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CREATE TABLE ProductMaterials (product_id INT, sustainable_materials BOOLEAN);
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What is the percentage of products made with sustainable materials in India?
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SELECT 100.0 * COUNT(*) / (SELECT COUNT(*) FROM ProductMaterials) FROM ProductMaterials WHERE sustainable_materials = TRUE AND country = 'India';
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gretelai_synthetic_text_to_sql
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CREATE TABLE intel_ops (id INT, name VARCHAR(255), type VARCHAR(255), location VARCHAR(255), start_date DATE, end_date DATE); INSERT INTO intel_ops (id, name, type, location, start_date, end_date) VALUES (1, 'Operation Iraqi Freedom', 'Military Operation', 'Iraq', '2003-03-20', '2011-12-15'); INSERT INTO intel_ops (id, name, type, location, start_date, end_date) VALUES (2, 'Operation Enduring Freedom', 'Military Operation', 'Afghanistan', '2001-10-07', '2021-08-31'); INSERT INTO intel_ops (id, name, type, location, start_date, end_date) VALUES (3, 'Operation Protective Edge', 'Military Operation', 'Gaza Strip', '2014-07-08', '2014-08-26');
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Which military operations were initiated after the ones initiated by Israel?
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SELECT name, type, location, start_date, LAG(start_date) OVER (ORDER BY start_date) as previous_start_date FROM intel_ops WHERE type = 'Military Operation';
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gretelai_synthetic_text_to_sql
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CREATE TABLE loans (loan_id INT, client_id INT, loan_type VARCHAR(50), issue_date DATE, country VARCHAR(50));
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Add a new row to the 'loans' table for a socially responsible loan issued to a client in Malaysia.
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INSERT INTO loans VALUES (1001, 3, 'Socially Responsible Loan', '2022-04-01', 'Malaysia');
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gretelai_synthetic_text_to_sql
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CREATE TABLE luxury_hotel_rooms (id INT, country VARCHAR(50), rooms INT); INSERT INTO luxury_hotel_rooms (id, country, rooms) VALUES (1, 'South Africa', 500), (2, 'South Africa', 600), (3, 'South Africa', 700), (4, 'Morocco', 400);
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What is the total number of luxury hotel rooms in South Africa?
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SELECT SUM(rooms) FROM luxury_hotel_rooms WHERE country = 'South Africa';
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gretelai_synthetic_text_to_sql
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CREATE TABLE savings_accounts (account_id INT, customer_id INT, account_open_date DATE, is_shariah_compliant BOOLEAN);CREATE TABLE customers (customer_id INT, customer_name VARCHAR(255), customer_type VARCHAR(255));INSERT INTO customers (customer_id, customer_name, customer_type) VALUES (1, 'John Doe', 'New'), (2, 'Jane Smith', 'Existing');
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How many Shariah-compliant savings accounts were opened in the last 6 months by new customers?
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SELECT COUNT(sa.account_id) as new_shariah_compliant_savings_accounts FROM savings_accounts sa INNER JOIN customers c ON sa.customer_id = c.customer_id WHERE sa.account_open_date BETWEEN (CURRENT_DATE - INTERVAL '6 months') AND CURRENT_DATE AND sa.is_shariah_compliant = TRUE AND c.customer_type = 'New';
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gretelai_synthetic_text_to_sql
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CREATE TABLE MentalHealthParity (CaseID INT, Region VARCHAR(25)); INSERT INTO MentalHealthParity (CaseID, Region) VALUES (1, 'Northeast'), (2, 'Midwest'), (3, 'South'), (4, 'Northeast'), (5, 'West');
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How many mental health parity cases were reported in each region?
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SELECT Region, COUNT(*) as NumCases FROM MentalHealthParity GROUP BY Region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE if NOT EXISTS community_education (program_id INT, program_name VARCHAR(50), donation_count INT); INSERT INTO community_education (program_id, program_name, donation_count) VALUES (1, 'Wildlife Conservation 101', 500); INSERT INTO community_education (program_id, program_name, donation_count) VALUES (2, 'Endangered Species Awareness', 300); INSERT INTO community_education (program_id, program_name, donation_count) VALUES (3, 'Habitat Protection Techniques', 700);
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List the community education programs that have received more than 500 donations.
