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CREATE TABLE DisasterPreparedness (id INT, month INT, year INT, disasterType VARCHAR(30), score INT);
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List all disaster types and their respective average preparedness scores, for the last 3 months, from 'DisasterPreparedness' table.
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SELECT disasterType, AVG(score) FROM DisasterPreparedness WHERE year = YEAR(CURRENT_DATE) AND month BETWEEN MONTH(CURRENT_DATE) - 2 AND MONTH(CURRENT_DATE) GROUP BY disasterType;
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gretelai_synthetic_text_to_sql
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CREATE TABLE student (id INT, program TEXT, gpa REAL); INSERT INTO student (id, program, gpa) VALUES (1, 'math', 3.8), (2, 'math', 3.9), (3, 'math', 4.0);
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What is the minimum GPA of graduate students in the 'math' program?
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SELECT MIN(gpa) FROM student WHERE program = 'math';
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales_data (drug_name TEXT, sale_amount INTEGER, sale_year INTEGER, region TEXT); INSERT INTO sales_data (drug_name, sale_amount, sale_year, region) VALUES ('DrugC', 1200, 2020, 'North'), ('DrugC', 1500, 2020, 'South'), ('DrugD', 2000, 2020, 'East'), ('DrugD', 1800, 2020, 'West');
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What is the total sales amount for a specific drug across different regions in a given year?
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SELECT SUM(sale_amount) FROM sales_data WHERE drug_name = 'DrugC' AND sale_year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE veteran_employment (employee_id INT, industry VARCHAR(255), date DATE); INSERT INTO veteran_employment (employee_id, industry, date) VALUES (1, 'defense', '2019-09-01'); INSERT INTO veteran_employment (employee_id, industry, date) VALUES (2, 'non-defense', '2019-12-05');
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How many veterans found employment in the defense industry in 2019?
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SELECT COUNT(*) FROM veteran_employment WHERE industry = 'defense' AND date BETWEEN '2019-01-01' AND '2019-12-31';
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gretelai_synthetic_text_to_sql
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CREATE TABLE SpaceExploration(mission VARCHAR(20), mission_year INT, company VARCHAR(20)); INSERT INTO SpaceExploration VALUES('Mission A', 2019, 'NASA'),('Mission B', 2020, 'SpaceX');
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How many space missions were conducted by 'NASA' in the year 2019?
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SELECT COUNT(*) FROM SpaceExploration WHERE mission_year=2019 AND company='NASA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE media_ethics (ethic_id INT PRIMARY KEY, ethic_name VARCHAR(255), description TEXT, source VARCHAR(255));
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Update the description of the ethic with ethic_id 1 in the 'media_ethics' table
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UPDATE media_ethics SET description = 'The right to access and distribute information without interference from government or other powers.' WHERE ethic_id = 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE transactions (transaction_id INT, employee_id INT, transaction_type VARCHAR(20), transaction_value DECIMAL(10,2), is_fraudulent BOOLEAN);
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Find the number of fraudulent transactions and their total value, excluding transactions with a value less than 1000, for each employee in the sales department.
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SELECT employee_id, COUNT(*) as fraud_count, SUM(transaction_value) as total_fraud_value FROM transactions WHERE transaction_type = 'Sales' AND is_fraudulent = TRUE AND transaction_value >= 1000 GROUP BY employee_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE therapy_sessions (id INT, session_name TEXT, cost INT, country TEXT);
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What is the average cost of group therapy sessions in France?
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SELECT AVG(cost) FROM therapy_sessions WHERE session_name = 'Group Therapy' AND country = 'France';
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gretelai_synthetic_text_to_sql
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CREATE TABLE environmental_impact (id INT, mine_id INT, year INT, co2_emissions INT, water_usage INT); INSERT INTO environmental_impact (id, mine_id, year, co2_emissions, water_usage) VALUES (7, 7, 2021, 40000, 900000); INSERT INTO environmental_impact (id, mine_id, year, co2_emissions, water_usage) VALUES (8, 8, 2021, 45000, 1000000);
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What is the total CO2 emissions for each year in the diamond mining industry?
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SELECT YEAR(e.year) AS year, SUM(e.co2_emissions) AS total_co2_emissions FROM environmental_impact e JOIN mines m ON e.mine_id = m.id WHERE m.mineral = 'Diamond' GROUP BY YEAR(e.year);
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gretelai_synthetic_text_to_sql
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CREATE TABLE MediaContent (ContentID INT PRIMARY KEY, ContentName VARCHAR(50), ContentType VARCHAR(30), DiversityScore DECIMAL(5,2), MediaPlatform VARCHAR(30)); INSERT INTO MediaContent (ContentID, ContentName, ContentType, DiversityScore, MediaPlatform) VALUES (1, 'Content 1', 'Video', 8.5, 'Platform A'), (2, 'Content 2', 'Podcast', 7.2, 'Platform B');
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List all the video contents with a diversity score greater than 8.5.
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SELECT * FROM MediaContent WHERE ContentType = 'Video' AND DiversityScore > 8.5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE whale_sightings (id INTEGER, species TEXT, sighting_date DATE, location TEXT); INSERT INTO whale_sightings (id, species, sighting_date, location) VALUES (1, 'Blue Whale', '2022-01-01', 'Pacific Ocean'); INSERT INTO whale_sightings (id, species, sighting_date, location) VALUES (2, 'Gray Whale', '2022-03-15', 'Pacific Ocean');
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Count the number of whale sightings in the Pacific Ocean in 2022.
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SELECT COUNT(*) FROM whale_sightings WHERE sighting_date >= '2022-01-01' AND sighting_date < '2023-01-01' AND location = 'Pacific Ocean';
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gretelai_synthetic_text_to_sql
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CREATE TABLE african_census (model_name TEXT, fairness_score FLOAT); INSERT INTO african_census (model_name, fairness_score) VALUES ('model1', 0.95), ('model2', 0.85), ('model3', 0.90);
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What is the maximum fairness score for models trained on the 'african_census' dataset?
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SELECT MAX(fairness_score) FROM african_census;
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gretelai_synthetic_text_to_sql
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CREATE TABLE package_destinations (id INT, package_weight FLOAT, shipped_from VARCHAR(20), shipped_to VARCHAR(20), shipped_date DATE); INSERT INTO package_destinations (id, package_weight, shipped_from, shipped_to, shipped_date) VALUES (1, 2.3, 'New Zealand', 'Australia', '2022-01-15');
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What is the total weight of packages shipped to Australia from any country in Oceania in the last month?
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SELECT SUM(package_weight) FROM package_destinations WHERE shipped_to = 'Australia' AND shipped_from LIKE 'Oceania%' AND shipped_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH);
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gretelai_synthetic_text_to_sql
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CREATE TABLE life_expectancy(id INT, country TEXT, continent TEXT, expectancy FLOAT);
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What is the average life expectancy in each continent?
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SELECT continent, AVG(expectancy) FROM life_expectancy GROUP BY continent;
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gretelai_synthetic_text_to_sql
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CREATE TABLE company_impact (id INT, name VARCHAR(50), sector VARCHAR(20), impact_score FLOAT); INSERT INTO company_impact (id, name, sector, impact_score) VALUES (1, 'Company X', 'Healthcare', 90.0), (2, 'Company Y', 'Finance', 85.0), (3, 'Company Z', 'Healthcare', 92.5);
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What is the maximum impact score achieved by a company in the healthcare sector?
