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 sales_data (drug_name TEXT, region TEXT, sales INTEGER); | Determine the market share of each drug in a specific sales region. | SELECT drug_name, SUM(sales) OVER (PARTITION BY region) / SUM(SUM(sales)) OVER () AS market_share FROM sales_data WHERE region = 'RegionA' GROUP BY drug_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE drug_info (drug_name TEXT, manufacturer TEXT); | Who is the manufacturer of 'DrugD'? | SELECT manufacturer FROM drug_info WHERE drug_name = 'DrugD'; | gretelai_synthetic_text_to_sql |
CREATE TABLE public.healthcare_access (id SERIAL PRIMARY KEY, state TEXT, city TEXT, facility_type TEXT, patients_served INT, rating INT); INSERT INTO public.healthcare_access (state, city, facility_type, patients_served, rating) VALUES ('California', 'San Francisco', 'Urgent Care', 6000, 6), ('New York', 'New York City', 'Hospital', 15000, 9), ('California', 'Los Angeles', 'Clinic', 7500, 7); | What is the distribution of healthcare facilities by type and patients served, for facilities serving over 7000 patients? | SELECT facility_type, patients_served, COUNT(*) FROM public.healthcare_access WHERE patients_served > 7000 GROUP BY facility_type, patients_served; | gretelai_synthetic_text_to_sql |
CREATE TABLE teams (team_id INT, team_name VARCHAR(255)); INSERT INTO teams (team_id, team_name) VALUES (1, 'Knicks'); CREATE TABLE venues (venue_id INT, venue_name VARCHAR(255)); INSERT INTO venues (venue_id, venue_name) VALUES (1, 'Madison Square Garden'); CREATE TABLE games (game_id INT, team_id INT, venue_id INT, game_date DATE); INSERT INTO games (game_id, team_id, venue_id, game_date) VALUES (1, 1, 1, '2020-01-01'); | What is the total number of basketball games played by the Knicks at Madison Square Garden? | SELECT COUNT(*) FROM games INNER JOIN teams ON games.team_id = teams.team_id INNER JOIN venues ON games.venue_id = venues.venue_id WHERE teams.team_name = 'Knicks' AND venues.venue_name = 'Madison Square Garden'; | gretelai_synthetic_text_to_sql |
CREATE TABLE schools (school_id INT, school_name VARCHAR(255)); INSERT INTO schools (school_id, school_name) VALUES (1, 'School A'), (2, 'School B'); CREATE TABLE students (student_id INT, school_id INT, mental_health_score INT); INSERT INTO students (student_id, school_id, mental_health_score) VALUES (1, 1, 80), (2, 1, 85), (3, 2, 70), (4, 2, 75); | What is the average mental health score of students in each school? | SELECT s.school_name, AVG(st.mental_health_score) as avg_mental_health_score FROM students st JOIN schools s ON st.school_id = s.school_id GROUP BY s.school_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE renewable_energy (id INT, country VARCHAR(50), source VARCHAR(50)); INSERT INTO renewable_energy (id, country, source) VALUES (1, 'Germany', 'Solar'), (2, 'US', 'Wind'), (3, 'Germany', 'Wind'), (4, 'France', 'Hydro'), (5, 'US', 'Solar'), (6, 'Germany', 'Hydro'); | How many renewable energy sources are there in each country, listed in the 'renewable_energy' table? | SELECT r.country, COUNT(DISTINCT r.source) as num_sources FROM renewable_energy r GROUP BY r.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE property_coowners (property_id INT, coowner VARCHAR(255)); INSERT INTO property_coowners (property_id, coowner) VALUES (1, 'John Doe'), (1, 'Jane Smith'), (2, 'Jane Smith'), (2, 'Mike Johnson'), (3, 'John Doe'); | Identify the unique co-owners across all properties. | SELECT DISTINCT coowner FROM property_coowners; | gretelai_synthetic_text_to_sql |
CREATE TABLE FestivalArtists (id INT, festival VARCHAR(20), year INT, artist VARCHAR(50), age INT); INSERT INTO FestivalArtists (id, festival, year, artist, age) VALUES (1, 'Coachella', 2022, 'Billie Eilish', 20), (2, 'Coachella', 2022, 'Harry Styles', 28); | What was the average age of artists who performed at Coachella in 2022? | SELECT AVG(age) FROM FestivalArtists WHERE festival = 'Coachella' AND year = 2022; | gretelai_synthetic_text_to_sql |
CREATE TABLE Feedback (Area TEXT, Year INTEGER, Feedback_Score INTEGER); INSERT INTO Feedback (Area, Year, Feedback_Score) VALUES ('Urban', 2021, 80), ('Urban', 2022, 85), ('Rural', 2021, 70), ('Rural', 2022, 75); | What was the citizen feedback score for public service delivery in urban and rural areas in 2021? | SELECT Area, AVG(Feedback_Score) FROM Feedback WHERE Year = 2021 GROUP BY Area; | gretelai_synthetic_text_to_sql |
CREATE TABLE LanguagePrograms (id INT, language VARCHAR(255), program VARCHAR(255), funding FLOAT); INSERT INTO LanguagePrograms (id, language, program, funding) VALUES (1, 'Spanish', 'Language Immersion', 20000), (2, 'French', 'Bilingual Education', 15000), (3, 'Mandarin', 'Community Workshops', 12000); | Which languages are preserved by the most programs and what is their total funding? | SELECT language, COUNT(*), SUM(funding) FROM LanguagePrograms GROUP BY language; | gretelai_synthetic_text_to_sql |
CREATE TABLE matches (id INT, team1 TEXT, team2 TEXT, match_date DATE); INSERT INTO matches (id, team1, team2, match_date) VALUES (1, 'India', 'England', '2021-07-01'), (2, 'India', 'Australia', '2022-02-12'); | How many matches has the Indian women's cricket team played in the last 5 years? | SELECT COUNT(*) FROM matches WHERE (team1 = 'India' OR team2 = 'India') AND match_date >= DATE_SUB(CURRENT_DATE, INTERVAL 5 YEAR); | gretelai_synthetic_text_to_sql |
CREATE SCHEMA if not exists bioprocess_biotech; CREATE TABLE if not exists bioprocess_biotech.projects (id INT, name VARCHAR(100), duration INT); INSERT INTO bioprocess_biotech.projects (id, name, duration) VALUES (1, 'Protein Production', 18), (2, 'Cell Culture', 15), (3, 'Fermentation', 9), (4, 'Bioprocess Optimization', 24); CREATE TABLE if not exists bioprocess_biotech.startups (id INT, name VARCHAR(100), location VARCHAR(50), funding DECIMAL(10,2), project_duration INT); INSERT INTO bioprocess_biotech.startups (id, name, location, funding, project_duration) VALUES (1, 'Genetech', 'San Francisco', 2500000.00, 18), (2, 'IncellDX', 'New York', 1500000.00, 15), (3, 'BiotechNY', 'New York', 5000000.00, 24); | List the bioprocess engineering projects for a specific duration, and show the average funding for biotech startups in the same duration range. | SELECT p.duration_range, AVG(startups.funding) as avg_funding FROM (SELECT projects.duration as duration_range FROM bioprocess_biotech.projects WHERE projects.duration BETWEEN 10 AND 20) p JOIN bioprocess_biotech.startups ON p.duration_range = startups.project_duration GROUP BY p.duration_range; | gretelai_synthetic_text_to_sql |
