context stringlengths 11 9.12k | question stringlengths 0 1.06k | SQL stringlengths 2 4.44k | source stringclasses 28
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CREATE TABLE agreements (id INT, union_id INT, region TEXT, date DATE, agreement_count INT); INSERT INTO agreements (id, union_id, region, date, agreement_count) VALUES (1, 1, 'Europe', '2021-01-01', 5), (2, 2, 'Asia-Pacific', '2021-02-15', 3); | How many collective bargaining agreements were signed in each region in the last 6 months? | SELECT region, COUNT(agreement_count) FROM agreements WHERE date >= DATEADD(month, -6, CURRENT_DATE) GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE broadband_usage (id INT, location VARCHAR(50), data_usage FLOAT); INSERT INTO broadband_usage (id, location, data_usage) VALUES (1, 'New York', 25.6), (2, 'Texas', 30.7), (3, 'California', 28.9); | What is the average monthly data usage for broadband customers in the state of New York? | SELECT AVG(data_usage) FROM broadband_usage WHERE location = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (DonationID INT, DonationDate DATE, CauseCategory VARCHAR(50), DonationAmount NUMERIC(15,2)); | What is the average donation amount per day for each cause category? | SELECT CauseCategory, AVG(DonationAmount) as AvgDonationAmount FROM Donations GROUP BY CauseCategory, DATEPART(year, DonationDate), DATEPART(month, DonationDate), DATEPART(day, DonationDate) ORDER BY CauseCategory, DATEPART(year, DonationDate), DATEPART(month, DonationDate), DATEPART(day, DonationDate); | gretelai_synthetic_text_to_sql |
CREATE TABLE local_impact (id INT, city VARCHAR(50), value INT); INSERT INTO local_impact (id, city, value) VALUES (1, 'New York', 1000), (2, 'Berlin', 1500), (3, 'Tokyo', 800), (4, 'Seoul', 1200); | What is the average local economic impact in Tokyo and Seoul? | SELECT AVG(value) FROM local_impact WHERE city IN ('Tokyo', 'Seoul'); | gretelai_synthetic_text_to_sql |
CREATE TABLE factories (factory_id INT, factory_name VARCHAR(20)); INSERT INTO factories VALUES (1, 'Factory A'), (2, 'Factory B'), (3, 'Factory C'); CREATE TABLE roles (role_id INT, role_name VARCHAR(20)); INSERT INTO roles VALUES (1, 'junior'), (2, 'senior'), (3, 'manager'); CREATE TABLE workers (worker_id INT, facto... | What is the average salary of 'junior' workers in each factory? | SELECT f.factory_name, AVG(salary) FROM workers w INNER JOIN roles r ON w.role_id = r.role_id INNER JOIN factories f ON w.factory_id = f.factory_id WHERE r.role_name = 'junior' GROUP BY f.factory_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE labor (employee_id INT, age_group VARCHAR(50), material VARCHAR(50), weight FLOAT); INSERT INTO labor (employee_id, age_group, material, weight) VALUES (1, '18-24', 'Iron', 500), (2, '25-34', 'Iron', 450), (3, '35-44', 'Iron', 400), (4, '45-54', 'Iron', 350), (5, '55-64', 'Iron', 300); | What was the total weight of minerals extracted by age group in the given dataset? | SELECT age_group, SUM(weight) as total_weight FROM labor GROUP BY age_group; | gretelai_synthetic_text_to_sql |
CREATE TABLE Shipments (id INT, weight INT, origin_country TEXT); INSERT INTO Shipments (id, weight, origin_country) VALUES (1, 8, 'USA'); INSERT INTO Shipments (id, weight, origin_country) VALUES (2, 12, 'USA'); INSERT INTO Shipments (id, weight, origin_country) VALUES (3, 5, 'Canada'); | Delete all shipments that have a weight greater than 10 tons and originated from the United States. | DELETE FROM Shipments WHERE weight > 10 AND origin_country = 'USA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE VolunteerHours (HourID INT, VolunteerID INT, ProgramID INT, Hours DECIMAL(10,2)); CREATE TABLE Donations (DonationID INT, DonorID INT, ProgramID INT, Amount DECIMAL(10,2)); CREATE TABLE Volunteers (VolunteerID INT, Name TEXT); CREATE TABLE Donors (DonorID INT, Name TEXT); INSERT INTO VolunteerHours (HourID... | What is the total number of volunteer hours and total donation amount per program, based on the 'VolunteerHours', 'Volunteers', 'Donations', and 'Donors' tables? | SELECT VolunteerPrograms.ProgramID, SUM(VolunteerHours.Hours) as TotalHours, SUM(Donations.Amount) as TotalDonation FROM VolunteerPrograms INNER JOIN VolunteerHours ON VolunteerPrograms.ProgramID = VolunteerHours.ProgramID INNER JOIN Donations ON VolunteerPrograms.ProgramID = Donations.ProgramID GROUP BY VolunteerProgr... | gretelai_synthetic_text_to_sql |
CREATE TABLE department_budgets (department TEXT, budget INT, year INT); INSERT INTO department_budgets (department, budget, year) VALUES ('intelligence', 1000000, 2020), ('reconnaissance', 1200000, 2020), ('intelligence', 1100000, 2019), ('reconnaissance', 1300000, 2019); | What is the difference in budget between the 'intelligence' and 'reconnaissance' departments for the year 2020, ordered by the difference in descending order? | SELECT LAG(budget, 1, 0) OVER (ORDER BY department) as prev_budget, budget, budget - LAG(budget, 1, 0) OVER (ORDER BY department) as budget_diff, department FROM department_budgets WHERE year = 2020 AND (department = 'intelligence' OR department = 'reconnaissance') ORDER BY budget_diff DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE volunteers (id INT, name TEXT, signup_date DATE, region TEXT); INSERT INTO volunteers (id, name, signup_date, region) VALUES (1, 'Alice', '2022-01-15', 'North'), (2, 'Bob', '2021-12-10', 'South'), (3, 'Charlie', '2022-02-25', 'East'), (4, 'David', '2021-11-05', 'West'), (5, 'Eve', '2022-03-05', 'North'); | Show the number of volunteers who signed up in each region for the past 12 months. | SELECT region, COUNT(DISTINCT id) as new_volunteers, DATE_FORMAT(signup_date, '%Y-%m') as month FROM volunteers WHERE signup_date BETWEEN DATE_SUB(NOW(), INTERVAL 12 MONTH) AND NOW() GROUP BY region, month; | gretelai_synthetic_text_to_sql |