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SELECT MAX(impact_score) FROM company_impact WHERE sector = 'Healthcare';
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gretelai_synthetic_text_to_sql
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CREATE TABLE teams (team_id INT, division VARCHAR(50)); CREATE TABLE ticket_sales (id INT, team_id INT, num_tickets INT);
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How many season tickets have been sold in the Pacific Division?
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SELECT SUM(ticket_sales.num_tickets) FROM ticket_sales JOIN teams ON ticket_sales.team_id = teams.team_id WHERE teams.division = 'Pacific';
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gretelai_synthetic_text_to_sql
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CREATE TABLE access_to_justice_cases (id INT, resolution_type VARCHAR(20), resolution_date DATE);
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What is the percentage of cases in the access to justice database that were resolved through mediation in the last quarter?
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SELECT (COUNT(*) FILTER (WHERE resolution_type = 'mediation')) * 100.0 / COUNT(*) FROM access_to_justice_cases WHERE resolution_date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTHS);
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gretelai_synthetic_text_to_sql
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CREATE TABLE space_objects (id INT, name VARCHAR(255), mass FLOAT, type VARCHAR(255)); INSERT INTO space_objects (id, name, mass, type) VALUES (1, 'Object 1', 1000.0, 'Rocket Stage'), (2, 'Object 2', 20.0, 'Fractured Debris'), (3, 'Object 3', 1500.0, 'Dead Satellite');
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What is the average mass of different types of space debris?
|
SELECT type, AVG(mass) FROM space_objects GROUP BY type;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE MusicArtists (id INT, name VARCHAR(100), country VARCHAR(50), rating FLOAT);
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What's the average rating of music artists from Asia?
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SELECT AVG(rating) FROM MusicArtists WHERE country = 'Asia';
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gretelai_synthetic_text_to_sql
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CREATE TABLE green_buildings (id INT, name TEXT, certification_level TEXT, city TEXT);
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Delete all green buildings in the green_buildings table associated with the 'Boston' city
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WITH cte AS (DELETE FROM green_buildings WHERE city = 'Boston') SELECT * FROM cte;
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gretelai_synthetic_text_to_sql
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CREATE TABLE species(id INT, name VARCHAR(255), common_name VARCHAR(255), population INT, endangered BOOLEAN);
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Add a new column endangered to the species table and update values
|
ALTER TABLE species ADD COLUMN endangered BOOLEAN;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Ethnicities (EthnicityID INT, Ethnicity VARCHAR(50)); CREATE TABLE MentalHealthScores (MH_ID INT, EthnicityID INT, MentalHealthScore INT); INSERT INTO Ethnicities (EthnicityID, Ethnicity) VALUES (1, 'Hispanic'), (2, 'African American'), (3, 'Asian'), (4, 'Caucasian'); INSERT INTO MentalHealthScores (MH_ID, EthnicityID, MentalHealthScore) VALUES (1, 1, 70), (2, 1, 75), (3, 2, 80), (4, 2, 85), (5, 3, 90), (6, 3, 95), (7, 4, 65), (8, 4, 70);
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What is the minimum mental health score by ethnicity?
|
SELECT e.Ethnicity, MIN(mhs.MentalHealthScore) as Min_Score FROM MentalHealthScores mhs JOIN Ethnicities e ON mhs.EthnicityID = e.EthnicityID GROUP BY e.Ethnicity;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE marine_species (id INT, name TEXT, ocean TEXT, affected_by_safety_issues BOOLEAN); INSERT INTO marine_species (id, name, ocean, affected_by_safety_issues) VALUES (1, 'Krill', 'Southern', TRUE), (2, 'Blue Whale', 'Atlantic', FALSE), (3, 'Penguin', 'Southern', TRUE);
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What is the total number of marine species in the Southern Ocean that are affected by maritime safety issues?
|
SELECT COUNT(*) FROM marine_species WHERE ocean = 'Southern' AND affected_by_safety_issues = TRUE;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Spacecraft (id INT, name VARCHAR(255), manufacturer VARCHAR(255), type VARCHAR(255), launch_date DATE); INSERT INTO Spacecraft (id, name, manufacturer, type, launch_date) VALUES (3, 'Galileo Orbiter', 'ESA', 'Robotic', '1989-10-18'); INSERT INTO Spacecraft (id, name, manufacturer, type, launch_date) VALUES (4, 'Rosetta', 'ESA', 'Robotic', '2004-03-02');
|
Which spacecraft have been launched by the European Space Agency?
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SELECT name FROM Spacecraft WHERE manufacturer = 'ESA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Labor_OR (labor_id INT, labor_cost FLOAT, labor_state VARCHAR(20), labor_date DATE); INSERT INTO Labor_OR (labor_id, labor_cost, labor_state, labor_date) VALUES (1, 300, 'Oregon', '2022-01-01'), (2, 350, 'Oregon', '2022-01-15'), (3, 400, 'Oregon', '2022-03-01');
|
What was the maximum labor cost for each month in Oregon in 2022?
|
SELECT labor_date, MAX(labor_cost) OVER (PARTITION BY EXTRACT(MONTH FROM labor_date)) AS max_labor_cost FROM Labor_OR WHERE labor_state = 'Oregon' AND labor_date >= '2022-01-01' AND labor_date < '2023-01-01' ORDER BY labor_date;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE location (location_id INT, location_name TEXT); INSERT INTO location (location_id, location_name) VALUES (1, 'Indian Ocean'); CREATE TABLE measurement (measurement_id INT, location_id INT, dissolved_oxygen FLOAT); INSERT INTO measurement (measurement_id, location_id, dissolved_oxygen) VALUES (1, 1, 6.5), (2, 1, 6.8), (3, 1, 6.9), (4, 1, 7.1), (5, 1, 7.2);
|
What is the minimum dissolved oxygen level in the Indian Ocean?
|
SELECT MIN(dissolved_oxygen) FROM measurement WHERE location_id = (SELECT location_id FROM location WHERE location_name = 'Indian Ocean');
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gretelai_synthetic_text_to_sql
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CREATE TABLE Aircraft_Accidents (aircraft_model VARCHAR(255), accident_date DATE, country VARCHAR(255)); INSERT INTO Aircraft_Accidents (aircraft_model, accident_date, country) VALUES ('Boeing 737', '2020-01-01', 'USA'), ('Airbus A320', '2020-02-01', 'France'), ('Boeing 747', '2020-03-01', 'UK'), ('Boeing 737', '2020-04-01', 'Canada'), ('Airbus A320', '2020-05-01', 'Germany');
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List the top 3 countries with the most aircraft accidents in 2020.
|
SELECT country, COUNT(*) AS num_accidents FROM Aircraft_Accidents WHERE YEAR(accident_date) = 2020 GROUP BY country ORDER BY num_accidents DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE mobile_subscribers (subscriber_id INT, home_location VARCHAR(50)); INSERT INTO mobile_subscribers (subscriber_id, home_location) VALUES (1, 'USA'), (2, 'Mexico'), (3, 'Canada'), (4, 'USA'), (5, 'Canada');
|
How many mobile subscribers are there in each country?