CREATE TABLE Volunteer_Info (VolunteerID INT, First_Name VARCHAR(50), Last_Name VARCHAR(50), Gender VARCHAR(10)); | Determine the total number of volunteers for each gender, from the 'Volunteer_Info' table, grouped by Gender. | SELECT Gender, COUNT(*) AS Number_Of_Volunteers FROM Volunteer_Info GROUP BY Gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE programs (id INT, name VARCHAR(50), institution_id INT, category VARCHAR(20)); INSERT INTO programs (id, name, institution_id, category) VALUES (1, 'Budgeting Workshop', 1, 'Financial Wellbeing'); CREATE TABLE financial_institutions (id INT, name VARCHAR(50)); INSERT INTO financial_institutions (id, name) VALUES (1, 'Bank of America'); | Identify the total number of financial wellbeing programs offered by each financial institution, along with the name of the institution. | SELECT financial_institutions.name, COUNT(programs.id) FROM programs INNER JOIN financial_institutions ON programs.institution_id = financial_institutions.id GROUP BY financial_institutions.name; | gretelai_synthetic_text_to_sql |
CREATE TABLE menu_sales_6 (menu_category VARCHAR(255), sale_date DATE, revenue INT); INSERT INTO menu_sales_6 (menu_category, sale_date, revenue) VALUES ('Appetizers', '2022-02-23', 1200), ('Appetizers', '2022-02-24', 1500), ('Entrees', '2022-02-23', 3000), ('Entrees', '2022-02-24', 3500); | Find the lowest revenue day for each menu category in February 2022. | SELECT menu_category, MIN(revenue) FROM menu_sales_6 WHERE sale_date BETWEEN '2022-02-01' AND '2022-02-28' GROUP BY menu_category; | gretelai_synthetic_text_to_sql |
CREATE TABLE paris_art(id INT, museum VARCHAR(30), category VARCHAR(30), revenue INT); INSERT INTO paris_art VALUES (1, 'Louvre', 'Painting', 500000); INSERT INTO paris_art VALUES (2, 'd''Orsay', 'Sculpture', 300000); | What is the total revenue generated by each art category in the museums in Paris? | SELECT category, SUM(revenue) FROM paris_art GROUP BY category; | gretelai_synthetic_text_to_sql |
CREATE TABLE mining_sites(id INT, site VARCHAR(50), accidents INT); INSERT INTO mining_sites (id, site, accidents) VALUES (1, 'Coal Mine', 1), (2, 'Gold Mine', 0), (3, 'Surface', 5), (4, 'Underground', 3); | How many accidents occurred at the 'Coal Mine' and 'Gold Mine' mining sites? | SELECT SUM(accidents) FROM mining_sites WHERE site IN ('Coal Mine', 'Gold Mine'); | gretelai_synthetic_text_to_sql |
CREATE TABLE production (element VARCHAR(10), year INT, month INT, quantity INT); INSERT INTO production (element, year, month, quantity) VALUES ('Lanthanum', 2015, 1, 100), ('Lanthanum', 2015, 2, 110), ('Lanthanum', 2016, 1, 120), ('Lanthanum', 2016, 2, 130), ('Cerium', 2015, 1, 140), ('Cerium', 2015, 2, 150), ('Cerium', 2016, 1, 160), ('Cerium', 2016, 2, 170); | Determine the percentage change in monthly production of Lanthanum and Cerium from 2015 to 2016 | SELECT element, (SUM(quantity * CASE WHEN year = 2016 THEN 1 ELSE -1 END) / SUM(quantity) * 100) AS percentage_change FROM production WHERE element IN ('Lanthanum', 'Cerium') GROUP BY element; | gretelai_synthetic_text_to_sql |
CREATE TABLE chemical_plants (id INT, name TEXT, region TEXT, safety_score INT); INSERT INTO chemical_plants (id, name, region, safety_score) VALUES (1, 'Plant A', 'Northeast', 92), (2, 'Plant B', 'Midwest', 88), (3, 'Plant C', 'West', 95); | What are the average safety scores for each chemical plant by region? | SELECT region, AVG(safety_score) FROM chemical_plants GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE Satellites (satellite_id INT, name VARCHAR(255), country VARCHAR(255), altitude FLOAT, constellation VARCHAR(255)); INSERT INTO Satellites (satellite_id, name, country, altitude, constellation) VALUES (1, 'Ibuki', 'Japan', 600, 'Earth Observation'), (2, 'H-II Transfer Vehicle', 'Japan', 400, 'Supply Vehicle'), (3, 'Kaguya', 'Japan', 100, 'Lunar Exploration'); | What is the minimum altitude of Japanese satellites? | SELECT MIN(altitude) FROM Satellites WHERE country = 'Japan'; | gretelai_synthetic_text_to_sql |
CREATE TABLE donations (donation_date DATE, donation_amount DECIMAL(10, 2)); INSERT INTO donations (donation_date, donation_amount) VALUES ('2022-01-01', 500.00), ('2022-02-01', 0.00), ('2022-03-01', 700.00), ('2022-04-01', 200.00); | What is the average donation amount per month, for the last 12 months, excluding records with a donation amount of 0? | SELECT AVG(donation_amount) as avg_donation_amount FROM (SELECT donation_amount FROM donations WHERE donation_date >= DATEADD(year, -1, GETDATE()) AND donation_amount > 0) t GROUP BY DATEPART(year, donation_date), DATEPART(month, donation_date); | gretelai_synthetic_text_to_sql |
CREATE TABLE new_york_water_usage (id INT, building_type VARCHAR(20), water_consumption FLOAT, month VARCHAR(10)); INSERT INTO new_york_water_usage (id, building_type, water_consumption, month) VALUES (1, 'Industrial', 20000, 'January'), (2, 'Industrial', 25000, 'February'); | What is the total water consumption for industrial buildings in New York for each month? | SELECT month, SUM(water_consumption) FROM new_york_water_usage WHERE building_type = 'Industrial' GROUP BY month; | gretelai_synthetic_text_to_sql |
CREATE TABLE wastewater_treatment ( id INT PRIMARY KEY, location VARCHAR(255), treatment_date DATE, water_volume INT); | Delete wastewater treatment records that are older than 5 years | DELETE FROM wastewater_treatment WHERE treatment_date < DATE_SUB(CURDATE(), INTERVAL 5 YEAR); | gretelai_synthetic_text_to_sql |
CREATE TABLE astronauts(id INT, name VARCHAR(50), age INT, last_mission_year INT); INSERT INTO astronauts VALUES(1, 'John Glenn', 77, 1998), (2, 'Peggy Whitson', 62, 2018); | What is the maximum age of astronauts at their last space mission? | SELECT MAX(age - last_mission_year) FROM astronauts; | gretelai_synthetic_text_to_sql |
