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CREATE TABLE client (id INT, name VARCHAR(50), region VARCHAR(50), score INT); INSERT INTO client (id, name, region, score) VALUES (1, 'John', 'Africa', 60), (2, 'Jane', 'Asia', 70), (3, 'Jim', 'Europe', 80), (4, 'Joan', 'America', 90);
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What is the average financial capability score for clients in each region?
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SELECT region, AVG(score) as avg_score FROM client GROUP BY region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE donations (id INT, donor_name TEXT, amount DECIMAL, donation_date DATE); INSERT INTO donations (id, donor_name, amount, donation_date) VALUES (1, 'John Doe', 50.00, '2022-01-01'); INSERT INTO donations (id, donor_name, amount, donation_date) VALUES (2, 'Jane Smith', 100.00, '2022-02-01');
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How many donation records were deleted in the last month?
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SELECT COUNT(*) FROM (SELECT * FROM donations WHERE DATE(donation_date) < DATE_SUB(CURRENT_DATE(), INTERVAL 1 MONTH) FOR UPDATE) AS deleted_donations;
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gretelai_synthetic_text_to_sql
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CREATE TABLE fire_stations (id INT, city VARCHAR(255), number_of_stations INT); INSERT INTO fire_stations (id, city, number_of_stations) VALUES (1, 'Los_Angeles', 100), (2, 'San_Francisco', 80);
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What is the total number of fire stations in the city of Los Angeles?
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SELECT SUM(number_of_stations) FROM fire_stations WHERE city = 'Los_Angeles';
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gretelai_synthetic_text_to_sql
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CREATE TABLE tree_data (region VARCHAR(255), species VARCHAR(255), height INTEGER);
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Calculate the average tree height per region.
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SELECT region, AVG(height) FROM tree_data GROUP BY region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE departments (department_id INT, department VARCHAR(20));CREATE TABLE worker_salaries (worker_id INT, department_id INT, salary INT);
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What is the maximum salary paid to a worker in the 'quality control' department?
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SELECT MAX(worker_salaries.salary) FROM worker_salaries INNER JOIN departments ON worker_salaries.department_id = departments.department_id WHERE departments.department = 'quality control';
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gretelai_synthetic_text_to_sql
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CREATE TABLE quarter (quarter VARCHAR(10), papers INTEGER); INSERT INTO quarter (quarter, papers) VALUES ('Q1 2021', 50), ('Q2 2021', 75), ('Q3 2021', 80), ('Q4 2021', 90), ('Q1 2022', 100), ('Q2 2022', 120);
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How many AI safety research papers have been published in each quarter?
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SELECT quarter, papers FROM quarter;
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gretelai_synthetic_text_to_sql
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CREATE TABLE explainability (model_id INT, name VARCHAR(255), country VARCHAR(255), score FLOAT); INSERT INTO explainability (model_id, name, country, score) VALUES (1, 'Model1', 'UK', 0.85), (2, 'Model2', 'UK', 0.92), (3, 'Model3', 'Canada', 0.78), (4, 'Model4', 'USA', 0.88), (5, 'Model5', 'UK', 0.90);
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What is the average explainability score for models from the UK?
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SELECT AVG(score) FROM explainability WHERE country = 'UK';
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gretelai_synthetic_text_to_sql
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CREATE TABLE military_personnel (personnel_id INT, country VARCHAR(50), region VARCHAR(50), operation_type VARCHAR(50), num_personnel INT); INSERT INTO military_personnel (personnel_id, country, region, operation_type, num_personnel) VALUES (1, 'United States', 'North America', 'Peacekeeping', 500), (2, 'Canada', 'North America', 'Humanitarian Assistance', 700), (3, 'Argentina', 'South America', 'Peacekeeping', 350);
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What is the total number of military personnel by region and type of operation?
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SELECT mp.region, mp.operation_type, SUM(mp.num_personnel) as total_personnel FROM military_personnel mp GROUP BY mp.region, mp.operation_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE country (country_code VARCHAR(3), country_name VARCHAR(50)); INSERT INTO country VALUES ('USA', 'United States'), ('CHN', 'China'), ('IND', 'India'); CREATE TABLE project (project_id INT, project_name VARCHAR(50), country_code VARCHAR(3), mitigation BOOLEAN); INSERT INTO project VALUES (1, 'Solar Farm', 'USA', false), (2, 'Wind Turbines', 'CHN', false), (3, 'Energy Efficiency', 'IND', true); CREATE TABLE finance (project_id INT, year INT, amount INT); INSERT INTO finance VALUES (1, 2020, 500000), (2, 2020, 1000000), (3, 2020, 200000), (1, 2019, 600000), (2, 2019, 800000), (3, 2019, 300000);
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What is the average annual climate finance committed by each country for adaptation projects?
|
SELECT c.country_name, AVG(f.amount/5) FROM country c JOIN project p ON c.country_code = p.country_code JOIN finance f ON p.project_id = f.project_id WHERE p.adaptation = true GROUP BY c.country_name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE mine_operators (id INT PRIMARY KEY, name VARCHAR(50), role VARCHAR(50), gender VARCHAR(10), years_of_experience INT); INSERT INTO mine_operators (id, name, role, gender, years_of_experience) VALUES (1, 'John Doe', 'Mining Engineer', 'Male', 7);
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Update the gender of the mining engineer with ID 1 to Female.
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UPDATE mine_operators SET gender = 'Female' WHERE id = 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE retailers (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255)); INSERT INTO retailers (id, name, location) VALUES (1, 'Eco Fashion', 'London, UK'); CREATE TABLE purchases (id INT PRIMARY KEY, retailer_id INT, manufacturer_id INT, date DATE, sustainability_score FLOAT, FOREIGN KEY (retailer_id) REFERENCES retailers(id), FOREIGN KEY (manufacturer_id) REFERENCES manufacturers(id)); INSERT INTO purchases (id, retailer_id, manufacturer_id, date, sustainability_score) VALUES (1, 1, 1, '2022-05-05', 9.1);
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Which retailers have purchased garments with a sustainability score above 8.5 in the last week?
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SELECT r.name, p.sustainability_score FROM retailers r JOIN purchases p ON r.id = p.retailer_id WHERE p.sustainability_score > 8.5 AND p.date BETWEEN DATE_SUB(CURDATE(), INTERVAL 1 WEEK) AND CURDATE();
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gretelai_synthetic_text_to_sql
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CREATE TABLE smart_contracts (id INT, category VARCHAR(255), name VARCHAR(255)); INSERT INTO smart_contracts (id, category, name) VALUES (1, 'DeFi', 'Compound'), (2, 'DEX', 'Uniswap'), (3, 'DeFi', 'Aave'), (4, 'NFT', 'CryptoKitties'), (5, 'DEX', 'SushiSwap'), (6, 'DeFi', 'MakerDAO'), (7, 'Gaming', 'Axie Infinity'), (8, 'Insurance', 'Nexus Mutual'), (9, 'Oracle', 'Chainlink');
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What are the top 3 smart contract categories with the most contracts?
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SELECT category, COUNT(*) as total FROM smart_contracts GROUP BY category ORDER BY total DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Donors (id INT, name TEXT, region TEXT, donation FLOAT); INSERT INTO Donors (id, name, region, donation) VALUES (1, 'Carol', 'Mid West', 120.5), (2, 'Dave', 'South East', 75.2);
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How many donors from the 'Mid West' region made donations larger than $100?
