining'), (2, 'Chicken Caesar', 'casual dining'), (3, 'Tofu Stir Fry', 'fine dining'); CREATE TABLE nutrition (meal_id INT, calorie_count INT); INSERT INTO nutrition (meal_id, calorie_count) VALUES (1, 1200), (2, 800), (3, 900); | What is the minimum calorie count for meals served at casual dining restaurants? | SELECT MIN(nutrition.calorie_count) FROM nutrition JOIN meals ON nutrition.meal_id = meals.id WHERE meals.restaurant_type = 'casual dining'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, Name VARCHAR(50), HireDate DATE, Salary FLOAT); INSERT INTO Employees (EmployeeID, Name, HireDate, Salary) VALUES (1, 'John Doe', '2022-01-01', 80000.00), (2, 'Jane Smith', '2022-02-14', 85000.00), (3, 'Mike Johnson', '2021-12-01', 90000.00); | What is the average salary of employees hired in 2022? | SELECT AVG(Salary) FROM Employees WHERE YEAR(HireDate) = 2022; | gretelai_synthetic_text_to_sql |
CREATE TABLE prices (id INT, brand VARCHAR(255), price DECIMAL(10, 2)); INSERT INTO prices (id, brand, price) VALUES (1, 'Lush', 25.99), (2, 'NYX', 12.99), (3, 'Burt’s Bees', 15.99), (4, 'Tarte', 28.99), (5, 'Urban Decay', 21.99); | Update the price of all Lush products to $30.00. | UPDATE prices SET price = 30.00 WHERE brand = 'Lush'; | gretelai_synthetic_text_to_sql |
CREATE TABLE construction_labor_stats (state TEXT, project_id INT, labor_cost FLOAT); | What is the maximum labor cost for construction projects in 'New York' in the 'construction_labor_stats' table? | SELECT MAX(labor_cost) FROM construction_labor_stats WHERE state = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE maritime_safety_ratings (route TEXT, safety_rating INTEGER); INSERT INTO maritime_safety_ratings (route, safety_rating) VALUES ('Route A', 7), ('Route B', 8), ('Route C', 6); | What is the minimum safety rating for maritime routes in the Indian Ocean? | SELECT MIN(safety_rating) FROM maritime_safety_ratings WHERE route LIKE '%Indian Ocean%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE MobileInvestments (Area varchar(10), Investment int); CREATE TABLE BroadbandInvestments (Area varchar(10), Investment int); INSERT INTO MobileInvestments (Area, Investment) VALUES ('North', 100000), ('South', 120000), ('rural', 75000); INSERT INTO BroadbandInvestments (Area, Investment) VALUES ('East', 80000), ('rural', 90000), ('West', 110000); | List the total network investments made in 'rural' areas for mobile and broadband networks separately, and the difference between the two. | SELECT SUM(CASE WHEN Area = 'rural' THEN Investment ELSE 0 END) AS RuralBroadband, SUM(CASE WHEN Area = 'rural' THEN 0 ELSE Investment END) AS RuralMobile, RuralBroadband - RuralMobile AS InvestmentDifference FROM MobileInvestments MI JOIN BroadbandInvestments BI ON 1=1; | gretelai_synthetic_text_to_sql |
CREATE TABLE patients (id INT, name VARCHAR(50), age INT, gender VARCHAR(10), region VARCHAR(50)); CREATE TABLE diseases (id INT, patient_id INT, name VARCHAR(50), diagnosis_date DATE, severity INT); INSERT INTO patients (id, name, age, gender, region) VALUES (1, 'James Smith', 65, 'Male', 'Rural Alabama'); INSERT INTO diseases (id, patient_id, name, diagnosis_date, severity) VALUES (1, 1, 'Diabetes', '2019-05-10', 5); | List the names of patients diagnosed with diabetes in rural Alabama and the diagnosis date. | SELECT patients.name, diseases.diagnosis_date FROM patients INNER JOIN diseases ON patients.id = diseases.patient_id WHERE patients.region = 'Rural Alabama' AND diseases.name = 'Diabetes'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Farm (id INT, farm_name TEXT, region TEXT, species TEXT, weight FLOAT, age INT); INSERT INTO Farm (id, farm_name, region, species, weight, age) VALUES (1, 'OceanPacific', 'Pacific', 'Tilapia', 500.3, 2), (2, 'SeaBreeze', 'Atlantic', 'Salmon', 300.1, 1), (3, 'OceanPacific', 'Pacific', 'Tilapia', 600.5, 3), (4, 'FarmX', 'Atlantic', 'Salmon', 700.2, 4), (5, 'SeaBreeze', 'Atlantic', 'Tilapia', 400, 2); | What is the total biomass of fish in the 'Atlantic' and 'Pacific' regions? | SELECT SUM(weight) FROM Farm WHERE region IN ('Atlantic', 'Pacific'); | gretelai_synthetic_text_to_sql |