CREATE TABLE train_lines (line_id INT, city VARCHAR(50)); INSERT INTO train_lines (line_id, city) VALUES (1, 'London'), (2, 'London'); CREATE TABLE trains (train_id INT, line_id INT, station VARCHAR(50)); INSERT INTO trains (train_id, line_id, station) VALUES (1, 1, 'Victoria'), (2, 1, 'Waterloo'), (3, 2, 'Paddington'); | What is the number of trains that passed through a specific station in London? | SELECT COUNT(*) FROM trains WHERE station = 'Victoria'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Satellites (SatelliteID INT, Name VARCHAR(100), Manufacturer VARCHAR(50), LaunchDate DATE); | How many satellites have been deployed by Aerospace Corp in the last 5 years? | SELECT COUNT(*) FROM Satellites WHERE Manufacturer = 'Aerospace Corp' AND LaunchDate >= DATEADD(year, -5, GETDATE()); | gretelai_synthetic_text_to_sql |
CREATE TABLE company (id INT, name TEXT, industry TEXT, founding_year INT, founder_race TEXT, exit_strategy TEXT); | List the number of companies founded by people from underrepresented racial backgrounds in the retail sector that have had successful exit strategies. | SELECT COUNT(id) FROM company WHERE industry = 'Retail' AND founder_race IN ('Black', 'Latinx', 'Indigenous') AND exit_strategy = 'Successful' | gretelai_synthetic_text_to_sql |
CREATE TABLE wildlife_sightings (species TEXT, location TEXT, date DATE); INSERT INTO wildlife_sightings (species, location, date) VALUES ('Polar Bear', 'Canadian Arctic Archipelago', '2022-01-01'), ('Narwhal', 'Canadian Arctic Archipelago', '2022-01-02'); | What is the number of wildlife sightings in the Canadian Arctic Archipelago in 2022? | SELECT COUNT(*) FROM wildlife_sightings WHERE location = 'Canadian Arctic Archipelago' AND date BETWEEN '2022-01-01' AND '2022-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE solar_plants (id INT, name VARCHAR(255), prefecture VARCHAR(255), power_output FLOAT, production DATE); | What is the total energy production from solar power plants in Japan, and how does it break down by prefecture? | SELECT prefecture, SUM(power_output) FROM solar_plants WHERE country = 'Japan' GROUP BY prefecture; | gretelai_synthetic_text_to_sql |
CREATE TABLE drone_production (id INT, country VARCHAR(255), year INT, production_count INT); INSERT INTO drone_production (id, country, year, production_count) VALUES (1, 'United States', 2017, 1234), (2, 'United States', 2018, 2000), (3, 'United States', 2019, 3000), (4, 'United States', 2020, 4000); | How many military drones were produced in the United States between 2018 and 2020? | SELECT SUM(production_count) FROM drone_production WHERE country = 'United States' AND year BETWEEN 2018 AND 2020; | gretelai_synthetic_text_to_sql |
CREATE TABLE Users (UserID INT, Age INT, UsedTech4Good BOOLEAN); INSERT INTO Users (UserID, Age, UsedTech4Good) VALUES (1, 34, true), (2, 45, false), (3, 29, true); | What is the maximum age of users who have used technology for social good? | SELECT MAX(Age) FROM Users WHERE UsedTech4Good = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE community_health_workers (worker_id INT, name VARCHAR(50), region VARCHAR(25)); INSERT INTO community_health_workers (worker_id, name, region) VALUES (1, 'John Doe', 'Northeast'), (2, 'Jane Smith', 'Southeast'), (3, 'Maria Garcia', 'Midwest'); CREATE TABLE regions (region VARCHAR(25), community VARCHAR(50)); INSERT INTO regions (region, community) VALUES ('Northeast', 'Community A'), ('Southeast', 'Community B'), ('Midwest', 'Community C'); | Who are the community health workers serving each region? | SELECT c.name, r.community FROM community_health_workers c INNER JOIN regions r ON c.region = r.region; | gretelai_synthetic_text_to_sql |
CREATE TABLE humanitarian_operations (operation_id INT, country VARCHAR(50), spending INT); INSERT INTO humanitarian_operations (operation_id, country, spending) VALUES (1, 'United States', 5000000), (2, 'Mexico', 3000000), (3, 'Chile', 2000000); CREATE TABLE countries (country VARCHAR(50), population INT); INSERT INTO countries (country, population) VALUES ('United States', 331002651), ('Mexico', 126577691), ('Chile', 19116209); | Which countries have participated in humanitarian assistance operations and what is their total spending? | SELECT co.country, SUM(ho.spending) as total_spending FROM humanitarian_operations ho JOIN countries co ON ho.country = co.country GROUP BY co.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE Cases (ID INT, CaseNumber INT, Date DATE, Resolution VARCHAR(255)); INSERT INTO Cases (ID, CaseNumber, Date, Resolution) VALUES (1, 12345, '2022-01-01', 'Restorative Justice'), (2, 67890, '2022-02-15', 'Trial'), (3, 111213, '2022-03-28', 'Mediation'); | What is the number of cases resolved using each type of resolution method in the last year? | SELECT Resolution, COUNT(*) as CasesResolved FROM Cases WHERE Date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR) GROUP BY Resolution; | gretelai_synthetic_text_to_sql |
CREATE TABLE organizations (id INT, industry VARCHAR(20), projects INT); INSERT INTO organizations (id, industry, projects) VALUES (1, 'technology', 15), (2, 'finance', 8), (3, 'healthcare', 12); | How many organizations are working on ethical AI in the technology industry? | SELECT COUNT(*) FROM organizations WHERE industry = 'technology' AND projects > 10; | gretelai_synthetic_text_to_sql |
CREATE TABLE renewable_energy_projects (project_id INT, project_name VARCHAR(255), state VARCHAR(255), project_type VARCHAR(255), installed_capacity FLOAT); | What is the total installed capacity of renewable energy projects in the state of Texas, broken down by project type? | SELECT project_type, SUM(installed_capacity) FROM renewable_energy_projects WHERE state = 'Texas' GROUP BY project_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE model_categories (model_name TEXT, train_year INTEGER, category TEXT); INSERT INTO model_categories (model_name, train_year, category) VALUES ('model1', 2018, 'creative_ai'), ('model2', 2020, 'explainable_ai'), ('model3', 2019, 'creative_ai'), ('model4', 2021, 'algorithmic_fairness'); | Find the number of models that were trained after 2019 and belong to the 'creative_ai' category. | SELECT COUNT(*) FROM model_categories WHERE train_year > 2019 AND category = 'creative_ai'; | gretelai_synthetic_text_to_sql |
CREATE TABLE projects (id INT PRIMARY KEY, project_name TEXT, project_category TEXT, cost FLOAT); INSERT INTO projects (id, project_name, project_category, cost) VALUES (1, 'Building Schools', 'Infrastructure Development', 500000); | Delete all records with the project_category 'Infrastructure Development' from the projects table. | DELETE FROM projects WHERE project_category = 'Infrastructure Development'; | gretelai_synthetic_text_to_sql |