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SELECT home_location, COUNT(*) FROM mobile_subscribers GROUP BY home_location;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE suppliers (id INT PRIMARY KEY, name TEXT, location TEXT, sustainability_rating REAL);
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Delete the supplier with id 2
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DELETE FROM suppliers WHERE id = 2;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE mine (id INT, name VARCHAR(50), location VARCHAR(50));CREATE TABLE coal_mine (mine_id INT, amount INT);CREATE TABLE iron_mine (mine_id INT, amount INT);CREATE TABLE gold_mine (mine_id INT, amount INT);CREATE TABLE silver_mine (mine_id INT, amount INT);
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List the names and locations of mines that have mined any type of metal.
|
SELECT m.name, m.location FROM mine m LEFT JOIN coal_mine c ON m.id = c.mine_id LEFT JOIN iron_mine i ON m.id = i.mine_id LEFT JOIN gold_mine g ON m.id = g.mine_id LEFT JOIN silver_mine s ON m.id = s.mine_id WHERE c.mine_id IS NOT NULL OR i.mine_id IS NOT NULL OR g.mine_id IS NOT NULL OR s.mine_id IS NOT NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE vendors(vendor_id INT, vendor_name TEXT, country TEXT); INSERT INTO vendors(vendor_id, vendor_name, country) VALUES (1, 'VendorA', 'India'), (2, 'VendorB', 'China'), (3, 'VendorC', 'Japan'); CREATE TABLE products(product_id INT, product_name TEXT, rating INT); INSERT INTO products(product_id, product_name, rating) VALUES (1, 'ProductA', 4), (2, 'ProductB', 5), (3, 'ProductC', 3);
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What is the average rating of products sold by vendors from Asia?
|
SELECT AVG(products.rating) FROM products JOIN vendors ON products.vendor_id = vendors.vendor_id WHERE vendors.country = 'Asia';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE ExhibitionAnalytics (ExhibitionID INT, ExhibitionName VARCHAR(50), TotalVisitors INT, TotalEngagement INT);
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Update the TotalEngagement column in the ExhibitionAnalytics table for the 'Ancient Art' exhibition to 300.
|
UPDATE ExhibitionAnalytics SET TotalEngagement = 300 WHERE ExhibitionName = 'Ancient Art';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE GarmentProduction (garmentID INT, material VARCHAR(20), year INT, quantity INT); INSERT INTO GarmentProduction (garmentID, material, year, quantity) VALUES (1, 'Recycled Polyester', 2020, 12000), (2, 'Organic Cotton', 2020, 15000), (3, 'Recycled Denim', 2019, 8000), (4, 'Recycled Polyester', 2019, 9000), (5, 'Recycled Cotton', 2020, 10000);
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What is the total quantity of recycled materials used in garment production?
|
SELECT SUM(quantity) FROM GarmentProduction WHERE material LIKE '%Recycled%';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Voyage (VoyageID INT, VesselID INT, StartPortID INT, EndPortID INT, StartDate DATETIME, EndDate DATETIME); INSERT INTO Voyage (VoyageID, VesselID, StartPortID, EndPortID, StartDate, EndDate) VALUES (1, 1, 1, 2, '2022-01-01 08:00:00', '2022-01-02 10:00:00'); INSERT INTO Voyage (VoyageID, VesselID, StartPortID, EndPortID, StartDate, EndDate) VALUES (2, 2, 2, 1, '2022-01-03 12:00:00', '2022-01-04 14:00:00');
|
List the voyages with their start and end ports and the time difference between arrivals.
|
SELECT v1.VesselID, p1.PortName AS StartPort, p2.PortName AS EndPort, DATEDIFF(HOUR, v1.StartDate, v1.EndDate) AS TimeDifference FROM Voyage v1 JOIN Port p1 ON v1.StartPortID = p1.PortID JOIN Port p2 ON v1.EndPortID = p2.PortID;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Buses (id INT, model VARCHAR(255), last_inspection DATETIME);
|
Which buses have not had a safety inspection in the last 6 months?
|
SELECT B.id, B.model FROM Buses B LEFT JOIN (SELECT bus_id, MAX(last_inspection) as max_inspection FROM Buses GROUP BY bus_id) BI ON B.id = BI.bus_id WHERE B.last_inspection < BI.max_inspection - INTERVAL 6 MONTH;
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gretelai_synthetic_text_to_sql
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CREATE TABLE posts (id INT, user_id INT, post_text VARCHAR(255), likes INT, language VARCHAR(10)); INSERT INTO posts (id, user_id, post_text, likes, language) VALUES (1, 1, 'Hola!', 20, 'es'), (2, 2, 'Hello!', 15, 'en'), (3, 3, 'Bonjour!', 25, 'fr'), (4, 4, 'Olá!', 18, 'pt');
|
What was the maximum number of likes received by posts in Spanish?
|
SELECT MAX(likes) FROM posts WHERE language = 'es';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE MentalHealthParity (id INT, law_name TEXT, state TEXT); INSERT INTO MentalHealthParity (id, law_name, state) VALUES (1, 'Parity Act 2020', 'Massachusetts'); INSERT INTO MentalHealthParity (id, law_name, state) VALUES (2, 'Equity Act 2018', 'Massachusetts');
|
List all mental health parity laws in Massachusetts.
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SELECT * FROM MentalHealthParity WHERE state = 'Massachusetts';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE production (production_id INT, location VARCHAR(255), year INT, gas_production FLOAT); INSERT INTO production (production_id, location, year, gas_production) VALUES (1, 'Nigeria', 2020, 5000000), (2, 'Algeria', 2020, 4000000), (3, 'Egypt', 2019, 3000000);
|
What is the average gas production in the 'Africa' region for the year 2020? (Assuming gas production values are stored in a separate column)
|
SELECT AVG(gas_production) FROM production WHERE location LIKE '%Africa%' AND year = 2020;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE employees (id INT, name VARCHAR(50), department VARCHAR(50), hire_date DATE); INSERT INTO employees (id, name, department, hire_date) VALUES (1, 'John Doe', 'IT', '2021-03-01'), (2, 'Jane Smith', 'Marketing', '2021-07-15'), (3, 'Mike Johnson', 'IT', '2021-02-12'), (4, 'Sara Connor', 'Marketing', '2021-10-04');
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Show the number of employees hired in each month of the year, broken down by department.
|
SELECT department, DATE_TRUNC('month', hire_date) AS hire_month, COUNT(*) AS num_hires FROM employees GROUP BY department, hire_month;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE vessels (id INT, name VARCHAR(255), safety_record JSON); CREATE TABLE inspections (vessel_id INT, inspection_date DATE, score INT); INSERT INTO vessels VALUES (1, 'Vessel A', '{"inspection_date": "2021-01-01", "score": 90}'::JSON), (2, 'Vessel B', '{"inspection_date": "2021-02-01", "score": 85}'::JSON); INSERT INTO inspections VALUES (1, '2021-03-01', 95), (2, '2021-04-01', 90);
|
Update the vessel's safety record with the latest inspection date and score.