CREATE TABLE climate_projects (project_id INT, project_name TEXT, location TEXT, project_type TEXT, start_year INT); INSERT INTO climate_projects (project_id, project_name, location, project_type, start_year) VALUES (1, 'Adaptation 1', 'Australia', 'climate adaptation', 2010), (2, 'Mitigation 1', 'New Zealand', 'climate mitigation', 2012), (3, 'Communication 1', 'Fiji', 'climate communication', 2015); | Identify the number of climate adaptation projects in Oceania for each year since 2010. | SELECT start_year, COUNT(*) as project_count FROM climate_projects WHERE project_type = 'climate adaptation' AND location LIKE 'Oceania%' AND start_year >= 2010 GROUP BY start_year; | gretelai_synthetic_text_to_sql |
CREATE TABLE timber_production (id INT, region VARCHAR(255), volume FLOAT); INSERT INTO timber_production (id, region, volume) VALUES (1, 'Northwest', 1234.56), (2, 'Southeast', 789.12), (3, 'Northwest', 456.34); | What is the maximum volume of timber in the timber_production table? | SELECT MAX(volume) FROM timber_production; | gretelai_synthetic_text_to_sql |
CREATE TABLE bollywood_movies (id INT, title VARCHAR(255), release_year INT, runtime INT); INSERT INTO bollywood_movies (id, title, release_year, runtime) VALUES (1, 'Tanhaji', 2020, 135), (2, 'Chhapaak', 2020, 123); | What's the average runtime of Bollywood movies released in 2020? | SELECT AVG(runtime) FROM bollywood_movies WHERE release_year = 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE WarzoneLegends (PlayerID INT, Kills INT, Matches INT); INSERT INTO WarzoneLegends (PlayerID, Kills, Matches) VALUES (1, 120, 25), (2, 85, 20), (3, 135, 30), (4, 90, 22), (5, 110, 28); | What is the average number of kills per match for players who have more than 100 kills in the "WarzoneLegends" table? | SELECT AVG(Kills/Matches) FROM WarzoneLegends WHERE Kills > 100; | gretelai_synthetic_text_to_sql |
CREATE TABLE cases (case_id INT, close_date DATE); INSERT INTO cases (case_id, close_date) VALUES (1, '2022-01-01'), (2, '2021-08-01'), (3, '2022-05-15'); | Delete all cases with a close date older than 6 months. | DELETE FROM cases WHERE close_date < DATE_SUB(CURRENT_DATE, INTERVAL 6 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE spacecraft_missions (id INT, spacecraft VARCHAR(50), altitude INT); INSERT INTO spacecraft_missions (id, spacecraft, altitude) VALUES (1, 'Starship', 10000); | What is the maximum altitude reached by spacecraft built by SpaceX? | SELECT MAX(altitude) FROM spacecraft_missions WHERE spacecraft = 'Starship'; | gretelai_synthetic_text_to_sql |
CREATE TABLE recycling_rates_tokyo (city VARCHAR(50), recycling_rate DECIMAL(5,2), date DATE); INSERT INTO recycling_rates_tokyo (city, recycling_rate, date) VALUES ('Tokyo', 0.75, '2022-01-01'), ('Tokyo', 0.76, '2022-02-01'), ('Tokyo', 0.77, '2022-03-01'), ('Tokyo', 0.78, '2022-04-01'), ('Tokyo', 0.79, '2022-05-01'), ('Tokyo', 0.80, '2022-06-01'), ('Tokyo', 0.81, '2022-07-01'), ('Tokyo', 0.82, '2022-08-01'), ('Tokyo', 0.83, '2022-09-01'), ('Tokyo', 0.84, '2022-10-01'), ('Tokyo', 0.85, '2022-11-01'), ('Tokyo', 0.86, '2022-12-01'); | What is the average recycling rate in Tokyo for the last 12 months? | SELECT AVG(recycling_rate) FROM recycling_rates_tokyo WHERE city = 'Tokyo' AND date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE ingredients (ingredient_id INT, ingredient_name TEXT, organic BOOLEAN, product_id INT); | List the top 5 ingredients used in cosmetic products that are sourced from organic farms, along with the number of products that use each ingredient. | SELECT ingredient_name, COUNT(*) as num_products FROM ingredients WHERE organic = TRUE GROUP BY ingredient_name ORDER BY num_products DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE subway_stations (station_name TEXT, entries INTEGER, exits INTEGER); INSERT INTO subway_stations (station_name, entries, exits) VALUES ('Times Square-42nd St', 45678, 43210), ('Grand Central-42nd St', 34567, 35432), ('34th St-Herald Sq', 23456, 24321); | What are the names of the busiest subway stations in New York City, based on the number of entries and exits? | SELECT station_name FROM subway_stations ORDER BY entries + exits DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE smart_contracts (contract_id INT PRIMARY KEY, name VARCHAR(255), last_update_date DATETIME); INSERT INTO smart_contracts (contract_id, name, last_update_date) VALUES (1, 'Contract1', '2022-01-10 15:00:00'), (2, 'Contract2', '2022-02-05 16:00:00'), (3, 'Contract3', '2022-03-01 14:00:00'), (4, 'Contract4', '2022-03-15 13:00:00'), (5, 'Contract5', '2022-02-20 12:00:00'); | Delete any smart contracts that have not been updated in the last 60 days. | DELETE FROM smart_contracts WHERE last_update_date < DATE_SUB(CURRENT_DATE, INTERVAL 60 DAY); | gretelai_synthetic_text_to_sql |