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SELECT COUNT(*) FROM Donors WHERE region = 'Mid West' AND donation > 100;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Programs (id INT, name TEXT); INSERT INTO Programs (id, name) VALUES (1, 'Youth Education'), (2, 'Women Empowerment'), (3, 'Clean Water'), (4, 'Refugee Support'); CREATE TABLE Volunteers (id INT, program INT, hours INT); INSERT INTO Volunteers (id, program, hours) VALUES (1, 1, 20), (2, 2, 30), (3, 3, 15), (4, 4, 25); CREATE TABLE Donors (id INT, program INT, amount DECIMAL(10, 2)); INSERT INTO Donors (id, program, amount) VALUES (1, 1, 100), (2, 2, 150), (3, 3, 75), (5, 4, 200);
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Find the number of unique volunteers and donors who have participated in each program.
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SELECT Programs.name, COUNT(DISTINCT Volunteers.id) + COUNT(DISTINCT Donors.id) as total_participants FROM Programs LEFT JOIN Volunteers ON Programs.id = Volunteers.program FULL OUTER JOIN Donors ON Programs.id = Donors.program GROUP BY Programs.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE DisabilityAccommodations (year INT, budget DECIMAL(5,2)); INSERT INTO DisabilityAccommodations (year, budget) VALUES (2018, 500000.00), (2019, 750000.00); CREATE TABLE DisabilitySupportPrograms (year INT, budget DECIMAL(5,2)); INSERT INTO DisabilitySupportPrograms (year, budget) VALUES (2018, 550000.00), (2019, 800000.00);
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What is the total budget allocated for disability accommodations and support programs in '2019'?
|
SELECT SUM(DisabilityAccommodations.budget) + SUM(DisabilitySupportPrograms.budget) FROM DisabilityAccommodations, DisabilitySupportPrograms WHERE DisabilityAccommodations.year = 2019 AND DisabilitySupportPrograms.year = 2019;
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gretelai_synthetic_text_to_sql
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CREATE TABLE baseball_players (player_id INT, name VARCHAR(50), height DECIMAL(3,2), position VARCHAR(20), team VARCHAR(30));
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What is the average height of athletes in the 'baseball_players' table?
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SELECT AVG(height) FROM baseball_players;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE CommunityHealthWorkers (CHW_ID INT, CHW_Name TEXT, Region TEXT); INSERT INTO CommunityHealthWorkers (CHW_ID, CHW_Name, Region) VALUES (1, 'John Doe', 'New York'), (2, 'Jane Smith', 'California'); CREATE TABLE CulturalCompetencyTrainings (Training_ID INT, CHW_ID INT, Training_Type TEXT); INSERT INTO CulturalCompetencyTrainings (Training_ID, CHW_ID, Training_Type) VALUES (1, 1, 'Cultural Competency Training 1'), (2, 1, 'Cultural Competency Training 2'), (3, 2, 'Cultural Competency Training 3');
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How many cultural competency trainings have been attended by community health workers in each region?
|
SELECT c.Region, COUNT(cc.CHW_ID) as Number_of_Trainings FROM CommunityHealthWorkers c INNER JOIN CulturalCompetencyTrainings cc ON c.CHW_ID = cc.CHW_ID GROUP BY c.Region;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE hotels (id INT, hotel_name VARCHAR(50), country VARCHAR(50), continent VARCHAR(50), revenue INT);
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What is the total revenue generated by the hotels table for each continent?
|
SELECT continent, SUM(revenue) FROM hotels GROUP BY continent;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ai_research_projects (id INT PRIMARY KEY, project_name VARCHAR(50), status VARCHAR(20));
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Delete all records with 'incomplete' status in the 'ai_research_projects' table
|
DELETE FROM ai_research_projects WHERE status = 'incomplete';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE veteran_employment (employment_id INT, industry TEXT, state TEXT, employment_rate FLOAT, quarter TEXT); INSERT INTO veteran_employment (employment_id, industry, state, employment_rate, quarter) VALUES (1, 'Defense', 'New York', 0.85, 'Q1 2022'), (2, 'Defense', 'California', 0.82, 'Q1 2022');
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What is the employment rate for veterans in the defense industry in the state of New York in Q1 2022?
|
SELECT employment_rate FROM veteran_employment WHERE industry = 'Defense' AND state = 'New York' AND quarter = 'Q1 2022';
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gretelai_synthetic_text_to_sql
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CREATE TABLE rural_infrastructure (id INT, name VARCHAR(50), type VARCHAR(50), budget FLOAT); INSERT INTO rural_infrastructure (id, name, type, budget) VALUES (1, 'Solar Irrigation', 'Agricultural Innovation', 150000.00), (2, 'Wind Turbines', 'Rural Infrastructure', 200000.00);
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What are the names of the agricultural innovation projects in the 'rural_infrastructure' table that have a budget less than 150000?
|
SELECT name FROM rural_infrastructure WHERE type = 'Agricultural Innovation' AND budget < 150000;
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gretelai_synthetic_text_to_sql
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CREATE TABLE community_health_workers_patients (worker_id INT, limited_english BOOLEAN, last_two_years BOOLEAN); INSERT INTO community_health_workers_patients (worker_id, limited_english, last_two_years) VALUES (1, TRUE, TRUE), (2, FALSE, TRUE), (3, TRUE, FALSE);
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Which community health workers have served the most patients with limited English proficiency in the last two years?
|
SELECT c.worker_id, c.limited_english FROM community_health_workers_patients c WHERE c.last_two_years = TRUE AND c.limited_english = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE crop_farmers (farmer_id INT, crop VARCHAR(50), region VARCHAR(50)); INSERT INTO crop_farmers (farmer_id, crop, region) VALUES (1, 'Wheat', 'Great Plains'), (2, 'Corn', 'Midwest'), (3, 'Soybean', 'Midwest');
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Which regions grow 'Wheat' in the 'crop_farmers' table?
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SELECT region FROM crop_farmers WHERE crop = 'Wheat';
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gretelai_synthetic_text_to_sql
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CREATE TABLE if not exists farms (id int, name varchar(50), region varchar(50), type varchar(50)); INSERT INTO farms (id, name, region, type) VALUES (1, 'Farm A', 'Asia', 'Tropical'); INSERT INTO farms (id, name, region, type) VALUES (2, 'Farm B', 'South America', 'Tropical'); CREATE TABLE if not exists water_temperature (id int, farm_id int, date date, temperature float); INSERT INTO water_temperature (id, farm_id, date, temperature) VALUES (1, 1, '2022-01-01', 29.5); INSERT INTO water_temperature (id, farm_id, date, temperature) VALUES (2, 1, '2022-02-01', 28.8); INSERT INTO water_temperature (id, farm_id, date, temperature) VALUES (3, 2, '2022-01-01', 27.9);
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What is the average water temperature in tropical aquaculture farms in the past 6 months, grouped by month and region, and only showing records with a temperature above 28 degrees Celsius?