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SELECT program_name FROM community_education WHERE donation_count > 500;
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gretelai_synthetic_text_to_sql
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CREATE TABLE circular_economy_performance (id INT AUTO_INCREMENT, company_name VARCHAR(50), waste_reduction_percentage FLOAT, PRIMARY KEY(id));
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Insert 3 records in the 'circular_economy_performance' table with values: ('Company A', 35.5), ('Company B', 28.6), ('Company C', 42.2)
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INSERT INTO circular_economy_performance (company_name, waste_reduction_percentage) VALUES ('Company A', 35.5), ('Company B', 28.6), ('Company C', 42.2);
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gretelai_synthetic_text_to_sql
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CREATE TABLE GlobalSales (id INT, vehicle_type VARCHAR(50), quantity INT); INSERT INTO GlobalSales (id, vehicle_type, quantity) VALUES (1, 'Hybrid', 35000), (2, 'Electric', 40000), (3, 'Autonomous', 20000), (4, 'Sedan', 45000), (5, 'SUV', 50000), (6, 'Truck', 55000);
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What is the total number of hybrid vehicles sold in the world?
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SELECT SUM(quantity) FROM GlobalSales WHERE vehicle_type = 'Hybrid';
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gretelai_synthetic_text_to_sql
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CREATE TABLE wastewater_treatment (id INT, location TEXT, treatment_date DATE, volume FLOAT); INSERT INTO wastewater_treatment (id, location, treatment_date, volume) VALUES (1, 'New York City', '2022-01-01', 1000000), (2, 'New York City', '2022-02-01', 1200000), (3, 'Buffalo', '2022-01-01', 500000);
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What is the total volume of wastewater treated in New York State by month?
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SELECT MONTH(treatment_date) as month, SUM(volume) as total_volume FROM wastewater_treatment WHERE location LIKE 'New York%' GROUP BY month;
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gretelai_synthetic_text_to_sql
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CREATE TABLE associated_press (article_id INT, title TEXT, category TEXT, publisher TEXT); INSERT INTO associated_press (article_id, title, category, publisher) VALUES (1, 'Article 1', 'US', 'Associated Press'), (2, 'Article 2', 'World', 'Associated Press'); CREATE TABLE reuters (article_id INT, title TEXT, category TEXT, publisher TEXT); INSERT INTO reuters (article_id, title, category, publisher) VALUES (3, 'Article 3', 'Business', 'Reuters'), (4, 'Article 4', 'World', 'Reuters');
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Identify the total number of articles published by 'Associated Press' and 'Reuters' in the 'US' and 'World' categories.
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SELECT COUNT(*) FROM ( (SELECT * FROM associated_press WHERE category IN ('US', 'World')) UNION (SELECT * FROM reuters WHERE category IN ('World')) );
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gretelai_synthetic_text_to_sql
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CREATE TABLE intelligence_ops (operation TEXT, region TEXT, cost INTEGER); INSERT INTO intelligence_ops (operation, region, cost) VALUES ('Operation Red', 'Asia', 10000), ('Operation Blue', 'Europe', 8000), ('Operation Green', 'Asia', 12000);
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List all intelligence operations in the 'Asia' region and their corresponding costs.
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SELECT operation, cost FROM intelligence_ops WHERE region = 'Asia'
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gretelai_synthetic_text_to_sql
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CREATE TABLE education_workers (id INT, sector VARCHAR(20), union_member BOOLEAN); INSERT INTO education_workers (id, sector, union_member) VALUES (1, 'education', TRUE), (2, 'education', FALSE), (3, 'education', TRUE), (4, 'education', FALSE);
|
Calculate the ratio of union members to non-union members in the 'education' sector
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SELECT (COUNT(*) FILTER (WHERE union_member = TRUE) * 1.0 / COUNT(*) FILTER (WHERE union_member = FALSE)) AS union_ratio FROM education_workers;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE posts (id INT, user_id INT, datetime DATETIME, hashtags VARCHAR(255)); INSERT INTO posts (id, user_id, datetime, hashtags) VALUES (1, 123, '2021-01-01 12:00:00', '#climatechange, #eco'), (2, 456, '2021-12-31 23:59:59', '#climatechange');
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What was the daily average number of user posts containing the hashtag "#climatechange" between January 1, 2021 and December 31, 2021?