CREATE TABLE MillE(mill_name TEXT, timber_volume INT); INSERT INTO MillE (mill_name, timber_volume) VALUES ('Mill E', 600); CREATE TABLE MillSales(mill_name TEXT, sale_volume INT); INSERT INTO MillSales (mill_name, sale_volume) VALUES ('Mill A', 500), ('Mill B', 350), ('Mill E', 700); | Display the total volume of timber sold by each mill, excluding sales from 'Mill E'. | SELECT ms.mill_name, SUM(ms.sale_volume) FROM MillSales ms WHERE ms.mill_name NOT IN ('Mill E') GROUP BY ms.mill_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE Visitors (id INT, city VARCHAR(50), language VARCHAR(50), visitors INT); INSERT INTO Visitors (id, city, language, visitors) VALUES (1, 'Istanbul', 'French', 2000); | Find the total number of visitors that attended exhibitions in Istanbul and spoke French. | SELECT SUM(visitors) FROM Visitors WHERE city = 'Istanbul' AND language = 'French'; | gretelai_synthetic_text_to_sql |
CREATE TABLE clients (id INT, name VARCHAR(50), total_billing_amount DECIMAL(10,2)); INSERT INTO clients (id, name, total_billing_amount) VALUES (1, 'ABC Corp', 50000.00), (2, 'XYZ Inc', 75000.00), (3, 'LMN LLC', 30000.00); | List the top 3 clients by total billing amount | SELECT name, total_billing_amount FROM clients ORDER BY total_billing_amount DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE co2_emission(country VARCHAR(50), co2_emission FLOAT); INSERT INTO co2_emission(country, co2_emission) VALUES('CountryX', 25.6), ('CountryY', 32.8), ('CountryZ', 38.1); | What is the total CO2 emission (in metric tons) for each country where textiles are sourced? | SELECT country, SUM(co2_emission) FROM co2_emission GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE menu_items (id INT, name VARCHAR(50), restaurant_id INT); CREATE TABLE sales (menu_item_id INT, revenue INT, restaurant_id INT); | Identify the top 3 menu items by sales across all restaurants | SELECT menu_items.name, SUM(sales.revenue) as total_sales FROM sales JOIN menu_items ON sales.menu_item_id = menu_items.id GROUP BY menu_items.name ORDER BY total_sales DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Cases (CaseID INT, Outcome VARCHAR(10)); INSERT INTO Cases (CaseID, Outcome) VALUES (1, 'Favorable'), (2, 'Unfavorable'); CREATE TABLE Attorneys (AttorneyID INT, CaseID INT); INSERT INTO Attorneys (AttorneyID, CaseID) VALUES (1, 1), (2, 2); | Which attorneys have worked on cases with a favorable outcome? | SELECT DISTINCT Attorneys.AttorneyID FROM Attorneys INNER JOIN Cases ON Attorneys.CaseID = Cases.CaseID WHERE Cases.Outcome = 'Favorable'; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA RuralHealth; USE RuralHealth; CREATE TABLE Counties (CountyID INT, CountyName VARCHAR(50), CountyPopulation INT, StateAbbreviation VARCHAR(10)); CREATE TABLE MentalHealthProviders (ProviderID INT, CountyID INT, ProviderType VARCHAR(50)); INSERT INTO Counties (CountyID, CountyName, CountyPopulation, StateAbbreviation) VALUES (1, 'CountyA', 50000, 'AL'), (2, 'CountyB', 150000, 'AK'); INSERT INTO MentalHealthProviders (ProviderID, CountyID, ProviderType) VALUES (1, 1, 'Psychiatrist'), (2, 1, 'Social Worker'), (3, 2, 'Psychiatrist'), (4, 2, 'Therapist'); INSERT INTO StatesPopulation (StateAbbreviation, StatePopulation) VALUES ('AL', 5000000), ('AK', 1000000); | What is the number of mental health providers per 100,000 people for each county, ordered from highest to lowest? | SELECT CountyID, (SUM(CASE WHEN ProviderType IN ('Psychiatrist', 'Social Worker', 'Therapist') THEN 1 ELSE 0 END) * 100000.0 / CountyPopulation) as MentalHealthProvidersPer100k FROM MentalHealthProviders INNER JOIN Counties ON MentalHealthProviders.CountyID = Counties.CountyID INNER JOIN StatesPopulation ON Counties.StateAbbreviation = StatesPopulation.StateAbbreviation GROUP BY CountyID ORDER BY MentalHealthProvidersPer100k DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE teacher_development (teacher_id INT, subject_teached VARCHAR(30), course_completed INT); | Find the number of teachers who have not completed any