context stringlengths 11 9.12k | question stringlengths 0 1.06k | SQL stringlengths 2 4.44k | source stringclasses 28
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CREATE TABLE album (id INT PRIMARY KEY, title VARCHAR(255), year INT, revenue INT); INSERT INTO album (id, title, year, revenue) VALUES (1, 'AlbumA', 2000, 5000000), (2, 'AlbumB', 2000, 7000000), (3, 'AlbumC', 2001, 6000000); | What's the total revenue of music albums released in 2000? | SELECT SUM(revenue) FROM album WHERE year = 2000; | gretelai_synthetic_text_to_sql |
CREATE TABLE containers (id INT, name TEXT, width INT, height INT, length INT); INSERT INTO containers (id, name, width, height, length) VALUES (1, 'Container 1', 10, 20, 30); INSERT INTO containers (id, name, width, height, length) VALUES (2, 'Container 2', 8, 15, 25); INSERT INTO containers (id, name, width, height, ... | Delete all records of containers with invalid measurements. | DELETE FROM containers WHERE width < 8 OR height < 8 OR length < 8; | gretelai_synthetic_text_to_sql |
CREATE TABLE articles (id INT, title VARCHAR(100), word_count INT, publication_date DATE, category VARCHAR(50)); | What is the average word count of articles published in the "articles" table in 2021? | SELECT AVG(word_count) FROM articles WHERE YEAR(publication_date) = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE wells (well_id INT, field VARCHAR(50), region VARCHAR(50), drill_year INT, production_oil FLOAT, production_gas FLOAT); INSERT INTO wells (well_id, field, region, drill_year, production_oil, production_gas) VALUES (1, 'Vankor', 'Siberia', 2018, 18000.0, 6000.0), (2, 'Severo-Kurilsk', 'Siberia', 2019, 12000... | How many wells were drilled in 'Siberia' between 2017 and 2020? | SELECT COUNT(*) FROM wells WHERE region = 'Siberia' AND drill_year BETWEEN 2017 AND 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE italy_heritage_sites (site_id INT, name TEXT, location TEXT, country TEXT, annual_revenue INT); INSERT INTO italy_heritage_sites (site_id, name, location, country, annual_revenue) VALUES (1, 'Colosseum', 'Rome', 'Italy', 4000000); | Which cultural heritage sites in Rome have annual revenues over 3 million? | SELECT name, annual_revenue FROM italy_heritage_sites WHERE location = 'Rome' AND annual_revenue > 3000000; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (id INT, name TEXT, country TEXT); INSERT INTO donors (id, name, country) VALUES (1, 'John Doe', 'USA'), (2, 'Jane Smith', 'Canada'); CREATE TABLE donations (id INT, donor_id INT, amount DECIMAL(10,2)); INSERT INTO donations (id, donor_id, amount) VALUES (1, 1, 500.00), (2, 1, 250.00), (3, 2, 100.00... | What is the total donation amount by each donor in the US? | SELECT d.name, SUM(donations.amount) as total_donation FROM donors d INNER JOIN donations ON d.id = donations.donor_id WHERE d.country = 'USA' GROUP BY d.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, country VARCHAR(255)); INSERT INTO users (id, country) VALUES (1, 'India'), (2, 'Pakistan'); CREATE TABLE posts (id INT, user_id INT, post_date DATE); INSERT INTO posts (id, user_id, post_date) VALUES (1, 1, '2022-01-01'), (2, 1, '2022-01-02'), (3, 2, '2022-01-01'); | What is the average number of posts per day for users from India? | SELECT AVG(posts_per_day) FROM (SELECT user_id, COUNT(*) AS posts_per_day FROM posts WHERE post_date BETWEEN '2022-01-01' AND LAST_DAY('2022-01-01') GROUP BY user_id) AS user_posts JOIN users ON users.id = user_posts.user_id WHERE users.country = 'India'; | gretelai_synthetic_text_to_sql |
CREATE TABLE geopolitical_risk_assessments (id INT, region VARCHAR(255), assessment VARCHAR(255)); INSERT INTO geopolitical_risk_assessments (id, region, assessment) VALUES (1, 'Africa', 'High'), (2, 'Europe', 'Medium'), (3, 'Americas', 'Low'), (4, 'Middle East', 'High'); | What is the geopolitical risk assessment for the Middle East? | SELECT assessment FROM geopolitical_risk_assessments WHERE region = 'Middle East'; | gretelai_synthetic_text_to_sql |
CREATE TABLE wind_farms (country VARCHAR(50), operational BOOLEAN, year INT); INSERT INTO wind_farms (country, operational, year) VALUES ('Canada', true, 2020), ('Brazil', true, 2020), ('Argentina', true, 2020), ('Mexico', false, 2020); | List the number of wind farms in Canada, Brazil, and Argentina, as of 2020. | SELECT country, COUNT(*) FROM wind_farms WHERE country IN ('Canada', 'Brazil', 'Argentina') AND operational = true GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE MammalSightings (ID INT, SightingDate DATE, Species VARCHAR(100), Reserve VARCHAR(100), Observations INT); INSERT INTO MammalSightings (ID, SightingDate, Species, Reserve, Observations) VALUES (1, '2022-05-01', 'Polar Bear', 'Nunavut Wildlife Reserve', 10); INSERT INTO MammalSightings (ID, SightingDate, Sp... | How many sightings of each mammal species were recorded in the last month across all Arctic reserves? | SELECT Species, Reserve, COUNT(Observations) OVER (PARTITION BY Species, Reserve ORDER BY Species, Reserve ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS SightingsCount FROM MammalSightings WHERE SightingDate >= DATEADD(month, -1, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE if not exists employment (id INT, industry VARCHAR, number_of_employees INT); INSERT INTO employment (id, industry, number_of_employees) VALUES (1, 'manufacturing', 5000), (2, 'technology', 8000), (3, 'healthcare', 7000); | What is the total number of employees in all industries? | SELECT SUM(number_of_employees) FROM employment; | gretelai_synthetic_text_to_sql |