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SELECT AVG(count) as avg_daily_posts FROM (SELECT DATE(datetime) as date, COUNT(*) as count FROM posts WHERE hashtags LIKE '%#climatechange%' AND datetime BETWEEN '2021-01-01' AND '2021-12-31' GROUP BY date) as daily_posts;
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gretelai_synthetic_text_to_sql
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CREATE VIEW first_medical_records AS SELECT astronaut_id, MIN(medical_record_date) AS first_date FROM astronaut_medical GROUP BY astronaut_id;
|
Calculate the average weight of astronauts on their first medical record.
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SELECT AVG(weight) FROM astronaut_medical INNER JOIN first_medical_records ON astronaut_medical.astronaut_id = first_medical_records.astronaut_id AND astronaut_medical.medical_record_date = first_medical_records.first_date;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE climate_data (region VARCHAR(255), year INT, anomaly FLOAT); INSERT INTO climate_data (region, year, anomaly) VALUES ('North America', 2016, 1.2), ('North America', 2017, 1.5), ('South America', 2018, 1.4), ('Asia', 2019, 1.8), ('Asia', 2020, 1.6), ('Africa', 2021, 2.0);
|
What is the maximum temperature anomaly for Asia?
|
SELECT MAX(anomaly) FROM climate_data WHERE region = 'Asia';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE resources (id INT, mine_type VARCHAR(50), country VARCHAR(50), reserve_tons INT);
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Insert a new record into the "resources" table for a new gold mine in "Peru" with ID 901 and reserves of 5000 tons
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INSERT INTO resources (id, mine_type, country, reserve_tons) VALUES (901, 'gold', 'Peru', 5000);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Contractors (ContractorID INT, ContractorName VARCHAR(50), City VARCHAR(50), State VARCHAR(2), Country VARCHAR(50)); CREATE TABLE LaborStatistics (StatisticID INT, ContractorID INT, EmployeeCount INT, HourlyRate FLOAT, Date DATE); INSERT INTO Contractors (ContractorID, ContractorName, City, State, Country) VALUES (2, 'GHI Construction', 'San Francisco', 'CA', 'USA'); INSERT INTO LaborStatistics (StatisticID, ContractorID, EmployeeCount, HourlyRate, Date) VALUES (1, 2, 50, 35, '2022-01-05');
|
What is the average hourly labor rate for contractors in California?
|
SELECT ContractorID FROM Contractors WHERE State = 'CA'; SELECT AVG(HourlyRate) FROM LaborStatistics WHERE ContractorID IN (SELECT ContractorID FROM Contractors WHERE State = 'CA');
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gretelai_synthetic_text_to_sql
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CREATE TABLE pilates_classes (class_id INT, user_id INT, duration INT, last_name VARCHAR(20));
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What is the total duration (in minutes) of all pilates classes taken by users with the last name 'Garcia'?
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SELECT SUM(duration) FROM pilates_classes WHERE last_name = 'Garcia';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE matches (match_id INT, home_team TEXT, away_team TEXT, home_points INT, away_points INT, match_date DATE);
|
Add a new volleyball match to the 'matches' table with the given details.
|
INSERT INTO matches (match_id, home_team, away_team, home_points, away_points, match_date) VALUES (1, 'Italy', 'Brazil', 3, 1, '2022-07-15');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Guides (id INT, name TEXT, city TEXT, country TEXT);CREATE TABLE VirtualTours (id INT, guide_id INT, date DATE);
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Determine the average number of virtual tours per guide in 2024, for guides who have led at least 10 tours.