professional development courses in the 'teacher_development' table, grouped by their teaching subject. | SELECT subject_teached, COUNT(teacher_id) FROM teacher_development WHERE course_completed = 0 GROUP BY subject_teached; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (species_name TEXT, population INTEGER, ocean TEXT); | What is the maximum population of any marine species in the Southern Ocean? | SELECT MAX(population) FROM marine_species WHERE ocean = 'Southern Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Funding (funding_id INT, event_type VARCHAR(20), funding_source VARCHAR(20), amount INT, event_location VARCHAR(20)); INSERT INTO Funding (funding_id, event_type, funding_source, amount, event_location) VALUES (1, 'Music', 'Private', 7000, 'New York'), (2, 'Dance', 'Private', 3000, 'Chicago'), (3, 'Music', 'Corporate', 8000, 'Los Angeles'); | What is the total funding received for music events from the "Private" funding source, excluding events in 'New York'? | SELECT SUM(amount) FROM Funding WHERE event_type = 'Music' AND funding_source = 'Private' AND event_location <> 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE sites (id INT, name TEXT, country TEXT, visitors INT); INSERT INTO sites (id, name, country, visitors) VALUES (1, 'Site1', 'Italy', 500), (2, 'Site2', 'Italy', 700); | What is the total number of visitors to cultural heritage sites in Italy? | SELECT SUM(visitors) FROM sites WHERE country = 'Italy'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Games (GameID INT, GameName VARCHAR(50), Genre VARCHAR(50), Rating INT); INSERT INTO Games (GameID, GameName, Genre, Rating) VALUES (1, 'Game1', 'Action', 9), (2, 'Game2', 'RPG', 8), (3, 'Game3', 'Strategy', 10), (4, 'Game4', 'Simulation', 7); | List all unique game genres that have a rating of 9 or higher. | SELECT DISTINCT Genre FROM Games WHERE Rating >= 9; | gretelai_synthetic_text_to_sql |
CREATE TABLE disasters (id INT PRIMARY KEY, name TEXT, start_date DATE); | Insert a new record for a disaster with ID 10, name 'Flood', and start date 2021-11-01 into the "disasters" table | INSERT INTO disasters (id, name, start_date) VALUES (10, 'Flood', '2021-11-01'); | gretelai_synthetic_text_to_sql |
CREATE TABLE organizations (id INT, sector VARCHAR(20), ESG_rating FLOAT); INSERT INTO organizations (id, sector, ESG_rating) VALUES (1, 'Healthcare', 7.5), (2, 'Technology', 8.2), (3, 'Healthcare', 8.0), (4, 'Renewable Energy', 9.0); CREATE TABLE investments (id INT, organization_id INT); INSERT INTO investments (id, organization_id) VALUES (1, 1), (2, 2), (3, 3), (4, 4); | List all organizations and their investments in the renewable energy sector | SELECT organizations.sector, organizations.id, investments.id AS investment_id FROM organizations JOIN investments ON organizations.id = investments.organization_id WHERE organizations.sector = 'Renewable Energy'; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations(id INT, donor_name TEXT, donation_amount FLOAT, donation_date DATE, industry TEXT); INSERT INTO donations(id, donor_name, donation_amount, donation_date, industry) VALUES (1, 'James Lee', 50, '2022-11-29', 'Technology'), (2, 'Grace Kim', 100, '2022-12-01', 'Finance'), (3, 'Anthony Nguyen', 25, '2022-11-29', 'Technology'); | What is the average donation amount for donors in the Technology industry who gave on Giving Tuesday? | SELECT AVG(donation_amount) FROM donations WHERE industry = 'Technology' AND donation_date = '2022-11-29'; | gretelai_synthetic_text_to_sql |
CREATE TABLE countries (country_name TEXT, num_research_stations INT); INSERT INTO countries (country_name, num_research_stations) VALUES ('Canada', 7), ('USA', 12), ('Australia', 6), ('Indonesia', 4), ('Japan', 8); | Identify countries with a minimum of 5 marine research stations. | SELECT country_name FROM countries WHERE num_research_stations >= 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE students (id INT, name VARCHAR(50), institution_id INT, mental_health_score INT, location VARCHAR(10)); INSERT INTO students (id, name, institution_id, mental_health_score, location) VALUES (1, 'Jane Doe', 1, 80, 'urban'), (2, 'John Doe', 2, 70, 'rural'), (3, 'Ava Smith', 1, 85, 'urban'), (4, 'Ben Johnson', 2, 75, 'rural'); | What is the average mental health score for students in rural and urban areas? | SELECT