context stringlengths 11 9.12k | question stringlengths 0 1.06k | SQL stringlengths 2 4.44k | source stringclasses 28 values |
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CREATE TABLE CybersecurityIncidents (IncidentID INT, IncidentType VARCHAR(20), IncidentDate DATE); INSERT INTO CybersecurityIncidents (IncidentID, IncidentType, IncidentDate) VALUES (1, 'Malware', '2021-01-01'), (2, 'Phishing', '2021-02-15'), (3, 'Data Breach', '2021-03-28'), (4, 'Malware', '2022-04-05'), (5, 'Phishing', '2022-06-20'); | What is the total number of cybersecurity incidents and their types for each year? | SELECT YEAR(IncidentDate) as Year, IncidentType, COUNT(*) as Total FROM CybersecurityIncidents GROUP BY YEAR(IncidentDate), IncidentType; | gretelai_synthetic_text_to_sql |
CREATE TABLE Accommodations (accommodation_id INT, student_id INT, accommodation_type VARCHAR(255), accommodation_date DATE); CREATE TABLE Students (student_id INT, department VARCHAR(255)); | What is the number of students who received accommodations for the first time each month? | SELECT MONTH(accommodation_date) as month, COUNT(DISTINCT student_id) as number_of_students FROM Accommodations WHERE student_id NOT IN ( SELECT student_id FROM Accommodations WHERE accommodation_date < ( SELECT MIN(accommodation_date) FROM Accommodations )) GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE wnba_players (player_id INT, name VARCHAR(50), team VARCHAR(50), position VARCHAR(20), points_per_game FLOAT); INSERT INTO wnba_players (player_id, name, team, position, points_per_game) VALUES (1, 'Breanna Stewart', 'Seattle Storm', 'Power Forward', 20.3); INSERT INTO wnba_players (player_id, name, team, position, points_per_game) VALUES (2, 'Sue Bird', 'Seattle Storm', 'Point Guard', 10.6); | What is the average points per game for a WNBA player? | SELECT AVG(points_per_game) FROM wnba_players; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (Employee_ID INT, Mine_ID INT, Age INT, Gender VARCHAR(10), Department VARCHAR(20), Hire_Date DATE); INSERT INTO Employees (Employee_ID, Mine_ID, Age, Gender, Department, Hire_Date) VALUES (101, 1, 32, 'Male', 'Mining', '2018-05-23'), (102, 1, 45, 'Female', 'Mining', '2017-08-11'), (103, 2, 42, 'Non-binary', 'Geology', '2019-02-14'); | Count the number of employees in each mine, categorized by gender. | SELECT Mine_ID, Gender, COUNT(*) FROM Employees GROUP BY Mine_ID, Gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE MusicHall (concert_id INT, concert_name VARCHAR(50), date DATE, ticket_price DECIMAL(5,2), fan_age INT); | What is the average age and ticket price for concerts in the 'MusicHall' venue? | SELECT AVG(fan_age) AS avg_age, AVG(ticket_price) AS avg_ticket_price FROM MusicHall; | gretelai_synthetic_text_to_sql |
CREATE TABLE submarines (id INT, name VARCHAR(20), max_depth FLOAT); INSERT INTO submarines (id, name, max_depth) VALUES (1, 'Nautilus', 5000), (2, 'Alvin', 4500), (3, 'Mir', 6170); | What is the maximum depth explored by each submarine? | SELECT name, max_depth FROM submarines; | gretelai_synthetic_text_to_sql |
CREATE TABLE power_plants (name TEXT, country TEXT, technology TEXT, capacity INTEGER, year_built INTEGER); INSERT INTO power_plants (name, country, technology, capacity, year_built) VALUES ('Solana', 'United States', 'Solar', 280, 2013); INSERT INTO power_plants (name, country, technology, capacity, year_built) VALUES ('Desert Sunlight', 'United States', 'Solar', 550, 2015); INSERT INTO power_plants (name, country, technology, capacity, year_built) VALUES ('Cestas Solar', 'France', 'Solar', 300, 2015); | Which renewable energy power plants were built after 2016 and have a higher installed capacity than any power plant in France? | SELECT * FROM power_plants WHERE country != 'France' AND year_built > 2016 AND capacity > (SELECT MAX(capacity) FROM power_plants WHERE country = 'France'); | gretelai_synthetic_text_to_sql |
CREATE TABLE releases (artist_id INT, release_date DATE); | Find the number of unique artists who have not released any music in the last 5 years, across all genres. | SELECT COUNT(DISTINCT artist_id) FROM releases WHERE release_date < DATE_SUB(CURDATE(), INTERVAL 5 YEAR); | gretelai_synthetic_text_to_sql |
CREATE TABLE cities (city_id INT, name VARCHAR(255), country VARCHAR(255)); CREATE TABLE virtual_tours (tour_id INT, city_id INT, type VARCHAR(255)); | Identify the top 5 cities with the highest number of virtual tours. | SELECT c.name, COUNT(vt.tour_id) as tour_count FROM cities c JOIN virtual_tours vt ON c.city_id = vt.city_id GROUP BY c.name ORDER BY tour_count DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE Founders (id INT, name TEXT, gender TEXT); INSERT INTO Founders (id, name, gender) VALUES (1, 'Acme Corp', 'Female'); INSERT INTO Founders (id, name, gender) VALUES (2, 'Brick Co', 'Male'); CREATE TABLE Investors (id INT, tier TEXT, name TEXT); INSERT INTO Investors (id, tier, name) VALUES (1, 'Tier 1', 'Sequoia'); CREATE TABLE Investments (investor_id INT, company_name TEXT); INSERT INTO Investments (investor_id, company_name) VALUES (1, 'Acme Corp'); | Which companies have female founders and have received funding from Tier 1 investors? | SELECT Founders.name FROM Founders JOIN Investments ON Founders.name = Investments.company_name JOIN Investors ON Investments.investor_id = Investors.id WHERE Founders.gender = 'Female' AND Investors.tier = 'Tier 1'; | gretelai_synthetic_text_to_sql |
CREATE TABLE genetic_data_1 (id INT, data TEXT); INSERT INTO genetic_data_1 (id, data) VALUES (1, 'ATGC'), (2, 'CGTA'), (3, 'TGAC'); CREATE TABLE genetic_data_2 (id INT, data TEXT); INSERT INTO genetic_data_2 (id, data) VALUES (1, 'ATGC'), (2, 'CGTA'), (3, 'TGAC'); | Which genetic research data tables have more than 1000 records? | SELECT name FROM (SELECT COUNT(*) as count, 'genetic_data_1' as name FROM genetic_data_1 UNION ALL SELECT COUNT(*), 'genetic_data_2' FROM genetic_data_2) as subquery WHERE count > 1000; | gretelai_synthetic_text_to_sql |
CREATE TABLE MonthlyVisitors (Destination VARCHAR(50), VisitorCount INT, VisitDate DATE); INSERT INTO MonthlyVisitors VALUES ('Berlin', 800, '2022-01-01'), ('Berlin', 900, '2022-01-31'), ('London', 1000, '2022-01-01'), ('London', 1100, '2022-01-31'); | Determine the percentage change in visitors for each destination between the first and last days of the month. | SELECT Destination, (VisitorCountEnd - VisitorCountStart) * 100.0 / VisitorCountStart as PercentageChange FROM (SELECT Destination, FIRST_VALUE(VisitorCount) OVER (PARTITION BY Destination ORDER BY VisitDate ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) as VisitorCountStart, LAST_VALUE(VisitorCount) OVER (PARTITION BY Destination ORDER BY VisitDate ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) as VisitorCountEnd FROM MonthlyVisitors) AS Subquery; | gretelai_synthetic_text_to_sql |