|
UPDATE vessels v SET safety_record = jsonb_set(v.safety_record, '{inspection_date, score}', jsonb_build_object('inspection_date', (SELECT i.inspection_date FROM inspections i WHERE i.vessel_id = v.id ORDER BY i.inspection_date DESC LIMIT 1), 'score', (SELECT i.score FROM inspections i WHERE i.vessel_id = v.id ORDER BY i.inspection_date DESC LIMIT 1))) WHERE id IN (SELECT i.vessel_id FROM inspections i);
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gretelai_synthetic_text_to_sql
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CREATE TABLE news.articles (article_id INT, title VARCHAR(100), publish_date DATE); INSERT INTO news.articles (article_id, title, publish_date) VALUES (1, 'Article 1', '2021-01-01'), (2, 'Article 2', '2021-02-01');
|
How many news articles were published per month in 2021 in the 'news' schema?
|
SELECT MONTH(publish_date), COUNT(*) FROM news.articles WHERE YEAR(publish_date) = 2021 GROUP BY MONTH(publish_date);
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Dispensaries (id INT, dispensary_name VARCHAR(255), state VARCHAR(255), income DECIMAL(10, 2)); INSERT INTO Dispensaries (id, dispensary_name, state, income) VALUES (1, 'Green Earth Dispensary', 'Colorado', 125000.00); CREATE TABLE Cannabis_Sales (id INT, dispensary_id INT, sale_year INT, sale_weight DECIMAL(10, 2), sale_type VARCHAR(255)); INSERT INTO Cannabis_Sales (id, dispensary_id, sale_year, sale_weight, sale_type) VALUES (1, 1, 2021, 500.00, 'Indoor');
|
What is the total weight of indoor grown cannabis sold by dispensaries in Colorado in 2021?
|
SELECT SUM(sale_weight) FROM Dispensaries d JOIN Cannabis_Sales s ON d.id = s.dispensary_id WHERE d.state = 'Colorado' AND s.sale_year = 2021 AND s.sale_type = 'Indoor';
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gretelai_synthetic_text_to_sql
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CREATE TABLE waste_generation (region VARCHAR(50), year INT, waste_kg FLOAT); INSERT INTO waste_generation (region, year, waste_kg) VALUES ('Greater Toronto', 2021, 123456.78);
|
What is the total waste generation in kg for the region 'Greater Toronto' for the year 2021?
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SELECT SUM(waste_kg) FROM waste_generation WHERE region = 'Greater Toronto' AND year = 2021;
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gretelai_synthetic_text_to_sql
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CREATE TABLE pipelines (id INT, name VARCHAR(50), location VARCHAR(50), construction_cost DECIMAL(10,2)); INSERT INTO pipelines (id, name, location, construction_cost) VALUES (1, 'Alberta Clipper Pipeline', 'Alberta', 1500000000.00);
|
Find the maximum construction cost for pipelines in 'Alberta'
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SELECT MAX(construction_cost) FROM pipelines WHERE location = 'Alberta';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE voice_plans (plan_id int, plan_cost float, plan_type varchar(10)); INSERT INTO voice_plans (plan_id, plan_cost, plan_type) VALUES (1, 30, 'basic'), (2, 50, 'premium'); CREATE TABLE voice_subscribers (subscriber_id int, voice_plan varchar(10), state varchar(20)); INSERT INTO voice_subscribers (subscriber_id, voice_plan, state) VALUES (1, 'basic', 'WA'), (2, 'premium', 'NY'), (3, 'basic', 'IL');
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How many subscribers are using premium voice plans in each state?
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SELECT state, COUNT(*) as num_premium_subscribers FROM voice_subscribers sub INNER JOIN voice_plans plan ON sub.voice_plan = plan.plan_type WHERE plan_type = 'premium' GROUP BY state;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ElectricAutonomousVehicles (id INT, make VARCHAR(50), model VARCHAR(50), electric BOOLEAN, autonomous BOOLEAN);
|
What is the total number of electric and autonomous vehicles in the electricautonomousvehicles schema?
|
SELECT COUNT(*) FROM electricautonomousvehicles.ElectricAutonomousVehicles WHERE electric = TRUE OR autonomous = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE EpicRacers (PlayerID INT, Name VARCHAR(50), Platform VARCHAR(10)); INSERT INTO EpicRacers (PlayerID, Name, Platform) VALUES (1, 'John', 'PC'), (2, 'Amy', 'Console'), (3, 'Mike', 'Mobile'), (4, 'Linda', 'PC'), (5, 'Sam', 'Console');
|
How many players are there in the "EpicRacers" table, grouped by their preferred gaming platform (PC, Console, Mobile)?
|
SELECT Platform, COUNT(PlayerID) FROM EpicRacers GROUP BY Platform;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Teams (TeamID INT, TeamName VARCHAR(50)); INSERT INTO Teams (TeamID, TeamName) VALUES (1, 'Red Dragons'), (2, 'Blue Warriors'); CREATE TABLE TicketSales (SaleID INT, TeamID INT, SaleDate DATE); INSERT INTO TicketSales (SaleID, TeamID, SaleDate) VALUES (1, 1, '2022-01-10'), (2, 1, '2022-03-05'), (3, 2, '2022-02-20'), (4, 2, '2022-04-10'), (5, 2, '2022-05-12');
|
Which teams have no ticket sales in the last month?
|
SELECT T.TeamName FROM Teams T LEFT JOIN TicketSales TS ON T.TeamID = TS.TeamID WHERE TS.SaleDate IS NULL OR TS.SaleDate < DATE_SUB(CURDATE(), INTERVAL 1 MONTH) GROUP BY T.TeamName;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE VesselInspections2 (ID INT, Vessel VARCHAR(50), InspectionDate DATE, ViolationCount INT); INSERT INTO VesselInspections2 (ID, Vessel, InspectionDate, ViolationCount) VALUES (1, 'SS Freedom', '2020-01-01', 3), (2, 'SS Liberty', '2020-01-02', 2), (3, 'SS Eagle', '2020-01-03', 4), (4, 'SS Freedom', '2020-01-04', 2);
|
Reveal vessels with decreasing violations.
|
SELECT Vessel, ViolationCount, LAG(ViolationCount) OVER (PARTITION BY Vessel ORDER BY InspectionDate) as PreviousViolationCount FROM VesselInspections2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE properties (id INT, affordability VARCHAR(20), sustainability_rating FLOAT); INSERT INTO properties (id, affordability, sustainability_rating) VALUES (1, 'affordable', 80.5), (2, 'unaffordable', 60.0);
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What is the total number of properties in areas with affordable housing and sustainability ratings above 70?
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SELECT COUNT(*) FROM properties WHERE affordability = 'affordable' AND sustainability_rating > 70;
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gretelai_synthetic_text_to_sql
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CREATE TABLE room_prices (hotel_id INT, year INT, price INT); INSERT INTO room_prices (hotel_id, year, price) VALUES (1, 2022, 150); INSERT INTO room_prices (hotel_id, year, price) VALUES (1, 2023, 150);
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Update the room prices for the 'Sustainable Hotel' in France by 10% for 2023.