|
SELECT AVG(virtual_tours_per_guide) FROM (SELECT guide_id, COUNT(*) AS virtual_tours_per_guide FROM VirtualTours WHERE YEAR(date) = 2024 GROUP BY guide_id HAVING COUNT(*) >= 10) AS Subquery;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Employees (EmployeeID INT, Name VARCHAR(50), Department VARCHAR(50), Manager VARCHAR(50)); INSERT INTO Employees (EmployeeID, Name, Department, Manager) VALUES (1, 'John Doe', 'HR', 'Peter'), (2, 'Jane Smith', 'IT', 'Sarah'), (3, 'Mike Johnson', 'HR', 'Peter'), (4, 'Emma White', 'Finance', 'David'); CREATE TABLE Departments (Department VARCHAR(50)); INSERT INTO Departments (Department) VALUES ('HR'), ('IT'), ('Finance');
|
Who is the manager for each department?
|
SELECT e.Department, e.Manager FROM Employees e JOIN Departments d ON e.Department = d.Department;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Berlin_Neighborhoods (Neighborhood VARCHAR(255), Price INT); INSERT INTO Berlin_Neighborhoods (Neighborhood, Price) VALUES ('Mitte', 800000), ('Prenzlauer Berg', 700000), ('Friedrichshain', 600000), ('Kreuzberg', 500000), ('Neukoelln', 400000);
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Show the top 3 most affordable neighborhoods in Berlin based on property price.
|
SELECT Neighborhood, Price FROM Berlin_Neighborhoods ORDER BY Price LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Patients (ID INT, Disease VARCHAR(20), State VARCHAR(20)); INSERT INTO Patients (ID, Disease, State) VALUES (1, 'Influenza', 'California'), (2, 'Pneumonia', 'California');
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What is the total number of patients diagnosed with Influenza or Pneumonia in each state?
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SELECT Disease, State, COUNT(*) AS Total FROM Patients WHERE Disease IN ('Influenza', 'Pneumonia') GROUP BY Disease, State;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Community_Centers (cc_name TEXT, families_assisted INTEGER, assist_date DATE); INSERT INTO Community_Centers (cc_name, families_assisted, assist_date) VALUES ('Center A', 200, '2021-04-01'); INSERT INTO Community_Centers (cc_name, families_assisted, assist_date) VALUES ('Center B', 150, '2021-05-15');
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How many families were assisted by each community center in Q2 of 2021?
|
SELECT cc_name, SUM(families_assisted) FROM Community_Centers WHERE assist_date BETWEEN '2021-04-01' AND '2021-06-30' GROUP BY cc_name;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Shipment (shipment_id INT, warehouse_id INT, delivery_date DATE); INSERT INTO Shipment (shipment_id, warehouse_id, delivery_date) VALUES (1, 1, '2022-01-01'), (2, 2, '2022-02-01'), (3, 3, '2022-03-01'), (4, 1, '2022-04-01'), (5, 2, '2022-05-01'); CREATE TABLE Warehouse (warehouse_id INT, warehouse_name VARCHAR(50), state VARCHAR(50)); INSERT INTO Warehouse (warehouse_id, warehouse_name, state) VALUES (1, 'Los Angeles Warehouse', 'California'), (2, 'New York Warehouse', 'New York'), (3, 'Texas Warehouse', 'Texas');
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What is the average delivery time for shipments that were delivered to warehouses in the state of New York?
|
SELECT AVG(DATEDIFF('day', s.delivery_date, w.state_joined_date)) as avg_delivery_time FROM Shipment s JOIN Warehouse w ON s.warehouse_id = w.warehouse_id WHERE w.state = 'New York';
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gretelai_synthetic_text_to_sql
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CREATE TABLE species (id INT PRIMARY KEY, name VARCHAR(50)); INSERT INTO species (id, name) VALUES (1, 'Spruce'); INSERT INTO species (id, name) VALUES (2, 'Pine'); CREATE TABLE trees (id INT PRIMARY KEY, species_id INT, age INT, height INT); INSERT INTO trees (id, species_id, age, height) VALUES (1, 1, 50, 30); INSERT INTO trees (id, species_id, age, height) VALUES (2, 2, 40, 40); INSERT INTO trees (id, species_id, age, height) VALUES (3, 1, 60, 45);
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What is the average age of trees in each species for trees with a height greater than 35?