CREATE TABLE Water_Usage (id INT, year INT, water_consumption FLOAT); INSERT INTO Water_Usage (id, year, water_consumption) VALUES (1, 2018, 12000.0), (2, 2019, 13000.0), (3, 2020, 14000.0), (4, 2021, 15000.0); | Update the water consumption value in the Water_Usage table for the year 2019 to 12800, if the consumption for that year is higher than the average consumption for the years 2018-2020. | UPDATE Water_Usage SET water_consumption = 12800 WHERE year = 2019 AND water_consumption = (SELECT AVG(water_consumption) FROM Water_Usage WHERE year BETWEEN 2018 AND 2020); | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (id INT, donor_id INT, amount DECIMAL(10,2), donation_date DATE); INSERT INTO donations (id, donor_id, amount, donation_date) VALUES (1, 101, 500.00, '2021-01-01'), (2, 102, 300.00, '2021-02-15'), (3, 101, 600.00, '2022-04-01'); | What is the total amount donated by each donor who has made a donation in both the last and current quarters? | SELECT donor_id, SUM(amount) FROM donations WHERE donation_date BETWEEN DATE_SUB(CURDATE(), INTERVAL 6 MONTH) AND DATE_SUB(CURDATE(), INTERVAL 3 MONTH) GROUP BY donor_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE teams (team_id INT, team_name VARCHAR(50), conference VARCHAR(50)); INSERT INTO teams (team_id, team_name, conference) VALUES (1, 'Atlanta Hawks', 'Eastern'), (2, 'Boston Celtics', 'Eastern'); CREATE TABLE players (player_id INT, player_name VARCHAR(50), team_id INT, age INT); | What is the average age of basketball players in the Eastern Conference by team? | SELECT t.conference, t.team_name, AVG(p.age) as avg_age FROM players p JOIN teams t ON p.team_id = t.team_id WHERE t.conference = 'Eastern' GROUP BY t.conference, t.team_name; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA publications;CREATE TABLE student_publications(student_name TEXT,department TEXT,num_publications INTEGER);INSERT INTO student_publications(student_name,department,num_publications)VALUES('Rajesh','Chemistry',4),('Sarah','Chemistry',3),('Tariq','Physics',0); | What is the average number of publications for graduate students in the Chemistry department? | SELECT department,AVG(num_publications) FROM publications.student_publications WHERE department='Chemistry' GROUP BY department; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA oceans;CREATE TABLE oceans.marine_life_data (id INT PRIMARY KEY, species VARCHAR(50)); INSERT INTO oceans.marine_life_data (id, species) VALUES (1, 'Tuna'), (2, 'Salmon'); | Provide the total number of marine life research data records by species. | SELECT context.species, COUNT(context.species) FROM oceans.marine_life_data AS context GROUP BY context.species; | gretelai_synthetic_text_to_sql |
CREATE TABLE Departments (DepartmentID int, DepartmentName varchar(255)); CREATE TABLE Faculty (FacultyID int, FacultyName varchar(255), DepartmentID int, Gender varchar(10)); | What is the number of female and male faculty members in each department, ordered by the department name? | SELECT DepartmentName, Gender, COUNT(*) as NumFaculty FROM Faculty f JOIN Departments d ON f.DepartmentID = d.DepartmentID GROUP BY DepartmentName, Gender ORDER BY DepartmentName; | gretelai_synthetic_text_to_sql |
CREATE TABLE account (account_id INT, client_id INT, region VARCHAR(50), account_type VARCHAR(50), open_date DATE); INSERT INTO account (account_id, client_id, region, account_type, open_date) VALUES (1, 1, 'Middle East', 'Shariah-compliant', '2022-01-01'), (2, 2, 'Asia', 'Shariah-compliant', '2022-02-01'); | What is the number of Shariah-compliant accounts opened by clients in the last month, partitioned by region? | SELECT region, COUNT(*) FROM account WHERE account_type = 'Shariah-compliant' AND open_date >= DATEADD(month, -1, GETDATE()) GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE Museums (id INT PRIMARY KEY, name VARCHAR(100), location VARCHAR(100), country VARCHAR(50)); INSERT INTO Museums (id, name, location, country) VALUES (1, 'Metropolitan Museum of Art', 'New York', 'USA'); CREATE TABLE Artworks (id INT PRIMARY KEY, title VARCHAR(100), year INT, museum_id INT, FOREIGN KEY (mu... | What is the oldest artwork in each museum's collection? | SELECT m.name, MIN(a.year) FROM Artworks a JOIN Museums m ON a.museum_id = m.id GROUP BY m.id; | gretelai_synthetic_text_to_sql |
CREATE TABLE SeaIceExtent (sea VARCHAR(255), date DATE, extent FLOAT); INSERT INTO SeaIceExtent (sea, date, extent) VALUES ('Barents Sea', '2022-01-01', 1.2); INSERT INTO SeaIceExtent (sea, date, extent) VALUES ('Barents Sea', '2022-02-01', 1.5); | What is the maximum sea ice extent in the Barents Sea during the winter months of 2022? | SELECT MAX(extent) FROM SeaIceExtent WHERE sea = 'Barents Sea' AND date BETWEEN '2022-01-01' AND '2022-12-31' AND MONTH(date) BETWEEN 12 AND 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE attorneys (id INT, name TEXT, gender TEXT, city TEXT); INSERT INTO attorneys (id, name, gender, city) VALUES (1, 'Alicia Florrick', 'Female', 'Chicago'); CREATE TABLE cases (id INT, attorney_id INT, result TEXT); INSERT INTO cases (id, attorney_id, result) VALUES (1, 1, 'dropped'); | Find the number of cases handled by female attorneys in Chicago. | SELECT COUNT(*) FROM cases INNER JOIN attorneys ON cases.attorney_id = attorneys.id WHERE attorneys.city = 'Chicago' AND attorneys.gender = 'Female'; | gretelai_synthetic_text_to_sql |
CREATE TABLE nonprofits (id INT, name VARCHAR(255), focus VARCHAR(255), state VARCHAR(2)); INSERT INTO nonprofits (id, name, focus, state) VALUES (1, 'ACLU', 'Social Justice', 'NY'), (2, 'Planned Parenthood', 'Healthcare', 'CA'), (3, 'Greenpeace', 'Environment', 'CA'); | List all nonprofits with a focus on social justice in New York. | SELECT name FROM nonprofits WHERE focus = 'Social Justice' AND state = 'NY'; | gretelai_synthetic_text_to_sql |
CREATE TABLE recycling (factory_id INT, water_recycling BOOLEAN); INSERT INTO recycling (factory_id, water_recycling) VALUES (1, TRUE), (2, FALSE), (3, TRUE), (4, TRUE), (5, FALSE); | What percentage of factories have a water recycling system? | SELECT (COUNT(*) * 100.0 / (SELECT COUNT(*) FROM recycling)) as percentage FROM recycling WHERE water_recycling = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE MobileSubscribers (SubscriberID int, Country varchar(10)); CREATE TABLE BroadbandSubscribers (SubscriberID int, Country varchar(10)); INSERT INTO MobileSubscribers (SubscriberID, Country) VALUES (1, 'USA'), (2, 'Canada'), (3, 'Mexico'), (4, 'Brazil'); INSERT INTO BroadbandSubscribers (SubscriberID, Country... | Identify the number of mobile and broadband subscribers per country, and their respective percentage contributions to total subscribers. | SELECT C.Country, COUNT(M.SubscriberID) AS MobileCount, COUNT(B.SubscriberID) AS BroadbandCount, (COUNT(M.SubscriberID)::float / (COUNT(M.SubscriberID) + COUNT(B.SubscriberID))) * 100 AS MobilePercent, (COUNT(B.SubscriberID)::float / (COUNT(M.SubscriberID) + COUNT(B.SubscriberID))) * 100 AS BroadbandPercent FROM Mobile... | gretelai_synthetic_text_to_sql |