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SELECT AVG(temperature) as avg_temperature, DATE_FORMAT(date, '%Y-%m') as month, region FROM farms f JOIN water_temperature w ON f.id = w.farm_id WHERE temperature > 28 AND type = 'Tropical' AND date >= DATE_SUB(CURDATE(), INTERVAL 6 MONTH) GROUP BY month, region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AutoShow (id INT, name VARCHAR(255), location VARCHAR(255), country VARCHAR(255), num_electric_vehicles INT); INSERT INTO AutoShow (id, name, location, country, num_electric_vehicles) VALUES (1, 'Detroit Auto Show', 'Detroit', 'USA', 50);
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Which auto show has the most electric vehicle models on display?
|
SELECT name, location, MAX(num_electric_vehicles) FROM AutoShow;
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gretelai_synthetic_text_to_sql
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CREATE TABLE agricultural_projects (id INT PRIMARY KEY, name VARCHAR(100), location VARCHAR(50), funding_source VARCHAR(50), start_date DATE, end_date DATE); INSERT INTO agricultural_projects (id, name, location, funding_source, start_date, end_date) VALUES (1, 'Solar Powered Irrigation', 'Rural Kenya', 'World Bank', '2022-01-01', '2023-12-31'), (2, 'Crop Diversification', 'Rural Peru', 'USAID', '2022-06-15', '2024-06-14');
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Show all agricultural projects in 'Rural Kenya'
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SELECT * FROM agricultural_projects WHERE location = 'Rural Kenya';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Soldiers (SoldierID INT, Name VARCHAR(50), Rank VARCHAR(20), EntryYear INT); INSERT INTO Soldiers (SoldierID, Name, Rank, EntryYear) VALUES (1, 'John Doe', 'Captain', 1995), (2, 'Jane Smith', 'Lieutenant', 2002);
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Insert a new record for a soldier with Name 'Mary Johnson', Rank 'Lieutenant', and EntryYear 2020.
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INSERT INTO Soldiers (Name, Rank, EntryYear) VALUES ('Mary Johnson', 'Lieutenant', 2020);
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gretelai_synthetic_text_to_sql
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CREATE TABLE animal_population (species VARCHAR(255), animal_count INT);
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Find the number of animals per species in the "animal_population" table
|
SELECT species, SUM(animal_count) FROM animal_population GROUP BY species;
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gretelai_synthetic_text_to_sql
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CREATE TABLE species (id INT, name VARCHAR(255), carbon_sequestration FLOAT); INSERT INTO species (id, name, carbon_sequestration) VALUES (1, 'Species1', 123.45); INSERT INTO species (id, name, carbon_sequestration) VALUES (2, 'Species2', 234.56); CREATE TABLE region (id INT, name VARCHAR(255)); INSERT INTO region (id, name) VALUES (1, 'Region1'); INSERT INTO region (id, name) VALUES (2, 'Region2');
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What is the total carbon sequestration for each species?
|
SELECT s.name, SUM(s.carbon_sequestration) as total_carbon FROM species s GROUP BY s.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Events (EventID INT, EventName VARCHAR(20), Game VARCHAR(10), Participants INT); INSERT INTO Events (EventID, EventName, Game, Participants) VALUES (1, 'Event1', 'Esports', 1200); INSERT INTO Events (EventID, EventName, Game, Participants) VALUES (2, 'Event2', 'Esports', 800);
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List the names of Esports events that have had more than 1000 participants.
|
SELECT EventName FROM Events WHERE Game = 'Esports' AND Participants > 1000;
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gretelai_synthetic_text_to_sql
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CREATE TABLE recycling_rates (material VARCHAR(255), year INT, rate FLOAT); INSERT INTO recycling_rates (material, year, rate) VALUES ('Plastic', 2019, 12.0), ('Glass', 2019, 22.0), ('Paper', 2019, 35.0), ('Metal', 2019, 45.0);
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What is the average recycling rate in percentage for the bottom 2 material types in 2019?
|
SELECT r.material, AVG(r.rate) as avg_rate FROM recycling_rates r WHERE r.year = 2019 AND r.material IN (SELECT material FROM recycling_rates WHERE year = 2019 ORDER BY rate LIMIT 2 OFFSET 2) GROUP BY r.material;
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gretelai_synthetic_text_to_sql
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CREATE TABLE artworks (artwork_id INT, title VARCHAR(50), year INT, artist_id INT, value INT, country VARCHAR(50)); INSERT INTO artworks (artwork_id, title, year, artist_id, value, country) VALUES (1, 'Guernica', 1937, 1, 20000000, 'Spain'); INSERT INTO artworks (artwork_id, title, year, artist_id, value, country) VALUES (2, 'Study for Portrait of Lucian Freud', 1969, 2, 15000000, 'UK');
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What is the average value of artworks in the 'artworks' table?
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SELECT AVG(value) FROM artworks;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AfricanPlate (volcano_name TEXT, location TEXT); INSERT INTO AfricanPlate (volcano_name, location) VALUES ('Tagoro', 'Atlantic Ocean'), ('Nazca', 'Atlantic Ocean');
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Which underwater volcanoes are within the African plate?
|
SELECT * FROM AfricanPlate WHERE location LIKE '%Atlantic Ocean%';
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gretelai_synthetic_text_to_sql
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CREATE TABLE music_streaming (id INT, user_id INT, song_id INT, country VARCHAR(255), timestamp TIMESTAMP);
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How many unique countries are represented in the music_streaming table?
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SELECT COUNT(DISTINCT country) FROM music_streaming;
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gretelai_synthetic_text_to_sql
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CREATE TABLE if not exists 'disease_data' (id INT, state TEXT, disease TEXT, prevalence INT, PRIMARY KEY(id));
|
Increase prevalence by 10 for disease 'Flu' in 'disease_data'
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UPDATE 'disease_data' SET prevalence = prevalence + 10 WHERE disease = 'Flu';
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gretelai_synthetic_text_to_sql
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CREATE TABLE community_health_workers (worker_id INT, worker_name TEXT, state TEXT); INSERT INTO community_health_workers (worker_id, worker_name, state) VALUES (1, 'Jamila', 'Florida'), (2, 'Keith', 'California'); CREATE TABLE mental_health_patients (patient_id INT, worker_id INT, diagnosis TEXT); INSERT INTO mental_health_patients (patient_id, worker_id, diagnosis) VALUES (101, 1, 'Anxiety'), (102, 1, 'Depression'), (201, NULL, 'Bipolar');
|
What is the count of community health workers serving mental health patients in Florida?
|
SELECT COUNT(DISTINCT c.worker_id) FROM community_health_workers c JOIN mental_health_patients m ON c.worker_id = m.worker_id WHERE c.state = 'Florida' AND m.diagnosis IS NOT NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Attorneys (AttorneyID INT, JoinYear INT, BillingAmount DECIMAL); INSERT INTO Attorneys (AttorneyID, JoinYear, BillingAmount) VALUES (1, 2016, 5000.00), (2, 2018, 3000.00), (3, 2015, 4000.00); CREATE TABLE Cases (CaseID INT, AttorneyID INT, CaseOutcome VARCHAR(10)); INSERT INTO Cases (CaseID, AttorneyID, CaseOutcome) VALUES (101, 1, 'Lost'), (102, 2, 'Won'), (103, 3, 'Won');
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What is the total billing amount for cases won by attorneys who joined the firm in 2018 or later?
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SELECT SUM(BillingAmount) FROM Attorneys JOIN Cases ON Attorneys.AttorneyID = Cases.AttorneyID WHERE CaseOutcome = 'Won' AND JoinYear >= 2018;
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gretelai_synthetic_text_to_sql
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CREATE TABLE investment (id INT, project TEXT, location TEXT, investment_amount INT, year INT); INSERT INTO investment (id, project, location, investment_amount, year) VALUES (1, 'Potato Seed Project', 'Peru', 200000, 2018), (2, 'Corn Seed Project', 'Brazil', 300000, 2019), (3, 'Rice Seed Project', 'Colombia', 150000, 2017), (4, 'Wheat Seed Project', 'Argentina', 250000, 2020);
|
What was the total investment in agricultural innovation projects in Latin America in the past 5 years?
|
SELECT SUM(investment_amount) FROM investment WHERE location LIKE 'Latin%' AND year BETWEEN 2017 AND 2022;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ArtifactContext (ArtifactID INT, ArtifactName TEXT, HistoricalContext TEXT); INSERT INTO ArtifactContext (ArtifactID, ArtifactName, HistoricalContext) VALUES (1, 'Pompeii Amphora', 'Ancient Roman trade');
|
What is the historical context of artifacts analyzed by French researchers?
|
SELECT ArtifactName, HistoricalContext FROM ArtifactContext INNER JOIN Artifacts ON ArtifactContext.ArtifactID = Artifacts.ArtifactID WHERE Artifacts.AnalyzedBy = 'France';
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gretelai_synthetic_text_to_sql
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CREATE TABLE ad_interactions (user_id INT, ad_id INT, country VARCHAR(2), interaction_time FLOAT); INSERT INTO ad_interactions (user_id, ad_id, country, interaction_time) VALUES (1, 1001, 'JP', 25.3), (2, 1001, 'KR', 30.5);
|
What is the total number of users in Japan and South Korea who have interacted with a specific ad, and what was the total engagement time for these users?