CREATE TABLE SafetyIncidents (IncidentID INT, PlantID INT, IncidentDate DATE); INSERT INTO SafetyIncidents (IncidentID, PlantID, IncidentDate) VALUES (1, 101, '2020-06-15'), (2, 102, '2020-07-22'), (3, 101, '2021-02-03'), (4, 103, '2021-04-10'), (5, 104, '2021-05-05'), (6, 105, '2021-05-20'); CREATE TABLE ManufacturingPlants (PlantID INT, PlantLocation VARCHAR(50)); INSERT INTO ManufacturingPlants (PlantID, PlantLocation) VALUES (101, 'Tokyo'), (102, 'Seoul'), (103, 'Beijing'), (104, 'Mumbai'), (105, 'Delhi'); | What are the top 5 manufacturing plants with the highest safety incident rate in the Asia region in the past 12 months? | SELECT PlantLocation, COUNT(DISTINCT PlantID) AS SafetyIncidentCount FROM SafetyIncidents JOIN ManufacturingPlants ON SafetyIncidents.PlantID = ManufacturingPlants.PlantID WHERE IncidentDate >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH) AND Region = 'Asia' GROUP BY PlantLocation ORDER BY SafetyIncidentCount DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE research_projects (project_id INT, project_name VARCHAR(255), region VARCHAR(255), focus_area VARCHAR(255), PRIMARY KEY(project_id)); INSERT INTO research_projects (project_id, project_name, region, focus_area) VALUES (1, 'Coral Conservation Research', 'Indian Ocean', 'Deep-sea Coral'); | Find total number of scientific research projects in the Indian Ocean on deep-sea coral conservation. | SELECT COUNT(*) FROM research_projects WHERE region = 'Indian Ocean' AND focus_area = 'Deep-sea Coral'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (id INT, donor_name VARCHAR(50), donation_amount DECIMAL(10,2), donation_date DATE, country VARCHAR(50)); INSERT INTO Donations (id, donor_name, donation_amount, donation_date, country) VALUES (1, 'John Doe', 50.00, '2021-01-01', 'USA'); INSERT INTO Donations (id, donor_name, donation_amount, donation_date, country) VALUES (2, 'Jane Smith', 100.00, '2021-01-02', 'Canada'); | Which countries have the highest total donation amounts? | SELECT country, SUM(donation_amount) as total_donations FROM Donations GROUP BY country ORDER BY total_donations DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE products (product_id INT, product_name TEXT, category TEXT, is_circular_supply_chain BOOLEAN); INSERT INTO products (product_id, product_name, category, is_circular_supply_chain) VALUES (1, 'Refurbished Smartphone', 'Electronics', FALSE), (2, 'Upcycled Furniture', 'Home Decor', TRUE), (3, 'Vintage Clothing', 'Fashion', FALSE); | How many products are there in each category that are not produced using circular supply chains? | SELECT category, COUNT(*) FROM products WHERE is_circular_supply_chain = FALSE GROUP BY category; | gretelai_synthetic_text_to_sql |
CREATE TABLE program_expenses (expense_id INT, program_name VARCHAR(50), expense_date DATE, amount DECIMAL(10,2)); INSERT INTO program_expenses VALUES (1, 'Education', '2022-01-15', 5000.00), (2, 'Health', '2022-03-01', 7000.00), (3, 'Education', '2022-02-28', 4000.00); | Which program had the highest expense in Q1 2022? | SELECT program_name, MAX(amount) as max_expense FROM program_expenses WHERE expense_date BETWEEN '2022-01-01' AND '2022-03-31' GROUP BY program_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE customer_data_usage (id INT PRIMARY KEY, customer_id INT, usage_bytes BIGINT, usage_date DATE); CREATE TABLE customer_demographics (id INT PRIMARY KEY, customer_id INT, age INT, gender VARCHAR(255), income FLOAT); | What is the total data usage for customers in a specific postal code, grouped by week and joined with the customer demographics table to show age, gender, and income? | SELECT WEEK(du.usage_date) as week, c.age, c.gender, c.income, SUM(du.usage_bytes) as total_usage FROM customer_data_usage du INNER JOIN customer_demographics c ON du.customer_id = c.customer_id WHERE c.postal_code = '12345' GROUP BY week, c.age, c.gender, c.income; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (species_id INT, name VARCHAR(50), habitat VARCHAR(50), population INT); | What is the total number of marine species found in deep-sea hydrothermal vents?' | SELECT SUM(population) AS total_species FROM marine_species WHERE habitat = 'deep-sea hydrothermal vents'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Garments (id INT, name VARCHAR(255), category VARCHAR(255), color VARCHAR(255), size VARCHAR(10), price DECIMAL(5, 2)); | Delete all garments in the 'Dresses' category with a price above $100.00 | DELETE FROM Garments WHERE category = 'Dresses' AND price > 100.00; | gretelai_synthetic_text_to_sql |
CREATE TABLE WastewaterTreatment (Id INT, Plant VARCHAR(50), Wastewater DECIMAL(5,2), Date DATE); INSERT INTO WastewaterTreatment (Id, Plant, Wastewater, Date) VALUES (1, 'Denver Plant', 1600.5, '2021-07-15'); INSERT INTO WastewaterTreatment (Id, Plant, Wastewater, Date) VALUES (2, 'Colorado Springs Plant', 1300.3, '2021-07-15'); | Which wastewater treatment plants treated more than 1500 m³ of wastewater on July 15, 2021? | SELECT Plant, SUM(Wastewater) FROM WastewaterTreatment WHERE Date = '2021-07-15' GROUP BY Plant HAVING SUM(Wastewater) > 1500; | gretelai_synthetic_text_to_sql |
CREATE TABLE AI_Safety_Papers3 (id INT, title TEXT, authors INT); INSERT INTO AI_Safety_Papers3 (id, title, authors) VALUES (1, 'Paper1', 15), (2, 'Paper2', 5), (3, 'Paper3', 35), (4, 'Paper4', 20); | Delete AI safety research papers with less than 10 authors. | DELETE FROM AI_Safety_Papers3 WHERE authors < 10; | gretelai_synthetic_text_to_sql |
CREATE TABLE veteran_employment (state VARCHAR(2), unemployment_rate DECIMAL(4,2), snapshot_date DATE); INSERT INTO veteran_employment VALUES ('CA', 3.2, '2021-07-15'), ('TX', 4.1, '2021-07-15'), ('NY', 5.0, '2021-07-15'); | List veteran unemployment rates by state for the most recent month. | SELECT state, unemployment_rate FROM veteran_employment WHERE snapshot_date = (SELECT MAX(snapshot_date) FROM veteran_employment); | gretelai_synthetic_text_to_sql |
CREATE TABLE Exhibition (exhibition_id INT, exhibition_name VARCHAR(30), genre VARCHAR(20), duration INT); | What is the total duration of all exhibitions in the 'Cubism' genre, in minutes? | SELECT SUM(Exhibition.duration) FROM Exhibition WHERE Exhibition.genre = 'Cubism'; | gretelai_synthetic_text_to_sql |