CREATE TABLE programs (id INT, name TEXT); INSERT INTO programs (id, name) VALUES (1, 'Feeding the Hungry'), (2, 'Tutoring Kids'), (3, 'Cleaning the Environment'), (4, 'Medical Aid'); CREATE TABLE donations (id INT, program_id INT, amount DECIMAL(10, 2)); | Insert a new program 'Elderly Care' with ID 5 and add corresponding donation records. | INSERT INTO programs (id, name) VALUES (5, 'Elderly Care'); INSERT INTO donations (id, program_id, amount) VALUES (1, 5, 250.00), (2, 5, 500.00); | gretelai_synthetic_text_to_sql |
CREATE TABLE job_applications (id INT, applicant_name VARCHAR(255), application_date DATE, job_title VARCHAR(255), status VARCHAR(255)); INSERT INTO job_applications (id, applicant_name, application_date, job_title, status) VALUES (1, 'John Doe', '2021-01-15', 'Software Engineer', 'Hired'), (2, 'Jane Smith', '2021-02-2... | How many employees were hired each month in 2021? | SELECT DATE_FORMAT(application_date, '%Y-%m') as month, COUNT(*) as num_hired FROM job_applications WHERE YEAR(application_date) = 2021 AND status = 'Hired' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE customers (customer_id INT, name VARCHAR(50)); INSERT INTO customers VALUES (1, 'John Doe'), (2, 'Jane Smith'); CREATE TABLE transactions (transaction_id INT, customer_id INT, amount DECIMAL(10,2), transaction_date DATE); INSERT INTO transactions VALUES (1, 1, 150.50, '2020-01-01'), (2, 1, 200.00, '2020-02... | What is the total amount of transactions for each customer in the year 2020? | SELECT c.customer_id, c.name, SUM(t.amount) FROM customers c JOIN transactions t ON c.customer_id = t.customer_id WHERE YEAR(t.transaction_date) = 2020 GROUP BY c.customer_id, c.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE artist_demographics (id INT, name VARCHAR(50), country VARCHAR(50), age INT); INSERT INTO artist_demographics (id, name, country, age) VALUES (1, 'John Doe', 'Cuba', 45), (2, 'Jane Smith', 'Bahamas', 35), (3, 'Mike Johnson', 'Jamaica', 55); | What is the minimum age of artists in the Caribbean? | SELECT MIN(age) FROM artist_demographics WHERE country IN ('Cuba', 'Bahamas', 'Jamaica'); | gretelai_synthetic_text_to_sql |
CREATE TABLE artist_listeners (listener_id INT, artist_id INT, platform VARCHAR(255), listener_month DATE, listeners INT); CREATE VIEW monthly_listeners AS SELECT artist_id, platform, listener_month, SUM(listeners) as total_listeners FROM artist_listeners GROUP BY artist_id, platform, listener_month; | Which artists have the highest number of monthly listeners in the last 12 months, for each platform? | SELECT artist_id, platform, listener_month, total_listeners, ROW_NUMBER() OVER (PARTITION BY platform ORDER BY total_listeners DESC) as rank FROM monthly_listeners WHERE listener_month >= DATEADD(month, -12, CURRENT_DATE) ORDER BY platform, rank; | gretelai_synthetic_text_to_sql |
CREATE TABLE forests (id INT, forest VARCHAR(50), year INT, carbon_sequestration FLOAT); INSERT INTO forests (id, forest, year, carbon_sequestration) VALUES (1, 'Forest A', 2019, 12.5), (2, 'Forest A', 2020, 15.2), (3, 'Forest B', 2019, 10.0), (4, 'Forest B', 2020, 11.8), (5, 'Forest C', 2019, 15.0), (6, 'Forest C', 20... | Identify the top three forests with the highest average carbon sequestration per year. | SELECT forest, AVG(carbon_sequestration) AS avg_carbon_sequestration FROM forests GROUP BY forest ORDER BY avg_carbon_sequestration DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE sensor_data (sensor_id INT, system VARCHAR(20), status VARCHAR(10), report_date DATE); INSERT INTO sensor_data (sensor_id, system, status, report_date) VALUES (1, 'Precision Irrigation System', 'malfunction', '2021-08-01'), (2, 'Precision Irrigation System', 'working', '2021-08-02'), (3, 'Precision Irrigat... | Identify the number of IoT sensors that reported malfunctions in 'Precision Irrigation System' during the first week of August, 2021. | SELECT COUNT(*) FROM sensor_data WHERE system = 'Precision Irrigation System' AND status = 'malfunction' AND report_date BETWEEN '2021-08-01' AND '2021-08-07'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Auto_Shows (Show_Name VARCHAR(30), Year INT, Attendance INT); INSERT INTO Auto_Shows (Show_Name, Year, Attendance) VALUES ('Detroit Auto Show', 2021, 750000), ('Frankfurt Auto Show', 2021, 850000), ('Tokyo Auto Show', 2021, 900000), ('Paris Auto Show', 2021, 1000000), ('Los Angeles Auto Show', 2021, 600000... | Which auto show had the highest attendance in 2021? | SELECT Show_Name, Attendance FROM Auto_Shows WHERE Year = 2021 ORDER BY Attendance DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_usage(industry_id INT, industry VARCHAR(50), state VARCHAR(50), usage FLOAT, year INT); INSERT INTO water_usage(industry_id, industry, state, usage, year) VALUES (1, 'Agriculture', 'California', 12345.6, 2019), (2, 'Manufacturing', 'California', 4567.8, 2019); | List the top 5 water consuming industries and their total water usage in the state of California for 2019. | SELECT industry, SUM(usage) FROM water_usage WHERE state = 'California' AND year = 2019 GROUP BY industry ORDER BY SUM(usage) DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE municipalities (id INT PRIMARY KEY, name VARCHAR(255));CREATE TABLE complaints (id INT PRIMARY KEY, municipality_id INT, title VARCHAR(255)); | Identify the top 5 municipalities with the highest number of citizen complaints, including the number of complaints for each. | SELECT m.name, COUNT(c.id) AS num_complaints FROM municipalities m JOIN complaints c ON m.id = c.municipality_id GROUP BY m.name ORDER BY num_complaints DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA if not exists africa_schema_3;CREATE TABLE africa_schema_3.african_mines (id INT, name VARCHAR, location VARCHAR);INSERT INTO africa_schema_3.african_mines (id, name, location) VALUES (1, 'Ghana mining', 'Ghana'), (2, 'South Africa mining', 'South Africa'); | List all mining operations in 'african_mines' located in Ghana. | SELECT name FROM africa_schema_3.african_mines WHERE location = 'Ghana'; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA Government;CREATE TABLE Government.State (name VARCHAR(255), budget INT);CREATE TABLE Government.Park (name VARCHAR(255), state VARCHAR(255), area INT, budget INT); | What is the total budget allocated to public parks in each state with a park area greater than 500 acres? | SELECT state, SUM(budget) FROM Government.Park WHERE state IN (SELECT name FROM Government.State WHERE area > 500) GROUP BY state; | gretelai_synthetic_text_to_sql |