CREATE TABLE TextileSourcing (country VARCHAR(20), material VARCHAR(20), quantity INT, is_organic BOOLEAN); INSERT INTO TextileSourcing VALUES ('India', 'Cotton', 4000, TRUE), ('Bangladesh', 'Cotton', 3000, TRUE), ('China', 'Silk', 5000, FALSE); | What is the total quantity of organic cotton textiles sourced from India and Bangladesh? | SELECT SUM(quantity) FROM TextileSourcing WHERE (country = 'India' OR country = 'Bangladesh') AND material = 'Cotton' AND is_organic = TRUE; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (donor_id INT, donor_name TEXT, donation_amount FLOAT, cause TEXT, donation_date DATE); | How many donations were made to children's charities between '2021-04-01' and '2021-06-30'? | SELECT COUNT(*) FROM donors WHERE cause = 'Children''s Charities' AND donation_date BETWEEN '2021-04-01' AND '2021-06-30'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Individuals (ID INT, Name VARCHAR(255), Age INT, Region VARCHAR(255), FinanciallyCapable BOOLEAN); INSERT INTO Individuals (ID, Name, Age, Region, FinanciallyCapable) VALUES (1, 'John', 30, 'Region1', true), (2, 'Jane', 25, 'Region2', false), (3, 'Mike', 45, 'Region1', true); | What is the percentage of financially capable individuals in each region, ordered by the percentage in descending order? | SELECT Region, COUNT(*) FILTER (WHERE FinanciallyCapable = true) * 100.0 / COUNT(*) as Percentage, RANK() OVER (ORDER BY Percentage DESC) as Rank FROM Individuals GROUP BY Region; | gretelai_synthetic_text_to_sql |
CREATE TABLE Military_Vehicles (id INT, country VARCHAR(50), type VARCHAR(50), maintenance_cost FLOAT); | What is the maximum maintenance cost for military vehicles in Europe? | SELECT MAX(maintenance_cost) FROM Military_Vehicles WHERE country = 'Europe'; | gretelai_synthetic_text_to_sql |
CREATE TABLE DeListing (AnimalID INT, AnimalName VARCHAR(50), DeListed INT, Location VARCHAR(50)); INSERT INTO DeListing (AnimalID, AnimalName, DeListed, Location) VALUES (1, 'Koala', 300, 'Australia'); INSERT INTO DeListing (AnimalID, AnimalName, DeListed, Location) VALUES (2, 'Wallaby', 250, 'Australia'); | How many animals have been de-listed from the endangered species list in Australia? | SELECT SUM(DeListed) FROM DeListing WHERE Location = 'Australia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE users (id INT, name VARCHAR(50), age INT, city VARCHAR(50)); INSERT INTO users (id, name, age, city) VALUES (1, 'Alice', 30, 'New York'); INSERT INTO users (id, name, age, city) VALUES (2, 'Bob', 25, 'Los Angeles'); INSERT INTO users (id, name, age, city) VALUES (3, 'Charlie', 35, 'New York'); | What is the total number of users by city? | SELECT city, COUNT(*) as total_users FROM users GROUP BY city; | gretelai_synthetic_text_to_sql |
CREATE TABLE revenue (game_id INT, team VARCHAR(255), city VARCHAR(255), date DATE, revenue DECIMAL(10,2)); INSERT INTO revenue (game_id, team, city, date, revenue) VALUES (1, 'Chicago Cubs', 'Chicago', '2023-04-02', 1200000), (2, 'Chicago White Sox', 'Chicago', '2023-04-03', 1300000); | What is the total revenue generated from baseball games in Chicago? | SELECT SUM(revenue) FROM revenue WHERE city = 'Chicago' AND sport = 'Baseball'; | gretelai_synthetic_text_to_sql |
CREATE SCHEMA if not exists genetic_research;CREATE TABLE if not exists genetic_research.projects(id INT, name TEXT, lead_researcher TEXT, disease_category TEXT);INSERT INTO genetic_research.projects (id, name, lead_researcher, disease_category) VALUES (1, 'ProjectX', 'Dr. Jane Smith', 'Cancer'), (2, 'ProjectY', 'Dr. John Doe', 'Neurological Disorders'), (3, 'ProjectZ', 'Dr. Maria Garcia', 'Cancer'); | List the genetic research projects by disease category. | SELECT disease_category, name FROM genetic_research.projects; | gretelai_synthetic_text_to_sql |
CREATE TABLE security_incidents (id INT, incident_date DATE, user_id INT, threat_type VARCHAR(50)); INSERT INTO security_incidents (id, incident_date, user_id, threat_type) VALUES (1, '2022-01-01', 1, 'Malware'), (2, '2022-01-05', 2, 'Phishing'), (3, '2022-01-10', 1, 'Ransomware'); CREATE TABLE users (id INT, username VARCHAR(50)); INSERT INTO users (id, username) VALUES (1, 'user1'), (2, 'user2'), (3, 'user3'); | Who are the top 5 users with the most security incidents in the past month? | SELECT u.username, COUNT(*) as incident_count FROM security_incidents s JOIN users u ON s.user_id = u.id WHERE incident_date >= DATEADD(month, -1, GETDATE()) GROUP BY u.username ORDER BY incident_count DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE Port (PortID INT, PortName VARCHAR(100), City VARCHAR(100), Country VARCHAR(100)); INSERT INTO Port (PortID, PortName, City, Country) VALUES (1, 'Port of Los Angeles', 'Los Angeles', 'USA'); INSERT INTO Port (PortID, PortName, City, Country) VALUES (2, 'Port of Rotterdam', 'Rotterdam', 'Netherlands'); CREATE TABLE Cargo (CargoID INT, CargoName VARCHAR(100), PortID INT, Weight INT, Volume INT); INSERT INTO Cargo (CargoID, CargoName, PortID, Weight, Volume) VALUES (1, 'Container 1', 1, 15000, 5000); INSERT INTO Cargo (CargoID, CargoName, PortID, Weight, Volume) VALUES (2, 'Container 2', 2, 18000, 5500); CREATE TABLE PortCargo (PortID INT, CargoID INT, Weight INT, Volume INT); INSERT INTO PortCargo (PortID, CargoID, Weight, Volume) VALUES (1, 1, 15000, 5000); INSERT INTO PortCargo (PortID, CargoID, Weight, Volume) VALUES (2, 2, 18000, 5500); | What is the percentage of total cargo weight that each cargo item represents, per port, in descending order? | SELECT PortID, CargoID, Weight, Volume, PERCENT_RANK() OVER(PARTITION BY PortID ORDER BY SUM(Weight) OVER(PARTITION BY PortID) DESC) AS WeightPercentage FROM PortCargo ORDER BY PortID, WeightPercentage DESC | gretelai_synthetic_text_to_sql |
CREATE TABLE restaurant (restaurant_id INTEGER, last_inspection_date DATE); INSERT INTO restaurant (restaurant_id, last_inspection_date) VALUES (1, '2022-05-01'), (2, '2023-02-01'), (3, '2023-03-15'); | Determine the number of days since the last food safety inspection for each restaurant. | SELECT restaurant_id, DATEDIFF('day', last_inspection_date, CURRENT_DATE) AS days_since_last_inspection FROM restaurant; | gretelai_synthetic_text_to_sql |