location, AVG(mental_health_score) as avg_score FROM students GROUP BY location; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA carbon_offsets; CREATE TABLE projects (project_name VARCHAR(255), region VARCHAR(255), investment_amount INT); INSERT INTO projects (project_name, region, investment_amount) VALUES ('Tropical Forest Conservation', 'Asia', 5000000), ('Wind Power Generation', 'Europe', 8000000), ('Soil Carbon Sequestration', 'Africa', 3000000), ('Oceanic Algae Farming', 'Oceania', 7000000); | Find the average investment amount for carbon offset projects in the 'Africa' and 'Europe' regions, excluding oceanic projects. | SELECT region, AVG(investment_amount) FROM carbon_offsets.projects WHERE region IN ('Africa', 'Europe') AND region != 'Oceania' GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE genetic_research (study_name VARCHAR(255), location VARCHAR(255), technology VARCHAR(255), publish_date DATE); INSERT INTO genetic_research (study_name, location, technology, publish_date) VALUES ('GeneUSA', 'USA', 'CRISPR-Cas9', '2023-01-01'); | Which genetic research studies from the USA or Mexico have used CRISPR technology and published results in the last 6 months? | SELECT study_name FROM genetic_research WHERE (location = 'USA' OR location = 'Mexico') AND technology = 'CRISPR-Cas9' AND publish_date BETWEEN DATEADD(MONTH, -6, GETDATE()) AND GETDATE(); | gretelai_synthetic_text_to_sql |
CREATE TABLE EmployeeBenefits (id INT, EmployeeID INT, CompanyType TEXT, HealthcareBenefits BOOLEAN); | What is the percentage of non-union workers in the 'Finance' sector who receive healthcare benefits? | SELECT (COUNT(*) / (SELECT COUNT(*) FROM EmployeeBenefits WHERE CompanyType != 'Union') * 100) FROM EmployeeBenefits WHERE CompanyType != 'Union' AND HealthcareBenefits = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE Highway (id INT, name TEXT, location TEXT, number_of_lanes INT); INSERT INTO Highway (id, name, location, number_of_lanes) VALUES (1, 'A1 Autoroute', 'France', 3), (2, 'A6 Autoroute', 'France', 2); | What is the minimum number of lanes for highways in France? | SELECT MIN(number_of_lanes) FROM Highway WHERE location = 'France'; | gretelai_synthetic_text_to_sql |
CREATE TABLE station (station_id INT, name TEXT, location TEXT); INSERT INTO station (station_id, name, location) VALUES (1, 'Station A', 'City Center'), (2, 'Station B', 'North District'); CREATE TABLE ticket_sales (sale_id INT, station_id INT, sale_date DATE, revenue FLOAT); INSERT INTO ticket_sales (sale_id, station_id, sale_date, revenue) VALUES (1, 1, '2022-01-01', 150.5), (2, 1, '2022-01-02', 120.3), (3, 2, '2022-01-01', 180.7), (4, 2, '2022-01-02', 160.2); | What was the total revenue for each station in January 2022? | SELECT station.name, SUM(ticket_sales.revenue) as total_revenue FROM station JOIN ticket_sales ON station.station_id = ticket_sales.station_id WHERE ticket_sales.sale_date BETWEEN '2022-01-01' AND '2022-01-31' GROUP BY station.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (id INT, country TEXT, amount DECIMAL(10,2)); INSERT INTO donations (id, country, amount) VALUES (4, 'Nigeria', 25.00), (5, 'South Africa', 75.50), (6, 'Egypt', 100.00); | What was the average gift size in Africa? | SELECT AVG(amount) FROM donations WHERE country IN ('Nigeria', 'South Africa', 'Egypt'); | gretelai_synthetic_text_to_sql |
CREATE TABLE labor_hours (labor_id INT, state VARCHAR(20), year INT, hours_worked INT); INSERT INTO labor_hours (labor_id, state, year, hours_worked) VALUES (1, 'California', 2019, 1500000), (2, 'California', 2018, 1400000), (3, 'New York', 2019, 1200000), (4, 'Texas', 2019, 1300000), (5, 'California', 2020, 1350000); | What is the minimum number of construction labor hours worked in a year in the state of California? | SELECT state, MIN(hours_worked) FROM labor_hours GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE Customers (CustomerID INT, Name VARCHAR(50));CREATE TABLE Investments (CustomerID INT, InvestmentType VARCHAR(10), Sector VARCHAR(10));INSERT INTO Customers VALUES (1,'John Doe'),(2,'Jane Smith'),(3,'Bob Johnson');INSERT INTO Investments VALUES (1,'Stocks','Real Estate'),(1,'Bonds','Healthcare'),(2,'Stocks','Real Estate'),(2,'Bonds','Healthcare'),(2,'Mutual Funds','Technology'),(3,'Stocks','Healthcare'),(4,1,'Real