CREATE TABLE peacekeeping_operations (operation_id INT, name VARCHAR(255), location VARCHAR(255), start_date DATE, end_date DATE); INSERT INTO peacekeeping_operations (operation_id, name, location, start_date, end_date) VALUES (1, 'MINUSMA', 'Mali', '2013-07-25', '2024-12-31'); | Insert data into the 'peacekeeping_operations' table | INSERT INTO peacekeeping_operations (operation_id, name, location, start_date, end_date) VALUES (2, 'MONUSCO', 'Democratic Republic of the Congo', '1999-11-30', '2024-12-31'); | gretelai_synthetic_text_to_sql |
CREATE TABLE WorkoutDuration (MemberId INT, TotalDuration INT); INSERT INTO WorkoutDuration (MemberId, TotalDuration) VALUES (1, 120), (2, 150), (3, 90); | Find the total time spent on workouts for each member? | SELECT MemberId, SUM(Duration) FROM Workouts GROUP BY MemberId; | gretelai_synthetic_text_to_sql |
CREATE TABLE PlayerStats (PlayerID INT, Kills INT, Deaths INT, Assists INT); | Determine the average KDA ratio for each player in 'PlayerStats' table | SELECT PlayerID, AVG(Kills/Deaths + Assists) as AverageKDA FROM PlayerStats GROUP BY PlayerID; | gretelai_synthetic_text_to_sql |
CREATE TABLE chemical_properties (id INT, name VARCHAR(50), min_temperature FLOAT); | What is the minimum temperature required to safely store chemical Y? | SELECT min_temperature FROM chemical_properties WHERE name = 'chemical Y'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Disasters (disaster_id INT, name VARCHAR(255), type VARCHAR(255), affected_people INT, region VARCHAR(255), date DATE); INSERT INTO Disasters (disaster_id, name, type, affected_people, region, date) VALUES (1, 'Floods', 'Hydrological', 800, 'Asia', '2018-01-01'); | What are the names and types of disasters that have impacted more than 100 people in the 'Africa' region in the year 2020, with no limitation on the date? | SELECT name, type FROM Disasters WHERE region = 'Africa' AND affected_people > 100 AND date >= '2020-01-01' AND date < '2021-01-01'; | gretelai_synthetic_text_to_sql |
CREATE TABLE resolved_complaints (id INT PRIMARY KEY, complaint TEXT, date DATE); | Create a table to archive resolved complaints | CREATE TABLE resolved_complaints AS SELECT id, complaint, date FROM customer_complaints WHERE resolved = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE research_vessels (vessel_id INT, name VARCHAR(50), type VARCHAR(50), last_visit_date DATE); INSERT INTO research_vessels (vessel_id, name, type, last_visit_date) VALUES (1, 'RRS Discovery', 'Oceanographic Research Vessel', '2018-03-21'), (2, 'MV Alucia', 'Oceanographic Research Vessel', '2015-06-02'), (3, 'RV Thomas G. Thompson', 'Oceanographic Research Vessel', '2012-10-14'); | Which oceanographic research vessels have visited the Galapagos Islands since 2010? | SELECT name FROM research_vessels WHERE type = 'Oceanographic Research Vessel' AND last_visit_date >= '2010-01-01' AND last_visit_date <= '2022-12-31' AND location = 'Galapagos Islands'; | gretelai_synthetic_text_to_sql |
CREATE TABLE artists (id INT, name VARCHAR(255), birth_date DATE, nationality VARCHAR(50)); | What is the total number of visual artists represented in the database, and what is the distribution by their country of origin? | SELECT COUNT(*) as total_artists, nationality FROM artists GROUP BY nationality; | gretelai_synthetic_text_to_sql |
CREATE TABLE dispensaries (id INT, name TEXT, state TEXT); CREATE TABLE sales (dispensary_id INT, strain_id INT, quantity INT, price DECIMAL(10,2), sale_date DATE); INSERT INTO dispensaries (id, name, state) VALUES (1, 'Dispensary A', 'Washington'); INSERT INTO sales (dispensary_id, strain_id, quantity, price, sale_date) VALUES (1, 1, 10, 50, '2023-01-01'); INSERT INTO sales (dispensary_id, strain_id, quantity, price, sale_date) VALUES (1, 2, 15, 60, '2023-01-15'); | Calculate the total revenue for each dispensary in Washington in Q1 2023 and sort by revenue in descending order | SELECT d.name, SUM(s.quantity * s.price) as total_revenue FROM dispensaries d JOIN sales s ON d.id = s.dispensary_id WHERE s.sale_date BETWEEN '2023-01-01' AND '2023-03-31' GROUP BY d.name ORDER BY total_revenue DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE SpaceMissions (Mission VARCHAR(50), LaunchSite VARCHAR(50), Satellites INT); INSERT INTO SpaceMissions (Mission, LaunchSite, Satellites) VALUES ('STS-1', 'Kennedy Space Center', 2), ('STS-2', 'Kennedy Space Center', 0), ('Spacelab-1', 'Kennedy Space Center', 7); | List the space missions and their launch sites, along with the number of satellites deployed in each mission. | SELECT Mission, LaunchSite, Satellites FROM SpaceMissions; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotel_revenue_quarterly (hotel_id INT, category TEXT, revenue FLOAT, quarter INT, year INT); INSERT INTO hotel_revenue_quarterly (hotel_id, category, revenue, quarter, year) VALUES (1, 'business', 5000, 1, 2022), (2, 'leisure', 3000, 3, 2022), (3, 'business', 7000, 2, 2022); | What is the total revenue for the 'leisure' category in Q3 of 2022? | SELECT SUM(revenue) FROM hotel_revenue_quarterly WHERE category = 'leisure' AND quarter = 3 AND year = 2022; | gretelai_synthetic_text_to_sql |
CREATE TABLE VesselPerformance(PerformanceID INT, VesselID INT, Speed FLOAT, PerformanceDate DATETIME); INSERT INTO VesselPerformance(PerformanceID, VesselID, Speed, PerformanceDate) VALUES (1, 1, 16.5, '2021-02-03 11:00:00'), (2, 2, 17.3, '2021-02-05 16:30:00'), (3, 3, 18.1, '2021-02-07 10:00:00'); | Who was the top performing vessel in terms of speed in the month of February 2021? | SELECT VesselID, MAX(Speed) FROM VesselPerformance WHERE PerformanceDate BETWEEN '2021-02-01' AND '2021-02-28' GROUP BY VesselID; | gretelai_synthetic_text_to_sql |
CREATE TABLE production (production_id INT, fabric_type VARCHAR(50), units INT, production_date DATE); | What is the total number of units produced for each fabric type in Q2 of 2022? | SELECT fabric_type, SUM(units) as q2_production FROM production WHERE production_date BETWEEN '2022-04-01' AND '2022-06-30' GROUP BY fabric_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE water_usage (id INT PRIMARY KEY, year INT, location VARCHAR(50), usage FLOAT); INSERT INTO water_usage (id, year, location, usage) VALUES (1, 2019, 'Miami', 1234.56), (2, 2019, 'Honolulu', 897.45), (3, 2019, 'Anchorage', 987.65), (4, 2019, 'Santa Fe', 789.12), (5, 2019, 'Boise', 567.89); | Calculate the average water usage in cubic meters for each location in the year 2019 | SELECT location, AVG(usage) FROM water_usage WHERE year = 2019 GROUP BY location; | gretelai_synthetic_text_to_sql |