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UPDATE room_prices SET price = price * 1.1 WHERE hotel_id = 1 AND year = 2023;
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gretelai_synthetic_text_to_sql
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CREATE TABLE forests (id INT, name VARCHAR(255), location VARCHAR(255), biome VARCHAR(255), area FLOAT, elevation_range VARCHAR(255)); INSERT INTO forests (id, name, location, biome, area, elevation_range) VALUES (1, 'Amazon Rainforest', 'South America', 'Tropical Rainforest', 6700000, '0 - 300 m'); CREATE TABLE timber_harvest (id INT, forest_id INT, year INT, volume FLOAT); INSERT INTO timber_harvest (id, forest_id, year, volume) VALUES (1, 1, 2020, 15000);
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What is the total volume of timber harvested in tropical rainforests in 2020?
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SELECT SUM(volume) FROM timber_harvest WHERE forest_id IN (SELECT id FROM forests WHERE biome = 'Tropical Rainforest') AND year = 2020;
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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), ManagerID INT, ManagerFirstName VARCHAR(50), ManagerLastName VARCHAR(50)); INSERT INTO Employees (EmployeeID, FirstName, LastName, Department, ManagerID, ManagerFirstName, ManagerLastName) VALUES (1, 'Jose', 'Garcia', 'Marketing', 2, 'John', 'Doe'), (2, 'John', 'Doe', 'IT', NULL, 'John', 'Doe'), (3, 'Alice', 'Williams', 'Marketing', 1, 'John', 'Doe'), (4, 'Charlie', 'Brown', 'HR', NULL, 'Sara', 'Lee'), (5, 'Denise', 'Davis', 'Marketing', 1, 'John', 'Doe');
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Find employees who have the same first name as their department head.
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SELECT E1.FirstName FROM Employees E1 INNER JOIN Employees E2 ON E1.ManagerID = E2.EmployeeID WHERE E1.FirstName = E2.FirstName AND E1.Department = E2.Department;
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gretelai_synthetic_text_to_sql
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CREATE TABLE climate_adaptation_projects (project VARCHAR(50), location VARCHAR(50), year INT); INSERT INTO climate_adaptation_projects (project, location, year) VALUES ('Sea Level Rise Mitigation', 'Maldives', 2019), ('Water Management', 'Barbados', 2020), ('Disaster Risk Reduction', 'Cape Verde', 2021), ('Coastal Protection', 'Marshall Islands', 2021); CREATE TABLE sids (location VARCHAR(50), sids_status VARCHAR(50)); INSERT INTO sids (location, sids_status) VALUES ('Maldives', 'SIDS'), ('Barbados', 'SIDS'), ('Cape Verde', 'SIDS'), ('Marshall Islands', 'SIDS');
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How many climate adaptation projects were implemented in Small Island Developing States (SIDS) in the last 3 years?
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SELECT COUNT(*) FROM climate_adaptation_projects cp INNER JOIN sids s ON cp.location = s.location WHERE s.sids_status = 'SIDS' AND cp.year BETWEEN 2019 AND 2021;
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gretelai_synthetic_text_to_sql
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CREATE TABLE social_media(user_id INT, user_name VARCHAR(50), region VARCHAR(50), post_date DATE, likes INT);
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Show the daily number of posts in the 'social_media' table for the top 5 regions with the most posts.
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SELECT post_date, region, COUNT(*) as daily_posts FROM (SELECT region, post_date, user_id FROM social_media GROUP BY region, post_date, user_id ORDER BY region, COUNT(*) DESC LIMIT 5) as top_regions GROUP BY post_date, region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE diversity (company_name VARCHAR(255), gender_distribution VARCHAR(50), ethnicity_distribution VARCHAR(50)); INSERT INTO diversity (company_name, gender_distribution, ethnicity_distribution) VALUES ('Acme Inc', '50/50', 'Diverse'), ('Beta Corp', '60/40', 'Not Diverse'), ('Charlie LLC', NULL, NULL);
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Identify companies with no diversity metrics recorded
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SELECT company_name FROM diversity WHERE gender_distribution IS NULL AND ethnicity_distribution IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE teachers (teacher_id INT, teacher_name VARCHAR(50)); INSERT INTO teachers (teacher_id, teacher_name) VALUES (1, 'Alice'), (2, 'Bob'), (3, 'Charlie'); CREATE TABLE professional_development_courses (course_id INT, course_name VARCHAR(50), completion_date DATE); INSERT INTO professional_development_courses (course_id, course_name, completion_date) VALUES (1, 'Python', '2023-01-01'), (2, 'R', '2023-02-15'), (3, 'JavaScript', '2023-04-20');
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How many teachers have completed professional development courses in the last 6 months?
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SELECT COUNT(DISTINCT teachers.teacher_id) as num_teachers FROM teachers JOIN professional_development_courses ON teachers.teacher_id = professional_development_courses.teacher_id WHERE professional_development_courses.completion_date >= DATEADD(month, -6, GETDATE());
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gretelai_synthetic_text_to_sql
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CREATE TABLE athletes (athlete_id INT, name VARCHAR(50), nationality VARCHAR(50), age INT, medal VARCHAR(10), event VARCHAR(50)); INSERT INTO athletes (athlete_id, name, nationality, age, medal, event) VALUES (1, 'Michael Phelps', 'United States', 35, 'Gold', 'Swimming');
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What is the total number of medals won by athletes in the 'Athletes' table who are from the United States, grouped by the type of medal?
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SELECT medal, SUM(1) as total_medals FROM athletes WHERE nationality = 'United States' GROUP BY medal;
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gretelai_synthetic_text_to_sql
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CREATE TABLE user_details (user_id INT, num_posts INT); INSERT INTO user_details (user_id, num_posts) VALUES (1, 25), (2, 32), (3, 18), (4, 45);
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List all users and their respective number of posts, ordered by the user_id in ascending order.
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SELECT user_id, num_posts FROM user_details ORDER BY user_id ASC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AircraftMaintenance (id INT, region VARCHAR(20), priority VARCHAR(10), request_date DATE); INSERT INTO AircraftMaintenance (id, region, priority, request_date) VALUES (1, 'Middle East', 'Urgent', '2021-09-15');
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How many aircraft maintenance requests were made in the Middle East in Q3 2021, with a priority level of 'Urgent'?
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SELECT COUNT(*) as urgent_requests FROM AircraftMaintenance WHERE region = 'Middle East' AND priority = 'Urgent' AND request_date BETWEEN '2021-07-01' AND '2021-09-30';
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gretelai_synthetic_text_to_sql
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CREATE TABLE destinations (destination_id INT, name VARCHAR(50), country_id INT); INSERT INTO destinations (destination_id, name, country_id) VALUES (3, 'Milford Sound', 1); INSERT INTO destinations (destination_id, name, country_id) VALUES (4, 'Prambanan Temple', 2);
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What is the total number of visitors for each destination in the international_visitors table?
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SELECT d.name, SUM(i.num_visitors) as total_visitors FROM destinations d INNER JOIN international_visitors i ON d.destination_id = i.country_id GROUP BY d.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE albums (id INT, title TEXT, release_date DATE); INSERT INTO albums (id, title, release_date) VALUES (1, 'Millennium', '1999-12-31'), (2, 'Hybrid Theory', '2000-01-02');
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Delete all albums released before the year 2000.
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DELETE FROM albums WHERE release_date < '2000-01-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE farm (id INT, farm_name VARCHAR(255), state VARCHAR(255), country VARCHAR(255)); INSERT INTO farm (id, farm_name, state, country) VALUES (1, 'Farm 1', 'California', 'USA'); INSERT INTO farm (id, farm_name, state, country) VALUES (2, 'Farm 2', 'Texas', 'USA');
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How many farms are in each state of the USA?