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SELECT SUM(CASE WHEN country IN ('JP', 'KR') THEN 1 ELSE 0 END) as total_users, SUM(interaction_time) as total_engagement_time FROM ad_interactions WHERE ad_id = 1001;
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gretelai_synthetic_text_to_sql
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CREATE TABLE pacific_volcanoes (name VARCHAR(255), location VARCHAR(255));
|
What is the total number of underwater volcanoes in the Pacific Ocean?
|
SELECT COUNT(*) FROM pacific_volcanoes WHERE location = 'Pacific Ocean';
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gretelai_synthetic_text_to_sql
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CREATE TABLE TVShows (ShowID INT, Title VARCHAR(255), Country VARCHAR(50), MarketingExpenses DECIMAL(10,2), ProductionCompany VARCHAR(255)); CREATE TABLE ProductionCompanies (CompanyID INT, CompanyName VARCHAR(255));
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List the TV shows with the highest marketing expenses for each country and their corresponding production companies.
|
SELECT T1.Title, T1.Country, T1.MarketingExpenses, T2.CompanyName FROM TVShows T1 INNER JOIN (SELECT Country, MAX(MarketingExpenses) AS Max_Expenses FROM TVShows GROUP BY Country) T2 ON T1.Country = T2.Country AND T1.MarketingExpenses = T2.Max_Expenses INNER JOIN ProductionCompanies T3 ON T1.ProductionCompany = T3.CompanyName;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Astronauts (name VARCHAR(30), age INT, mission_name VARCHAR(30)); INSERT INTO Astronauts (name, age, mission_name) VALUES ('Gus Grissom', 36, 'Mercury-Redstone 4'), ('John Glenn', 40, 'Friendship 7');
|
Who is the youngest astronaut to have participated in a space mission?
|
SELECT name, age FROM Astronauts ORDER BY age LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE community_health_workers (worker_id INT, name TEXT, identity TEXT); INSERT INTO community_health_workers (worker_id, name, identity) VALUES (1, 'John Doe', 'Straight'), (2, 'Jane Smith', 'Two-Spirit'), (3, 'Maria Garcia', 'Native Hawaiian');
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How many community health workers identify as Two-Spirit or Native Hawaiian?
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SELECT COUNT(*) FROM community_health_workers WHERE identity IN ('Two-Spirit', 'Native Hawaiian');
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gretelai_synthetic_text_to_sql
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CREATE TABLE fans (fan_id INT, name VARCHAR(100), country VARCHAR(100)); INSERT INTO fans (fan_id, name, country) VALUES (1, 'John Doe', 'USA'); INSERT INTO fans (fan_id, name, country) VALUES (2, 'Jane Smith', 'Canada'); INSERT INTO fans (fan_id, name, country) VALUES (3, 'Jose Garcia', 'Mexico');
|
Delete all records of fans from a specific country.
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DELETE FROM fans WHERE country = 'USA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE YttriumProduction (Refiner VARCHAR(50), Year INT, Production FLOAT); INSERT INTO YttriumProduction(Refiner, Year, Production) VALUES ('RefinerX', 2017, 123.5), ('RefinerX', 2018, 127.8), ('RefinerX', 2019, 134.5), ('RefinerY', 2017, 109.1), ('RefinerY', 2018, 113.5), ('RefinerY', 2019, 119.8);
|
Find the yttrium production difference between 2018 and 2017 for each refiner.
|
SELECT Refiner, Production - LAG(Production) OVER (PARTITION BY Refiner ORDER BY Year) as Difference FROM YttriumProduction WHERE Refiner IN ('RefinerX', 'RefinerY');
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gretelai_synthetic_text_to_sql
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CREATE TABLE annual_water_usage (year INT, user_type VARCHAR(10), water_usage INT);
|
What is the annual change in water usage for agricultural users in Colorado?
|
SELECT EXTRACT(YEAR FROM date_trunc('year', date)) as year, AVG(water_usage) - LAG(AVG(water_usage)) OVER (ORDER BY year) as annual_change FROM annual_water_usage JOIN (SELECT date_trunc('year', date) as date, user_type FROM water_consumption_by_day) tmp ON annual_water_usage.year = EXTRACT(YEAR FROM tmp.date) WHERE user_type = 'agricultural' AND state = 'Colorado' GROUP BY year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE tweets (tweet_id INT, user_id INT, tweet_date DATE);CREATE TABLE user_settings (user_id INT, location_sharing BOOLEAN);
|
What is the average number of tweets per day for users who have opted in to location sharing?
|
SELECT AVG(num_tweets_per_day) as avg_num_tweets FROM (SELECT u.user_id, COUNT(t.tweet_id) as num_tweets_per_day FROM user_settings u JOIN tweets t ON u.user_id = t.user_id WHERE u.location_sharing = TRUE GROUP BY u.user_id) subquery;
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales (sale_id INT, dispensary_id INT, strain VARCHAR(255), quantity INT);CREATE TABLE dispensaries (dispensary_id INT, name VARCHAR(255), state VARCHAR(255));
|
Find the total quantity of each strain sold in California and Washington.
|
SELECT strain, SUM(quantity) as total_quantity FROM sales JOIN dispensaries ON sales.dispensary_id = dispensaries.dispensary_id WHERE state IN ('California', 'Washington') GROUP BY strain;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ingredient_safety (ingredient_id INT, country_safety_score INT); INSERT INTO ingredient_safety (ingredient_id, country_safety_score) VALUES (1, 95), (2, 90), (3, 85), (4, 92), (5, 88), (6, 97), (7, 80), (8, 96), (9, 85), (10, 93), (11, 95), (12, 98); CREATE TABLE product_ingredients (product_id INT, ingredient_id INT); INSERT INTO product_ingredients (product_id, ingredient_id) VALUES (1, 1), (1, 2), (2, 3), (2, 4), (3, 5), (3, 6), (4, 7), (4, 8), (5, 9), (5, 10), (6, 11), (6, 12);
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List all products that contain an ingredient sourced from a country with a high safety record, and the associated safety score of that country.
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SELECT p.product_name, p.brand_name, i.country_name, i.country_safety_score FROM product_ingredients pi INNER JOIN cosmetic_products p ON pi.product_id = p.product_id INNER JOIN ingredient_sourcing i ON pi.ingredient_id = i.ingredient_id INNER JOIN ingredient_safety s ON i.country_name = s.country_name WHERE s.country_safety_score >= 90;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Patients (PatientID INT, Age INT, Gender VARCHAR(10), RuralHealthFacility VARCHAR(20), Disease VARCHAR(20)); INSERT INTO Patients (PatientID, Age, Gender, RuralHealthFacility, Disease) VALUES (1, 55, 'Male', 'Bumpkinsville RHF', 'Diabetes');
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What is the average age of patients diagnosed with diabetes in the rural county of "Bumpkinsville"?