CREATE TABLE accessibility_data (service_type VARCHAR(50), usage_date DATE); INSERT INTO accessibility_data (service_type, usage_date) VALUES ('Wheelchair Ramp', '2021-01-01'), ('Wheelchair Ramp', '2021-01-05'), ('Service Animal', '2021-01-03'); | Count the number of passengers who used accessible services in January 2021 | SELECT COUNT(*) FROM accessibility_data WHERE usage_date BETWEEN '2021-01-01' AND '2021-01-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE processed_foods (id INT PRIMARY KEY, name VARCHAR(100), category VARCHAR(50), calories INT); | Update the 'calories' column in the 'processed_foods' table for all records with 'name' containing 'chocolate' and set the value to 250 | UPDATE processed_foods SET calories = 250 WHERE name LIKE '%chocolate%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE TerbiumProduction (country VARCHAR(20), year INT, quantity INT); INSERT INTO TerbiumProduction (country, year, quantity) VALUES ('Malaysia', 2018, 70), ('Malaysia', 2019, 75); | What is the total production quantity of terbium in Malaysia for the year 2018? | SELECT SUM(quantity) FROM TerbiumProduction WHERE country = 'Malaysia' AND year = 2018; | gretelai_synthetic_text_to_sql |
CREATE TABLE Chemicals (id INT, name VARCHAR(255), max_safe_temp FLOAT); CREATE TABLE Storage (id INT, chemical_id INT, facility_id INT, storage_date DATE); | What is the maximum safe operating temperature for each chemical stored at a specific facility? | SELECT Chemicals.name, Chemicals.max_safe_temp FROM Chemicals INNER JOIN Storage ON Chemicals.id = Storage.chemical_id WHERE Storage.facility_id = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE attendance_data (id INT, user_id INT, program VARCHAR(50), attend_date DATE); INSERT INTO attendance_data (id, user_id, program, attend_date) VALUES (10, 9, 'Tai Chi', '2021-06-01'), (11, 10, 'Zumba', '2021-07-01'), (12, 11, 'Tai Chi', '2021-08-01'), (13, 12, 'Yoga', '2021-09-01'), (14, 13, 'Pilates', '202... | Which wellness programs were attended by users from Argentina and Colombia, and how many times did they attend? | SELECT program, COUNT(*) as attend_count FROM attendance_data WHERE country IN ('Argentina', 'Colombia') GROUP BY program; | gretelai_synthetic_text_to_sql |
CREATE TABLE school_districts (district_id INT, district_name TEXT, average_mental_health_score DECIMAL(5,2)); CREATE TABLE students (student_id INT, district_id INT, mental_health_score INT); | What are the names and number of students for the top 5 school districts with the highest average mental health scores, and what is the overall average mental health score across all school districts? | SELECT d.district_name, COUNT(s.student_id) as num_students, AVG(s.mental_health_score) as avg_mental_health_score FROM students s JOIN school_districts d ON s.district_id = d.district_id GROUP BY d.district_id, d.district_name ORDER BY avg_mental_health_score DESC LIMIT 5; SELECT AVG(s.mental_health_score) as overall_... | gretelai_synthetic_text_to_sql |
CREATE TABLE events (id INT, event_date DATE, visitor_count INT, visitor_ethnicity VARCHAR(20)); INSERT INTO events (id, event_date, visitor_count, visitor_ethnicity) VALUES (1, '2021-07-10', 250, 'Latinx'), (2, '2021-07-11', 300, 'Asian'), (3, '2021-07-12', 150, 'African American'), (4, '2021-08-01', 400, 'Caucasian')... | How many visitors identified as Latinx attended events in the past 6 months? | SELECT SUM(visitor_count) FROM events WHERE visitor_ethnicity = 'Latinx' AND event_date BETWEEN '2021-07-01' AND '2021-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE explainable_model (id INT PRIMARY KEY, model_name TEXT, training_date DATE); INSERT INTO explainable_model (id, model_name, training_date) VALUES (1, 'model1', '2021-01-01'), (2, 'model2', '2021-02-01'); | What is the earliest 'explainable_model' training date for 'model1'? | SELECT MIN(training_date) FROM explainable_model WHERE model_name = 'model1'; | gretelai_synthetic_text_to_sql |
CREATE TABLE cultural_tourism(location_id INT, location_name TEXT, country TEXT, tourism_impact INT); INSERT INTO cultural_tourism (location_id, location_name, country, tourism_impact) VALUES (1, 'Tokyo National Museum', 'Japan', 150), (2, 'Asakusa', 'Japan', 200), (3, 'Ueno Park', 'Japan', 120); | What is the local economic impact of cultural tourism in Tokyo, Japan? | SELECT SUM(tourism_impact) FROM cultural_tourism WHERE country = 'Japan' AND location_name IN ('Tokyo National Museum', 'Asakusa'); | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, transparency_rating TEXT); INSERT INTO products (product_id, transparency_rating) VALUES (1, 'High'), (2, 'Medium'), (3, 'High'), (4, 'Low'); CREATE TABLE sales (sale_id INT, product_id INT, price DECIMAL(5,2)); INSERT INTO sales (sale_id, product_id, price) VALUES (1, 1, 20.99), ... | What is the total revenue generated from products with a high transparency rating? | SELECT SUM(sales.price) FROM sales INNER JOIN products ON sales.product_id = products.product_id WHERE products.transparency_rating = 'High'; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, product_name TEXT, is_cruelty_free BOOLEAN, sales INT, country TEXT); INSERT INTO products (product_id, product_name, is_cruelty_free, sales, country) VALUES (1, 'Lipstick', true, 500, 'USA'), (2, 'Foundation', false, 700, 'USA'), (3, 'Mascara', true, 600, 'USA'); | What are the top 3 cruelty-free cosmetic products by sales in the USA? | SELECT product_name, SUM(sales) as total_sales FROM products WHERE is_cruelty_free = true AND country = 'USA' GROUP BY product_name ORDER BY total_sales DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE vulnerabilities (id INT, department VARCHAR(20), resolved BOOLEAN); INSERT INTO vulnerabilities (id, department, resolved) VALUES (1, 'Marketing', FALSE), (2, 'IT', TRUE), (3, 'Marketing', TRUE), (4, 'Marketing', FALSE); | How many vulnerabilities were resolved in the 'Marketing' department in the last 6 months? | SELECT COUNT(*) FROM vulnerabilities WHERE department = 'Marketing' AND resolved = TRUE AND detection_date >= DATE_SUB(CURDATE(), INTERVAL 6 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (id INT, continent VARCHAR(50), name VARCHAR(50), endemic BOOLEAN); INSERT INTO marine_species (id, continent, name, endemic) VALUES (1, 'Africa', 'Coelacanth', true); INSERT INTO marine_species (id, continent, name, endemic) VALUES (2, 'Asia', 'Dugong', false); | How many marine species are endemic to each continent? | SELECT continent, COUNT(*) FROM marine_species WHERE endemic = true GROUP BY continent; | gretelai_synthetic_text_to_sql |