CREATE TABLE Sales (SaleID INT, ProductID INT, QuantitySold INT, SaleDate DATE, DispensaryID INT); | Insert new records of edibles sold in Oregon in June 2021 | INSERT INTO Sales (SaleID, ProductID, QuantitySold, SaleDate, DispensaryID) VALUES (1, 101, 15, '2021-06-01', 1001), (2, 102, 20, '2021-06-02', 1001), (3, 103, 10, '2021-06-03', 1001); | gretelai_synthetic_text_to_sql |
CREATE TABLE daily_visitors (date DATE, exhibition_id INT, visitors INT); INSERT INTO daily_visitors (date, exhibition_id, visitors) VALUES ('2022-01-01', 5, 200), ('2022-01-02', 5, 250), ('2022-01-03', 6, 300); | What is the average number of visitors per day for the "Ancient Civilizations" exhibition? | SELECT AVG(visitors) FROM daily_visitors WHERE exhibition_id = 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE ClothingManufacturers (manufacturer TEXT, sustainable BOOLEAN, last_sustainable_update DATE); INSERT INTO ClothingManufacturers (manufacturer, sustainable, last_sustainable_update) VALUES ('Manufacturer1', true, '2019-01-01'), ('Manufacturer2', false, '2016-01-01'), ('Manufacturer3', true, '2021-01-01'), (... | Count the number of sustainable clothing manufacturers, and show only those manufacturers that have adopted sustainable practices in the last 3 years. | SELECT manufacturer, COUNT(*) as sustainable_manufacturers FROM ClothingManufacturers WHERE sustainable = true AND last_sustainable_update >= DATE_SUB(CURRENT_DATE, INTERVAL 3 YEAR) GROUP BY manufacturer HAVING COUNT(*) > 500; | gretelai_synthetic_text_to_sql |
CREATE TABLE WasteGeneration (country VARCHAR(255), waste_generation_kg_per_capita DECIMAL(5,2), region VARCHAR(255)); INSERT INTO WasteGeneration (country, waste_generation_kg_per_capita, region) VALUES ('Israel', 3.4, 'Middle East'), ('Saudi Arabia', 3.1, 'Middle East'), ('Turkey', 2.5, 'Middle East'); | What is the average waste generation per capita in the Middle East? | SELECT AVG(waste_generation_kg_per_capita) FROM WasteGeneration WHERE region = 'Middle East'; | gretelai_synthetic_text_to_sql |
CREATE TABLE infrastructure_investments (investment_id INT, investment_type VARCHAR(20), investment_date DATE, state VARCHAR(50)); INSERT INTO infrastructure_investments (investment_id, investment_type, investment_date, state) VALUES (1, '5G tower', '2023-01-15', 'Ontario'); | Which network infrastructure investments were made in the last 3 months in Ontario, Canada? | SELECT * FROM infrastructure_investments WHERE state = 'Ontario' AND investment_date > DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE organizations (id INT, name TEXT);CREATE TABLE funding (id INT, organization_id INT, amount DECIMAL, initiative_year INT, initiative_category TEXT); | Which organizations received the most funding for climate change initiatives in 2020? | SELECT o.name, SUM(funding.amount) as total_funding FROM organizations o JOIN funding ON o.id = funding.organization_id WHERE funding.initiative_year = 2020 AND funding.initiative_category = 'climate change' GROUP BY o.id ORDER BY total_funding DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE DeepestTrenches (id INT, name VARCHAR(255), depth FLOAT); INSERT INTO DeepestTrenches (id, name, depth) VALUES (1, 'Marianas Trench', 10994); INSERT INTO DeepestTrenches (id, name, depth) VALUES (2, 'Tonga Trench', 10882); | What are the names and depths of the deepest ocean trenches in the Pacific Ocean? | SELECT name, depth FROM DeepestTrenches WHERE depth = (SELECT MAX(depth) FROM DeepestTrenches); | gretelai_synthetic_text_to_sql |
CREATE TABLE cause_donations (cause VARCHAR(50), country VARCHAR(50), donation DECIMAL(10,2)); INSERT INTO cause_donations (cause, country, donation) VALUES ('Global Health', 'Australia', 5000.00), ('Education', 'Japan', 7000.00), ('Environment', 'India', 8000.00), ('Animal Welfare', 'China', 9000.00); | What is the total donation amount for each cause in the Asia-Pacific region? | SELECT country, SUM(donation) FROM cause_donations WHERE country IN ('Australia', 'Japan', 'India', 'China') GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE Workers (WorkerID int, Name varchar(50), State varchar(25), Earnings decimal(10,2)); INSERT INTO Workers (WorkerID, Name, State, Earnings) VALUES (1, 'John Doe', 'WA', 50000.00), (2, 'Jane Smith', 'WA', 60000.00), (3, 'Mike Johnson', 'WA', 55000.00); | Who are the top 3 construction workers by total earnings in WA? | SELECT Name, ROW_NUMBER() OVER (ORDER BY Earnings DESC) AS Rank FROM Workers WHERE State = 'WA' GROUP BY Name HAVING Rank <= 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE Events (event_id INT, venue_name VARCHAR(255), attendance INT); INSERT INTO Events (event_id, venue_name, attendance) VALUES (1, 'Artistic Hub', 300), (2, 'Artistic Hub', 400), (3, 'Creative Space', 250); | What is the average attendance for events at the 'Artistic Hub' venue? | SELECT AVG(attendance) FROM Events WHERE venue_name = 'Artistic Hub'; | gretelai_synthetic_text_to_sql |
CREATE TABLE grad_enrollment (id INT, student_id INT, student_major VARCHAR(50)); INSERT INTO grad_enrollment (id, student_id, student_major) VALUES (1, 2001, 'Environmental Science'), (2, 2002, 'Marine Biology'), (3, 2003, 'Wildlife Conservation'), (4, 2004, 'Botany'), (5, 2005, 'Ecology'), (6, 2006, 'Zoology'); | How many graduate students are enrolled in each department in the College of Environmental and Life Sciences? | SELECT student_major, COUNT(*) FROM grad_enrollment WHERE student_major LIKE '%Environmental and Life Sciences%' GROUP BY student_major; | gretelai_synthetic_text_to_sql |
CREATE TABLE employees (id INT, salary FLOAT, organization_type VARCHAR(255)); INSERT INTO employees (id, salary, organization_type) VALUES (1, 70000.00, 'social good'), (2, 80000.00, 'tech company'), (3, 60000.00, 'social good'), (4, 90000.00, 'tech company'); | What is the maximum salary of employees working in social good organizations? | SELECT MAX(salary) FROM employees WHERE organization_type = 'social good'; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, username VARCHAR(50)); CREATE TABLE status_updates (user_id INT, update_time TIMESTAMP); CREATE TABLE photos (user_id INT, photo_time TIMESTAMP); | Which users have posted a status update or a photo in the last 30 days, and what are their usernames? | SELECT users.username FROM users JOIN status_updates ON users.id = status_updates.user_id WHERE status_updates.update_time > NOW() - INTERVAL '30 days' UNION SELECT users.username FROM users JOIN photos ON users.id = photos.user_id WHERE photos.photo_time > NOW() - INTERVAL '30 days'; | gretelai_synthetic_text_to_sql |