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SELECT AVG(Age) FROM Patients WHERE RuralHealthFacility = 'Bumpkinsville RHF' AND Disease = 'Diabetes';
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gretelai_synthetic_text_to_sql
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CREATE TABLE fans (id INT PRIMARY KEY, name VARCHAR(50), age INT, gender VARCHAR(10), state VARCHAR(50));
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Delete fan records from the "fans" table for fans who are over 60
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DELETE FROM fans WHERE age > 60;
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gretelai_synthetic_text_to_sql
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CREATE TABLE water_usage (state VARCHAR(20), year INT, volume_m3 INT); INSERT INTO water_usage (state, year, volume_m3) VALUES ('Texas', 2017, 25000000), ('Texas', 2018, 26000000), ('Texas', 2019, 27000000), ('Texas', 2020, 28000000), ('Texas', 2021, 29000000);
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What is the average water usage in Texas over the last 5 years?
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SELECT AVG(volume_m3) FROM water_usage WHERE state = 'Texas' AND year BETWEEN 2017 AND 2021;
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gretelai_synthetic_text_to_sql
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CREATE TABLE PRODUCT ( id INT PRIMARY KEY, name TEXT, material TEXT, quantity INT, price INT, country TEXT, certifications TEXT, is_recycled BOOLEAN ); INSERT INTO PRODUCT (id, name, material, quantity, price, country, certifications, is_recycled) VALUES (1, 'Organic Cotton Shirt', 'Organic Cotton', 30, 50, 'USA', 'GOTS, Fair Trade', FALSE); INSERT INTO PRODUCT (id, name, material, quantity, price, country, certifications, is_recycled) VALUES (2, 'Recycled Poly Shoes', 'Recycled Polyester', 25, 75, 'Germany', 'BlueSign', TRUE); INSERT INTO PRODUCT (id, name, material, quantity, price, country) VALUES (3, 'Bamboo T-Shirt', 'Bamboo', 15, 30, 'China'); INSERT INTO PRODUCT (id, name, material, quantity, price, country, certifications, is_recycled) VALUES (4, 'GOTS Certified Organic Shoes', 'Organic Cotton', 20, 60, 'Italy', 'GOTS', TRUE);
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Increase the price of all products made from recycled materials by 10%.
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UPDATE PRODUCT SET price = price * 1.1 WHERE is_recycled = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE astronauts(name TEXT, missions INTEGER, days_in_space REAL); INSERT INTO astronauts(name, missions, days_in_space) VALUES('Neil Armstrong', 1, 265.5), ('Buzz Aldrin', 1, 216.4);
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Who has spent the most time in space?
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SELECT name, MAX(days_in_space) FROM astronauts;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ResearchPapers(Id INT, Title VARCHAR(50), Author VARCHAR(50), Year INT, Domain VARCHAR(50)); INSERT INTO ResearchPapers(Id, Title, Author, Year, Domain) VALUES (1, 'Autonomous Driving Algorithms', 'Li, X.', 2020, 'Asia'); INSERT INTO ResearchPapers(Id, Title, Author, Year, Domain) VALUES (2, 'Deep Learning for Self-Driving Cars', 'Kim, Y.', 2020, 'Asia');
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What is the total number of autonomous driving research papers published by Asian authors in 2020?
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SELECT COUNT(*) FROM ResearchPapers WHERE Year = 2020 AND Domain = 'Asia';
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gretelai_synthetic_text_to_sql
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CREATE TABLE DiveSite (Name VARCHAR(50) PRIMARY KEY, Depth INT);
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Add a new "DiveSite" record with a name of Blue Hole and a depth of 120 meters
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INSERT INTO DiveSite (Name, Depth) VALUES ('Blue Hole', 120);
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gretelai_synthetic_text_to_sql
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CREATE TABLE carbon_footprint (name VARCHAR(255), location VARCHAR(255), year INT, footprint DECIMAL(5,2)); INSERT INTO carbon_footprint (name, location, year, footprint) VALUES ('Resort Stay', 'Maldives', 2015, 21.34), ('Liveaboard', 'Maldives', 2015, 12.15);
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What is the average carbon footprint of tourists visiting the Maldives?
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SELECT AVG(footprint) FROM carbon_footprint WHERE location = 'Maldives';
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gretelai_synthetic_text_to_sql
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CREATE TABLE community_health_workers (id INT, name VARCHAR(50), race VARCHAR(50), ethnicity VARCHAR(50), years_of_experience INT); INSERT INTO community_health_workers (id, name, race, ethnicity, years_of_experience) VALUES (1, 'John Doe', 'White', 'Not Hispanic or Latino', 5), (2, 'Jane Smith', 'Black or African American', 'Not Hispanic or Latino', 10);
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Which community health workers have the most experience?
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SELECT name, years_of_experience, RANK() OVER (ORDER BY years_of_experience DESC) as rank FROM community_health_workers;
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gretelai_synthetic_text_to_sql
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CREATE TABLE researchers (id INT, name VARCHAR(50), country VARCHAR(50)); INSERT INTO researchers (id, name, country) VALUES (1, 'Sanna Simula', 'Finland'), (2, 'Kristian Olsen', 'Greenland'), (3, 'Agnes Sorensen', 'Greenland'), (4, 'Joseph Okpik', 'Canada');
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Which countries have researchers in the database?
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SELECT DISTINCT country FROM researchers;
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gretelai_synthetic_text_to_sql
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CREATE TABLE legal_precedents (precedent_id INT, precedent_name VARCHAR(100)); CREATE TABLE civil_cases (case_id INT, case_type VARCHAR(20), precedent_id INT); CREATE TABLE criminal_cases (case_id INT, case_type VARCHAR(20), precedent_id INT);
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Find the unique legal precedents that have been cited in cases from both the 'civil' and 'criminal' case type tables.
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SELECT precedent_name FROM legal_precedents WHERE precedent_id IN (SELECT precedent_id FROM civil_cases) INTERSECT SELECT precedent_name FROM legal_precedents WHERE precedent_id IN (SELECT precedent_id FROM criminal_cases);
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gretelai_synthetic_text_to_sql
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CREATE TABLE PlayerDemographics (PlayerID INT, Age INT, GamePreference VARCHAR(20)); INSERT INTO PlayerDemographics (PlayerID, Age, GamePreference) VALUES (1, 24, 'sports');
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How many players play sports games and are younger than 25?
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SELECT COUNT(*) FROM PlayerDemographics WHERE Age < 25 AND GamePreference = 'sports';
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gretelai_synthetic_text_to_sql
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CREATE TABLE MineTypes (MineID int, MineType varchar(50)); INSERT INTO MineTypes VALUES (1, 'Small-scale Mine'), (2, 'Medium-scale Mine'), (3, 'Large-scale Mine'); CREATE TABLE ExtractionData (MineID int, ExtractionDate date, Material varchar(10), Quantity int); INSERT INTO ExtractionData VALUES (1, '2022-01-01', 'Gold', 1000), (1, '2022-01-15', 'Gold', 1500), (2, '2022-01-30', 'Gold', 800), (1, '2022-02-05', 'Gold', 1200), (3, '2022-03-01', 'Gold', 1000);
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What is the total quantity of minerals extracted by small-scale mines in Zambia in 2022?