CREATE TABLE factories_asia (factory_id INT, country VARCHAR(50), certification_1 VARCHAR(50), certification_2 VARCHAR(50), certification_3 VARCHAR(50)); INSERT INTO factories_asia (factory_id, country, certification_1, certification_2, certification_3) VALUES (1, 'China', 'Fair Trade', 'SA8000', 'BSCI'), (2, 'India', ... | What is the percentage of factories in Asia with at least one fair labor practice certification? | SELECT COUNT(*) * 100.0 / (SELECT COUNT(*) FROM factories_asia) FROM factories_asia WHERE certification_1 IS NOT NULL OR certification_2 IS NOT NULL OR certification_3 IS NOT NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE workouts (id INT, member_id INT, workout_type VARCHAR(50), duration INT, date DATE, avg_heart_rate DECIMAL(3,1)); INSERT INTO workouts (id, member_id, workout_type, duration, date, avg_heart_rate) VALUES (1, 1, 'Cycling', 60, '2022-03-10', 120.5), (2, 3, 'Yoga', 45, '2022-03-15', 85.0); | Calculate the average heart rate for each member during their workouts in the last month. | SELECT w.member_id, AVG(w.avg_heart_rate) AS avg_heart_rate FROM workouts w WHERE w.date >= DATE_SUB(CURDATE(), INTERVAL 1 MONTH) GROUP BY w.member_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE subscribers(id INT, plan_type VARCHAR(10), region VARCHAR(10)); INSERT INTO subscribers VALUES (1, 'unlimited', 'Western'); INSERT INTO subscribers VALUES (2, 'limited', 'Northern'); INSERT INTO subscribers VALUES (3, NULL, 'Southern'); CREATE TABLE data_usage(subscriber_id INT, data_used INT); INSERT INTO... | List all the mobile subscribers with their plan type and the amount of data they have used in the Western region, if available. If not, return null values. | SELECT subscribers.id, subscribers.plan_type, data_usage.data_used FROM subscribers LEFT JOIN data_usage ON subscribers.id = data_usage.subscriber_id WHERE subscribers.region = 'Western'; | gretelai_synthetic_text_to_sql |
CREATE TABLE virtual_tours (tour_id INT, hotel_id INT, user_id INT, timestamp TIMESTAMP); | What is the most popular virtual tour for hotels in Brazil? | SELECT hotel_id, COUNT(*) FROM virtual_tours WHERE country = 'Brazil' GROUP BY hotel_id ORDER BY COUNT(*) DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotels (id INT, name TEXT, city TEXT, is_eco_friendly BOOLEAN, revenue FLOAT); INSERT INTO hotels (id, name, city, is_eco_friendly, revenue) VALUES (1, 'Eco Hotel New York', 'New York', TRUE, 15000.0), (2, 'Green Hotel New York', 'New York', TRUE, 18000.0); | What is the total revenue of eco-friendly hotels in New York? | SELECT SUM(revenue) FROM hotels WHERE city = 'New York' AND is_eco_friendly = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE FareCollection (CollectionID INT, CollectionDate DATE, VehicleType VARCHAR(50)); INSERT INTO FareCollection (CollectionID, CollectionDate, VehicleType) VALUES (1, '2023-01-01', 'Bus'), (2, '2023-01-05', 'Tram'), (3, '2023-02-10', 'Train'); | What is the earliest and latest collection date for each vehicle type? | SELECT VehicleType, MIN(CollectionDate) as EarliestCollectionDate, MAX(CollectionDate) as LatestCollectionDate FROM FareCollection GROUP BY VehicleType; | gretelai_synthetic_text_to_sql |
CREATE TABLE species (id INT, name VARCHAR(50), habitat_ocean VARCHAR(50)); CREATE TABLE conservation_status (id INT, species_id INT, status VARCHAR(50), score FLOAT); | Show the number of marine species in each ocean and their average conservation status score. | SELECT habitat_ocean, AVG(score), COUNT(*) FROM species INNER JOIN conservation_status ON species.id = conservation_status.species_id GROUP BY habitat_ocean; | gretelai_synthetic_text_to_sql |
CREATE TABLE peacekeeping_operations (id INT PRIMARY KEY, operation_name VARCHAR(50), location VARCHAR(50)); | Insert a new record into the 'peacekeeping_operations' table with the following values: (3, 'MINUSCA', 'Central African Republic') | INSERT INTO peacekeeping_operations (id, operation_name, location) VALUES (3, 'MINUSCA', 'Central African Republic'); | gretelai_synthetic_text_to_sql |
CREATE TABLE matches (team1 VARCHAR(255), team2 VARCHAR(255), goals_scored INT); | List all soccer matches with more than 3 goals scored | SELECT * FROM matches WHERE goals_scored > 3; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA art; CREATE TABLE art_pieces (artist_id INT, artist_name VARCHAR(255), country VARCHAR(50), art_count INT); INSERT INTO art.art_pieces (artist_id, artist_name, country, art_count) VALUES (1, 'Nana Asante', 'Ghana', 15), (2, 'Aisha Dia', 'Senegal', 20), (3, 'Kwame Opoku', 'Nigeria', 12); | What is the average number of art pieces created per artist in Africa? | SELECT AVG(art_count) FROM art.art_pieces WHERE country = 'Africa'; | gretelai_synthetic_text_to_sql |
CREATE TABLE VulnerabilityDatabase (id INT, country VARCHAR(50), severity INT, timestamp DATETIME); INSERT INTO VulnerabilityDatabase (id, country, severity, timestamp) VALUES (1, 'Brazil', 7, '2021-01-01 10:00:00'), (2, 'India', 6, '2021-01-01 10:00:00'); | What are the top 3 countries with the lowest average vulnerability severity in the last 6 months, according to our Vulnerability Database? | SELECT country, AVG(severity) as avg_severity FROM VulnerabilityDatabase WHERE timestamp >= DATE_SUB(NOW(), INTERVAL 6 MONTH) GROUP BY country ORDER BY avg_severity ASC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE forest_type (forest_type_id INT, forest_type_name TEXT, region_id INT, PRIMARY KEY (forest_type_id)); CREATE TABLE forest (forest_id INT, forest_type_id INT, tree_species_count INT, age INT, carbon_sequestered INT, PRIMARY KEY (forest_id), FOREIGN KEY (forest_type_id) REFERENCES forest_type(forest_type_id)... | Display the total carbon sequestered and the average age of forests, grouped by forest type, for forests located in Asia, sorted by the average age in ascending order. | SELECT ft.forest_type_name, AVG(f.age) AS avg_age, SUM(f.carbon_sequestered) AS total_carbon_sequestered FROM forest_type ft INNER JOIN forest f ON ft.forest_type_id = f.forest_type_id INNER JOIN region r ON ft.region_id = r.region_id WHERE r.region_name = 'Asia' GROUP BY ft.forest_type_name ORDER BY avg_age ASC; | gretelai_synthetic_text_to_sql |