CREATE TABLE facilities (city TEXT, facility_type TEXT); INSERT INTO facilities (city, facility_type) VALUES ('CityA', 'hospital'), ('CityB', 'hospital'), ('CityC', 'hospital'), ('CityA', 'school'), ('CityB', 'school'), ('CityC', 'school'), ('CityA', 'library'), ('CityB', 'library'), ('CityC', 'library'); | List all unique facility types across all cities, excluding libraries. | SELECT DISTINCT facility_type FROM facilities WHERE facility_type != 'library'; | gretelai_synthetic_text_to_sql |
CREATE TABLE europe (country VARCHAR(50), doctors_per_1000 DECIMAL(3,1)); INSERT INTO europe (country, doctors_per_1000) VALUES ('France', 3.2), ('Germany', 4.3), ('Italy', 4.0); | How many doctors are there per 1000 people in Europe by country? | SELECT country, AVG(doctors_per_1000 * 1000) as doctors_per_1000_people FROM europe GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE deepest_points(ocean VARCHAR(255), depth INT);INSERT INTO deepest_points(ocean, depth) VALUES ('Pacific Ocean', 36070), ('Atlantic Ocean', 8648), ('Indian Ocean', 7258), ('Southern Ocean', 7290), ('Arctic Ocean', 4261); | What is the minimum depth of the deepest point in each ocean? | SELECT MIN(depth) FROM deepest_points; | gretelai_synthetic_text_to_sql |
CREATE TABLE user (user_id INT, username VARCHAR(20), posts INT, created_at DATE); INSERT INTO user (user_id, username, posts, created_at) VALUES (1, 'user1', 10, '2022-01-01'), (2, 'user2', 20, '2022-01-02'), (3, 'user3', 30, '2022-01-03'), (4, 'user4', 40, '2022-01-04'), (5, 'user5', 50, '2022-01-05'); | What is the average number of posts per day for users in the social_media database? | SELECT AVG(posts / (DATEDIFF('2022-01-05', created_at))) FROM user; | gretelai_synthetic_text_to_sql |
CREATE TABLE social_enterprises (id INT, region VARCHAR(20), registration_date DATE); INSERT INTO social_enterprises (id, region, registration_date) VALUES (1, 'Asia-Pacific', '2021-01-01'), (2, 'Europe', '2022-03-15'), (3, 'Americas', '2020-05-03'), (4, 'Americas', '2019-09-20'); | List all social enterprises in the 'Americas' region, ordered by their registration date. | SELECT * FROM social_enterprises WHERE region = 'Americas' ORDER BY registration_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE Accommodations(id INT, name TEXT, country TEXT, eco_friendly BOOLEAN); INSERT INTO Accommodations(id, name, country, eco_friendly) VALUES (1, 'Eco Lodge', 'Brazil', true), (2, 'Green Apartment', 'Germany', true), (3, 'Regular Hotel', 'Australia', false), (4, 'Sustainable Villa', 'France', true); | How many eco-friendly accommodations are available in Australia and France? | SELECT country, COUNT(*) FROM Accommodations WHERE eco_friendly = true AND country IN ('Australia', 'France') GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE mexico_autonomous_vehicles (vehicle_id INT, type VARCHAR(20), trips INT); CREATE TABLE sao_paulo_autonomous_vehicles (vehicle_id INT, type VARCHAR(20), trips INT); INSERT INTO mexico_autonomous_vehicles (vehicle_id, type, trips) VALUES (1, 'Car', 30), (2, 'Bus', 25), (3, 'Truck', 15); INSERT INTO sao_paulo... | Get the types of autonomous vehicles in Mexico City and Sao Paulo with more than 20 trips. | SELECT DISTINCT type FROM mexico_autonomous_vehicles WHERE trips > 20 UNION SELECT DISTINCT type FROM sao_paulo_autonomous_vehicles WHERE trips > 20; | gretelai_synthetic_text_to_sql |
CREATE TABLE CommunityPolicing (id INT, state VARCHAR(20), program_type VARCHAR(20), quantity INT); | What is the maximum number of community policing programs in the state of California? | SELECT MAX(quantity) FROM CommunityPolicing WHERE state = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE climate_mitigation (id INT, project VARCHAR(255), location VARCHAR(255), budget FLOAT); | Insert a new record into the climate_mitigation table for a project in South America with a budget of 4,500,000. | INSERT INTO climate_mitigation (id, project, location, budget) VALUES (1, 'Reforestation Program', 'South America', 4500000); | gretelai_synthetic_text_to_sql |
CREATE TABLE wells (well_id INT, company VARCHAR(255), region VARCHAR(255)); INSERT INTO wells (well_id, company, region) VALUES (1, 'ExxonMobil', 'North Sea'); INSERT INTO wells (well_id, company, region) VALUES (2, 'ExxonMobil', 'Gulf of Mexico'); | What is the total number of wells drilled by ExxonMobil in the North Sea? | SELECT COUNT(*) FROM wells WHERE company = 'ExxonMobil' AND region = 'North Sea'; | gretelai_synthetic_text_to_sql |
CREATE TABLE manufacturers (manufacturer_id INT, manufacturer_name VARCHAR(255));CREATE TABLE garments (garment_id INT, garment_name VARCHAR(255), manufacturer_id INT, price DECIMAL(10,2), is_eco_friendly BOOLEAN); | Which manufacturers have the highest and lowest average prices for eco-friendly garments? | SELECT m.manufacturer_name, AVG(g.price) AS avg_price FROM garments g JOIN manufacturers m ON g.manufacturer_id = m.manufacturer_id WHERE g.is_eco_friendly = TRUE GROUP BY m.manufacturer_name ORDER BY avg_price DESC, m.manufacturer_name ASC LIMIT 1; SELECT m.manufacturer_name, AVG(g.price) AS avg_price FROM garments g... | gretelai_synthetic_text_to_sql |