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SELECT s.name, AVG(t.age) FROM trees t JOIN species s ON t.species_id = s.id WHERE t.height > 35 GROUP BY s.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE environmental_impact (country VARCHAR(20), element VARCHAR(10), impact FLOAT); INSERT INTO environmental_impact VALUES ('China', 'Europium', 6.1), ('China', 'Gadolinium', 7.6), ('United States', 'Europium', 2.7), ('United States', 'Gadolinium', 3.5), ('Australia', 'Europium', 2.2), ('Australia', 'Gadolinium', 3.3), ('India', 'Europium', 4.1), ('India', 'Gadolinium', 5.6);
|
Compare the environmental impact of Europium and Gadolinium production in different countries
|
SELECT element, country, impact FROM environmental_impact WHERE element IN ('Europium', 'Gadolinium') ORDER BY element, country, impact;
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gretelai_synthetic_text_to_sql
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CREATE TABLE museums (id INT, name VARCHAR(50), sector VARCHAR(50), revenue DECIMAL(10,2)); INSERT INTO museums (id, name, sector, revenue) VALUES (1, 'Louvre Museum', 'public', 320000000.00); INSERT INTO museums (id, name, sector, revenue) VALUES (2, 'Vatican Museums', 'public', 450000000.00); INSERT INTO museums (id, name, sector, revenue) VALUES (3, 'Getty Center', 'private', 200000000.00);
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What is the total revenue generated by each museum in the 'public' sector?
|
SELECT sector, SUM(revenue) FROM museums WHERE sector = 'public' GROUP BY sector;
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gretelai_synthetic_text_to_sql
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CREATE TABLE students (student_id INT, student_name VARCHAR(255), gender VARCHAR(255), age INT, accommodation_date DATE);
|
Identify the number of students who received accommodations in the last year, grouped by their gender, age, and the type of accommodation?
|
SELECT s.gender, s.age, a.accommodation_type, COUNT(*) as accommodations_count FROM students s JOIN (SELECT EXTRACT(YEAR FROM accommodation_date) as accommodation_year, accommodation_type FROM accommodations WHERE accommodation_date >= DATEADD(year, -1, CURRENT_DATE)) a ON s.student_id = a.student_id GROUP BY s.gender, s.age, a.accommodation_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE researchers (id serial, name text); CREATE TABLE grants (id serial, researcher_id integer, title text, amount real, year integer);
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Insert a new research grant for researcher 3 in 2022
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INSERT INTO grants (researcher_id, title, amount, year) VALUES (3, 'Glacier Melt in Greenland', 50000, 2022);
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gretelai_synthetic_text_to_sql
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CREATE TABLE mining_unions.strikes (id INT, union TEXT, year INT, duration INT);
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How many strikes took place in 'mining_unions' in the year 2010?
|
SELECT COUNT(*) FROM mining_unions.strikes WHERE year = 2010 AND union_member = TRUE;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE PollutionSources (SourceID INT PRIMARY KEY, SourceName TEXT);CREATE TABLE PollutionLevels (LevelID INT PRIMARY KEY, SourceID INT, PollutionLevel FLOAT, FOREIGN KEY (SourceID) REFERENCES PollutionSources(SourceID));
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Show all pollution sources with their respective maximum pollution levels in the 'PollutionLevels' table.
|
SELECT PollutionSources.SourceName, PollutionLevels.PollutionLevel FROM PollutionSources JOIN PollutionLevels ON PollutionSources.SourceID = PollutionLevels.SourceID;
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales_figures_2 (drug_name TEXT, region TEXT, sales_value NUMERIC); INSERT INTO sales_figures_2 (drug_name, region, sales_value) VALUES ('Drexo', 'South Africa', 800000), ('Axo', 'Nigeria', 900000);
|
Calculate the total sales figure for all drugs in Africa.