CREATE TABLE rd_expenditures (expenditure_id INT, department TEXT, amount INT, expenditure_date DATE); INSERT INTO rd_expenditures (expenditure_id, department, amount, expenditure_date) VALUES (1, 'R&D-A', 150000, '2020-01-01'), (2, 'R&D-B', 200000, '2020-05-15'), (3, 'R&D-C', 0, '2020-12-31'); | Calculate the total R&D expenditures for each department for the year 2020, including departments with zero expenditures, from the 'rd_expenditures' table. | SELECT department, COALESCE(SUM(amount), 0) AS total_expenditures FROM rd_expenditures WHERE expenditure_date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY department; | gretelai_synthetic_text_to_sql |
CREATE TABLE rangers (id INT, name VARCHAR(255), region VARCHAR(255)); INSERT INTO rangers (id, name, region) VALUES (1, 'John', 'North America'), (2, 'Sophia', 'South America'), (3, 'Emma', 'Europe'), (4, 'Ethan', 'Africa'), (5, 'Ava', 'Asia'); | Count the number of rangers in each region | SELECT region, COUNT(*) AS ranger_count FROM rangers GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE indian_marine_species (species VARCHAR(255), count INT); INSERT INTO indian_marine_species (species, count) VALUES ('Turtle', 150), ('Shark', 200), ('Manta Ray', 100), ('Dolphin', 120); | Find the total number of marine species and their observation counts in the Indian Ocean, excluding sharks and rays. | SELECT COUNT(DISTINCT species) AS species_count, SUM(count) AS total_count FROM indian_marine_species WHERE species NOT IN ('Shark', 'Manta Ray'); | gretelai_synthetic_text_to_sql |
CREATE TABLE user_posts (user_id INT, country VARCHAR(50)); INSERT INTO user_posts (user_id, country) VALUES (1, 'USA'), (2, 'Canada'), (3, 'Mexico'), (4, 'Brazil'), (5, 'Australia'), (6, 'India'), (7, 'China'), (8, 'Germany'), (9, 'France'), (10, 'UK'); | What are the top 3 countries with the most number of users who have posted more than 10 times on "social_media"? | SELECT country, COUNT(DISTINCT user_id) as num_users FROM user_posts WHERE user_id IN (SELECT user_id FROM posts GROUP BY user_id, post_id HAVING COUNT(*) > 10) GROUP BY country ORDER BY num_users DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE textile_waste (id INT, country VARCHAR(50), waste_per_capita INT); INSERT INTO textile_waste (id, country, waste_per_capita) VALUES (1, 'Bangladesh', 20), (2, 'China', 15), (3, 'India', 18), (4, 'USA', 30); | Which country has the highest textile waste per capita? | SELECT country, MAX(waste_per_capita) as max_waste_per_capita FROM textile_waste GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE travel_advisories (country VARCHAR(255), level INT); INSERT INTO travel_advisories (country, level) VALUES ('USA', 1), ('Canada', 1), ('Mexico', 2), ('Kenya', 2); | Update the travel_advisories table to mark Kenya as a level 3 travel advisory country due to recent political unrest. | UPDATE travel_advisories SET level = 3 WHERE country = 'Kenya'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Safety_Testing (id INT PRIMARY KEY, vehicle_id INT, test_type VARCHAR(50), score INT, date DATE); CREATE TABLE Vehicles (id INT PRIMARY KEY, make VARCHAR(50), model VARCHAR(50), year INT, type VARCHAR(50)); | What is the average safety score for electric sedans released after 2019? | SELECT v.make, v.model, AVG(s.score) as avg_safety_score FROM Vehicles v INNER JOIN Safety_Testing s ON v.id = s.vehicle_id WHERE v.type = 'Sedan' AND v.year > 2019 AND s.test_type = 'Crash Test' GROUP BY v.make, v.model; | gretelai_synthetic_text_to_sql |
CREATE TABLE movie_studios (studio_id INT, studio_name TEXT, country TEXT); INSERT INTO movie_studios (studio_id, studio_name, country) VALUES (1, 'Studio A', 'USA'), (2, 'Studio B', 'Canada'), (3, 'Studio C', 'UK'); CREATE TABLE movies (movie_id INT, title TEXT, release_date DATE, studio_id INT, revenue INT); INSERT I... | What is the total revenue of movies produced by Studio C in 2020 and 2021? | SELECT SUM(movies.revenue) FROM movies JOIN movie_studios ON movies.studio_id = movie_studios.studio_id WHERE movie_studios.studio_name = 'Studio C' AND YEAR(movies.release_date) BETWEEN 2020 AND 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE landfill_capacity (country VARCHAR(10), capacity INT); INSERT INTO landfill_capacity (country, capacity) VALUES ('CountryA', 20000), ('CountryB', 15000); | What is the difference in landfill capacity between 'CountryA' and 'CountryB' in the 'landfill_capacity' table? | SELECT capacity - (SELECT capacity FROM landfill_capacity WHERE country = 'CountryB') FROM landfill_capacity WHERE country = 'CountryA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE students (id INT, name VARCHAR(100), department VARCHAR(50), publication_count INT); INSERT INTO students VALUES (1, 'Bob Brown', 'Humanities', 3); | What is the publication rate of graduate students in the Humanities department? | SELECT department, AVG(publication_count) FROM students WHERE department = 'Humanities' GROUP BY department; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, name VARCHAR(50), price DECIMAL(5, 2), sustainable BOOLEAN, material VARCHAR(50)); | Insert a new product called "Natural Fiber Scarf" made of bamboo, priced at $24.99 and set it as sustainable. | INSERT INTO products (product_id, name, price, sustainable, material) VALUES (3, 'Natural Fiber Scarf', 24.99, TRUE, 'Bamboo'); | gretelai_synthetic_text_to_sql |
CREATE TABLE WeatherData (region VARCHAR(255), date DATE, temperature INT); INSERT INTO WeatherData (region, date, temperature) VALUES ('Canada', '2022-12-01', -10), ('Canada', '2022-12-02', -12), ('Russia', '2022-12-01', -15), ('Russia', '2022-12-02', -17), ('Sweden', '2022-12-01', -5), ('Sweden', '2022-12-02', -7); | List the bottom 2 regions with the lowest average temperature in December. | SELECT region, AVG(temperature) as Avg_Temperature FROM WeatherData WHERE date BETWEEN '2022-12-01' AND '2022-12-31' GROUP BY region ORDER BY Avg_Temperature ASC LIMIT 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE field_temperature (field_id INT, date DATE, temperature DECIMAL(5,2)); INSERT INTO field_temperature (field_id, date, temperature) VALUES (33333, '2022-02-01', 20.5), (33333, '2022-02-02', 21.0), (33333, '2022-02-14', 19.5), (33333, '2022-02-15', 20.0); | Delete the temperature data for field ID 33333 that was recorded before 2022-02-15. | DELETE FROM field_temperature