CREATE TABLE heritage_sites (id INT PRIMARY KEY, name TEXT, location TEXT); | Insert a new heritage site in 'Japan' named 'Meiji Shrine' | INSERT INTO heritage_sites (id, name, location) VALUES (1, 'Meiji Shrine', 'Japan'); | gretelai_synthetic_text_to_sql |
CREATE TABLE mines (id INT, name TEXT, location TEXT, total_employees INT, female_employees INT, male_employees INT); INSERT INTO mines (id, name, location, total_employees, female_employees, male_employees) VALUES (1, 'Golden Mine', 'Colorado, USA', 300, 150, 150), (2, 'Silver Ridge', 'Nevada, USA', 400, 200, 200), (3, 'Bronze Basin', 'Utah, USA', 500, 250, 250); | Which mines have a higher proportion of female employees compared to male employees? | SELECT name FROM mines WHERE female_employees > (male_employees * 1.0) * (SELECT AVG(female_employees / male_employees) FROM mines) | gretelai_synthetic_text_to_sql |
CREATE TABLE tugboats (id INT PRIMARY KEY, name VARCHAR(50), year_built INT, type VARCHAR(50)); | What are the names and types of all tugboats in the 'tugboats' table that were built before 1990? | SELECT name, type FROM tugboats WHERE year_built < 1990; | gretelai_synthetic_text_to_sql |
CREATE TABLE container_ships (id INT, name VARCHAR(100), ports_of_call INT, region VARCHAR(50)); | List the names and number of ports of call for container ships in the Southern Ocean. | SELECT name, ports_of_call FROM container_ships WHERE region = 'Southern Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE judges (id INT, first_name VARCHAR(20), last_name VARCHAR(20), court_id INT); INSERT INTO judges (id, first_name, last_name, court_id) VALUES (1, 'Maria', 'Garcia', 1); INSERT INTO judges (id, first_name, last_name, court_id) VALUES (2, 'Juan', 'Rodriguez', 2); | Delete all records in the "judges" table where the judge's last name is "Garcia" | DELETE FROM judges WHERE last_name = 'Garcia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE therapy_info (patient_id INT, therapy VARCHAR(50), frequency INT); INSERT INTO therapy_info (patient_id, therapy, frequency) VALUES (1, 'Therapy', 10), (2, 'Therapy', 15), (3, 'CBT', 20), (4, 'Therapy', 5), (5, 'Family Therapy', 8); CREATE TABLE patient_address (patient_id INT, address VARCHAR(50)); INSERT INTO patient_address (patient_id, address) VALUES (1, 'Florida'), (2, 'Florida'), (3, 'California'), (4, 'Florida'), (5, 'Florida'); | Count the number of patients who received therapy in Florida. | SELECT COUNT(patient_id) FROM therapy_info JOIN patient_address ON therapy_info.patient_id = patient_address.patient_id WHERE therapy = 'Therapy' AND address = 'Florida'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ocean_depths (location TEXT, depth INT); INSERT INTO ocean_depths (location, depth) VALUES ('Atlantic Ocean Shallows', '100'), ('Pacific Ocean Depths', '8000'); | Identify the shallowest point in the Atlantic Ocean. | SELECT location, depth FROM ocean_depths WHERE depth = (SELECT MIN(depth) FROM ocean_depths WHERE location = 'Atlantic Ocean') AND location = 'Atlantic Ocean'; | gretelai_synthetic_text_to_sql |
CREATE TABLE svalbard_temperature(month INT, year INT, temperature FLOAT); INSERT INTO svalbard_temperature(month, year, temperature) VALUES (1, 2000, 2.5), (2, 2000, 3.2), (1, 2001, 1.8); | Which month has the highest temperature in Svalbard? | SELECT month, MAX(temperature) max_temp FROM svalbard_temperature GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE defense_projects(id INT, project_name VARCHAR(50), start_date DATE, end_date DATE, status VARCHAR(20), country VARCHAR(20)); | What is the total number of defense projects in each country and their average duration? | SELECT country, AVG(DATEDIFF(end_date, start_date)) AS avg_duration, COUNT(*) AS total_projects FROM defense_projects GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE PublicMeetings (ID INT, Date DATE, Status VARCHAR(255)); | Add a new record to the "PublicMeetings" table with the ID of 4, a date of '2022-09-15', and a status of 'Scheduled' | INSERT INTO PublicMeetings (ID, Date, Status) VALUES (4, '2022-09-15', 'Scheduled'); | gretelai_synthetic_text_to_sql |
CREATE TABLE teacher_pd (teacher_id INT, course_id INT, pd_date DATE); INSERT INTO teacher_pd (teacher_id, course_id, pd_date) VALUES (1, 1, '2021-01-01'), (2, 2, '2021-02-15'), (3, 1, '2021-03-10'), (4, 3, '2021-12-31'); CREATE TABLE courses (course_id INT, course_name TEXT); INSERT INTO courses (course_id, course_name) VALUES (1, 'Tech Tools'), (2, 'Inclusive Classrooms'), (3, 'Project-Based Learning'); | Which professional development courses were most popular among teachers in 2021? | SELECT c.course_name, COUNT(pd.teacher_id) AS num_teachers FROM teacher_pd pd JOIN courses c ON pd.course_id = c.course_id WHERE pd.pd_date >= '2021-01-01' AND pd.pd_date <= '2021-12-31' GROUP BY pd.course_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE mine (id INT, name VARCHAR(50), location VARCHAR(50));CREATE TABLE gold_mine (mine_id INT, amount INT);CREATE TABLE silver_mine (mine_id INT, amount INT); | List the names and locations of mines that have mined either gold or silver, but not both. | SELECT m.name, m.location FROM mine m LEFT JOIN gold_mine g ON m.id = g.mine_id LEFT JOIN silver_mine s ON m.id = s.mine_id WHERE g.mine_id IS NOT NULL AND s.mine_id IS NULL OR s.mine_id IS NOT NULL AND g.mine_id IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE Accommodations (StudentID INT, DisabilityType VARCHAR(50), Gender VARCHAR(50), Region VARCHAR(50), AccommodationYear INT); INSERT INTO Accommodations (StudentID, DisabilityType, Gender, Region, AccommodationYear) VALUES (1, 'Visual Impairment', 'Male', 'Midwest', 2020), (2, 'Hearing Impairment', 'Female', 'Midwest', 2020), (3, 'Autism Spectrum Disorder', 'Non-binary', 'Midwest', 2020); | What is the total number of students who received accommodations by disability type and gender in the Midwest region for the year 2020? | SELECT DisabilityType, Gender, COUNT(StudentID) FROM Accommodations WHERE Region = 'Midwest' AND AccommodationYear = 2020 GROUP BY DisabilityType, Gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotels (hotel_id INT, hotel_name TEXT, country TEXT, num_virtual_tours INT, ai_customer_service BOOLEAN); INSERT INTO hotels (hotel_id, hotel_name, country, num_virtual_tours, ai_customer_service) VALUES (1, 'Hotel Y', 'Canada', 100, TRUE), (2, 'Hotel Z', 'Canada', 75, FALSE), (3, 'Hotel AA', 'Canada', 125, TRUE); | What is the average number of virtual tours per hotel in Canada for hotels that have adopted AI-based customer service? | SELECT AVG(num_virtual_tours) FROM hotels WHERE country = 'Canada' AND ai_customer_service = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE Programs (ProgramID INT, ProgramName TEXT); CREATE TABLE Budgets (BudgetID INT, ProgramID INT, BudgetAmount DECIMAL(10,2)); INSERT INTO Programs (ProgramID, ProgramName) VALUES (1, 'Education'), (2, 'Health'); INSERT INTO Budgets (BudgetID, ProgramID, BudgetAmount) VALUES (1, 1, 1000.00), (2, 1, 500.00), (3, 2, 1500.00); | List the programs with their associated outcomes and total budget from the 'Programs' and 'Budgets' tables. | SELECT Programs.ProgramName, SUM(Budgets.BudgetAmount) as TotalBudget FROM Programs INNER JOIN Budgets ON Programs.ProgramID = Budgets.ProgramID GROUP BY Programs.ProgramName; | gretelai_synthetic_text_to_sql |