|
SELECT SUM(sales_value) FROM sales_figures_2 WHERE region = 'Africa';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE diversity (id INT, company_id INT, gender VARCHAR(50), race VARCHAR(50), role VARCHAR(50)); INSERT INTO diversity (id, company_id, gender, race, role) VALUES (1, 1, 'Female', 'Asian', 'Engineer'); INSERT INTO diversity (id, company_id, gender, race, role) VALUES (2, 2, 'Male', 'Hispanic', 'Executive'); CREATE TABLE company (id INT, name VARCHAR(50), founding_year INT, industry VARCHAR(50), country VARCHAR(50)); INSERT INTO company (id, name, founding_year, industry, country) VALUES (1, 'Acme Inc', 2010, 'Tech', 'Brazil'); INSERT INTO company (id, name, founding_year, industry, country) VALUES (2, 'Bravo Corp', 2015, 'Biotech', 'India');
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What is the percentage of diverse individuals in the workforce for companies with headquarters in 'Brazil' and 'India'?
|
SELECT d.company_id, ROUND(COUNT(*) * 100.0 / (SELECT COUNT(*) FROM diversity WHERE company_id = d.company_id), 2) as percentage FROM diversity d WHERE (SELECT country FROM company WHERE id = d.company_id) IN ('Brazil', 'India') GROUP BY d.company_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE companies (company_id INT, department VARCHAR(20)); INSERT INTO companies (company_id, department) VALUES (1, 'manufacturing'), (2, 'HR'), (3, 'manufacturing'); CREATE TABLE employees (employee_id INT, company_id INT); CREATE TABLE training (employee_id INT, training VARCHAR(20)); INSERT INTO employees (employee_id, company_id) VALUES (1, 1), (2, 1), (3, 2); INSERT INTO training (employee_id, training) VALUES (1, 'welding'), (2, 'safety'), (3, 'safety');
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What is the total number of employees working in the 'manufacturing' department, excluding any employees who also appear in the 'training' table?
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SELECT COUNT(*) FROM companies INNER JOIN employees ON companies.company_id = employees.company_id WHERE companies.department = 'manufacturing' AND employees.employee_id NOT IN (SELECT employee_id FROM training);
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gretelai_synthetic_text_to_sql
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CREATE TABLE farmers (id INT, name TEXT, region TEXT, year INT);CREATE TABLE projects (id INT, name TEXT, region TEXT, year INT);
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What is the total number of farmers and community development projects in 'rural_development' database, grouped by region and year?
|
SELECT region, year, COUNT(DISTINCT farmers.id) + COUNT(DISTINCT projects.id) FROM farmers FULL OUTER JOIN projects ON farmers.region = projects.region AND farmers.year = projects.year GROUP BY region, year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE seoul_bikeshare (trip_id INT, start_station VARCHAR(100), end_station VARCHAR(100), start_time TIMESTAMP); CREATE TABLE tokyo_bikeshare (ride_id INT, start_station VARCHAR(100), end_station VARCHAR(100), start_time TIMESTAMP);
|
Find the difference in the number of bike-sharing trips between Seoul and Tokyo.
|
SELECT COUNT(*) FROM seoul_bikeshare EXCEPT SELECT COUNT(*) FROM tokyo_bikeshare;
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales (id INT, dish_id INT, sale_date DATE, revenue DECIMAL(10,2)); INSERT INTO sales (id, dish_id, sale_date, revenue) VALUES (1, 101, '2021-07-01', 50.00), (2, 102, '2021-07-02', 35.00), (3, 103, '2021-07-03', 60.00); CREATE TABLE dishes (id INT, name TEXT, is_vegan BOOLEAN); INSERT INTO dishes (id, name, is_vegan) VALUES (101, 'Quinoa Salad', true), (102, 'Pizza Margherita', false), (103, 'Tofu Stir Fry', true);
|
What is the total revenue generated from vegan dishes in the last six months?