CREATE TABLE artists_countries (artist_id INT, country VARCHAR(50)); INSERT INTO artists_countries (artist_id, country) VALUES (1, 'USA'), (2, 'Canada'), (3, 'Mexico'), (4, 'USA'), (5, 'Brazil'), (6, 'USA'), (7, 'Australia'), (8, 'Canada'), (9, 'USA'), (10, 'Germany'); CREATE TABLE artists_sales (artist_id INT, revenue... | What is the number of unique countries represented by the top 5 best-selling artists? | SELECT COUNT(DISTINCT country) FROM artists_countries ac JOIN (SELECT artist_id FROM artists_sales ORDER BY revenue DESC LIMIT 5) as t ON ac.artist_id = t.artist_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE habitats (id INT, habitat_type VARCHAR(255)); INSERT INTO habitats (id, habitat_type) VALUES (1, 'Forest'), (2, 'Grassland'), (3, 'Wetlands'); CREATE TABLE animals (id INT, animal_name VARCHAR(255), habitat_id INT); INSERT INTO animals (id, animal_name, habitat_id) VALUES (1, 'Tiger', 1), (2, 'Elephant', 2... | Find the number of animals in each habitat type | SELECT h.habitat_type, COUNT(a.id) as animal_count FROM habitats h INNER JOIN animals a ON h.id = a.habitat_id GROUP BY h.habitat_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE PeacekeepingOperations (id INT, country VARCHAR(50), operation_count INT, year INT); INSERT INTO PeacekeepingOperations (id, country, operation_count, year) VALUES (1, 'China', 5, 2016), (2, 'India', 3, 2016), (3, 'Japan', 4, 2016), (4, 'China', 6, 2017), (5, 'India', 4, 2017), (6, 'Japan', 5, 2017); | What is the total number of peacekeeping operations led by countries in Asia since 2015? | SELECT SUM(operation_count) FROM PeacekeepingOperations WHERE country IN ('China', 'India', 'Japan') AND year >= 2015; | gretelai_synthetic_text_to_sql |
CREATE TABLE landfills(region VARCHAR(255), capacity FLOAT); INSERT INTO landfills(region, capacity) VALUES('Region1', 12345.67), ('Region2', 23456.78), ('Region3', 34567.89), ('Region4', 45678.90); | What is the current landfill capacity in cubic meters for the top 3 regions with the highest capacity? | SELECT region, capacity FROM (SELECT region, capacity, ROW_NUMBER() OVER (ORDER BY capacity DESC) as rn FROM landfills) tmp WHERE rn <= 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT PRIMARY KEY, name VARCHAR(255)); CREATE TABLE diversity_metrics (id INT PRIMARY KEY, company_id INT, gender VARCHAR(50), diversity_score DECIMAL(3,2)); | Insert diversity metrics for 'SmartHome' | INSERT INTO diversity_metrics (id, company_id, gender, diversity_score) VALUES (6, 105, 'Female', 0.55), (7, 105, 'Male', 0.45); | gretelai_synthetic_text_to_sql |
CREATE TABLE vehicle_specs (vehicle_name VARCHAR(50), vehicle_type VARCHAR(20), max_speed INT); | What is the maximum speed of sports cars compared to electric vehicles in the 'vehicle_specs' table? | SELECT vehicle_type, MAX(max_speed) FROM vehicle_specs GROUP BY vehicle_type ORDER BY max_speed DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE ArcticOcean (volcano_name TEXT, location TEXT); INSERT INTO ArcticOcean (volcano_name, location) VALUES ('Ormen Lange', 'Norwegian Sea'), ('Kolbeinsey Ridge', 'Greenland Sea'), ('Gakkel Ridge', 'Eurasian Basin'); | List all underwater volcanoes in the Arctic Ocean. | SELECT volcano_name FROM ArcticOcean; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, name TEXT); CREATE TABLE user_actions (id INT, user_id INT, action TEXT, album_id INT, platform TEXT); CREATE VIEW unique_platform_users AS SELECT platform, COUNT(DISTINCT user_id) as user_count FROM user_actions GROUP BY platform; | Display the number of unique users who have streamed or downloaded music on each platform. | SELECT platform, user_count FROM unique_platform_users; | gretelai_synthetic_text_to_sql |
CREATE TABLE fish_farms (id INT, name TEXT, location TEXT, water_type TEXT); INSERT INTO fish_farms (id, name, location, water_type) VALUES (1, 'Farm C', 'Tokyo', 'Saltwater'); INSERT INTO fish_farms (id, name, location, water_type) VALUES (2, 'Farm D', 'Beijing', 'Freshwater'); | What is the average dissolved oxygen level for fish farms in Asia? | SELECT AVG(wq.dissolved_oxygen) FROM fish_farms ff JOIN water_quality wq ON ff.id = wq.fish_farm_id WHERE ff.location LIKE 'Asia%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species_population (species_name VARCHAR(255), region VARCHAR(255), avg_population_size FLOAT, conservation_status VARCHAR(255)); INSERT INTO marine_species_population (species_name, region, avg_population_size, conservation_status) VALUES ('Ross Seal', 'Southern Ocean', 1000, 'Fully Protected'), ('... | What is the average population size of all marine species in the Southern Ocean, grouped by conservation status?" | SELECT conservation_status, AVG(avg_population_size) as avg_population_size FROM marine_species_population WHERE region = 'Southern Ocean' GROUP BY conservation_status; | gretelai_synthetic_text_to_sql |
CREATE TABLE Festivals (FestivalID INT, FestivalName VARCHAR(255)); INSERT INTO Festivals (FestivalID, FestivalName) VALUES (1, 'Festival1'), (2, 'Festival2'), (3, 'Festival3'), (4, 'Festival4'), (5, 'Festival5'); CREATE TABLE Concerts (ConcertID INT, FestivalID INT, GenreID INT); INSERT INTO Concerts (ConcertID, Festi... | List all festivals that have had hip hop or rock concerts. | SELECT DISTINCT FestivalName FROM Festivals F JOIN Concerts C ON F.FestivalID = C.FestivalID WHERE C.GenreID IN (2, 4); | gretelai_synthetic_text_to_sql |
CREATE TABLE agency (agency_id INT, agency_name VARCHAR(50)); INSERT INTO agency (agency_id, agency_name) VALUES (1, 'Police Department'), (2, 'Courts'), (3, 'Probation Department'); | What is the total number of cases handled by each agency? | SELECT agency_name, COUNT(*) as total_cases FROM agency JOIN cases ON agency.agency_id = cases.agency_id GROUP BY agency_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE Clients (ClientID INT, ClientName VARCHAR(100), Region VARCHAR(50), FinanciallyCapable BOOLEAN, LastLoanDate DATE, LastDepositDate DATE); INSERT INTO Clients (ClientID, ClientName, Region, FinanciallyCapable, LastLoanDate, LastDepositDate) VALUES (1, 'AB Johnson', 'Africa', FALSE, '2020-02-01', '2021-03-01... | Delete records of financially incapable clients from the African region who have not taken any loans or made any deposits in the past 6 months. | DELETE FROM Clients WHERE FinanciallyCapable = FALSE AND Region = 'Africa' AND (LastLoanDate < DATE_SUB(CURDATE(), INTERVAL 6 MONTH) OR LastDepositDate < DATE_SUB(CURDATE(), INTERVAL 6 MONTH)); | gretelai_synthetic_text_to_sql |
CREATE TABLE ships (id INT, name VARCHAR(50), type VARCHAR(50), year_built INT, max_capacity INT, port_id INT); CREATE TABLE cargos (id INT, description VARCHAR(50), weight FLOAT, port_id INT, ship_id INT); CREATE VIEW ship_cargo AS SELECT s.name AS ship_name, c.description AS cargo_description, c.weight FROM ships s J... | What is the maximum weight of cargo handled by vessels in the 'Container' type that were built before 2010? | SELECT MAX(c.weight) AS max_weight FROM ships s JOIN ship_cargo sc ON s.name = sc.ship_name JOIN cargos c ON sc.cargo_description = c.description WHERE s.type = 'Container' AND s.year_built < 2010; | gretelai_synthetic_text_to_sql |