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SELECT mt.MineType, SUM(ed.Quantity) as TotalExtraction FROM ExtractionData ed JOIN MineTypes mt ON ed.MineID = mt.MineID WHERE ed.ExtractionDate BETWEEN '2022-01-01' AND '2022-12-31' AND mt.MineType = 'Small-scale Mine' AND ed.Material = 'Gold' GROUP BY mt.MineType;
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gretelai_synthetic_text_to_sql
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CREATE TABLE deep_sea_trenches (name VARCHAR(255), region VARCHAR(255), depth FLOAT);INSERT INTO deep_sea_trenches (name, region, depth) VALUES ('Trench 1', 'Indian Ocean', 6000), ('Trench 2', 'Atlantic Ocean', 7000), ('Trench 3', 'Indian Ocean', 5000);
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What is the minimum depth of all deep-sea trenches in the Indian Ocean?
|
SELECT MIN(depth) FROM deep_sea_trenches WHERE region = 'Indian Ocean';
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gretelai_synthetic_text_to_sql
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CREATE TABLE MatchStats (MatchID int, PlayerID int, Kills int, Deaths int); INSERT INTO MatchStats VALUES (1, 1, 15, 5), (2, 2, 10, 8), (3, 1, 20, 10), (4, 3, 12, 7);
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What is the maximum number of kills achieved by a player in a single match?
|
SELECT PlayerID, MAX(Kills) as MaxKills FROM MatchStats GROUP BY PlayerID;
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gretelai_synthetic_text_to_sql
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CREATE TABLE network_investments (investment FLOAT, region VARCHAR(20)); INSERT INTO network_investments (investment, region) VALUES (120000, 'Western'), (150000, 'Northern'), (180000, 'Western');
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What is the maximum network investment for the telecom provider in the Western region?
|
SELECT MAX(investment) FROM network_investments WHERE region = 'Western';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Exhibitions (ID INT, Title VARCHAR(50), City VARCHAR(20), Country VARCHAR(20), Date DATE, TicketPrice INT); INSERT INTO Exhibitions (ID, Title, City, Country, Date, TicketPrice) VALUES (1, 'Traditional Japanese Art', 'Tokyo', 'Japan', '2019-03-01', 15); CREATE TABLE TicketSales (ID INT, ExhibitionID INT, Quantity INT, Date DATE); INSERT INTO TicketSales (ID, ExhibitionID, Quantity, Date) VALUES (1, 1, 500, '2019-03-01');
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What is the total revenue generated from ticket sales for exhibitions in Tokyo, Japan in 2019?'
|
SELECT SUM(TicketSales.Quantity * Exhibitions.TicketPrice) FROM TicketSales INNER JOIN Exhibitions ON TicketSales.ExhibitionID = Exhibitions.ID WHERE Exhibitions.City = 'Tokyo' AND Exhibitions.Country = 'Japan' AND Exhibitions.Date BETWEEN '2019-01-01' AND '2019-12-31';
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gretelai_synthetic_text_to_sql
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CREATE TABLE space_debris (id INT, name VARCHAR(50), type VARCHAR(50), country VARCHAR(50), launch_date DATE, mass FLOAT);
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Display the average mass of space debris in the space_debris table for the debris items from the USA
|
SELECT AVG(mass) as average_mass FROM space_debris WHERE country = 'USA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Employees (EmployeeID INT, FirstName VARCHAR(50), LastName VARCHAR(50), Department VARCHAR(50), Salary DECIMAL(10,2), LeftCompany BOOLEAN);
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Update the salary of all employees in the accounting department
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UPDATE Employees SET Salary = 65000 WHERE Department = 'Accounting';
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gretelai_synthetic_text_to_sql
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CREATE TABLE inspections (inspection_id INT PRIMARY KEY, restaurant_id INT, inspection_date DATE, violation_code INT, description VARCHAR(255));
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List restaurants that have had a food safety violation in the last 3 months
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SELECT r.restaurant_id, r.restaurant_name FROM restaurants r JOIN inspections i ON r.restaurant_id = i.restaurant_id WHERE i.inspection_date >= DATEADD(month, -3, GETDATE()) AND i.violation_code IS NOT NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE italy_data (year INT, network VARCHAR(15), revenue FLOAT); INSERT INTO italy_data (year, network, revenue) VALUES (2020, 'Vodafone', 15000000), (2020, 'TIM', 12000000), (2020, 'Wind Tre', 13000000);
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What is the total revenue generated by each mobile network in Italy for the year 2020?
|
SELECT network, SUM(revenue) as total_revenue FROM italy_data WHERE year = 2020 GROUP BY network;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Farmers(FarmerID INT, Name VARCHAR(50), Local BOOLEAN);CREATE TABLE FruitsVeggies(FruitVeggieID INT, FarmerID INT, Product VARCHAR(50), Quantity INT, DeliveryDate DATE);INSERT INTO Farmers VALUES (1, 'Amy Johnson', TRUE), (2, 'Bob Smith', FALSE);INSERT INTO FruitsVeggies VALUES (1, 1, 'Apples', 300, '2022-05-15'), (2, 1, 'Carrots', 400, '2022-05-01'), (3, 2, 'Bananas', 500, '2022-04-20');
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Identify the total quantity of fruits and vegetables that were supplied by local farmers in the last month?
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SELECT SUM(Quantity) FROM FruitsVeggies WHERE DeliveryDate >= DATEADD(month, -1, GETDATE()) AND Local = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE VeteranEmployment (VEID INT, Age INT, Gender VARCHAR(10), State VARCHAR(20), NumVeterans INT); INSERT INTO VeteranEmployment (VEID, Age, Gender, State, NumVeterans) VALUES (1, 25, 'Male', 'California', 100), (2, 35, 'Female', 'Texas', 200), (3, 45, 'Male', 'Florida', 150);
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Find the number of veterans employed by age group and gender, in each state?
|
SELECT State, Gender, Age, COUNT(NumVeterans) as NumVeterans FROM VeteranEmployment GROUP BY State, Gender, Age;
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales(item VARCHAR(20), location VARCHAR(20), quantity INT, sale_date DATE); INSERT INTO sales (item, location, quantity, sale_date) VALUES ('Dress', 'Paris', 15, '2021-01-01'); INSERT INTO sales (item, location, quantity, sale_date) VALUES ('Top', 'Paris', 20, '2021-01-02');
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What was the total quantity of 'Dress' items sold in 'Paris' in 2021?
|
SELECT SUM(quantity) FROM sales WHERE item = 'Dress' AND location = 'Paris' AND sale_date BETWEEN '2021-01-01' AND '2021-12-31';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE PublicTransportation (TripID INT, TripDate DATE, Mode VARCHAR(255), Trips INT); INSERT INTO PublicTransportation (TripID, TripDate, Mode, Trips) VALUES (1, '2022-01-01', 'Bus', 50000), (2, '2022-01-02', 'Subway', 70000), (3, '2022-01-03', 'Bus', 55000);
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What is the maximum number of public transportation trips taken in a single day for each mode of transportation?
|
SELECT MAX(Trips), Mode FROM PublicTransportation GROUP BY Mode;
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gretelai_synthetic_text_to_sql
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CREATE TABLE artists (id INT, name VARCHAR(255), gender VARCHAR(6)); CREATE TABLE albums (id INT, artist_id INT, year INT);
|
How many female and male artists released albums in 2021?
|
SELECT artists.gender, COUNT(*) FROM albums JOIN artists ON albums.artist_id = artists.id WHERE albums.year = 2021 GROUP BY artists.gender;
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gretelai_synthetic_text_to_sql
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CREATE TABLE tax_rates_3 (id INT, neighborhood TEXT, city TEXT, state TEXT, property_type TEXT, rate FLOAT);
|
Which neighborhood in Boston has the highest property tax?