CREATE TABLE wastewater_treatment (region VARCHAR(50), date DATE, volume FLOAT); INSERT INTO wastewater_treatment (region, date, volume) VALUES ('Lima', '2020-01-01', 500), ('Lima', '2020-02-01', 550), ('Lima', '2020-03-01', 600); | Calculate the total volume of wastewater treated in 'Lima' for each month of the year 2020 | SELECT date, SUM(volume) FROM wastewater_treatment WHERE region = 'Lima' AND date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY date; | gretelai_synthetic_text_to_sql |
CREATE TABLE startups (id INT, name VARCHAR(50), location VARCHAR(50), funding FLOAT); INSERT INTO startups (id, name, location, funding) VALUES (1, 'StartupA', 'USA', 15000000); INSERT INTO startups (id, name, location, funding) VALUES (2, 'StartupB', 'USA', 22000000); | What is the average funding amount for biotech startups in the USA? | SELECT AVG(funding) FROM startups WHERE location = 'USA'; | gretelai_synthetic_text_to_sql |
CREATE TABLE country_emissions (mine_id INT, co2_emissions INT, country TEXT); INSERT INTO country_emissions (mine_id, co2_emissions, country) VALUES (1, 5000, 'Canada'); INSERT INTO country_emissions (mine_id, co2_emissions, country) VALUES (2, 7000, 'Mexico'); | What is the total CO2 emissions for each country where mining operations are present? | SELECT country, SUM(co2_emissions) FROM country_emissions GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE JobOffers2 (OfferID INT, HiringManager VARCHAR(50), CandidateRaceEthnicity VARCHAR(50), DateOffered DATE); | What is the percentage of job offers made to candidates who identify as members of underrepresented racial or ethnic groups, by hiring manager? | SELECT HiringManager, COUNT(*) * 100.0 / (SELECT COUNT(*) FROM JobOffers2 WHERE CandidateRaceEthnicity NOT IN ('White', 'Asian')) as Percentage_Underrepresented FROM JobOffers2 WHERE CandidateRaceEthnicity NOT IN ('White', 'Asian') GROUP BY HiringManager; | gretelai_synthetic_text_to_sql |
CREATE TABLE graduate_students (student_id INT, name VARCHAR(50), country VARCHAR(50)); | How many students from each country are enrolled in graduate programs? | SELECT gs.country, COUNT(*) AS num_students FROM graduate_students gs GROUP BY gs.country; | gretelai_synthetic_text_to_sql |
CREATE TABLE inspections (inspection_id INT, restaurant_id INT, inspection_date DATE, score INT); INSERT INTO inspections (inspection_id, restaurant_id, inspection_date, score) VALUES (1, 1, '2022-01-01', 95); | List the top 10 restaurants with the highest food safety inspection scores, along with their average score. | SELECT restaurant_id, AVG(score) as avg_score FROM inspections GROUP BY restaurant_id ORDER BY avg_score DESC FETCH FIRST 10 ROWS ONLY; | gretelai_synthetic_text_to_sql |
CREATE TABLE donors (donor_id INT, donor_name TEXT, donation_amount FLOAT, cause TEXT, donation_date DATE); | What is the average donation amount for environmental causes in Q1 2022? | SELECT AVG(donation_amount) FROM donors WHERE cause = 'Environment' AND donation_date BETWEEN '2022-01-01' AND '2022-03-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE ORGANIC_FOOD (id INT, name VARCHAR(50), category VARCHAR(50), avg_calories FLOAT); INSERT INTO ORGANIC_FOOD (id, name, category, avg_calories) VALUES (1, 'Carrot', 'Vegetable', 25), (2, 'Lettuce', 'Vegetable', 5); | What is the average calorie count for vegetables in the ORGANIC_FOOD table? | SELECT AVG(avg_calories) FROM ORGANIC_FOOD WHERE category = 'Vegetable'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Workshops_For_Students (id INT, country VARCHAR(255), quarter INT, number_of_workshops INT); | What is the total number of workshops organized for students in Japan during Q1 2022? | SELECT SUM(number_of_workshops) FROM Workshops_For_Students WHERE country = 'Japan' AND quarter = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE MobilityAssistiveDevices (student_id INT, device_type VARCHAR(255), usage_frequency INT); | What is the average number of mobility assistive devices used per student? | SELECT AVG(usage_frequency) FROM MobilityAssistiveDevices GROUP BY student_id; | gretelai_synthetic_text_to_sql |
CREATE TABLE energy_consumption (factory_id INT, industry VARCHAR(50), region VARCHAR(50), energy_consumption INT); | What is the total energy consumption of the top 3 most energy-intensive manufacturing industries in Africa? | SELECT industry, SUM(energy_consumption) FROM energy_consumption e JOIN (SELECT factory_id, MIN(row_number) FROM (SELECT factory_id, ROW_NUMBER() OVER (PARTITION BY industry ORDER BY energy_consumption DESC) row_number FROM energy_consumption) t GROUP BY industry) x ON e.factory_id = x.factory_id GROUP BY industry HAVING COUNT(*) <= 3 AND region = 'Africa'; | gretelai_synthetic_text_to_sql |
CREATE TABLE user_assets(user_id INT, asset_id INT); INSERT INTO user_assets(user_id, asset_id) VALUES (1, 101), (1, 102), (2, 103), (3, 104), (3, 105), (3, 106), (4, 107), (4, 108), (5, 109); CREATE TABLE assets(id INT, asset_name VARCHAR(255)); INSERT INTO assets(id, asset_name) VALUES (101, 'AssetA'), (102, 'AssetB'), (103, 'AssetC'), (104, 'AssetD'), (105, 'AssetE'), (106, 'AssetF'), (107, 'AssetG'), (108, 'AssetH'), (109, 'AssetI'); | Identify the number of digital assets owned by each user and rank them by the number of assets they own. | SELECT u.user_id, COUNT(ua.asset_id) as asset_count FROM users u JOIN user_assets ua ON u.user_id = ua.user_id JOIN assets a ON ua.asset_id = a.id GROUP BY u.user_id ORDER BY asset_count DESC; | gretelai_synthetic_text_to_sql |
CREATE TABLE Employees (EmployeeID INT, Name VARCHAR(50), Department VARCHAR(50), Age INT, Nationality VARCHAR(50)); | How many employees of each nationality work in the 'Mining Operations' department? | SELECT Department, Nationality, COUNT(*) FROM Employees WHERE Department = 'Mining Operations' GROUP BY Department, Nationality; | gretelai_synthetic_text_to_sql |
CREATE TABLE Feedback(service VARCHAR(20), region VARCHAR(20), feedback_id INT); INSERT INTO Feedback VALUES ('ServiceA', 'RegionC', 1001), ('ServiceA', 'RegionC', 1002), ('ServiceB', 'RegionD', 2001), ('ServiceB', 'RegionD', 2002), ('ServiceC', 'RegionE', 3001), ('ServiceC', 'RegionE', 3002); | How many citizen feedback records are there for 'ServiceC' in 'RegionE'? | SELECT COUNT(*) FROM Feedback WHERE service = 'ServiceC' AND region = 'RegionE'; | gretelai_synthetic_text_to_sql |