Estate'),(5,2,'Real Estate'); | What are the names of customers who have invested in at least three different sectors? | SELECT DISTINCT c.Name FROM Customers c INNER JOIN Investments i ON c.CustomerID = i.CustomerID GROUP BY c.CustomerID, c.Name HAVING COUNT(DISTINCT i.Sector) >= 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE suppliers(supplier_id INT, supplier_name TEXT, state TEXT); INSERT INTO suppliers(supplier_id, supplier_name, state) VALUES (1, 'Eco-Friendly Fabrics', 'California'); CREATE TABLE products(product_id INT, product_name TEXT, supplier_id INT); INSERT INTO products(product_id, product_name, supplier_id) VALUES (1, 'Organic Cotton T-Shirt', 1); CREATE TABLE sales(sale_id INT, product_id INT, quantity INT); INSERT INTO sales(sale_id, product_id, quantity) VALUES (1, 1, 50); | What is the total quantity of 'organic cotton' products sold by suppliers in California? | SELECT SUM(sales.quantity) FROM sales JOIN products ON sales.product_id = products.product_id JOIN suppliers ON products.supplier_id = suppliers.supplier_id WHERE suppliers.state = 'California' AND products.product_name LIKE '%organic cotton%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE customers (customer_id INT, registration_date DATE, name VARCHAR(50)); CREATE TABLE transactions (transaction_id INT, customer_id INT, transaction_amount DECIMAL(10,2)); INSERT INTO customers (customer_id, registration_date, name) VALUES (1, '2022-01-01', 'Charlie Brown'); INSERT INTO transactions (transaction_id, customer_id, transaction_amount) VALUES (1, 1, 100.00); | Show the number of new customers and total transaction amount for new customers in the past week. | SELECT COUNT(DISTINCT c.customer_id) as num_new_customers, SUM(t.transaction_amount) as total_transaction_amount FROM customers c INNER JOIN transactions t ON c.customer_id = t.customer_id WHERE c.registration_date BETWEEN DATEADD(day, -7, GETDATE()) AND GETDATE(); | gretelai_synthetic_text_to_sql |
CREATE TABLE programs (program_id INT, program_name TEXT, manager_name TEXT); INSERT INTO programs VALUES (1, 'Education', 'Alice Johnson'), (2, 'Health', 'Bob Brown'); | List all programs in the 'programs' table and their respective managers. | SELECT * FROM programs; | gretelai_synthetic_text_to_sql |
CREATE TABLE public.medical_emergencies (id SERIAL PRIMARY KEY, city VARCHAR(255), response_time INTEGER); INSERT INTO public.medical_emergencies (city, response_time) VALUES ('Chicago', 120), ('Chicago', 150), ('Chicago', 90); | What is the average response time for medical emergencies in the city of Chicago? | SELECT AVG(response_time) FROM public.medical_emergencies WHERE city = 'Chicago'; | gretelai_synthetic_text_to_sql |
CREATE TABLE buildings (id INT, green_certified BOOLEAN, city VARCHAR(20), zip_code INT); INSERT INTO buildings (id, green_certified, city, zip_code) VALUES (1, true, 'Los Angeles', 90001), (2, false, 'Los Angeles', 90001), (3, true, 'Los Angeles', 90002), (4, true, 'Los Angeles', 90002), (5, false, 'Los Angeles', 90003), (6, true, 'Los Angeles', 90003), (7, true, 'Los Angeles', 90003), (8, false, 'Los Angeles', 90004), (9, true, 'Los Angeles', 90004), (10, false, 'Los Angeles', 90005); | Identify the top 3 zip codes with the highest number of green-certified buildings in the city of Los Angeles. | SELECT zip_code, COUNT(*) as num_green_buildings FROM buildings WHERE city = 'Los Angeles' AND green_certified = true GROUP BY zip_code ORDER BY num_green_buildings DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE dispensaries (dispensary_id INT, name VARCHAR(255), state VARCHAR(255));CREATE TABLE sales (sale_id INT, dispensary_id INT, strain VARCHAR(255), quantity INT); | What are the top 5 strains sold in California dispensaries? | SELECT strain, SUM(quantity) as total_quantity FROM sales JOIN dispensaries ON sales.dispensary_id = dispensaries.dispensary_id WHERE state = 'California' GROUP BY strain ORDER BY total_quantity DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE virtual_tours (id INT, hotel_id INT, country TEXT, views INT); INSERT INTO virtual_tours (id, hotel_id, country, views) VALUES (1, 1, 'Japan', 200), (2, 2, 'China', 350), (3, 3, 'Japan', 400), (4, 4, 'India', 150), (5, 5, 'China', 50); | List the top 3 countries with the highest virtual tour engagement in 'Asia'? | SELECT