WHERE field_id = 33333 AND date < '2022-02-15'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Residential_Buildings (id INT, building_type VARCHAR(20), location VARCHAR(20), energy_efficiency_rating FLOAT); INSERT INTO Residential_Buildings (id, building_type, location, energy_efficiency_rating) VALUES (1, 'Apartment', 'City of Toronto', 82.5), (2, 'Townhouse', 'City of Toronto', 85.0), (3, 'Single... | What is the average energy efficiency rating for residential buildings in the City of Toronto? | SELECT AVG(energy_efficiency_rating) FROM Residential_Buildings WHERE location = 'City of Toronto'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_conservation_orgs (org_name TEXT, country TEXT, year_founded INTEGER); INSERT INTO marine_conservation_orgs (org_name, country, year_founded) VALUES ('Ocean Conservancy', 'USA', 1972), ('National Marine Sanctuary Foundation', 'USA', 2000); | What is the average year of founding for marine conservation organizations in the USA? | SELECT AVG(year_founded) FROM marine_conservation_orgs WHERE country = 'USA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE device_cost (country VARCHAR(20), device VARCHAR(20), cost FLOAT); INSERT INTO device_cost (country, device, cost) VALUES ('Brazil', 'Screen Reader', 100.00), ('Argentina', 'Adaptive Keyboard', 80.00), ('Colombia', 'Speech Recognition Software', 120.00); | What is the minimum cost of a device for accessibility in South America? | SELECT MIN(cost) FROM device_cost WHERE country = 'South America'; | gretelai_synthetic_text_to_sql |
CREATE TABLE wind_turbines (id INT, manufacturer VARCHAR(255), installed_year INT, capacity FLOAT); | Update the 'capacity' of all wind turbines manufactured by 'FutureEnergy' to 2.5 MW | UPDATE wind_turbines SET capacity = 2.5 WHERE manufacturer = 'FutureEnergy'; | gretelai_synthetic_text_to_sql |
CREATE TABLE cultural_competency_trainings (training_id INT, state VARCHAR(20)); INSERT INTO cultural_competency_trainings (training_id, state) VALUES (1, 'California'), (2, 'Texas'), (3, 'California'), (4, 'New York'), (5, 'Florida'), (6, 'Florida'); CREATE TABLE community_health_workers (worker_id INT, state VARCHAR(... | How many cultural competency trainings are in each state? | SELECT a.state, COUNT(*) FROM cultural_competency_trainings a JOIN community_health_workers b ON a.state = b.state GROUP BY a.state | gretelai_synthetic_text_to_sql |
CREATE TABLE brands (brand_id INT, brand_name TEXT); CREATE TABLE cruelty_free_certifications (certification_id INT, brand_id INT, certification_date DATE); | How many cruelty-free certifications were granted to each brand in the past 2 years? | SELECT brand_name, COUNT(*) as certifications_in_past_2_years FROM brands JOIN cruelty_free_certifications ON brands.brand_id = cruelty_free_certifications.brand_id WHERE certification_date > DATEADD(year, -2, CURRENT_DATE) GROUP BY brand_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE CreativeAIs (id INT, name VARCHAR(50), safety_score INT, region VARCHAR(50)); INSERT INTO CreativeAIs (id, name, safety_score, region) VALUES (1, 'AI Painter', 85, 'North America'); INSERT INTO CreativeAIs (id, name, safety_score, region) VALUES (2, 'AI Music Composer', 90, 'Europe'); INSERT INTO CreativeA... | List all creative AI applications that have a safety score above 85, ordered by region | SELECT name FROM CreativeAIs WHERE safety_score > 85 ORDER BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE user_action_hist (user_id INT, user_country VARCHAR(50), ad_clicks INT); | What is the total number of users in the United States who have never clicked on any ads? | SELECT COUNT(user_id) FROM user_action_hist WHERE user_country = 'United States' AND ad_clicks = 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE monthly_water_usage (month INT, usage INT); INSERT INTO monthly_water_usage (month, usage) VALUES (1, 1000), (2, 1500), (3, 1200), (4, 1800), (5, 2000), (6, 2500), (7, 1500), (8, 1200), (9, 1000), (10, 1400), (11, 1800), (12, 2000); | What is the total water usage in the first half of the year compared to the second half? | SELECT SUM(CASE WHEN month <= 6 THEN usage ELSE 0 END) as first_half, SUM(CASE WHEN month > 6 THEN usage ELSE 0 END) as second_half FROM monthly_water_usage; | gretelai_synthetic_text_to_sql |
CREATE TABLE artist_albums (artist_id INT, platform VARCHAR(50), album_count INT); INSERT INTO artist_albums (artist_id, platform, album_count) VALUES (1, 'Pandora', 5), (2, 'Pandora', 6); | _Get the names of the top 3 artists with the highest total number of streams on Pandora, from the Hip Hop genre, who have released at least 5 albums._ | SELECT a.name FROM artists a JOIN artist_albums al ON a.id = al.artist_id WHERE a.genre = 'Hip Hop' AND al.platform = 'Pandora' AND a.album_count >= 5 GROUP BY a.name ORDER BY SUM(s.stream_count) DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Programs (ProgramID INT, ProgramName VARCHAR(50)); CREATE TABLE Donations (DonorID INT, ProgramID INT, Amount DECIMAL(10, 2)); INSERT INTO Programs (ProgramID, ProgramName) VALUES (1, 'Youth Mentoring'), (2, 'Food Bank'), (3, 'Climate Action'); INSERT INTO Donations (DonorID, ProgramID, Amount) VALUES (1, ... | Which programs have the highest average donation in the 'Programs' and 'Donations' tables? | SELECT Programs.ProgramName, AVG(Donations.Amount) as AverageDonation FROM Programs INNER JOIN Donations ON Programs.ProgramID = Donations.ProgramID GROUP BY Programs.ProgramID ORDER BY AverageDonation DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE CaseBilling (CaseID int, OpenDate date, BillingAmount decimal(10,2)); INSERT INTO CaseBilling (CaseID, OpenDate, BillingAmount) VALUES (1, '2020-01-01', 1000.00), (2, '2020-02-15', 2000.00), (3, '2020-03-05', 3000.00); | What is the total billing amount per case, ordered by case open date? | SELECT CaseID, OpenDate, BillingAmount, ROW_NUMBER() OVER (ORDER BY OpenDate) AS RowNum, SUM(BillingAmount) OVER (ORDER BY OpenDate) AS RunningTotal FROM CaseBilling; | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, name TEXT, founder_gender TEXT, founded_date DATE); INSERT INTO companies (id, name, founder_gender, founded_date) VALUES (1, 'GreenTech', 'Female', '2017-01-01'); | Count the