CREATE TABLE companies (id INT, sector TEXT, ESG_rating FLOAT); INSERT INTO companies (id, sector, ESG_rating) VALUES (1, 'technology', 78.2), (2, 'finance', 82.5), (3, 'technology', 84.6); | Update the sector for company with id 1 to 'green_technology'. | UPDATE companies SET sector = 'green_technology' WHERE id = 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE customers (customer_id INT, name TEXT, total_spend DECIMAL(10,2)); | What are the top 5 customers by total spend in the past year from the 'customers' table? | SELECT customer_id, name, total_spend FROM customers ORDER BY total_spend DESC LIMIT 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE economic_impact (impact_id INT, hotel_id INT, city TEXT, amount DECIMAL(10,2)); INSERT INTO economic_impact (impact_id, hotel_id, city, amount) VALUES (1, 1, 'Paris', 50000.00), (2, 2, 'Paris', 75000.00); | What is the total local economic impact of eco-friendly hotels in Paris last year? | SELECT SUM(amount) FROM economic_impact WHERE city = 'Paris' AND DATE_TRUNC('year', timestamp) = DATE_TRUNC('year', NOW() - INTERVAL '1 year') AND hotel_id IN (SELECT hotel_id FROM eco_hotels WHERE city = 'Paris'); | gretelai_synthetic_text_to_sql |
CREATE TABLE GameDesigners (DesignerID INT, DesignerName VARCHAR(50), Gender VARCHAR(10), NumberOfGames INT); INSERT INTO GameDesigners (DesignerID, DesignerName, Gender, NumberOfGames) VALUES (1, 'Alice', 'Female', 3), (2, 'Bob', 'Male', 2), (3, 'Charlie', 'Non-binary', 1); | What is the average number of games designed by all game designers? | SELECT AVG(NumberOfGames) FROM GameDesigners; | gretelai_synthetic_text_to_sql |
CREATE TABLE tourism_data (id INT, country VARCHAR(50), arrival_date DATE); INSERT INTO tourism_data (id, country, arrival_date) VALUES (1, 'Brazil', '2015-01-01'), (2, 'Argentina', '2016-03-15'), (3, 'Colombia', '2021-04-20'); | What is the total number of tourists visiting South America from 2015 to Q3 2021, grouped by year and quarter? | SELECT country, DATE_FORMAT(arrival_date, '%Y-%q') AS quarter, COUNT(*) AS total_tourists FROM tourism_data WHERE country IN ('Brazil', 'Argentina', 'Colombia') AND arrival_date BETWEEN '2015-01-01' AND '2021-09-30' GROUP BY quarter, country; | gretelai_synthetic_text_to_sql |
CREATE TABLE Supplies (org_name TEXT, supply_cost INTEGER, supply_date DATE); INSERT INTO Supplies (org_name, supply_cost, supply_date) VALUES ('Organization A', 3000, '2021-01-05'); INSERT INTO Supplies (org_name, supply_cost, supply_date) VALUES ('Organization B', 4000, '2021-06-12'); | What is the total amount spent on supplies by each organization in 2021? | SELECT org_name, SUM(supply_cost) FROM Supplies WHERE supply_date BETWEEN '2021-01-01' AND '2021-12-31' GROUP BY org_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE company_diversity (id INT PRIMARY KEY, company_id INT, founder_gender VARCHAR(10), founder_ethnicity VARCHAR(20), country VARCHAR(20)); INSERT INTO company_diversity (id, company_id, founder_gender, founder_ethnicity, country) VALUES (1, 1001, 'male', 'white', 'US'), (2, 1002, 'male', 'asian', 'CA'); | Insert a new record for a female African American founder from Nigeria into the "company_diversity" table | INSERT INTO company_diversity (id, company_id, founder_gender, founder_ethnicity, country) VALUES (3, 1003, 'female', 'African American', 'NG'); | gretelai_synthetic_text_to_sql |
CREATE TABLE TextileSourcing (id INT, location VARCHAR(50), fabric_type VARCHAR(50), quantity INT); INSERT INTO TextileSourcing (id, location, fabric_type, quantity) VALUES (1, 'Italy', 'Organic Cotton', 500), (2, 'France', 'Tencel', 350), (3, 'Germany', 'Recycled Polyester', 400); | What is the average quantity of sustainable fabric sourced from Europe? | SELECT AVG(quantity) FROM TextileSourcing WHERE fabric_type = 'Organic Cotton' AND location IN ('Italy', 'France', 'Germany'); | gretelai_synthetic_text_to_sql |
CREATE TABLE military_spending (country TEXT, spending FLOAT); INSERT INTO military_spending (country, spending) VALUES ('Egypt', 10.5), ('Israel', 9.2), ('Algeria', 11.7), ('Saudi Arabia', 8.8); | Show the military spending of the top 3 countries in Africa and the Middle East. | SELECT m.country, m.spending FROM military_spending m WHERE m.spending >= (SELECT AVG(m2.spending) FROM military_spending m2) ORDER BY m.spending DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE energy_efficiency_programs (id INT, program_name VARCHAR(100), location VARCHAR(50)); | How many energy efficiency programs were implemented in 'Asia'? | SELECT COUNT(*) FROM energy_efficiency_programs WHERE location = 'Asia'; | gretelai_synthetic_text_to_sql |
CREATE TABLE countries (name VARCHAR(255), coastline FLOAT); | Which country has the longest coastline? | SELECT name FROM countries ORDER BY coastline DESC LIMIT 1; | gretelai_synthetic_text_to_sql |
CREATE TABLE carbon_prices (region VARCHAR(20), price DECIMAL(5,2), year INT); INSERT INTO carbon_prices (region, price, year) VALUES ('European Union', 25.50, 2021), ('European Union', 26.30, 2021), ('European Union', 24.80, 2021); | What is the average carbon price per metric ton for the European Union in 2021? | SELECT AVG(price) FROM carbon_prices WHERE region = 'European Union' AND year = 2021; | gretelai_synthetic_text_to_sql |
CREATE TABLE chicago_communities (id INT, name TEXT); INSERT INTO chicago_communities (id, name) VALUES (1, 'Downtown'), (2, 'North Side'), (3, 'South Side'); CREATE TABLE emergency_response (id INT, community_id INT, incident_id INT, response_time INT); INSERT INTO emergency_response (id, community_id, incident_id, response_time) VALUES (1, 1, 1, 300), (2, 1, 2, 450), (3, 3, 3, 600); CREATE TABLE emergency_incidents (id INT, type TEXT, date DATE); INSERT INTO emergency_incidents (id, type, date) VALUES (1, 'Fire', '2021-01-01'), (2, 'Theft', '2021-01-02'), (3, 'Assault', '2021-01-03'); | What is the total number of emergency incidents and corresponding response times for each community in Chicago? | SELECT c.name, COUNT(er.incident_id) as total_incidents, AVG(er.response_time) as avg_response_time FROM chicago_communities c JOIN emergency_response er ON c.id = er.community_id GROUP BY c.id; | gretelai_synthetic_text_to_sql |