|
SELECT SUM(sales.revenue) FROM sales JOIN dishes ON sales.dish_id = dishes.id WHERE dishes.is_vegan = true AND sales.sale_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 6 MONTH) AND CURRENT_DATE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Satellites (satellite_id INT, name VARCHAR(255), country VARCHAR(255), altitude FLOAT, constellation VARCHAR(255)); INSERT INTO Satellites (satellite_id, name, country, altitude, constellation) VALUES (1, 'SpaceX-1', 'USA', 550, 'Starlink'), (2, 'SpaceX-2', 'USA', 550, 'Starlink'), (3, 'OneWeb-1', 'UK', 1200, 'OneWeb');
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What is the average altitude of satellites in the Starlink constellation?
|
SELECT AVG(altitude) FROM Satellites WHERE constellation = 'Starlink';
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gretelai_synthetic_text_to_sql
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CREATE TABLE ElectricVehicleAdoption (Model VARCHAR(20), Country VARCHAR(10), AdoptionRate FLOAT);
|
List the electric vehicle models and their adoption rates in the US.
|
SELECT Model, AdoptionRate FROM ElectricVehicleAdoption WHERE Country = 'US';
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gretelai_synthetic_text_to_sql
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CREATE TABLE FluShots (ShotID INT, Organization VARCHAR(255), Date DATE); INSERT INTO FluShots (ShotID, Organization, Date) VALUES (1, 'Pharmacy A', '2021-10-01');
|
What is the total number of flu shots administered, broken down by the organization that administered them?
|
SELECT Organization, COUNT(*) FROM FluShots GROUP BY Organization;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Chemical_Sales (Product_ID INT, Product_Name VARCHAR(50), Sales INT, Safety_Violation BOOLEAN); INSERT INTO Chemical_Sales (Product_ID, Product_Name, Sales, Safety_Violation) VALUES (1, 'ProductA', 1000, FALSE), (2, 'ProductB', 1200, TRUE), (3, 'ProductC', 1500, FALSE), (4, 'ProductD', 800, FALSE);
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Identify the top three chemical products with the highest sales in Q1 2022, excluding those with safety violations.
|
SELECT Product_Name, Sales FROM (SELECT Product_Name, Sales, RANK() OVER(ORDER BY Sales DESC) as rnk FROM Chemical_Sales WHERE Safety_Violation = FALSE) tmp WHERE rnk <= 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE cultural_competency_training (id INT, community_health_worker_id INT, hours INT, gender VARCHAR(50)); INSERT INTO cultural_competency_training (id, community_health_worker_id, hours, gender) VALUES (1, 1, 10, 'Female'), (2, 1, 5, 'Female'), (3, 2, 8, 'Male'), (4, 3, 12, 'Non-binary');
|
What is the average cultural competency training hours for community health workers by gender?
|
SELECT gender, AVG(hours) as avg_hours FROM cultural_competency_training GROUP BY gender;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE if not exists Projects (id INT, name VARCHAR(50), type VARCHAR(50), budget DECIMAL(10,2)); INSERT INTO Projects (id, name, type, budget) VALUES (1, 'Seawall', 'Resilience', 5000000.00), (2, 'Floodgate', 'Resilience', 3000000.00), (3, 'Bridge', 'Transportation', 8000000.00), (4, 'Highway', 'Transportation', 12000000.00);
|
What is the maximum budget for all transportation projects in the infrastructure development database?
|
SELECT MAX(budget) FROM Projects WHERE type = 'Transportation';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Players (PlayerID INT, Age INT, Platform VARCHAR(10)); INSERT INTO Players (PlayerID, Age, Platform) VALUES (1, 25, 'PC'), (2, 30, 'Console'), (3, 20, 'Mobile'); CREATE TABLE EsportsEvents (EventID INT, PlayerID INT); INSERT INTO EsportsEvents (EventID, PlayerID) VALUES (1, 1), (2, 2), (3, 3);
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What is the average age of console players who have participated in esports events, compared to PC players?