CREATE TABLE CitizenFeedback (District VARCHAR(10), Year INT, FeedbackCount INT); INSERT INTO CitizenFeedback VALUES ('District E', 2022, 800), ('District E', 2022, 900), ('District F', 2022, 700), ('District F', 2022, 600); | How many citizens provided feedback in District E and F in 2022? | SELECT SUM(FeedbackCount) FROM CitizenFeedback WHERE District IN ('District E', 'District F') AND Year = 2022; | gretelai_synthetic_text_to_sql |
CREATE TABLE grants (grant_id INT, title VARCHAR(50), budget INT); INSERT INTO grants VALUES (1, 'Research Grant 1', 50000); INSERT INTO grants VALUES (2, 'Research Grant 2', 120000); | Update the budget of a research grant with a given grant_id. | UPDATE grants SET budget = 75000 WHERE grant_id = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE Household_Types (name VARCHAR(50), median_income INT); INSERT INTO Household_Types (name, median_income) VALUES ('Single', 50000), ('Family', 75000), ('Senior', 40000); | What is the median income for each household type? | SELECT name, MEDIAN(median_income) FROM Household_Types GROUP BY name; | gretelai_synthetic_text_to_sql |
CREATE TABLE dispensaries (id INT PRIMARY KEY, location TEXT, minority_owner BOOLEAN); INSERT INTO dispensaries (id, location, minority_owner) VALUES (1, 'Colorado', TRUE); INSERT INTO dispensaries (id, location, minority_owner) VALUES (2, 'Colorado', FALSE); CREATE TABLE inventory (id INT PRIMARY KEY, dispensary_id INT, product_id INT, quantity INT, price DECIMAL); INSERT INTO inventory (id, dispensary_id, product_id, quantity, price) VALUES (1, 1, 1, 100, 12.50); INSERT INTO inventory (id, dispensary_id, product_id, quantity, price) VALUES (2, 2, 2, 150, 15.00); CREATE TABLE transactions (id INT PRIMARY KEY, sale_id INT, consumer_id INT); INSERT INTO transactions (id, sale_id, consumer_id) VALUES (1, 1, 1); INSERT INTO transactions (id, sale_id, consumer_id) VALUES (2, 1, 2); | For dispensaries located in Colorado with a minority owner, what is the average price of their products, and how many consumers have made a purchase from each of these dispensaries? | SELECT d.location, AVG(i.price) as avg_price, COUNT(t.sale_id) as num_consumers FROM dispensaries d INNER JOIN inventory i ON d.id = i.dispensary_id INNER JOIN transactions t ON i.id = t.sale_id WHERE d.location = 'Colorado' AND d.minority_owner = TRUE GROUP BY d.location; | gretelai_synthetic_text_to_sql |
CREATE TABLE ElectricVehicleAdoptionStatistics (Id INT, Country VARCHAR(50), AdoptionRate DECIMAL(5,2), Year INT); INSERT INTO ElectricVehicleAdoptionStatistics (Id, Country, AdoptionRate, Year) VALUES (1, 'USA', 0.12, 2018); INSERT INTO ElectricVehicleAdoptionStatistics (Id, Country, AdoptionRate, Year) VALUES (2, 'China', 0.23, 2018); INSERT INTO ElectricVehicleAdoptionStatistics (Id, Country, AdoptionRate, Year) VALUES (3, 'Germany', 0.08, 2018); INSERT INTO ElectricVehicleAdoptionStatistics (Id, Country, AdoptionRate, Year) VALUES (4, 'Japan', 0.17, 2018); INSERT INTO ElectricVehicleAdoptionStatistics (Id, Country, AdoptionRate, Year) VALUES (5, 'South Korea', 0.14, 2020); | Update the adoption rate of electric vehicles in South Korea to 0.15 for the year 2021. | UPDATE ElectricVehicleAdoptionStatistics SET AdoptionRate = 0.15 WHERE Country = 'South Korea' AND Year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE mines (id INT, name VARCHAR(20)); INSERT INTO mines (id, name) VALUES (1, 'Golden Mine'), (2, 'Silver Mine'); CREATE TABLE mine_production (mine_id INT, volume INT); INSERT INTO mine_production (mine_id, volume) VALUES (1, 1000), (1, 1200), (2, 1500); | Show the total production volume for each mine in the "mine_production" and "mines" tables | SELECT m.name, SUM(mp.volume) as total_volume FROM mines m JOIN mine_production mp ON m.id = mp.mine_id GROUP BY m.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE Items (item_id INT, item_name TEXT); | Update the item_name for item_id 123 to 'First Aid Kit'. | UPDATE Items SET Items.item_name = 'First Aid Kit' WHERE Items.item_id = 123; | gretelai_synthetic_text_to_sql |
CREATE TABLE user_interests (user_id INT, interest VARCHAR(50)); INSERT INTO user_interests (user_id, interest) VALUES (1, 'climate change'), (1, 'veganism'), (2, 'climate change'), (3, 'veganism'), (3, 'animal rights'), (4, 'climate change'), (5, 'veganism'), (6, 'climate change'), (6, 'renewable energy'); | What are the unique interests of users who have engaged with both posts about climate change and posts about veganism? | SELECT interest FROM user_interests WHERE user_id IN (SELECT user_id FROM user_interests WHERE interest = 'climate change' INTERSECT SELECT user_id FROM user_interests WHERE interest = 'veganism'); | gretelai_synthetic_text_to_sql |
CREATE TABLE states (state_id INT PRIMARY KEY, state_name VARCHAR(255)); INSERT INTO states (state_id, state_name) VALUES (1, 'Alabama'), (2, 'Alaska'), (3, 'Arizona'); CREATE TABLE vaccinations (state_id INT, vaccine_count INT); INSERT INTO vaccinations (state_id, vaccine_count) VALUES (1, 2000), (2, 3000), (3, 4000); | What is the number of vaccines administered per state? | SELECT s.state_name, v.vaccine_count FROM states s JOIN vaccinations v ON s.state_id = v.state_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE organizations (org_id int, num_employees int, country varchar(50), donation_date date); INSERT INTO organizations (org_id, num_employees, country, donation_date) VALUES (1, 150, 'Canada', '2021-01-01'), (2, 50, 'Canada', '2021-02-01'), (3, 200, 'Canada', '2021-03-01'); | What is the total amount donated by organizations with more than 100 employees in Canada, in the year 2021? | SELECT SUM(donation_amount) FROM donations INNER JOIN organizations ON donations.org_id = organizations.org_id WHERE organizations.country = 'Canada' AND YEAR(donation_date) = 2021 GROUP BY organizations.org_id HAVING num_employees > 100; | gretelai_synthetic_text_to_sql |