CREATE TABLE claims (claim_id INT, policy_id INT, claim_amount DECIMAL(10,2), city VARCHAR(50), policy_type VARCHAR(50)); CREATE TABLE policies (policy_id INT, policy_holder_id INT, policy_type VARCHAR(50), issue_date DATE); | Determine the top 3 cities with the highest average claim amount for life insurance policies. | SELECT c.city, AVG(claim_amount) FROM claims c JOIN policies p ON c.policy_id = p.policy_id WHERE policy_type = 'life' GROUP BY c.city ORDER BY AVG(claim_amount) DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE threats (id INT, ip VARCHAR(255), country VARCHAR(255), threat_level INT); INSERT INTO threats (id, ip, country, threat_level) VALUES (1, '192.168.0.1', 'USA', 5); | What are the IP addresses and threat levels of all threats originating from a specific country? | SELECT ip, threat_level FROM threats WHERE country = 'specific_country'; | gretelai_synthetic_text_to_sql |
CREATE TABLE vessels (id INT PRIMARY KEY, name VARCHAR(50), type VARCHAR(50), length FLOAT, year_built INT); | Get the names of all vessels built before 2005 | SELECT name FROM vessels WHERE year_built < 2005; | gretelai_synthetic_text_to_sql |
CREATE TABLE students (id INT, name VARCHAR(50), gender VARCHAR(10), program VARCHAR(50), publications INT); INSERT INTO students (id, name, gender, program, publications) VALUES (1, 'Charlie', 'Non-binary', 'Social Sciences', 1), (2, 'Dana', 'Female', 'Physics', 0), (3, 'Eli', 'Male', 'Engineering', 0); | How many graduate students in the Social Sciences program have published at least one paper? | SELECT COUNT(*) FROM students WHERE program LIKE 'Social%' AND publications > 0; | gretelai_synthetic_text_to_sql |
CREATE TABLE vehicles (id INT, type VARCHAR(255), last_maintenance DATE);INSERT INTO vehicles (id, type, last_maintenance) VALUES (1, 'Tank', '2021-03-01'), (2, 'Armored Personnel Carrier', '2020-08-15'), (3, 'Artillery', '2022-01-20'), (4, 'Tank', '2021-12-05'), (5, 'Helicopter', '2021-06-10'); | How many different types of military vehicles are maintained? | SELECT COUNT(DISTINCT type) as num_types FROM vehicles; | gretelai_synthetic_text_to_sql |
CREATE TABLE strain_production (strain_type VARCHAR(10), state VARCHAR(20), production_quantity INT); INSERT INTO strain_production (strain_type, state, production_quantity) VALUES ('CBD', 'Oregon', 100); INSERT INTO strain_production (strain_type, state, production_quantity) VALUES ('THC', 'Oregon', 200); INSERT INTO strain_production (strain_type, state, production_quantity) VALUES ('CBD', 'Washington', 150); INSERT INTO strain_production (strain_type, state, production_quantity) VALUES ('THC', 'Washington', 250); | Find the average production quantity of CBD and THC strains in Oregon and Washington. | SELECT strain_type, AVG(production_quantity) FROM strain_production WHERE state IN ('Oregon', 'Washington') GROUP BY strain_type; | gretelai_synthetic_text_to_sql |
CREATE TABLE driver (driver_id INT, name VARCHAR(255), gender VARCHAR(10)); CREATE TABLE trip (trip_id INT, driver_id INT, fare DECIMAL(10,2)); INSERT INTO driver (driver_id, name, gender) VALUES (1, 'John Doe', 'Male'), (2, 'Jane Smith', 'Female'), (3, 'Bob Johnson', 'Male'); INSERT INTO trip (trip_id, driver_id, fare) VALUES (1, 1, 2.00), (2, 1, 3.00), (3, 2, 4.00), (4, 3, 5.00); | What is the total number of trips for each driver by gender? | SELECT d.gender, d.driver_id, d.name, COUNT(t.trip_id) AS trip_count FROM driver d JOIN trip t ON d.driver_id = t.driver_id GROUP BY d.driver_id, d.gender; | gretelai_synthetic_text_to_sql |
CREATE TABLE defense_contractors (contractor_id INT, contractor_name VARCHAR(255), contract_value FLOAT, country VARCHAR(255)); INSERT INTO defense_contractors (contractor_id, contractor_name, contract_value, country) VALUES (1, 'Lockheed Martin', 6000000, 'USA'), (2, 'Boeing', 5000000, 'USA'), (3, 'Raytheon', 4000000, 'USA'), (4, 'Northrop Grumman', 3500000, 'USA'), (5, 'General Dynamics', 3000000, 'USA'); | What are the top 5 defense contractors in the USA in terms of contract value? | SELECT contractor_name, contract_value FROM (SELECT contractor_name, contract_value, RANK() OVER (ORDER BY contract_value DESC) as rnk FROM defense_contractors WHERE country = 'USA') t WHERE rnk <= 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE patient (id INT, name TEXT, mental_health_score INT, community TEXT); INSERT INTO patient (id, name, mental_health_score, community) VALUES (1, 'John Doe', 60, 'Straight'), (2, 'Jane Smith', 70, 'LGBTQ+'); | What is the average mental health score for patients belonging to the LGBTQ+ community? | SELECT AVG(mental_health_score) FROM patient WHERE community = 'LGBTQ+'; | gretelai_synthetic_text_to_sql |
CREATE TABLE health_equity_metrics (id INT, community_health_worker_id INT, score INT); INSERT INTO health_equity_metrics (id, community_health_worker_id, score) VALUES (1, 1, 80), (2, 2, 90), (3, 3, 95), (4, 4, 70); CREATE TABLE community_health_workers (id INT, name VARCHAR(100), state VARCHAR(50)); INSERT INTO community_health_workers (id, name, state) VALUES (1, 'Jane Smith', 'California'), (2, 'Jose Garcia', 'Texas'), (3, 'Sophia Lee', 'California'), (4, 'Ali Ahmed', 'New York'); | What is the maximum health equity metric score achieved by any community health worker in California? | SELECT MAX(score) FROM health_equity_metrics JOIN community_health_workers ON health_equity_metrics.community_health_worker_id = community_health_workers.id WHERE community_health_workers.state = 'California'; | gretelai_synthetic_text_to_sql |
CREATE TABLE site (site_id INT, site_name VARCHAR(50)); INSERT INTO site (site_id, site_name) VALUES (1, 'Site A'), (2, 'Site B'); CREATE TABLE production (production_id INT, site_id INT, product VARCHAR(10), production_date DATE, quantity INT); INSERT INTO production (production_id, site_id, product, production_date, quantity) VALUES (1, 1, 'coal', '2021-01-01', 500), (2, 1, 'coal', '2021-02-01', 600), (3, 1, 'coal', '2021-03-01', 700), (4, 2, 'coal', '2021-01-01', 800), (5, 2, 'coal', '2021-02-01', 900), (6, 2, 'coal', '2021-03-01', 1000); | What is the total coal production by site in the last quarter? | SELECT site_name, SUM(quantity) AS total_coal_production FROM production JOIN site ON production.site_id = site.site_id WHERE product = 'coal' AND production_date >= DATEADD(quarter, -1, GETDATE()) GROUP BY site_name; | gretelai_synthetic_text_to_sql |
CREATE TABLE MilitarySpending (Year INT, Country VARCHAR(50), Spending FLOAT, Region VARCHAR(50)); INSERT INTO MilitarySpending (Year, Country, Spending, Region) VALUES (2015, 'Indonesia', 14.5, 'Southeast Asia'), (2015, 'Malaysia', 12.6, 'Southeast Asia'), (2016, 'Indonesia', 15.2, 'Southeast Asia'); | What is the total military spending by each country in the Southeast Asia region from 2015 to 2020? | SELECT Country, SUM(Spending) as Total_Spending FROM MilitarySpending WHERE Year BETWEEN 2015 AND 2020 AND Region = 'Southeast Asia' GROUP BY Country; | gretelai_synthetic_text_to_sql |