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SELECT state, COUNT(*) AS num_farms FROM farm WHERE country = 'USA' GROUP BY state;
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gretelai_synthetic_text_to_sql
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CREATE TABLE tour_bookings(id INT, city TEXT, booking_date DATE, booking_type TEXT); INSERT INTO tour_bookings (id, city, booking_date, booking_type) VALUES (1, 'New York', '2022-04-01', 'virtual'), (2, 'Los Angeles', '2022-04-02', 'virtual'), (3, 'Chicago', '2022-04-03', 'in-person');
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Identify the top 2 cities with the highest number of virtual tours in the US.
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SELECT city, COUNT(*) AS num_virtual_tours FROM tour_bookings WHERE booking_type = 'virtual' GROUP BY city ORDER BY num_virtual_tours DESC LIMIT 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE network_towers (tower_id INT, location VARCHAR(50), latitude DECIMAL(9,6), longitude DECIMAL(9,6), installed_date DATE);
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Add a new network tower to the network_towers table
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INSERT INTO network_towers (tower_id, location, latitude, longitude, installed_date) VALUES (54321, 'City Center', 40.7128, -74.0060, '2021-12-15');
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gretelai_synthetic_text_to_sql
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CREATE TABLE members (id INT, age INT, gender VARCHAR(10)); CREATE TABLE wearables (id INT, member_id INT, heart_rate INT);
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What is the average heart rate of members aged 25-30 who use our wearable devices, grouped by gender?
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SELECT gender, AVG(heart_rate) FROM members INNER JOIN wearables ON members.id = wearables.member_id WHERE members.age BETWEEN 25 AND 30 GROUP BY gender;
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gretelai_synthetic_text_to_sql
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CREATE TABLE tourists (id INT, country VARCHAR(255), destination VARCHAR(255), year INT, expenditure DECIMAL(10,2)); INSERT INTO tourists (id, country, destination, year, expenditure) VALUES (1, 'USA', 'Costa Rica', 2019, 1500), (2, 'USA', 'Costa Rica', 2019, 1800), (3, 'USA', 'Costa Rica', 2019, 1200), (4, 'USA', 'Costa Rica', 2018, 1300), (5, 'Canada', 'Costa Rica', 2019, 1000);
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What was the average travel expenditure for US tourists visiting Costa Rica in 2019?
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SELECT AVG(expenditure) FROM tourists WHERE country = 'USA' AND destination = 'Costa Rica' AND year = 2019;
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gretelai_synthetic_text_to_sql
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CREATE TABLE wells (well_id INT, well_name VARCHAR(255), location VARCHAR(255), country VARCHAR(255)); INSERT INTO wells (well_id, well_name, location, country) VALUES (1, 'Well A', 'North Sea', 'UK'), (2, 'Well B', 'North Sea', 'Norway'), (3, 'Well C', 'Gulf of Mexico', 'USA'), (4, 'Well D', 'South China Sea', 'Vietnam');
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List the number of wells in each country, sorted by the number of wells in descending order.
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SELECT country, COUNT(*) AS num_wells FROM wells GROUP BY country ORDER BY num_wells DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE project_wind (project_name TEXT, country TEXT); INSERT INTO project_wind (project_name, country) VALUES ('Project A', 'Country A'), ('Project B', 'Country A'), ('Project C', 'Country B'), ('Project D', 'Country C'), ('Project E', 'Country D'), ('Project F', 'Country D');
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Which countries have the most wind power projects?
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SELECT country, COUNT(*) FROM project_wind GROUP BY country ORDER BY COUNT(*) DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE health_equity_metrics (region VARCHAR(10), metric INT); INSERT INTO health_equity_metrics (region, metric) VALUES ('North', 90), ('South', 85), ('East', 95), ('West', 88);
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What is the maximum health equity metric by region?
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SELECT region, MAX(metric) OVER (PARTITION BY 1) as max_metric FROM health_equity_metrics;
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gretelai_synthetic_text_to_sql
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CREATE TABLE marine_species_2 (name TEXT, location TEXT, num_individuals INT); INSERT INTO marine_species_2 (name, location, num_individuals) VALUES ('Clownfish', 'Indian Ocean', '10000'), ('Dolphin', 'Pacific Ocean', '20000');
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Display the total number of marine species in the Pacific Ocean.
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SELECT SUM(num_individuals) FROM marine_species_2 WHERE location = 'Pacific Ocean';
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gretelai_synthetic_text_to_sql
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CREATE TABLE country_reserves (country VARCHAR(50), reserves INT); INSERT INTO country_reserves (country, reserves) VALUES ('China', 44000), ('USA', 1300), ('Australia', 3800), ('India', 674), ('Brazil', 220);
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What are the total rare earth element reserves for each country?
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SELECT country, SUM(reserves) FROM country_reserves GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE vessels_2 (vessel_id INT, name VARCHAR(255), operating_region VARCHAR(255));
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What is the total number of vessels operating in the Pacific and Atlantic Oceans?
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SELECT COUNT(*) FROM vessels_2 WHERE operating_region IN ('Pacific', 'Atlantic');
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gretelai_synthetic_text_to_sql
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CREATE TABLE cybersecurity_incident (id INT, department_id INT, severity INT, incident_date DATE); INSERT INTO cybersecurity_incident (id, department_id, severity, incident_date) VALUES (1, 1, 8, '2021-03-15'); INSERT INTO cybersecurity_incident (id, department_id, severity, incident_date) VALUES (2, 2, 5, '2022-01-10'); CREATE TABLE department (id INT, name VARCHAR(255)); INSERT INTO department (id, name) VALUES (1, 'IT'); INSERT INTO department (id, name) VALUES (2, 'Security');
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What is the total number of cybersecurity incidents and the average severity for each department, partitioned by month and ordered by total number of cybersecurity incidents in descending order?
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SELECT d.name as department, DATEPART(YEAR, incident_date) as year, DATEPART(MONTH, incident_date) as month, COUNT(ci.id) as total_cybersecurity_incidents, AVG(ci.severity) as avg_severity, ROW_NUMBER() OVER (PARTITION BY d.name ORDER BY COUNT(ci.id) DESC) as rank FROM cybersecurity_incident ci JOIN department d ON ci.department_id = d.id GROUP BY d.name, DATEPART(YEAR, incident_date), DATEPART(MONTH, incident_date) ORDER BY total_cybersecurity_incidents DESC;
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA IF NOT EXISTS public_transport;CREATE TABLE IF NOT EXISTS public_transport.payment (payment_id SERIAL PRIMARY KEY, passenger_id INTEGER, route_id INTEGER, fare DECIMAL, payment_date DATE);CREATE TABLE IF NOT EXISTS public_transport.route (route_id INTEGER PRIMARY KEY, route_name TEXT);INSERT INTO public_transport.payment (passenger_id, route_id, fare, payment_date) VALUES (1, 101, 2.50, '2021-10-01'), (2, 102, 4.00, '2021-10-02'), (3, 101, 2.00, '2021-10-03');INSERT INTO public_transport.route (route_id, route_name) VALUES (101, 'Route A'), (102, 'Route B');
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Show the total fare collected per route and day of the week in the 'payment' and 'route' tables
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SELECT EXTRACT(DOW FROM payment_date) AS day_of_week, route_id, SUM(fare) FROM public_transport.payment JOIN public_transport.route ON payment.route_id = route.route_id GROUP BY EXTRACT(DOW FROM payment_date), route_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE game_designers (designer_id INT, gender VARCHAR(10), genre VARCHAR(10), players INT);
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Which female game designers have created RPG games with more than 10,000 players?