|
SELECT MAX(rate) FROM tax_rates_3 WHERE city = 'Boston' AND property_type = 'Residential' GROUP BY neighborhood;
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gretelai_synthetic_text_to_sql
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CREATE TABLE RevenueData (GameID INT, GameType VARCHAR(20), Revenue INT); INSERT INTO RevenueData (GameID, GameType, Revenue) VALUES (1, 'Action', 5000), (2, 'Adventure', 6000), (3, 'Simulation', 8000), (4, 'Action', 7000), (5, 'Simulation', 9000), (6, 'Adventure', 10000);
|
What is the average revenue for each game type?
|
SELECT GameType, AVG(Revenue) FROM RevenueData GROUP BY GameType;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE daily_usage (city VARCHAR(50), date DATE, water_usage FLOAT); INSERT INTO daily_usage VALUES ('Dallas', '2022-01-01', 500000), ('Dallas', '2022-01-02', 600000), ('Dallas', '2022-01-03', 550000), ('Houston', '2022-01-01', 450000), ('Houston', '2022-01-02', 500000), ('Houston', '2022-01-03', 480000), ('Austin', '2022-01-01', 350000), ('Austin', '2022-01-02', 370000), ('Austin', '2022-01-03', 360000), ('San Antonio', '2022-01-01', 400000), ('San Antonio', '2022-01-02', 420000), ('San Antonio', '2022-01-03', 390000);
|
Find the daily water usage for the top 5 water consuming cities in Texas.
|
SELECT city, SUM(water_usage) as total_usage FROM daily_usage WHERE date >= '2022-01-01' AND date <= '2022-01-03' AND city IN ('Dallas', 'Houston', 'Austin', 'San Antonio', 'Fort Worth') GROUP BY city ORDER BY total_usage DESC LIMIT 5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE seafood_exports (id INT, export_date DATE, export_country TEXT, import_country TEXT, quantity INT); INSERT INTO seafood_exports (id, export_date, export_country, import_country, quantity) VALUES (1, '2022-01-01', 'Thailand', 'Singapore', 500); INSERT INTO seafood_exports (id, export_date, export_country, import_country, quantity) VALUES (2, '2022-02-15', 'Thailand', 'Singapore', 600);
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What was the total quantity of shrimp exported from Thailand to Singapore in 2022?
|
SELECT SUM(quantity) FROM seafood_exports WHERE export_country = 'Thailand' AND import_country = 'Singapore' AND EXTRACT(YEAR FROM export_date) = 2022 AND species = 'Shrimp';
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gretelai_synthetic_text_to_sql
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CREATE TABLE donors (donor_id INT, donor_type TEXT, donation_amount DECIMAL(10,2)); INSERT INTO donors VALUES (1, 'Individual', 50.00); INSERT INTO donors VALUES (2, 'Corporation', 5000.00);
|
What was the average donation amount for each donor type?
|
SELECT donor_type, AVG(donation_amount) as avg_donation FROM donors GROUP BY donor_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE if NOT EXISTS satellite_images (id int, location varchar(50), image_date datetime, purpose varchar(50)); INSERT INTO satellite_images (id, location, image_date, purpose) VALUES (1, 'Brazil', '2021-01-01 10:00:00', 'agriculture'), (2, 'Brazil', '2021-01-02 10:00:00', 'agriculture');
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What is the count of satellite images taken for agricultural purposes in Brazil in January 2021?
|
SELECT COUNT(*) FROM satellite_images WHERE location = 'Brazil' AND purpose = 'agriculture' AND image_date >= '2021-01-01' AND image_date < '2021-02-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Artists (ArtistID INT PRIMARY KEY, ArtistName VARCHAR(100), Gender VARCHAR(10), Genre VARCHAR(50), TicketsSold INT); INSERT INTO Artists (ArtistID, ArtistName, Gender, Genre, TicketsSold) VALUES (1, 'Artist A', 'Female', 'Jazz', 3000), (2, 'Artist B', 'Male', 'Jazz', 4000), (3, 'Artist C', 'Female', 'Jazz', 5000), (4, 'Artist D', 'Male', 'Jazz', 2000), (5, 'Artist E', 'Female', 'Rock', 6000);
|
Who are the female jazz artists with the highest ticket sales?
|
SELECT ArtistName FROM Artists WHERE Gender = 'Female' AND Genre = 'Jazz' ORDER BY TicketsSold DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE endangered_species (species VARCHAR(255), habitat_type VARCHAR(255), endangered BOOLEAN); CREATE TABLE habitat_preservation (habitat_type VARCHAR(255), location VARCHAR(255)); CREATE TABLE habitats (habitat_type VARCHAR(255), area_size FLOAT);
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Calculate the percentage of endangered species for each habitat type, considering the total number of species in the "endangered_species", "habitat_preservation", and "habitats" tables
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SELECT h1.habitat_type, (COUNT(e1.species) * 100.0 / (SELECT COUNT(DISTINCT e2.species) FROM endangered_species e2 WHERE e2.habitat_type = h1.habitat_type)) as endangered_percentage FROM endangered_species e1 INNER JOIN habitat_preservation h1 ON e1.habitat_type = h1.habitat_type INNER JOIN habitats h2 ON h1.habitat_type = h2.habitat_type GROUP BY h1.habitat_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE MaxSalaries (id INT, company_id INT, job_role VARCHAR(50), salary INT); INSERT INTO MaxSalaries (id, company_id, job_role, salary) VALUES (1, 1, 'Engineer', 90000), (2, 1, 'Manager', 120000), (3, 2, 'Engineer', 95000), (4, 2, 'Engineer', 100000);
|
What is the maximum salary by company and job role?
|
SELECT company_id, job_role, MAX(salary) as max_salary FROM MaxSalaries GROUP BY company_id, job_role;
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gretelai_synthetic_text_to_sql
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CREATE TABLE donor (id INT, name VARCHAR(50)); CREATE TABLE donation (id INT, donor_id INT, amount DECIMAL(10,2), donation_date DATE); CREATE TABLE volunteer (id INT, donor_id INT, volunteer_date DATE);
|
What is the number of volunteers who have not made a donation?
|
SELECT COUNT(DISTINCT v.id) as total_volunteers FROM volunteer v LEFT JOIN donation d ON v.donor_id = d.donor_id WHERE d.id IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Exhibitions (ExhibitionID INT, ExhibitionName VARCHAR(255)); INSERT INTO Exhibitions (ExhibitionID, ExhibitionName) VALUES (1, 'Modern Art'); INSERT INTO Exhibitions (ExhibitionID, ExhibitionName) VALUES (2, 'Natural History'); CREATE TABLE Visitors (VisitorID INT, VisitorName VARCHAR(255), HasVisitedMultipleExhibitions BOOLEAN); INSERT INTO Visitors (VisitorID, VisitorName, HasVisitedMultipleExhibitions) VALUES (1, 'John Doe', true); INSERT INTO Visitors (VisitorID, VisitorName, HasVisitedMultipleExhibitions) VALUES (2, 'Jane Doe', false); INSERT INTO Visitors (VisitorID, VisitorName, HasVisitedMultipleExhibitions) VALUES (3, 'Jim Smith', true); CREATE TABLE VisitorExhibitions (VisitorID INT, ExhibitionID INT); INSERT INTO VisitorExhibitions (VisitorID, ExhibitionID) VALUES (1, 1); INSERT INTO VisitorExhibitions (VisitorID, ExhibitionID) VALUES (1, 2); INSERT INTO VisitorExhibitions (VisitorID, ExhibitionID) VALUES (3, 1); INSERT INTO VisitorExhibitions (VisitorID, ExhibitionID) VALUES (3, 2);
|
What is the total number of visitors who have attended multiple exhibitions?