CREATE TABLE legal_aid_organizations (org_id INT, name VARCHAR(50), cases_handled INT, cases_type VARCHAR(50), state VARCHAR(2)); INSERT INTO legal_aid_organizations (org_id, name, cases_handled, cases_type, state) VALUES (1, 'California Legal Aid', 200, 'access to justice, criminal justice reform', 'CA'), (2, 'New York Legal Aid', 300, 'legal technology', 'NY'), (3, 'Texas Legal Aid', 150, 'criminal justice reform', 'TX'), (4, 'Florida Legal Aid', 250, 'restorative justice', 'FL'), (5, 'Los Angeles Legal Aid', 400, 'criminal justice reform', 'CA'); | Find the number of criminal justice reform cases handled by legal aid organizations in New York | SELECT SUM(cases_handled) FROM legal_aid_organizations WHERE cases_type LIKE '%criminal justice reform%' AND state = 'NY'; | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, name TEXT, country TEXT); INSERT INTO companies (id, name, country) VALUES (1, 'Acme Inc', 'USA'), (2, 'Beta Corp', 'USA'); CREATE TABLE funding (company_id INT, amount INT); INSERT INTO funding (company_id, amount) VALUES (1, 5000000), (2, 7000000); | What is the average funding amount per company founded in the US? | SELECT AVG(funding.amount) FROM funding JOIN companies ON funding.company_id = companies.id WHERE companies.country = 'USA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE security_incidents (id INT, timestamp TIMESTAMP, region VARCHAR(255), incident_type VARCHAR(255)); INSERT INTO security_incidents (id, timestamp, region, incident_type) VALUES (1, '2022-06-01 10:00:00', 'North America', 'Phishing'), (2, '2022-06-01 10:00:00', 'Asia', 'Malware'); | What is the distribution of security incidents by geographical region for the last month? | SELECT region, incident_type, COUNT(*) as incident_count FROM security_incidents WHERE timestamp >= DATE_SUB(CURRENT_TIMESTAMP, INTERVAL 1 MONTH) GROUP BY region, incident_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE buildings (id INT, name TEXT, city TEXT, energy_efficiency FLOAT); INSERT INTO buildings (id, name, city, energy_efficiency) VALUES (1, 'The Shard', 'London', 0.20), (2, '20 Fenchurch Street', 'London', 0.25); | What is the minimum energy efficiency (in kWh/m^2) of buildings in the city 'London'? | SELECT MIN(energy_efficiency) FROM buildings WHERE city = 'London'; | gretelai_synthetic_text_to_sql |
CREATE TABLE EconomicDiversification (id INT, program VARCHAR(20), score FLOAT, year INT); INSERT INTO EconomicDiversification (id, program, score, year) VALUES (1, 'Agriculture', 75.0, 2020), (2, 'Industry', 77.5, 2021), (3, 'Services', 80.0, 2019), (4, 'Tourism', 82.5, 2018), (5, 'Agriculture', 70.0, 2020); | Which economic diversification programs had the lowest score in 2020? | SELECT program, MIN(score) FROM EconomicDiversification WHERE year = 2020 GROUP BY program; | gretelai_synthetic_text_to_sql |
CREATE TABLE attack_vectors (id INT, attack_vector VARCHAR(255), region VARCHAR(255), incident_count INT); INSERT INTO attack_vectors (id, attack_vector, region, incident_count) VALUES (1, 'Phishing', 'APAC', 50), (2, 'Malware', 'APAC', 75), (3, 'SQL Injection', 'APAC', 30), (4, 'Cross-site Scripting', 'APAC', 40), (5, 'DoS/DDoS', 'APAC', 60); | What are the top 5 attack vectors by total count of incidents in the APAC region? | SELECT attack_vector, SUM(incident_count) as total_incidents FROM attack_vectors WHERE region = 'APAC' GROUP BY attack_vector ORDER BY total_incidents DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE building_data (building_id INT, building_type VARCHAR(255), square_footage INT, construction_year INT); | What is the total square footage of commercial buildings that were constructed in 2020 in the 'building_data' table? | select sum(square_footage) as total_square_footage from building_data where building_type = 'commercial' and construction_year = 2020; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA CleanEnergy; CREATE TABLE Projects (project_id INT, name VARCHAR(100), type VARCHAR(50), installed_capacity INT, carbon_offset INT); INSERT INTO CleanEnergy.Projects (project_id, name, type, installed_capacity, carbon_offset) VALUES (1, 'SolarFarm 1', 'Solar', 150000, 5000), (2, 'WindFarm 2', 'Wind', 120000, 7000), (3, 'HydroProject 1', 'Hydro', 180000, 6000); | What are the carbon offsets and renewable energy types for projects with installed capacities greater than 100000 in the 'CleanEnergy' schema? | SELECT type, carbon_offset FROM CleanEnergy.Projects WHERE installed_capacity > 100000; | gretelai_synthetic_text_to_sql |
CREATE TABLE RetailerC (item VARCHAR(20), stock INT); INSERT INTO RetailerC VALUES ('Pants', 400); | How many 'Pants' are in stock with 'Retailer C'? | SELECT SUM(stock) FROM RetailerC WHERE item = 'Pants' AND retailer = 'Retailer C'; | gretelai_synthetic_text_to_sql |
CREATE TABLE drug_approval (drug_name VARCHAR(255), approval_region VARCHAR(255), approval_date DATE); INSERT INTO drug_approval (drug_name, approval_region, approval_date) VALUES ('DrugX', 'Asia-Pacific', '2017-01-01'); | What is the number of drugs approved in the 'Asia-Pacific' region for each year? | SELECT approval_region, YEAR(approval_date) AS year, COUNT(*) FROM drug_approval WHERE approval_region = 'Asia-Pacific' GROUP BY approval_region, year; | gretelai_synthetic_text_to_sql |
CREATE TABLE sales_price (drug_name TEXT, quarter TEXT, year INTEGER, sale_price NUMERIC(10, 2)); INSERT INTO sales_price (drug_name, quarter, year, sale_price) VALUES ('DrugA', 'Q1', 2021, 120.50), ('DrugA', 'Q2', 2021, 125.00), ('DrugB', 'Q1', 2021, 150.75), ('DrugB', 'Q2', 2021, 155.00); | What was the average sales price for each drug by quarter in 2021? | SELECT drug_name, quarter, AVG(sale_price) as avg_sales_price FROM sales_price WHERE year = 2021 GROUP BY drug_name, quarter; | gretelai_synthetic_text_to_sql |
CREATE TABLE green_buildings (id INT, property_price FLOAT, size INT); INSERT INTO green_buildings (id, property_price, size) VALUES (1, 600000, 200), (2, 700000, 250), (3, 800000, 300); | What is the minimum property price per square meter for properties larger than 150 square meters in the green_buildings table? | SELECT MIN(property_price/size) FROM green_buildings WHERE size > 150; | gretelai_synthetic_text_to_sql |