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SELECT COUNT(*) FROM game_designers WHERE gender = 'female' AND genre = 'RPG' AND players > 10000;
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gretelai_synthetic_text_to_sql
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CREATE TABLE environmental_impact (year INT, impact_statistic VARCHAR(255)); INSERT INTO environmental_impact (year, impact_statistic) VALUES (2017, 'Carbon emissions: 5000 tons'), (2018, 'Water usage: 20000 cubic meters'), (2019, 'Energy consumption: 15000 MWh'), (2020, 'Waste generation: 8000 tons'), (2021, 'Land degradation: 20 hectares');
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List REE environmental impact statistics for each year since 2017?
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SELECT year, impact_statistic FROM environmental_impact;
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gretelai_synthetic_text_to_sql
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CREATE TABLE social_media (user_id INT, post_id INT, post_date DATE, likes INT);
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Count the number of posts that have more than 100 likes in the 'social_media' table.
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SELECT COUNT(*) FROM social_media WHERE likes > 100;
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gretelai_synthetic_text_to_sql
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CREATE TABLE public_transportation (id INT, trip_id INT, mode VARCHAR(255), start_time TIMESTAMP, end_time TIMESTAMP, city VARCHAR(255)); INSERT INTO public_transportation (id, trip_id, mode, start_time, end_time, city) VALUES (1, 123, 'Metro', '2022-01-01 08:00:00', '2022-01-01 08:15:00', 'Paris'); INSERT INTO public_transportation (id, trip_id, mode, start_time, end_time, city) VALUES (2, 456, 'Bus', '2022-01-01 09:30:00', '2022-01-01 10:00:00', 'Paris');
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What is the total number of trips and average trip duration for public transportation in Paris?
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SELECT COUNT(DISTINCT trip_id) as total_trips, AVG(TIMESTAMPDIFF(MINUTE, start_time, end_time)) as avg_duration FROM public_transportation WHERE city = 'Paris';
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gretelai_synthetic_text_to_sql
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CREATE TABLE conservation_initiatives (id INT, country VARCHAR(50), year INT, initiatives INT); INSERT INTO conservation_initiatives (id, country, year, initiatives) VALUES (1, 'Australia', 2017, 10), (2, 'Australia', 2018, 15), (3, 'Australia', 2019, 20), (4, 'Canada', 2017, 12), (5, 'Canada', 2018, 14), (6, 'Canada', 2019, 16);
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How many water conservation initiatives were implemented in Australia for the year 2017 and 2018?
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SELECT SUM(initiatives) FROM conservation_initiatives WHERE country = 'Australia' AND year IN (2017, 2018);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Armaments (name TEXT, type TEXT); CREATE TABLE Countries (country TEXT, peacekeeping_operation TEXT); CREATE TABLE Supplies (armament TEXT, country TEXT); INSERT INTO Armaments (name, type) VALUES ('AK-47', 'Assault Rifle'), ('M16', 'Assault Rifle'), ('Carl Gustaf', 'Recoilless Rifle'); INSERT INTO Countries (country, peacekeeping_operation) VALUES ('United States', 'MINUSMA'), ('China', 'MONUSCO'), ('Russia', 'UNMISS'); INSERT INTO Supplies (armament, country) VALUES ('AK-47', 'United States'), ('Carl Gustaf', 'China'), ('M16', 'Russia');
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List the name and type of all armaments that have been supplied to peacekeeping operations by each country from the 'Armaments', 'Countries', and 'Supplies' tables
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SELECT Armaments.name, Armaments.type, Countries.country FROM Armaments INNER JOIN (Supplies INNER JOIN Countries ON Supplies.country = Countries.country) ON Armaments.name = Supplies.armament;
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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', 'Pacific Ocean', 8000), ('Trench 2', 'Atlantic Ocean', 7000), ('Trench 3', 'Pacific Ocean', 10000);
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What is the maximum depth of all deep-sea trenches in the Pacific Ocean?
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SELECT MAX(depth) FROM deep_sea_trenches WHERE region = 'Pacific Ocean';
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gretelai_synthetic_text_to_sql
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CREATE TABLE cases (id INT, year INT, restorative_justice BOOLEAN);
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How many cases were resolved using restorative justice practices in the cases table in each year?
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SELECT year, COUNT(*) FROM cases WHERE restorative_justice = TRUE GROUP BY year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE LocalTourOperators (name VARCHAR(50), location VARCHAR(20), year INT, revenue DECIMAL(10,2));
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What is the total revenue generated by local tour operators in Germany for the year 2022?
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SELECT SUM(revenue) FROM LocalTourOperators WHERE location = 'Germany' AND year = 2022;
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gretelai_synthetic_text_to_sql
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CREATE TABLE cultural_sites_paris (site_id INT, name TEXT, city TEXT, visitors INT); INSERT INTO cultural_sites_paris (site_id, name, city, visitors) VALUES (1, 'Eiffel Tower', 'Paris', 7000000), (2, 'Notre Dame Cathedral', 'Paris', 6000000), (3, 'Louvre Museum', 'Paris', 5000000);
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List the top 2 cultural heritage sites in Paris by visitor count.
|
SELECT name, visitors FROM cultural_sites_paris WHERE city = 'Paris' ORDER BY visitors DESC LIMIT 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE items_produced (product_id INT, country VARCHAR(255), year INT); INSERT INTO items_produced (product_id, country, year) VALUES (1, 'USA', 2021), (2, 'Canada', 2022), (3, 'Mexico', 2021), (4, 'USA', 2021);
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What is the number of items produced in each country in 2021?
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SELECT country, COUNT(*) as items_produced FROM items_produced WHERE year = 2021 GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE attorneys (attorney_id INT, gender VARCHAR(20), successful_cases INT); INSERT INTO attorneys (attorney_id, gender, successful_cases) VALUES (1, 'Female', 12), (2, 'Male', 8), (3, 'Non-binary', 7);
|
What is the average number of successful cases handled by attorneys who identify as non-binary?
|
SELECT AVG(successful_cases) FROM attorneys WHERE gender = 'Non-binary';
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gretelai_synthetic_text_to_sql
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CREATE TABLE SafetyRecord (ProductID INT, SafetyTestDate DATE, Result VARCHAR(255)); INSERT INTO SafetyRecord (ProductID, SafetyTestDate, Result) VALUES (8, '2022-06-01', 'Pass'), (8, '2022-07-01', 'Pass'), (9, '2022-06-05', 'Pass'); CREATE TABLE Product (ProductID INT, ProductName VARCHAR(255), Price DECIMAL(5,2)); INSERT INTO Product (ProductID, ProductName, Price) VALUES (8, 'Foundation', 29.99), (9, 'Highlighter', 24.99); CREATE TABLE CrueltyFree (ProductID INT, CertificationDate DATE); INSERT INTO CrueltyFree (ProductID, CertificationDate) VALUES (8, '2022-01-15'), (9, '2022-02-20');
|
Identify the cruelty-free certified products and their safety records.