number of female and male founders in companies founded in 2016 or later, and list their names and founding dates. | SELECT companies.name, companies.founded_date, COUNT(*) filter (where companies.founder_gender = 'Female') as num_female_founders, COUNT(*) filter (where companies.founder_gender = 'Male') as num_male_founders FROM companies WHERE companies.founded_date >= '2016-01-01' GROUP BY companies.name, companies.founded_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE hospitals (hospital_name VARCHAR(50), state VARCHAR(50), num_beds INTEGER, offers_maternity BOOLEAN); INSERT INTO hospitals (hospital_name, state, num_beds, offers_maternity) VALUES ('Hospital A', 'California', 250, TRUE), ('Hospital B', 'California', 150, FALSE), ('Hospital C', 'Texas', 300, TRUE), ('Hosp... | Calculate the minimum and maximum number of hospital beds for hospitals that offer maternity services, in each state. | SELECT state, MIN(num_beds) as min_beds, MAX(num_beds) as max_beds FROM hospitals WHERE offers_maternity = TRUE GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE producers (id INT, name VARCHAR(255), city VARCHAR(255), state VARCHAR(255)); INSERT INTO producers (id, name, city, state) VALUES (1, 'Producer A', 'Portland', 'OR'); CREATE TABLE production (id INT, producer_id INT, quantity INT); | Calculate total cannabis production (in pounds) for each producer in Oregon, grouped by city. | SELECT p.city, SUM(pr.quantity) as total_production FROM producers p INNER JOIN production pr ON p.id = pr.producer_id WHERE p.state = 'OR' GROUP BY p.city; | gretelai_synthetic_text_to_sql |
CREATE TABLE Attorneys (attorney_id INT, name TEXT, region TEXT, join_date DATE); INSERT INTO Attorneys (attorney_id, name, region, join_date) VALUES (1, 'John Doe', 'New York', '2015-01-01'), (2, 'Jane Smith', 'California', '2018-05-01'), (3, 'Mike Johnson', 'Texas', '2016-03-15'); CREATE TABLE Cases (case_id INT, att... | What is the average billing amount for cases handled by attorneys from the 'Texas' region who have been with the firm for more than 5 years? | SELECT AVG(Cases.billing_amount) FROM Cases INNER JOIN Attorneys ON Cases.attorney_id = Attorneys.attorney_id WHERE Attorneys.region = 'Texas' AND Attorneys.join_date <= '2016-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE equipment_maintenance (id INT, incident_number VARCHAR(255), equipment_type VARCHAR(255), state VARCHAR(255), cost DECIMAL(10,2)); | What is the average cost of military equipment maintenance per incident for each type of equipment in the last year? | SELECT equipment_type, AVG(cost) FROM equipment_maintenance WHERE date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) GROUP BY equipment_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE investor (investor_id INT, name VARCHAR(255), country VARCHAR(255)); INSERT INTO investor (investor_id, name, country) VALUES (1, 'Acme Corp', 'United States'); CREATE TABLE investment (investment_id INT, investor_id INT, strategy VARCHAR(255), impact_score FLOAT); | Delete all impact investments with an impact score lower than 70.0. | DELETE FROM investment WHERE impact_score < 70.0; | gretelai_synthetic_text_to_sql |
CREATE TABLE clients (id INT, name TEXT, region TEXT); INSERT INTO clients (id, name, region) VALUES (1, 'Alice', 'austin'), (2, 'Bob', 'austin'), (3, 'Charlie', 'austin'); | What is the count of clients in the 'austin' region? | SELECT COUNT(*) FROM clients WHERE region = 'austin'; | gretelai_synthetic_text_to_sql |
CREATE TABLE regulations (id INT, proposal TEXT, comments INT); INSERT INTO regulations (id, proposal, comments) VALUES (1, 'Regulation A', 50); INSERT INTO regulations (id, proposal, comments) VALUES (2, 'Regulation B', 100); | What is the total number of proposed regulations for the Transportation sector? | SELECT COUNT(*) FROM regulations WHERE proposal LIKE '%Transportation%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE middle_east_region_table (id INT, mission_name VARCHAR(100), country VARCHAR(50), num_troops INT); INSERT INTO middle_east_region_table (id, mission_name, country, num_troops) VALUES (1, 'Operation Inherit Resolve', 'Jordan', 3000); | What is the maximum number of troops deployed for a peacekeeping mission in 'middle_east_region_table'? | SELECT MAX(num_troops) FROM middle_east_region_table; | gretelai_synthetic_text_to_sql |
CREATE TABLE ports (port_id INT, port_name VARCHAR(50), avg_cargo_time INT); INSERT INTO ports (port_id, port_name, avg_cargo_time) VALUES (1, 'Port of Long Beach', 60), (2, 'Port of Los Angeles', 55), (3, 'Port of Oakland', 50); | What is the average cargo handling time in minutes for each port in the 'ports' table? | SELECT port_name, avg(avg_cargo_time) FROM ports GROUP BY port_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE events (id INT PRIMARY KEY, name VARCHAR(255), date DATE, location VARCHAR(255)); INSERT INTO events (id, name, date, location) VALUES (1, 'Community Meeting', '2023-03-22', 'City Hall'); | Update the location of the event with id 1 | UPDATE events SET location = 'Park' WHERE id = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE ProgramCategories (CategoryID INT, Category VARCHAR(20)); INSERT INTO ProgramCategories (CategoryID, Category) VALUES (1, 'Education'), (2, 'Health'), (3, 'Environment'); CREATE TABLE Programs (ProgramID INT, CategoryID INT, ProgramName VARCHAR(50)); INSERT INTO Programs (ProgramID, CategoryID, ProgramName... | What's the average donation amount for each program category? | SELECT pc.Category, AVG(d.DonationAmount) AS AverageDonationAmount FROM ProgramCategories pc JOIN Programs p ON pc.CategoryID = p.CategoryID JOIN Donations d ON p.ProgramID = d.ProgramID GROUP BY pc.Category; | gretelai_synthetic_text_to_sql |
CREATE TABLE biotech_funding (id INT PRIMARY KEY, startup_name VARCHAR(100), funding_round VARCHAR(50), funding_amount INT); | Delete the 'biotech_funding' record with 'id' = 7 | DELETE FROM biotech_funding WHERE id = 7; | gretelai_synthetic_text_to_sql |
CREATE TABLE security_incidents (id INT, department VARCHAR(255), resolution_time INT, timestamp DATETIME); | What is the minimum time to resolve a security incident for each department in the last year? | SELECT department, MIN(resolution_time) as min_resolution_time FROM security_incidents WHERE timestamp >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR) GROUP BY department; | gretelai_synthetic_text_to_sql |