CREATE TABLE space_debris (id INT, name VARCHAR(50), type VARCHAR(50), launch_date DATE, orbit VARCHAR(50), mass FLOAT); | What is the total mass (in kg) of space debris in Low Earth Orbit? | SELECT SUM(mass) FROM space_debris WHERE orbit = 'Low Earth Orbit'; | gretelai_synthetic_text_to_sql |
CREATE TABLE districts (district_id INT, num_students INT, num_teachers INT); INSERT INTO districts (district_id, num_students, num_teachers) VALUES (101, 500, 100), (102, 700, 150), (103, 600, 120), (104, 650, 130), (105, 450, 90); | What is the number of districts with more than 600 students? | SELECT COUNT(*) FROM (SELECT district_id FROM districts WHERE num_students > 600 GROUP BY district_id HAVING COUNT(*) > 1); | gretelai_synthetic_text_to_sql |
CREATE TABLE ai_algorithms (algorithm_id INT, algorithm_name VARCHAR(50), algorithm_subtype VARCHAR(50), region VARCHAR(50), safety_score FLOAT); INSERT INTO ai_algorithms (algorithm_id, algorithm_name, algorithm_subtype, region, safety_score) VALUES (1, 'AlgoA', 'Deep RL', 'Asia-Pacific', 0.85), (2, 'AlgoB', 'Computer... | What is the average safety score for AI algorithms, grouped by algorithm subtype in the Asia-Pacific region? | SELECT algorithm_subtype, region, AVG(safety_score) AS avg_safety_score FROM ai_algorithms WHERE region = 'Asia-Pacific' GROUP BY algorithm_subtype, region; | gretelai_synthetic_text_to_sql |
CREATE TABLE renewable_energy (project_name VARCHAR(50), country VARCHAR(50), year INT, investment INT, renewable_source VARCHAR(50)); INSERT INTO renewable_energy (project_name, country, year, investment, renewable_source) VALUES ('Kenya Wind', 'Kenya', 2018, 300000, 'Wind'); INSERT INTO renewable_energy (project_name... | What is the number of renewable energy projects and their total investment in Africa in the year 2018? | SELECT COUNT(*) as num_projects, SUM(investment) as total_investment FROM renewable_energy WHERE year = 2018 AND country = 'Africa'; | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, name TEXT, industry TEXT, founder_underrepresented BOOLEAN); INSERT INTO companies (id, name, industry, founder_underrepresented) VALUES (1, 'Xi Inc', 'tech', true); INSERT INTO companies (id, name, industry, founder_underrepresented) VALUES (2, 'Omicron Corp', 'finance', false); INSERT ... | What is the count of startups by industry with at least one underrepresented founder? | SELECT industry, COUNT(*) FROM companies WHERE founder_underrepresented = true GROUP BY industry; | gretelai_synthetic_text_to_sql |
nato_equipment | List all military equipment from NATO countries | SELECT * FROM nato_equipment; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (id INT, donor_id INT, cause VARCHAR(255), amount DECIMAL(10, 2), donation_date DATE); INSERT INTO Donations (id, donor_id, cause, amount, donation_date) VALUES (1, 1001, 'Education', 5000, '2022-01-05'), (2, 1002, 'Health', 3000, '2022-03-15'), (3, 1003, 'Environment', 7000, '2022-01-30'); | What is the average donation amount per donor in 2022? | SELECT donor_id, AVG(amount) as avg_donation FROM Donations WHERE donation_date BETWEEN '2022-01-01' AND '2022-12-31' GROUP BY donor_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE workers (id INT, name VARCHAR(50), sector VARCHAR(50), salary DECIMAL(10,2)); INSERT INTO workers (id, name, sector, salary) VALUES (1, 'John Doe', 'Ethical Manufacturing', 50000.00), (2, 'Jane Smith', 'Ethical Manufacturing', 55000.00), (3, 'Mike Johnson', 'Ethical Manufacturing', 45000.00); | Update the salary of a worker in the ethical manufacturing sector. | UPDATE workers SET salary = 57000 WHERE name = 'John Doe' AND sector = 'Ethical Manufacturing'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Properties(id INT, size FLOAT, price INT, city VARCHAR(20));INSERT INTO Properties(id, size, price, city) VALUES (1, 1200, 500000, 'Seattle'), (2, 1500, 650000, 'Seattle'), (3, 1000, 400000, 'Portland'), (4, 2000, 800000, 'SanFrancisco'); | What is the average size and price of properties, excluding the most expensive city? | SELECT AVG(size), AVG(price) FROM Properties WHERE city != (SELECT city FROM Properties ORDER BY price DESC LIMIT 1); | gretelai_synthetic_text_to_sql |
CREATE TABLE customers (id INT, segment VARCHAR(20)); CREATE TABLE transactions (id INT, customer_id INT, amount DECIMAL(10,2), transaction_date DATE); INSERT INTO customers (id, segment) VALUES (1, 'Online'); INSERT INTO transactions (id, customer_id, amount, transaction_date) VALUES (1, 1, 500, '2022-04-01'); | What is the total transaction amount for the 'Online' customer segment in the last quarter? | SELECT SUM(amount) FROM transactions JOIN customers ON transactions.customer_id = customers.id WHERE customers.segment = 'Online' AND transaction_date >= DATE_SUB(CURDATE(), INTERVAL 3 MONTH); | gretelai_synthetic_text_to_sql |
CREATE TABLE GameScore (GameID int, GameName varchar(50), Genre varchar(50), Score int); INSERT INTO GameScore (GameID, GameName, Genre, Score) VALUES (1, 'GameA', 'Shooter', 80), (2, 'GameB', 'RPG', 90), (3, 'GameC', 'Shooter', 70), (4, 'GameD', 'RPG', 85); | What is the average score for each game genre? | SELECT Genre, AVG(Score) as AvgScore FROM GameScore GROUP BY Genre; | gretelai_synthetic_text_to_sql |
CREATE TABLE tv_shows (id INT, title VARCHAR(255), duration INT, country VARCHAR(50)); INSERT INTO tv_shows (id, title, duration, country) VALUES (1, 'Show1', 30, 'South Korea'), (2, 'Show2', 60, 'South Korea'), (3, 'Show3', 45, 'USA'); | What is the average duration of TV shows in South Korea? | SELECT AVG(duration) FROM tv_shows WHERE country = 'South Korea'; | gretelai_synthetic_text_to_sql |
CREATE TABLE MuseumVisits (ID INT, VisitDate DATE, VisitorID INT, Museum VARCHAR(255), State VARCHAR(50)); CREATE TABLE RepeatVisitors (ID INT, VisitorID INT, FirstVisit DATE, SecondVisit DATE); | What is the percentage of repeat visitors from different states for historical sites? | SELECT m.State, COUNT(DISTINCT m.VisitorID) as TotalVisitors, COUNT(DISTINCT r.VisitorID) as RepeatVisitors, (COUNT(DISTINCT r.VisitorID) * 100.0 / COUNT(DISTINCT m.VisitorID)) as RepeatVisitorPercentage FROM MuseumVisits m JOIN RepeatVisitors r ON m.VisitorID = r.VisitorID WHERE m.Museum = 'Historical Site' GROUP BY m... | gretelai_synthetic_text_to_sql |