CREATE TABLE hotel_info (hotel_id INT, hotel_name VARCHAR(50), region VARCHAR(50), ai_adoption INT); INSERT INTO hotel_info (hotel_id, hotel_name, region, ai_adoption) VALUES (1, 'Hotel A', 'Region 1', 1), (2, 'Hotel B', 'Region 1', 0), (3, 'Hotel C', 'Region 2', 1), (4, 'Hotel D', 'Region 2', 1); | Calculate the percentage of hotels adopting AI technology in each region | SELECT region, 100.0 * SUM(ai_adoption) / COUNT(*) as adoption_percentage FROM hotel_info GROUP BY region; | gretelai_synthetic_text_to_sql |
CREATE TABLE shariah_compliant_finance (id INT, institution_name VARCHAR(255), country VARCHAR(255), num_branches INT); INSERT INTO shariah_compliant_finance (id, institution_name, country, num_branches) VALUES (1, 'Islamic Bank', 'Indonesia', 7), (2, 'Shariah Finance Ltd', 'India', 6), (3, 'Al-Baraka Bank', 'Pakistan', 3); | Count the number of Shariah-compliant financial institutions in Asia with more than 5 branches. | SELECT COUNT(*) FROM shariah_compliant_finance WHERE country = 'Asia' AND num_branches > 5; | gretelai_synthetic_text_to_sql |
CREATE TABLE sustainable_material_brands (brand_id INT PRIMARY KEY, brand_name VARCHAR(100), added_date DATE); | How many sustainable material brands were added in the past year? | SELECT COUNT(*) FROM sustainable_material_brands WHERE added_date >= DATE_SUB(NOW(), INTERVAL 1 YEAR); | gretelai_synthetic_text_to_sql |
CREATE TABLE Supplier (id INT PRIMARY KEY, name VARCHAR(50), country VARCHAR(50), sustainability_score INT); | Update the 'sustainability_score' for 'Green Fabrics Inc.' to '90' in the 'Supplier' table | UPDATE Supplier SET sustainability_score = 90 WHERE name = 'Green Fabrics Inc.'; | gretelai_synthetic_text_to_sql |
CREATE TABLE emissions (id INT, country VARCHAR(255), vehicle_type VARCHAR(255), co2_emissions INT); INSERT INTO emissions (id, country, vehicle_type, co2_emissions) VALUES (1, 'USA', 'Diesel', 120); | What is the total CO2 emissions of diesel vehicles per country in the "emissions" table? | SELECT country, SUM(co2_emissions) FROM emissions WHERE vehicle_type = 'Diesel' GROUP BY country; | gretelai_synthetic_text_to_sql |
CREATE TABLE startups (id INT, name VARCHAR(255), founding_year INT, founder_disability BOOLEAN); INSERT INTO startups (id, name, founding_year, founder_disability) VALUES (1, 'Delta X', 2018, true), (2, 'Echo Y', 2019, false); CREATE TABLE funding (startup_id INT, amount INT); INSERT INTO funding (startup_id, amount) VALUES (1, 750000), (2, 1000000); | How many founders with disabilities have received funding? | SELECT COUNT(*) FROM funding INNER JOIN startups ON funding.startup_id = startups.id WHERE startups.founder_disability = true; | gretelai_synthetic_text_to_sql |
CREATE TABLE open_data_initiatives (initiative_id INT, initiative_date DATE, initiative_country VARCHAR(50)); INSERT INTO open_data_initiatives (initiative_id, initiative_date, initiative_country) VALUES (1, '2021-01-01', 'Canada'), (2, '2021-02-01', 'Canada'); | How many open data initiatives were launched by the government of Canada in 2021? | SELECT COUNT(*) FROM open_data_initiatives WHERE initiative_country = 'Canada' AND initiative_date BETWEEN '2021-01-01' AND '2021-12-31'; | gretelai_synthetic_text_to_sql |
CREATE TABLE Customer_Preferences (customer_id INT, preference_date DATE, fashion_trend VARCHAR(255)); INSERT INTO Customer_Preferences (customer_id, preference_date, fashion_trend) VALUES (1, '2021-01-01', 'Sustainable'), (2, '2021-01-15', 'Vintage'), (3, '2021-02-01', 'Minimalist'), (4, '2021-02-10', 'Streetwear'), (5, '2021-03-01', 'Bohemian'), (6, '2021-03-15', 'Sustainable'), (7, '2021-04-01', 'Vintage'), (8, '2021-04-10', 'Minimalist'), (9, '2021-05-01', 'Sustainable'), (10, '2021-05-15', 'Vintage'); | Identify the top 3 fashion trends by customer preference in the last year. | SELECT fashion_trend, COUNT(*) AS preference_count FROM Customer_Preferences WHERE preference_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR) AND CURRENT_DATE GROUP BY fashion_trend ORDER BY preference_count DESC LIMIT 3; | gretelai_synthetic_text_to_sql |
CREATE TABLE countries (id INT, name TEXT); CREATE TABLE satellites (id INT, country_id INT, name TEXT, launch_date DATE, manufacturer TEXT); INSERT INTO countries (id, name) VALUES (1, 'USA'), (2, 'Russia'), (3, 'China'), (4, 'India'); INSERT INTO satellites (id, country_id, name, launch_date, manufacturer) VALUES (1, 1, 'StarDragon', '2012-05-25', 'SpaceX'), (2, 1, 'Falcon', '2015-12-21', 'SpaceX'), (3, 2, 'Sputnik', '1957-10-04', 'Russia'), (4, 3, 'ChinaSat 1E', '2000-12-05', 'CAST'), (5, 4, 'EDUSAT', '2004-09-20', 'ISRO'); | What is the total number of satellites launched by India? | SELECT COUNT(*) FROM satellites WHERE country_id = 4; | gretelai_synthetic_text_to_sql |
CREATE TABLE player_stats (id INT, name VARCHAR(50), country VARCHAR(50)); INSERT INTO player_stats (id, name, country) VALUES (1, 'John Doe', 'USA'), (2, 'Jane Smith', 'Canada'), (3, 'Maria Garcia', 'Mexico'), (4, 'Li Chen', 'China'), (5, 'Hiroshi Tanaka', 'Japan'); | What is the total number of players from Asia? | SELECT COUNT(*) FROM player_stats WHERE country LIKE 'China%' OR country LIKE 'Japan%' OR country LIKE 'India%' OR country LIKE 'Korea%'; | gretelai_synthetic_text_to_sql |
CREATE TABLE timber_production(year INT, volume INT); INSERT INTO timber_production(year, volume) VALUES (2018, 5000), (2019, 5500), (2020, 6000); | What is the total volume of timber production for each year, grouped by year? | SELECT year, SUM(volume) FROM timber_production GROUP BY year; | gretelai_synthetic_text_to_sql |
CREATE TABLE strains (id INT, state VARCHAR(50), year INT, strain VARCHAR(50)); INSERT INTO strains (id, state, year, strain) VALUES (1, 'Colorado', 2020, 'Blue Dream'), (2, 'Colorado', 2021, 'Green Crack'), (3, 'California', 2020, 'Sour Diesel'); | How many unique strains were available in Colorado in 2020 and 2021? | SELECT COUNT(DISTINCT strain) FROM strains WHERE state = 'Colorado' AND (year = 2020 OR year = 2021); | gretelai_synthetic_text_to_sql |
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