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SELECT P.ProductName, SR.Result FROM CrueltyFree CF INNER JOIN Product P ON CF.ProductID = P.ProductID INNER JOIN SafetyRecord SR ON P.ProductID = SR.ProductID;
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gretelai_synthetic_text_to_sql
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CREATE TABLE healthcare_union (member_id INT, union_name VARCHAR(20)); INSERT INTO healthcare_union (member_id, union_name) VALUES (1, 'Healthcare Workers Union'), (2, 'Nurses Union'), (3, 'Doctors Union');
|
What is the total number of members in the 'healthcare_union' table?
|
SELECT COUNT(*) FROM healthcare_union;
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gretelai_synthetic_text_to_sql
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CREATE TABLE building_efficiency (id INT, city VARCHAR(50), efficiency FLOAT); INSERT INTO building_efficiency (id, city, efficiency) VALUES (1, 'Tokyo', 120), (2, 'Osaka', 110), (3, 'Sydney', 140);
|
Show the energy efficiency (kWh/m2) of buildings in Sydney
|
SELECT efficiency FROM building_efficiency WHERE city = 'Sydney';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Suppliers (name text, product text, is_organic boolean); INSERT INTO Suppliers (name, product, is_organic) VALUES ('Down to Earth', 'Quinoa', true), ('Down to Earth', 'Rice', false), ('Fresh Harvest', 'Carrots', true);
|
List all suppliers from 'Down to Earth' that provide organic products.
|
SELECT DISTINCT name FROM Suppliers WHERE is_organic = true AND name = 'Down to Earth';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE student_enrollment (student_id INT, continent VARCHAR(50), program VARCHAR(50)); INSERT INTO student_enrollment (student_id, continent, program) VALUES (1, 'North America', 'Lifelong Learning 101'), (2, 'Europe', 'Lifelong Learning 202'), (3, 'Asia', 'Lifelong Learning 101');
|
How many students are enrolled in lifelong learning programs in each continent?
|
SELECT continent, COUNT(DISTINCT student_id) as num_students FROM student_enrollment GROUP BY continent;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE mines (id INT, name TEXT, location TEXT, gadolinium_production FLOAT, timestamp DATE); INSERT INTO mines (id, name, location, gadolinium_production, timestamp) VALUES (1, 'Mine A', 'Canada', 120.5, '2021-01-01'), (2, 'Mine B', 'Canada', 150.7, '2021-02-01'), (3, 'Mine C', 'USA', 200.3, '2021-03-01'), (4, 'Mine D', 'Canada', 250.3, '2022-01-01'), (5, 'Mine E', 'USA', 300.3, '2022-02-01');
|
What is the average Gadolinium production by month for 2021 and 2022?
|
SELECT MONTH(timestamp), AVG(gadolinium_production) FROM mines WHERE YEAR(timestamp) IN (2021, 2022) GROUP BY MONTH(timestamp);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Transactions (transaction_id INT, user_id INT, gender VARCHAR(10), transaction_amount DECIMAL(10,2)); INSERT INTO Transactions (transaction_id, user_id, gender, transaction_amount) VALUES (1, 101, 'Male', 50.00), (2, 102, 'Female', 75.00), (3, 103, 'Non-binary', 35.00), (4, 104, 'Male', 60.00);
|
What is the total number of transactions for each gender?
|
SELECT gender, SUM(transaction_amount) as total_amount FROM Transactions GROUP BY gender;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE company (id INT, name TEXT, founder_lgbtq INT, industry TEXT); INSERT INTO company (id, name, founder_lgbtq, industry) VALUES (1, 'EduTech', 1, 'Education Technology'); INSERT INTO company (id, name, founder_lgbtq, industry) VALUES (2, 'LearningPlatforms', 0, 'Education Technology');
|
What is the number of startups founded by people who identify as LGBTQ+ in the education technology industry?
|
SELECT COUNT(*) FROM company WHERE founder_lgbtq = 1 AND industry = 'Education Technology';
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gretelai_synthetic_text_to_sql
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CREATE TABLE habitat (id INT, size FLOAT); CREATE TABLE animal_population (id INT, habitat_id INT, animal_count INT);
|
What is the total number of animals in habitats larger than 100 square kilometers?
|
SELECT SUM(ap.animal_count) FROM animal_population ap INNER JOIN habitat h ON ap.habitat_id = h.id WHERE h.size > 100;
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gretelai_synthetic_text_to_sql
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CREATE TABLE smart_city_tech (tech_id INT, tech_name VARCHAR(30), city VARCHAR(20), population INT); INSERT INTO smart_city_tech (tech_id, tech_name, city, population) VALUES (1, 'Smart Grids', 'New York', 8500000), (2, 'Smart Lighting', 'Los Angeles', 4000000), (3, 'Smart Traffic Management', 'Toronto', 3000000);
|
List all smart city technology adoptions in the North American cities with a population greater than 1 million.
|
SELECT tech_name, city FROM smart_city_tech WHERE population > 1000000 AND city IN ('New York', 'Los Angeles', 'Toronto');
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gretelai_synthetic_text_to_sql
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CREATE TABLE GreenBuildingMaterials (MaterialID INT, MaterialName VARCHAR(50));CREATE TABLE GreenBuildingMaterialsUsage (UsageID INT, MaterialID INT, CityID INT, ProjectID INT);
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List all green building materials and the number of each material used in a specific city, for projects in London.
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SELECT GreenBuildingMaterials.MaterialName, COUNT(GreenBuildingMaterialsUsage.UsageID) FROM GreenBuildingMaterials INNER JOIN GreenBuildingMaterialsUsage ON GreenBuildingMaterials.MaterialID = GreenBuildingMaterialsUsage.MaterialID WHERE GreenBuildingMaterialsUsage.CityID = 2 GROUP BY GreenBuildingMaterials.MaterialName;
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gretelai_synthetic_text_to_sql
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CREATE TABLE refugee (id INT, name VARCHAR(255), age INT, location VARCHAR(255), supported_by VARCHAR(255), support_date DATE); INSERT INTO refugee (id, name, age, location, supported_by, support_date) VALUES (1, 'Jane Doe', 35, 'Europe', 'Red Crescent', '2022-01-01');
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What is the average age of refugees supported by 'Red Crescent' in 'Europe'?
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SELECT AVG(age) FROM refugee WHERE location = 'Europe' AND supported_by = 'Red Crescent';
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gretelai_synthetic_text_to_sql
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CREATE TABLE building_info (info_id INT, sq_footage INT, city TEXT, sustainable BOOLEAN); INSERT INTO building_info VALUES (1, 50000, 'Seattle', TRUE), (2, 60000, 'Houston', FALSE), (3, 70000, 'Seattle', TRUE), (4, 40000, 'New York', FALSE), (5, 30000, 'Denver', TRUE);
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What is the total number of sustainable buildings in each city?
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SELECT city, COUNT(*) FILTER (WHERE sustainable = TRUE) FROM building_info GROUP BY city;
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gretelai_synthetic_text_to_sql
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