|
SELECT COUNT(V.VisitorID) as TotalVisitors FROM Visitors V INNER JOIN VisitorExhibitionsVE ON V.VisitorID = VE.VisitorID GROUP BY V.VisitorID HAVING COUNT(VE.ExhibitionID) > 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE SUSTAINABILITY (store_id INT, waste_reduction FLOAT, water_conservation FLOAT); INSERT INTO SUSTAINABILITY VALUES (1, 0.15, 0.20), (2, 0.10, 0.15), (3, 0.20, 0.25), (4, 0.12, 0.18);
|
List stores that meet or exceed the specified sustainability thresholds for waste reduction and water conservation.
|
SELECT store_id, waste_reduction, water_conservation FROM SUSTAINABILITY WHERE waste_reduction >= 0.15 AND water_conservation >= 0.20;
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gretelai_synthetic_text_to_sql
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CREATE TABLE military_tech (country VARCHAR(50), tech_type VARCHAR(50), quantity INT); INSERT INTO military_tech (country, tech_type, quantity) VALUES ('USA', 'Aircraft', 13000), ('USA', 'Vessels', 500), ('China', 'Aircraft', 5000), ('China', 'Vessels', 700), ('Russia', 'Aircraft', 4000), ('Russia', 'Vessels', 600);
|
What is the distribution of military technology types by country?
|
SELECT country, tech_type, quantity FROM military_tech;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE climate_finance (country VARCHAR(255), sector VARCHAR(255), investment_amount NUMERIC, region VARCHAR(255), year INT);
|
What is the total amount of climate finance invested in sustainable agriculture projects in the Middle East in 2023?
|
SELECT SUM(investment_amount) FROM climate_finance WHERE sector = 'sustainable agriculture' AND region = 'Middle East' AND year = 2023;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE ports (id INT, name VARCHAR(50), location VARCHAR(50), un_code VARCHAR(10)); CREATE TABLE vessels (id INT, name VARCHAR(50), type VARCHAR(50), year_built INT, port_id INT); CREATE TABLE captains (id INT, name VARCHAR(50), age INT, license_number VARCHAR(20), vessel_id INT); CREATE TABLE cargo (id INT, description VARCHAR(50), weight FLOAT, port_id INT, vessel_id INT); CREATE VIEW captain_vessel AS SELECT captains.name AS captain_name, vessels.name AS vessel_name FROM captains INNER JOIN vessels ON captains.vessel_id = vessels.id;
|
What is the maximum cargo weight and corresponding port for cargo handled by the vessel 'Sea Serpent'?
|
SELECT ports.name, MAX(cargo.weight) AS max_cargo_weight FROM ports INNER JOIN (vessels INNER JOIN cargo ON vessels.id = cargo.vessel_id) ON ports.id = vessels.port_id WHERE vessels.name = 'Sea Serpent' GROUP BY ports.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE fortnite_scores (id INT, player TEXT, score INT, game TEXT); INSERT INTO fortnite_scores (id, player, score, game) VALUES (1, 'Mia', 120, 'Fortnite'), (2, 'Mia', 115, 'Fortnite'), (3, 'Max', 130, 'Fortnite');
|
What is the maximum score achieved by player 'Mia' in the game 'Fortnite'?
|
SELECT MAX(score) FROM fortnite_scores WHERE player = 'Mia' AND game = 'Fortnite';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE company (id INT, name VARCHAR(255), country VARCHAR(255), num_employees INT, avg_salary DECIMAL(10,2));CREATE VIEW mining_companies AS SELECT * FROM company WHERE industry = 'Mining';
|
Find the number of employees and total salary costs for mining companies in the top 2 countries with the highest total salary costs.
|
SELECT c.country, SUM(c.num_employees) as total_employees, SUM(c.num_employees * c.avg_salary) as total_salary_costs FROM mining_companies c JOIN (SELECT country, SUM(num_employees * avg_salary) as total_salary_costs FROM mining_companies GROUP BY country ORDER BY total_salary_costs DESC LIMIT 2) mc ON c.country = mc.country GROUP BY c.country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE clinics (id INT, name VARCHAR(50), location VARCHAR(50), type VARCHAR(20), budget INT);
|
List all the dental clinics in rural areas of Australia with their budget.
|
SELECT name, budget FROM clinics WHERE location LIKE '%Australia%' AND location LIKE '%rural%' AND type = 'dental';
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gretelai_synthetic_text_to_sql
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CREATE TABLE companies (id INT, name VARCHAR(255));CREATE TABLE veteran_employment (company_id INT, num_veterans INT);INSERT INTO companies (id, name) VALUES (1, 'Lockheed Martin'), (2, 'Boeing'), (3, 'Raytheon Technologies'), (4, 'Northrop Grumman');INSERT INTO veteran_employment (company_id, num_veterans) VALUES (1, 25000), (2, 30000), (3, 15000), (4, 20000);
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How many veterans have been employed by each company?
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SELECT c.name, SUM(ve.num_veterans) as total_veterans FROM companies c JOIN veteran_employment ve ON c.id = ve.company_id GROUP BY c.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE energy_efficiency_scores (score INT); INSERT INTO energy_efficiency_scores (score) VALUES (90), (85), (88);
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What is the maximum energy efficiency score?
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SELECT MAX(score) FROM energy_efficiency_scores;
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gretelai_synthetic_text_to_sql
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CREATE TABLE College_of_Engineering_Grants (faculty_gender VARCHAR(10), grant_year INT, grant_amount INT); INSERT INTO College_of_Engineering_Grants (faculty_gender, grant_year, grant_amount) VALUES ('Female', 2017, 50000), ('Male', 2017, 70000), ('Female', 2018, 60000), ('Male', 2018, 80000), ('Female', 2019, 75000), ('Male', 2019, 65000);
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What is the total amount of research grants awarded to female faculty members in the College of Engineering for each year since 2017?
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SELECT grant_year, SUM(grant_amount) as total_grant_amount FROM College_of_Engineering_Grants WHERE faculty_gender = 'Female' GROUP BY grant_year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Carbon_Sequestration (ID INT, Region VARCHAR(50), Area FLOAT); INSERT INTO Carbon_Sequestration (ID, Region, Area) VALUES (1, 'Region1', 30.2), (2, 'Region2', 45.6), (3, 'Region3', 60.8);
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How many hectares of forest are dedicated to carbon sequestration in each region?
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SELECT Region, Area FROM Carbon_Sequestration;
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gretelai_synthetic_text_to_sql
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CREATE TABLE baseball_tickets (id INT, city VARCHAR(20), ticket_sales INT);
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Show the top 3 cities with the highest number of ticket purchases for baseball games.
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SELECT city, SUM(ticket_sales) AS total_sales FROM baseball_tickets GROUP BY city ORDER BY total_sales DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE supplier_holmium (year INT, supplier VARCHAR(20), holmium_supply INT); INSERT INTO supplier_holmium VALUES (2015, 'Supplier A', 20), (2016, 'Supplier B', 25), (2017, 'Supplier C', 30), (2018, 'Supplier D', 35), (2019, 'Supplier E', 40);
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Which supplier provided the most Holmium in 2017?
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SELECT supplier, MAX(holmium_supply) FROM supplier_holmium WHERE year = 2017 GROUP BY supplier;
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gretelai_synthetic_text_to_sql
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