CREATE TABLE city (id INT, name VARCHAR(255)); INSERT INTO city (id, name) VALUES (1, 'Mumbai'); CREATE TABLE restaurant (id INT, name VARCHAR(255), city_id INT); INSERT INTO restaurant (id, name, city_id) VALUES (1, 'Spice Kitchen', 1), (2, 'Pizza Palace', 1), (3, 'Sushi House', 1); CREATE TABLE menu (id INT, item VARCHAR(255), price DECIMAL(5,2), daily_sales INT, restaurant_id INT); | Show the total daily sales for each restaurant in 'Mumbai' | SELECT r.name, SUM(m.daily_sales) as total_sales FROM menu m JOIN restaurant r ON m.restaurant_id = r.id JOIN city c ON r.city_id = c.id WHERE c.name = 'Mumbai' GROUP BY r.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE building_permits (permit_id INT, building_type VARCHAR(20), city VARCHAR(20), issue_date DATE); INSERT INTO building_permits (permit_id, building_type, city, issue_date) VALUES (4, 'Commercial', 'Los Angeles', '2018-04-01'), (5, 'Residential', 'Los Angeles', '2019-07-15'), (6, 'Commercial', 'Los Angeles', '2020-11-05'); | How many permits were issued for commercial buildings in Los Angeles between 2018 and 2020? | SELECT COUNT(*) FROM building_permits WHERE building_type = 'Commercial' AND city = 'Los Angeles' AND issue_date BETWEEN '2018-01-01' AND '2020-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE artists (artist_id INT, name VARCHAR(50), age INT, gender VARCHAR(10)); | Who is the oldest female artist in the 'artists' table? | SELECT name FROM artists WHERE gender = 'female' ORDER BY age DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE union_region (union_id INT, region_id INT, total_members INT); CREATE TABLE regions (region_id INT, region_name TEXT); INSERT INTO union_region (union_id, region_id, total_members) VALUES (1, 1, 100), (2, 1, 200), (3, 2, 300), (4, 2, 400), (5, 3, 500); INSERT INTO regions (region_id, region_name) VALUES (1, 'Region A'), (2, 'Region B'), (3, 'Region C'); | Calculate the average number of members per union in each region. | SELECT regions.region_name, AVG(union_region.total_members) FROM union_region INNER JOIN regions ON union_region.region_id = regions.region_id GROUP BY regions.region_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE ratings (rating_id INT, product_id INT, brand_name VARCHAR(100), rating DECIMAL(3,2)); | Which beauty brands have a high consumer satisfaction rating in the North American region? | SELECT brand_name, AVG(rating) as avg_rating FROM ratings WHERE sale_date >= '2022-01-01' AND country LIKE 'North America%' GROUP BY brand_name ORDER BY avg_rating DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE cosmetics (product_id INT, product_name VARCHAR(100), rating DECIMAL(2,1), is_recyclable BOOLEAN); | What is the average rating of cosmetic products with a recyclable packaging label? | SELECT AVG(rating) FROM cosmetics WHERE is_recyclable = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE regions (id INT, country VARCHAR(255), sales_volume FLOAT); INSERT INTO regions (id, country, sales_volume) VALUES (3, 'Germany', 7000.00); INSERT INTO regions (id, country, sales_volume) VALUES (4, 'Spain', 4000.00); | What is the total revenue for stores in each country, with a 10% discount applied? | SELECT r.country, SUM(s.revenue * 0.9) as total_revenue FROM sales s JOIN regions r ON s.store LIKE CONCAT('%', r.country, '%') GROUP BY r.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE waste (ingredient VARCHAR(255), quantity INT, waste_date DATE); INSERT INTO waste VALUES ('Garlic', 50, '2022-01-01'); INSERT INTO waste VALUES ('Tomatoes', 200, '2022-01-02'); | What is the total waste generated for each ingredient in a given time period? | SELECT i.ingredient, SUM(w.quantity) AS total_waste, w.waste_date FROM waste w INNER JOIN inventory i ON w.ingredient = i.ingredient GROUP BY i.ingredient, w.waste_date; | gretelai_synthetic_text_to_sql |
CREATE TABLE grants (id INT, department VARCHAR(255), year INT, amount DECIMAL(10,2)); INSERT INTO grants (id, department, year, amount) VALUES (1, 'Engineering', 2020, 100000), (2, 'Engineering', 2019, 120000), (3, 'Biology', 2020, 80000); | What is the maximum grant amount awarded to the Engineering department? | SELECT MAX(amount) FROM grants WHERE department = 'Engineering'; | gretelai_synthetic_text_to_sql |
CREATE TABLE marine_species (id INT, region VARCHAR(255)); INSERT INTO marine_species (id, region) VALUES (1, 'Arctic'), (2, 'Antarctic'), (3, 'Indian'); | Identify the number of marine species in the Arctic and Antarctic regions. | SELECT region, COUNT(id) FROM marine_species WHERE region IN ('Arctic', 'Antarctic') GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE actors (id INT, title TEXT, actor TEXT); | What is the name of the actor who has acted in the most movies in the actors table? | SELECT actor FROM actors GROUP BY actor ORDER BY COUNT(*) DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (donor_id INT, donation_amount DECIMAL(10,2), donation_date DATE, donor_name VARCHAR(50)); | What is the maximum and minimum donation amount made by a single donor in 2021? | SELECT donor_id, MAX(donation_amount) FROM donors WHERE donation_date >= '2021-01-01' AND donation_date < '2022-01-01' GROUP BY donor_id; SELECT donor_id, MIN(donation_amount) FROM donors WHERE donation_date >= '2021-01-01' AND donation_date < '2022-01-01' GROUP BY donor_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE company (id INT, name TEXT, founding_year INT, founder_gender TEXT); INSERT INTO company (id, name, founding_year, founder_gender) VALUES (1, 'Delta Inc', 2016, 'female'); INSERT INTO company (id, name, founding_year, founder_gender) VALUES (2, 'Epsilon Corp', 2019, 'male'); INSERT INTO company (id, name, founding_year, founder_gender) VALUES (3, 'Zeta Inc', 2017, 'female'); INSERT INTO company (id, name, founding_year, founder_gender) VALUES (4, 'Eta Corp', 2015, 'non-binary'); INSERT INTO company (id, name, founding_year, founder_gender) VALUES (5, 'Theta Corp', 2014, 'female'); INSERT INTO company (id, name, founding_year, founder_gender) VALUES (6, 'Iota Inc', 2020, 'male'); | What is the total funding amount for companies founded by women in the last 5 years? | SELECT SUM(funding_amount) FROM investment_rounds ir INNER JOIN company c ON ir.company_id = c.id WHERE c.founder_gender = 'female' AND c.founding_year >= YEAR(CURRENT_DATE) - 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE Projects (id INT, name VARCHAR(50), category VARCHAR(50), cost FLOAT, year INT, status VARCHAR(20)); INSERT INTO Projects (id, name, category, cost, year, status) VALUES (1, 'Wind Farm', 'Renewable Energy', 