CREATE TABLE if not exists 'disease_data' (id INT, state TEXT, disease TEXT, prevalence INT, PRIMARY KEY(id)); | Remove records where prevalence > 1000 from 'disease_data' | DELETE FROM 'disease_data' WHERE prevalence > 1000; | gretelai_synthetic_text_to_sql |
CREATE TABLE train_routes (id INT, route_name VARCHAR(255), is_accessible BOOLEAN, fare DECIMAL(5,2)); INSERT INTO train_routes (id, route_name, is_accessible, fare) VALUES (1, 'Red Line', TRUE, 2.50), (2, 'Blue Line', FALSE, 3.00), (3, 'Green Line', TRUE, 1.75); | Find all wheelchair-accessible train routes and their respective fare prices. | SELECT route_name, fare FROM train_routes WHERE is_accessible = TRUE | gretelai_synthetic_text_to_sql |
CREATE TABLE customer_complaints (complaint_id INT, complaint_date DATE, plan_id INT, complaint_description VARCHAR(50)); | How many customer complaints were there in total for each mobile plan in the past month? | SELECT plan_id, COUNT(complaint_id) as total_complaints FROM customer_complaints WHERE MONTH(complaint_date) = MONTH(current_date) - 1 GROUP BY plan_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE Projects (id INT, name TEXT, region TEXT, cost FLOAT); INSERT INTO Projects (id, name, region, cost) VALUES (1, 'ProjectA', 'Caribbean', 1500000.00), (2, 'ProjectB', 'Caribbean', 1200500.75), (3, 'ProjectC', 'Caribbean', 1700000.50); | Which public works project in 'Caribbean' region has the lowest construction cost? | SELECT name, MIN(cost) FROM Projects WHERE region = 'Caribbean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotel_reviews_3 (hotel_id INT, guest_rating INT, review_date DATE, review_text TEXT, city TEXT); INSERT INTO hotel_reviews_3 (hotel_id, guest_rating, review_date, review_text, city) VALUES (5, 8, '2021-09-03', 'Wonderful stay', 'Paris'), (6, 9, '2021-09-05', 'Excellent experience', 'Paris'); | What is the average local employment for hotels in Paris? | SELECT AVG(ei.local_employment) FROM economic_impact ei INNER JOIN hotel_reviews_3 hr ON ei.hotel_id = hr.hotel_id WHERE hr.city = 'Paris'; | gretelai_synthetic_text_to_sql |
CREATE TABLE military_tech_cost (id INT, tech VARCHAR, cost INT); INSERT INTO military_tech_cost (id, tech, cost) VALUES (1, 'Stealth Helicopter', 20000000), (2, 'AI-Powered Drone', 15000000), (3, 'Electric Tank', 10000000); | Display the military technologies and their development costs, and calculate the total development cost. | SELECT tech, cost, SUM(cost) OVER () as total_cost FROM military_tech_cost; | gretelai_synthetic_text_to_sql |
CREATE TABLE curators (id INT, name TEXT); CREATE TABLE exhibitions (id INT, title TEXT, cancelled BOOLEAN, curator_id INT); INSERT INTO curators (id, name) VALUES (1, 'John Doe'), (2, 'Jane Smith'); INSERT INTO exhibitions (id, title, cancelled, curator_id) VALUES (1, 'Expressionism', false, 1), (2, 'Cubism', true, 1)... | How many exhibitions have been curated by John Doe, including cancelled ones? | SELECT COUNT(*) FROM exhibitions e INNER JOIN curators c ON e.curator_id = c.id WHERE c.name = 'John Doe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE oceanographic_research_stations (id INT, station_name VARCHAR(50), region VARCHAR(20), min_depth INT, max_depth INT, year_established INT, year_decommissioned INT);INSERT INTO oceanographic_research_stations (id, station_name, region, min_depth, max_depth, year_established, year_decommissioned) VALUES (1, ... | List all the oceanographic research stations that have been established in the Indian Ocean and are still active. | SELECT station_name FROM oceanographic_research_stations WHERE region = 'Indian' AND year_decommissioned IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE emergency_response (incident_type VARCHAR(255), response_time INT); | Insert a new record into the emergency_response table for the 'Rescue' incident type and a response_time of 8 minutes | INSERT INTO emergency_response (incident_type, response_time) VALUES ('Rescue', 8); | gretelai_synthetic_text_to_sql |
CREATE TABLE TraditionalArtsEvents (id INT, city VARCHAR(50), country VARCHAR(50), event_name VARCHAR(100), event_date DATE); INSERT INTO TraditionalArtsEvents (id, city, country, event_name, event_date) VALUES (1, 'Kyoto', 'Japan', 'Kabuki', '2023-04-01'), (2, 'Kyoto', 'Japan', 'Ikebana', '2023-05-15'); | What traditional arts events are planned for Kyoto in the next 6 months? | SELECT event_name FROM TraditionalArtsEvents WHERE city = 'Kyoto' AND event_date BETWEEN CURDATE() AND DATE_ADD(CURDATE(), INTERVAL 6 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE volunteers (id INT, name TEXT, country TEXT, hours_served INT); | List the top 3 countries with the highest number of volunteer hours in Q1 of 2022. | SELECT country, SUM(hours_served) as total_hours FROM volunteers WHERE QUARTER(volunteer_date) = 1 AND YEAR(volunteer_date) = 2022 GROUP BY country ORDER BY total_hours DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (id INT, first_name VARCHAR(50), last_name VARCHAR(50), training_completion_date DATE, accessibility_training_completion_date DATE); | List the employees who have not completed training related to accessibility | SELECT id, first_name, last_name FROM Employees WHERE accessibility_training_completion_date IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE system_status (system_id INT PRIMARY KEY, status_date DATE, is_online BOOLEAN); INSERT INTO system_status (system_id, status_date, is_online) VALUES (1, '2022-04-01', TRUE), (2, '2022-04-10', FALSE), (3, '2022-04-20', FALSE); | Which systems have been offline for more than 10 days? | SELECT system_id, status_date FROM system_status WHERE is_online = FALSE AND status_date < DATE_SUB(CURRENT_DATE, INTERVAL 10 DAY); | gretelai_synthetic_text_to_sql |
CREATE TABLE broadband_subscribers (subscriber_id INT, state VARCHAR(20)); INSERT INTO broadband_subscribers (subscriber_id, state) VALUES (1, 'New York'), (2, 'Texas'), (3, 'New York'); | How many broadband subscribers are there in the state of New York? | SELECT COUNT(*) FROM broadband_subscribers WHERE state = 'New York'; | gretelai_synthetic_text_to_sql |