CREATE TABLE habitats (habitat_type VARCHAR(255), area_size FLOAT); CREATE TABLE endangered_species (species VARCHAR(255), habitat_type VARCHAR(255), endangered BOOLEAN); | Show the average area size and total number of endangered species for each habitat type in the "habitats" and "endangered_species" tables | SELECT h1.habitat_type, AVG(h1.area_size) as avg_area_size, SUM(CASE WHEN e1.endangered THEN 1 ELSE 0 END) as total_endangered FROM habitats h1 LEFT JOIN endangered_species e1 ON h1.habitat_type = e1.habitat_type GROUP BY h1.habitat_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species_biomass (species_name VARCHAR(255), region VARCHAR(255), max_biomass FLOAT, conservation_status VARCHAR(255)); INSERT INTO marine_species_biomass (species_name, region, max_biomass, conservation_status) VALUES ('Ross Seal', 'Southern Ocean', 1500, 'Fully Protected'), ('Antarctic Krill', 'Sou... | What is the maximum biomass of all marine species in the Southern Ocean, grouped by conservation status?" | SELECT conservation_status, MAX(max_biomass) as max_biomass FROM marine_species_biomass WHERE region = 'Southern Ocean' GROUP BY conservation_status; | gretelai_synthetic_text_to_sql |
CREATE TABLE grants (grant_id INT, faculty_id INT, amount FLOAT, grant_date DATE); | How many research grants have been awarded to each department in the past year? | SELECT department, COUNT(grant_id) FROM grants JOIN faculty ON grants.faculty_id = faculty.faculty_id WHERE grant_date >= DATEADD(year, -1, GETDATE()) GROUP BY department; | gretelai_synthetic_text_to_sql |
CREATE TABLE ExoplanetMissions (Mission VARCHAR(50), Spacecraft VARCHAR(50), Discoveries INT, StartYear INT, EndYear INT); INSERT INTO ExoplanetMissions (Mission, Spacecraft, Discoveries, StartYear, EndYear) VALUES ('Kepler', 'Kepler', 2680, 2009, 2018), ('K2', 'K2', 415, 2013, 2021), ('TESS', 'TESS', 25, 2018, NULL), ... | List the space missions that have discovered exoplanets. | SELECT DISTINCT Mission, Spacecraft FROM ExoplanetMissions WHERE Discoveries > 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE creative_ai (id INT, tool VARCHAR(20), application VARCHAR(50), country VARCHAR(20)); INSERT INTO creative_ai (id, tool, application, country) VALUES (1, 'GAN', 'Art Generation', 'Canada'); INSERT INTO creative_ai (id, tool, application, country) VALUES (2, 'DALL-E', 'Text-to-Image', 'USA'); | Delete records in the 'creative_ai' table where 'tool' is 'GAN' and 'country' is 'Canada' | DELETE FROM creative_ai WHERE tool = 'GAN' AND country = 'Canada'; | gretelai_synthetic_text_to_sql |
CREATE TABLE fabrics_sourced (id INT PRIMARY KEY, fabric_type VARCHAR(255), country VARCHAR(255), sustainability_rating INT); | Insert records for cotton, hemp, and silk into 'fabrics_sourced' table | INSERT INTO fabrics_sourced (id, fabric_type, country, sustainability_rating) VALUES (1, 'cotton', 'India', 7), (2, 'hemp', 'China', 9), (3, 'silk', 'China', 6); | gretelai_synthetic_text_to_sql |
CREATE TABLE prices (id INT, element TEXT, date DATE, price INT); INSERT INTO prices (id, element, date, price) VALUES (1, 'europium', '2020-01-01', 1000), (2, 'europium', '2021-01-01', 1200); | What is the average price of europium per kilogram in the last 2 years? | SELECT AVG(price) FROM prices WHERE element = 'europium' AND extract(year from date) >= 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE posts (id INT, country VARCHAR(255), likes INT, created_at TIMESTAMP); | What was the average number of likes on posts containing the hashtag "#sustainability" in the United States, in the past week? | SELECT AVG(likes) FROM posts WHERE country = 'United States' AND hashtags LIKE '%#sustainability%' AND created_at > NOW() - INTERVAL '1 week'; | gretelai_synthetic_text_to_sql |
CREATE TABLE oceanography (id INT PRIMARY KEY, ocean_name VARCHAR(255), depth FLOAT); INSERT INTO oceanography (id, ocean_name, depth) VALUES (1, 'Pacific Ocean', 3970); INSERT INTO oceanography (id, ocean_name, depth) VALUES (2, 'Atlantic Ocean', 3000); | Update the 'depth' column to '3980' for all records in the 'oceanography' table where the 'ocean_name' is 'Atlantic Ocean' | UPDATE oceanography SET depth = 3980 WHERE ocean_name = 'Atlantic Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE CommunityImpacts (community TEXT, year INT, impact_level TEXT); INSERT INTO CommunityImpacts (community, year, impact_level) VALUES ('Inuit', 2010, 'High'), ('Inuit', 2015, 'Very High'), ('Inuit', 2020, 'Severe'), ('Sami', 2015, 'High'), ('Sami', 2020, 'Very High'), ('Gwich’in', 2015, 'High'), ('Gwich’in',... | Identify indigenous communities facing severe impacts from climate change | SELECT community, STRING_AGG(DISTINCT impact_level, ', ') AS impact_levels FROM CommunityImpacts WHERE year >= 2015 GROUP BY community HAVING COUNT(DISTINCT impact_level) > 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (id INT, name VARCHAR(255), habitat_type VARCHAR(255), average_depth FLOAT); INSERT INTO marine_species (id, name, habitat_type, average_depth) VALUES (1, 'Clownfish', 'Coral Reef', 20.0); INSERT INTO marine_species (id, name, habitat_type, average_depth) VALUES (2, 'Blue Whale', 'Open Ocean... | What is the total number of marine species in the 'Coral Reef' and 'Open Ocean' habitats? | SELECT SUM(CASE WHEN ms.habitat_type IN ('Coral Reef', 'Open Ocean') THEN 1 ELSE 0 END) as total_species FROM marine_species ms; | gretelai_synthetic_text_to_sql |
CREATE TABLE Weather (date DATE, temperature INT, crop_type VARCHAR(20)); | What is the average temperature for each crop type in the past 3 years? | SELECT crop_type, AVG(temperature) OVER(PARTITION BY crop_type ORDER BY crop_type ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) as avg_temp FROM Weather; | gretelai_synthetic_text_to_sql |
CREATE TABLE education_programs (program_id INT, program_name VARCHAR(50), program_year INT); INSERT INTO education_programs (program_id, program_name, program_year) VALUES (1, 'Program A', 2021), (2, 'Program B', 2022); | How many community education programs were held in '2021'? | SELECT COUNT(*) FROM education_programs WHERE program_year = 2021; | gretelai_synthetic_text_to_sql |
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