1000000, 2018, 'Completed'), (2, 'Solar Farm', 'Renewable Energy', 1200000, 2019, 'Completed'), (3, 'Geothermal Plant', 'Renewable Energy', 1500000, 2020, 'In Progress'), (4, 'Hydroelectric Dam', 'Renewable Energy', 2000000, 2021, 'Planned'); | How many projects were completed in 'Renewable Energy' category each year? | SELECT category, year, COUNT(*) FROM Projects WHERE category = 'Renewable Energy' AND status = 'Completed' GROUP BY category, year; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donors (DonorID INT, DonorName VARCHAR(50), DonationAmount DECIMAL(10,2), CauseID INT, Age INT);CREATE TABLE Causes (CauseID INT, CauseName VARCHAR(50)); | Which causes received the most donations from donors aged 30-40? | SELECT C.CauseName, SUM(D.DonationAmount) FROM Donors D JOIN Causes C ON D.CauseID = C.CauseID WHERE D.Age BETWEEN 30 AND 40 GROUP BY C.CauseName ORDER BY SUM(D.DonationAmount) DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE art_forms_2 (id INT, name TEXT, type TEXT, num_practitioners INT, location TEXT); INSERT INTO art_forms_2 (id, name, type, num_practitioners, location) VALUES (1, 'Ukiyo-e', 'Printmaking', 400, 'Asia'), (2, 'Kabuki', 'Theater', 600, 'Asia'), (3, 'Ikebana', 'Flower Arrangement', 700, 'Asia'); | Which traditional arts have the highest number of active practitioners in Asia? | SELECT name FROM art_forms_2 WHERE location = 'Asia' AND num_practitioners = (SELECT MAX(num_practitioners) FROM art_forms_2 WHERE location = 'Asia'); | gretelai_synthetic_text_to_sql |
CREATE TABLE vessels (vessel_id INT, name VARCHAR(50), type VARCHAR(50)); INSERT INTO vessels (vessel_id, name, type) VALUES (1, 'MV Ocean Wave', 'Container Ship'), (2, 'MS Ocean Breeze', 'Tanker'), (3, 'MV Ocean Tide', 'Tanker'); | What is the type of the vessel with ID 2 in the 'vessels' table? | SELECT type FROM vessels WHERE vessel_id = 2; | gretelai_synthetic_text_to_sql |
CREATE TABLE artists (artist_id INT, name VARCHAR(50), genre VARCHAR(50)); INSERT INTO artists (artist_id, name, genre) VALUES (1, 'Claude Monet', 'Painting'); CREATE TABLE art_pieces (art_piece_id INT, title VARCHAR(50), year_made INT, artist_id INT); INSERT INTO art_pieces (art_piece_id, title, year_made, artist_id) VALUES (1, 'Water Lilies', 1906, 1); | Which artists have not created any art pieces? | SELECT a.name FROM artists a LEFT JOIN art_pieces ap ON a.artist_id = ap.artist_id WHERE ap.art_piece_id IS NULL; | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_offsets (country VARCHAR(255), program VARCHAR(255)); INSERT INTO carbon_offsets (country, program) VALUES ('US', 'Tree Planting'), ('US', 'Renewable Energy'), ('Canada', 'Tree Planting'), ('Germany', 'Energy Efficiency'); | How many carbon offset programs have been implemented in each country? | SELECT country, COUNT(program) AS num_programs FROM carbon_offsets GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE athletes (athlete_id INT, name VARCHAR(50)); INSERT INTO athletes (athlete_id, name) VALUES (1, 'John Doe'); CREATE TABLE stadiums (stadium_id INT, name VARCHAR(50)); INSERT INTO stadiums (stadium_id, name) VALUES (1, 'Yankee Stadium'); | Which athletes in the 'Athletes' table have the same name as a stadium in the 'Stadiums' table? | SELECT a.name FROM athletes a INNER JOIN stadiums s ON a.name = s.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE Donations (DonationID INT, DonorID INT, Amount FLOAT, DonationDate DATE); INSERT INTO Donations (DonationID, DonorID, Amount, DonationDate) VALUES (1, 1, 500.00, '2021-01-01'), (2, 1, 250.00, '2021-02-14'); | What was the average donation amount per month in 2021, sorted by month? | SELECT MONTH(DonationDate) as Month, AVG(Amount) as AvgDonation FROM Donations WHERE YEAR(DonationDate) = 2021 GROUP BY Month ORDER BY Month; | gretelai_synthetic_text_to_sql |
CREATE TABLE refugee_support (refugee_id INT, organization_id INT, age INT, gender VARCHAR(10), support_date DATE); INSERT INTO refugee_support (refugee_id, organization_id, age, gender, support_date) VALUES (1, 201, 23, 'Male', '2021-01-12'), (2, 201, 30, 'Female', '2021-02-03'), (3, 202, 18, 'Male', '2021-03-25'), (4, 203, 45, 'Female', '2021-01-05'); | How many refugees were supported by each organization by age group and gender in Q1 2021? | SELECT organization_id, gender, age_group, COUNT(*) as supported_refugees FROM (SELECT organization_id, gender, CASE WHEN age <= 17 THEN 'Minor' WHEN age BETWEEN 18 AND 64 THEN 'Adult' ELSE 'Senior' END as age_group FROM refugee_support WHERE EXTRACT(QUARTER FROM support_date) = 1 AND EXTRACT(YEAR FROM support_date) = 2021) t GROUP BY organization_id, gender, age_group; | gretelai_synthetic_text_to_sql |
CREATE TABLE Accommodations (ID INT, Type VARCHAR(50), Cost FLOAT, Disability VARCHAR(50), Region VARCHAR(50)); INSERT INTO Accommodations (ID, Type, Cost, Disability, Region) VALUES (1, 'Note-taking Services', 1000.0, 'Learning Disability', 'Midwest'), (2, 'Extra Time for Exams', 1200.0, 'Learning Disability', 'Midwest'); CREATE TABLE SupportPrograms (ID INT, Type VARCHAR(50), Cost FLOAT, Disability VARCHAR(50), Region VARCHAR(50)); INSERT INTO SupportPrograms (ID, Type, Cost, Disability, Region) VALUES (1, 'Tutoring Services', 1500.0, 'Learning Disability', 'Midwest'), (2, 'Assistive Technology', 2000.0, 'Learning Disability', 'Midwest'); | What is the total budget for accommodations and support programs for students with learning disabilities in the Midwest? | SELECT SUM(A.Cost) + SUM(S.Cost) FROM Accommodations A, SupportPrograms S WHERE A.Disability = 'Learning Disability' AND S.Disability = 'Learning Disability' AND A.Region = 'Midwest' AND S.Region = 'Midwest'; | gretelai_synthetic_text_to_sql |
CREATE TABLE music_sales (id INT, title VARCHAR(255), genre VARCHAR(50), revenue FLOAT); INSERT INTO music_sales (id, title, genre, revenue) VALUES (1, 'Song1', 'Pop', 25000.0), (2, 'Song2', 'Rock', 30000.0), (3, 'Song3', 'Pop', 20000.0); | What is the total revenue for the 'Pop' genre in the 'music_sales' table? | SELECT SUM(revenue) FROM music_sales WHERE genre = 'Pop'; | gretelai_synthetic_text_to_sql |
CREATE TABLE claims (policyholder_id INT, claim_number INT, state VARCHAR(2)); INSERT INTO claims (policyholder_id, claim_number, state) VALUES (1, 1, 'MI'), (2, 1, 'MI'), (3, 1, 'OH'); | Identify policyholders who have never made a claim in Michigan | SELECT policyholder_id FROM claims WHERE state = 'MI' GROUP BY policyholder_id HAVING COUNT(claim_number) = 1; | gretelai_synthetic_text_to_sql |
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