CREATE TABLE crops_country (id INT, name VARCHAR(50), country VARCHAR(50), year INT, production INT); INSERT INTO crops_country (id, name, country, year, production) VALUES (1, 'Rice', 'India', 2020, 8000), (2, 'Wheat', 'Pakistan', 2020, 6000), (3, 'Corn', 'Mexico', 2020, 4000), (4, 'Potatoes', 'Peru', 2020, 3000), (5,... | What is the production of crops by country in a given year? | SELECT country, name, SUM(production) as total_production FROM crops_country GROUP BY country, name; | gretelai_synthetic_text_to_sql |
CREATE TABLE europium_production (country VARCHAR(20), quantity INT); INSERT INTO europium_production (country, quantity) VALUES ('China', 1200), ('USA', 450), ('Australia', 180), ('Russia', 600); | List all the distinct europium production quantities and countries. | SELECT DISTINCT country, quantity FROM europium_production; | gretelai_synthetic_text_to_sql |
CREATE TABLE centers (center_id INT, center_name TEXT, community TEXT, population INT, year INT); INSERT INTO centers (center_id, center_name, community, population, year) VALUES (1, 'Health A', 'Riverview', 3000, 2018), (2, 'Health B', 'Riverview', 3500, 2019), (3, 'Health C', 'Seaside', 2500, 2018); | What is the population trend for each community health center? | SELECT community, year, population, LAG(population, 1) OVER (PARTITION BY community ORDER BY year) AS previous_year_population FROM centers ORDER BY community, year; | gretelai_synthetic_text_to_sql |
CREATE TABLE ProductionTargets (WellID int, ProductionDate date, TargetBarrelsPerDay decimal(5, 2)); INSERT INTO ProductionTargets (WellID, ProductionDate, TargetBarrelsPerDay) VALUES (501, '2022-01-01', 1000), (502, '2022-01-01', 1200), (501, '2022-01-02', 1100); | Increase the production target for Well ID 501 by 10% in the ProductionTargets table. | UPDATE ProductionTargets SET TargetBarrelsPerDay = 1000 * 1.10 WHERE WellID = 501; | gretelai_synthetic_text_to_sql |
CREATE TABLE african_tourists (id INT, country VARCHAR(20), continent VARCHAR(20), year INT, visitors INT); INSERT INTO african_tourists (id, country, continent, year, visitors) VALUES (1, 'Egypt', 'Africa', 2019, 1500000), (2, 'South Africa', 'Africa', 2019, 2000000), (3, 'Morocco', 'Africa', 2019, 1000000); | What is the total number of tourists who visited the African continent in 2019? | SELECT SUM(visitors) as total_visitors FROM african_tourists WHERE continent = 'Africa' AND year = 2019; | gretelai_synthetic_text_to_sql |
CREATE TABLE students (student_id INT, gender_identity VARCHAR(255), hours_spent_on_open_pedagogy_programs INT); INSERT INTO students (student_id, gender_identity, hours_spent_on_open_pedagogy_programs) VALUES (1, 'Transgender', 80), (2, 'Genderqueer', 70), (3, 'Non-binary', 90); | What is the maximum number of hours spent on open pedagogy programs by students who identify as LGBTQ+, broken down by their gender identity? | SELECT gender_identity, MAX(hours_spent_on_open_pedagogy_programs) as max_hours FROM students WHERE gender_identity LIKE '%LGBTQ%' GROUP BY gender_identity; | gretelai_synthetic_text_to_sql |
CREATE TABLE climate_adaptation_projects (year INT, region VARCHAR(255), project VARCHAR(255)); INSERT INTO climate_adaptation_projects (year, region, project) VALUES (2018, 'Asia', 'Sea Wall A'), (2019, 'Africa', 'Drought Resistant Crops B'), (2019, 'Asia', 'Flood Early Warning C'); | How many climate adaptation projects were completed in 2018 and 2019, grouped by region? | SELECT region, COUNT(*) as project_count FROM climate_adaptation_projects WHERE year IN (2018, 2019) GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE skincare_products (id INT, brand VARCHAR(255), product_category VARCHAR(255), contains_fragrance BOOLEAN, is_natural BOOLEAN); | What is the percentage of skincare products that contain fragrance, grouped by brand and categorized as natural or synthetic? | SELECT brand, 100.0 * AVG(CASE WHEN contains_fragrance THEN 1 ELSE 0 END) as percentage, product_category FROM skincare_products GROUP BY brand, product_category; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotel_info_2 (hotel_id INT, city TEXT); INSERT INTO hotel_info_2 (hotel_id, city) VALUES (7, 'Kyoto'), (8, 'Osaka'); | What is the total number of virtual tour views for hotels in Kyoto? | SELECT SUM(vt.num_views) FROM virtual_tours vt INNER JOIN hotel_info_2 hi ON vt.hotel_id = hi.hotel_id WHERE hi.city = 'Kyoto'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Manufacturers (ManufacturerID int, ManufacturerName varchar(50), Region varchar(50)); INSERT INTO Manufacturers (ManufacturerID, ManufacturerName, Region) VALUES (1, 'EcoStitch', 'Southeast'); INSERT INTO Manufacturers (ManufacturerID, ManufacturerName, Region) VALUES (2, 'GreenThreads', 'Northeast'); CREA... | Which manufacturers in the Southeast region produce the most items made from recycled materials, ordered by the total quantity? | SELECT m.ManufacturerName, SUM(pm.Quantity) as TotalQuantity FROM Manufacturers m INNER JOIN ProductManufacturers pm ON m.ManufacturerID = pm.ManufacturerID INNER JOIN Products p ON pm.ProductID = p.ProductID WHERE m.Region = 'Southeast' AND p.RecycledMaterials = true GROUP BY m.ManufacturerName ORDER BY TotalQuantity ... | gretelai_synthetic_text_to_sql |
CREATE TABLE Restaurants (restaurant_id INT, city VARCHAR(50), revenue INT); INSERT INTO Restaurants (restaurant_id, city, revenue) VALUES (1, 'New York', 5000), (2, 'Los Angeles', 6000), (3, 'New York', 7000); | What is the total revenue for each city? | SELECT city, SUM(revenue) as total_revenue FROM Restaurants GROUP BY city; | gretelai_synthetic_text_to_sql |
CREATE TABLE restaurant_data (id INT, restaurant_name VARCHAR(255), revenue INT, number_of_inspections INT); INSERT INTO restaurant_data (id, restaurant_name, revenue, number_of_inspections) VALUES (1, 'Bella Italia', 25000, 4); INSERT INTO restaurant_data (id, restaurant_name, revenue, number_of_inspections) VALUES (2... | Find the average revenue of restaurants with more than 3 inspections | SELECT restaurant_name, AVG(revenue) FROM restaurant_data WHERE number_of_inspections > 3 GROUP BY restaurant_name; | gretelai_synthetic_text_to_sql |
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