country, SUM(views) as total_views FROM virtual_tours WHERE country LIKE 'Asia%' GROUP BY country ORDER BY total_views DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, name VARCHAR(50), followers INT, country VARCHAR(50)); INSERT INTO users (id, name, followers, country) VALUES (1, 'Ayu Saputra', 1000, 'Indonesia'), (2, 'Budi Prasetyo', 2000, 'Indonesia'), (3, 'Dewi Santoso', 3000, 'Indonesia'); | What is the average number of followers for users in Indonesia? | SELECT AVG(followers) FROM users WHERE country = 'Indonesia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Attorneys (AttorneyID int, Name varchar(50), Region varchar(50)); INSERT INTO Attorneys VALUES (1, 'John Smith', 'Northeast'), (2, 'Jane Doe', 'Southeast'); CREATE TABLE Billing (BillingID int, AttorneyID int, Amount decimal(10,2)); INSERT INTO Billing VALUES (1, 1, 500.00), (2, 1, 750.00), (3, 2, 300.00), (4, 2, 600.00); | What is the average billing amount per attorney by region? | SELECT A.Region, A.Name, AVG(B.Amount) as AvgBillingPerAttorney FROM Attorneys A JOIN Billing B ON A.AttorneyID = B.AttorneyID GROUP BY A.Region, A.Name; | gretelai_synthetic_text_to_sql |
CREATE TABLE projects(id INT, project_name VARCHAR(50), project_type VARCHAR(50), country VARCHAR(50));CREATE TABLE carbon_offsets(project_id INT, carbon_offset_value INT); | What is the average carbon offset value for each project type in the projects and carbon_offsets tables? | SELECT p.project_type, AVG(co.carbon_offset_value) AS avg_offset_value FROM projects p INNER JOIN carbon_offsets co ON p.id = co.project_id GROUP BY p.project_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_conservation_scores (state VARCHAR(20), score INT); INSERT INTO water_conservation_scores (state, score) VALUES ('California', 85), ('Texas', 70), ('New York', 80), ('Florida', 75); | Which states have water conservation initiative scores above 80? | SELECT state FROM water_conservation_scores WHERE score > 80 | gretelai_synthetic_text_to_sql |
CREATE TABLE subscriber_tech (subscriber_id INT, subscription_start_date DATE, technology VARCHAR(50), subscription_fee DECIMAL(10, 2)); INSERT INTO subscriber_tech (subscriber_id, subscription_start_date, technology, subscription_fee) VALUES (1, '2020-01-01', 'Fiber', 50.00), (2, '2019-06-15', 'Cable', 40.00), (3, '2021-02-20', 'Fiber', 55.00); | What is the maximum subscription fee for each technology in the 'subscriber_tech' table? | SELECT technology, MAX(subscription_fee) as max_fee FROM subscriber_tech GROUP BY technology; | gretelai_synthetic_text_to_sql |
CREATE TABLE transactions (transaction_date DATE, customer_id INT, amount DECIMAL(10,2)); INSERT INTO transactions (transaction_date, customer_id, amount) VALUES ('2022-01-01', 1, 100), ('2022-01-05', 1, 200), ('2022-01-02', 2, 150), ('2022-01-03', 2, 50), ('2021-01-04', 3, 300), ('2021-01-05', 3, 250), ('2021-01-10', 1, 50), ('2021-01-15', 2, 350), ('2021-01-20', 3, 400); | What is the moving average of transaction amounts for each customer over the past year? | SELECT customer_id, AVG(amount) OVER (PARTITION BY customer_id ORDER BY transaction_date ROWS BETWEEN 364 PRECEDING AND CURRENT ROW) AS moving_avg FROM transactions; | gretelai_synthetic_text_to_sql |
CREATE TABLE EmployeeSalaries (EmployeeID int, Gender varchar(10), Department varchar(20), Salary decimal(10,2)); INSERT INTO EmployeeSalaries (EmployeeID, Gender, Department, Salary) VALUES (1, 'Female', 'IT', 75000.00), (2, 'Male', 'IT', 80000.00), (3, 'Non-binary', 'IT', 70000.00), (4, 'Female', 'Marketing', 72000.00), (5, 'Male', 'Marketing', 78000.00); | What is the average salary for employees in the Marketing department by gender? | SELECT Department, Gender, AVG(Salary) FROM EmployeeSalaries WHERE Department = 'Marketing' GROUP BY Department, Gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE Dispensaries (id INT, name TEXT, state TEXT);CREATE TABLE Sales (id INT, dispensary_id INT, revenue DECIMAL(10,2), sale_date DATE); INSERT INTO Dispensaries (id, name, state) VALUES (1, 'Dispensary A', 'Washington DC'); INSERT INTO Sales (id, dispensary_id, revenue, sale_date) VALUES (1, 1, 15000, '2022-06-01'); | What is the total revenue for each dispensary in Washington DC in the last week? | SELECT d.name, SUM(s.revenue) FROM Dispensaries d JOIN Sales s ON d.id = s.dispensary_id WHERE d.state = 'Washington DC' AND s.sale_date BETWEEN DATE_SUB(CURDATE(), INTERVAL 1 WEEK) AND CURDATE() GROUP BY d.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE departments (dept_name VARCHAR(255), num_professors INT, num_female_professors INT); INSERT INTO departments (dept_name, num_professors, num_female_professors) VALUES ('Humanities', 50, 20), ('Social Sciences', 60, 25), ('Sciences', 70, 30), ('Arts', 45, 15); | Find the number of professors in the 'Arts' department. | SELECT num_professors FROM departments WHERE dept_name = 'Arts'; | gretelai_synthetic_text_to_sql |
CREATE TABLE stores (store_id INT, store_location VARCHAR(255));CREATE TABLE products (product_id INT, product_name VARCHAR(255), store_id INT, transparency_score DECIMAL(3, 2), FK_store_id REFERENCES stores(store_id));CREATE TABLE certifications (certification_id INT, certification_date DATE, FK_product_id REFERENCES products(product_id)); | Calculate the average product transparency score for each store, along with the store's location and certification date. | SELECT s.store_location, AVG(p.transparency_score) as avg_transparency_score, c.certification_date FROM stores s JOIN products p ON s.store_id = p.store_id JOIN certifications c ON p.product_id = c.product_id GROUP BY s.store_id, c.certification_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE routes (route_id INT, route_name VARCHAR(255)); INSERT INTO routes (route_id, route_name) VALUES (1, 'Green Line'), (2, 'Red Line'); | Delete the 'Red Line' route | DELETE FROM routes WHERE route_name = 'Red Line'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Exhibitions (exhibition_id INT, city VARCHAR(20), country VARCHAR(20)); INSERT INTO Exhibitions (exhibition_id, city, country) VALUES (1, 'New York', 'USA'), (2, 'Los Angeles', 'USA'), (3, 'Chicago', 'USA'), (4, 'Paris', 'France'), (5, 'London', 'UK'), (6, 'Tokyo', 'Japan'), (7, 'Sydney', 'Australia'), (8, 'Berlin', 'Germany'); CREATE TABLE Visitors (visitor_id INT, exhibition_id INT, age INT); INSERT INTO Visitors (visitor_id, exhibition_id, age) VALUES (1, 1, 30), (2, 1, 35), (3, 2, 25), (4, 2, 28), (5, 3, 40), (6, 3, 45), (7, 4, 22), (8, 4, 27), (9, 4, 30), (10, 5, 35), (11, 5, 40), (12, 6, 20), (13, 7, 45), (14, 7, 50), (15, 8, 35); | How many exhibitions were held in each country, and how many visitors attended in total? | SELECT e.country, COUNT(DISTINCT e.exhibition_id) AS num_exhibitions, SUM(v.visitor_id) AS num_visitors FROM Exhibitions e LEFT JOIN Visitors v ON e.exhibition_id = v.exhibition_id GROUP BY e.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE mature_forest (id INT, species VARCHAR(255), age INT); INSERT INTO mature_forest (id, species, age) VALUES (1, 'Pine', 25), (2, 'Oak', 30), (3, 'Maple', 28); | What is the total age of trees in the mature_forest table? | SELECT SUM(age) FROM mature_forest; | gretelai_synthetic_text_to_sql |
CREATE TABLE Port (port_id INT, port_name TEXT, country TEXT); INSERT INTO Port (port_id, port_name, country) VALUES (1, 'Port of Kolkata', 'India'); INSERT INTO Port (port_id, port_name, country) VALUES (2, 'Port of Chittagong', 'Bangladesh'); CREATE TABLE Shipment (shipment_id INT, container_id INT, port_id INT, shipping_date DATE); CREATE TABLE Container (container_id INT, weight FLOAT); | What is the average weight of containers shipped from the Port of Kolkata to Bangladesh in the last 3 months? | SELECT AVG(c.weight) as avg_weight FROM Container c JOIN Shipment s ON c.container_id = s.container_id JOIN Port p ON s.port_id = p.port_id WHERE p.country = 'Bangladesh' AND s.shipping_date >= NOW() - INTERVAL '3 months' AND s.port_id = (SELECT port_id FROM Port WHERE port_name = 'Port of Kolkata'); | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, name VARCHAR(100), is_vegan BOOLEAN, category VARCHAR(50), country VARCHAR(50)); INSERT INTO products (product_id, name, is_vegan, category, country) VALUES (1, 'Lipstick', false, 'Makeup', 'UK'); INSERT INTO products (product_id, name, is_vegan, category, country) VALUES (2, 'Mascara', true, 'Makeup', 'UK'); | Find the number of non-vegan makeup products in the UK. | SELECT COUNT(*) FROM products WHERE is_vegan = false AND category = 'Makeup' AND country = 'UK'; | gretelai_synthetic_text_to_sql |
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