|
SELECT p1.Platform, AVG(p1.Age) as AvgAge FROM Players p1 JOIN EsportsEvents e ON p1.PlayerID = e.PlayerID WHERE p1.Platform IN ('PC', 'Console') GROUP BY p1.Platform;
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gretelai_synthetic_text_to_sql
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CREATE TABLE SpaceMissionExperiments (id INT, mission VARCHAR(255), num_experiments INT); INSERT INTO SpaceMissionExperiments (id, mission, num_experiments) VALUES (1, 'Apollo 17', 113); INSERT INTO SpaceMissionExperiments (id, mission, num_experiments) VALUES (2, 'Gemini 12', 52);
|
What is the maximum number of scientific experiments conducted during a single space mission?
|
SELECT mission, MAX(num_experiments) FROM SpaceMissionExperiments;
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gretelai_synthetic_text_to_sql
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CREATE TABLE recycling_rates (region TEXT, rate REAL); INSERT INTO recycling_rates (region, rate) VALUES ('NA', 0.35), ('EU', 0.50), ('AS', 0.28);
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Which regions have recycling rates higher than the global average?
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SELECT region FROM recycling_rates WHERE rate > (SELECT AVG(rate) FROM recycling_rates);
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gretelai_synthetic_text_to_sql
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CREATE TABLE geothermal_plants (id INT PRIMARY KEY, country VARCHAR(50), name VARCHAR(50), capacity FLOAT); INSERT INTO geothermal_plants (id, country, name, capacity) VALUES (1, 'New Zealand', 'Geothermal Plant A', 60.5), (2, 'New Zealand', 'Geothermal Plant B', 85.2);
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What is the maximum capacity of geothermal plants in New Zealand?
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SELECT MAX(capacity) FROM geothermal_plants WHERE country = 'New Zealand';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Vehicles (vehicle_id INT PRIMARY KEY, license_plate VARCHAR(255), model VARCHAR(255), year INT); INSERT INTO Vehicles (vehicle_id, license_plate, model, year) VALUES (2, 'XYZ123', 'Bus', 2018); CREATE TABLE Maintenance (maintenance_id INT PRIMARY KEY, vehicle_id INT, last_maintenance_date DATE, next_maintenance_date DATE); INSERT INTO Maintenance (maintenance_id, vehicle_id, last_maintenance_date, next_maintenance_date) VALUES (1, 2, '2022-02-01', '2022-05-01');
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What is the next maintenance date for the vehicle with license plate XYZ123?
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SELECT m.next_maintenance_date FROM Maintenance m WHERE m.vehicle_id = (SELECT v.vehicle_id FROM Vehicles v WHERE v.license_plate = 'XYZ123');
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gretelai_synthetic_text_to_sql
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CREATE TABLE legal_tech_patents (patent_id INT, patent_number VARCHAR(20), issue_date DATE, patent_type VARCHAR(30), description VARCHAR(100));
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What is the total number of legal technology patents issued by year in the 'legal_tech_patents' table?
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SELECT YEAR(issue_date) AS year, COUNT(*) AS patent_count FROM legal_tech_patents GROUP BY year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Streaming (StreamID INT, SongID INT, UserID INT, Location VARCHAR(50), Revenue DECIMAL(10,2), Genre VARCHAR(50), Artist VARCHAR(100)); INSERT INTO Streaming (StreamID, SongID, UserID, Location, Revenue, Genre, Artist) VALUES (5, 5, 5, 'Mexico', 1.29, 'Latin', 'Carlos Santana'); INSERT INTO Streaming (StreamID, SongID, UserID, Location, Revenue, Genre, Artist) VALUES (6, 6, 6, 'USA', 0.99, 'Pop', 'Shakira');
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Who is the most popular Latin artist based on streaming?
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SELECT Artist, COUNT(*) FROM Streaming WHERE Genre = 'Latin' GROUP BY Artist ORDER BY COUNT(*) DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE artists (id INT, city VARCHAR(20), collections INT); INSERT INTO artists (id, city, collections) VALUES (1, 'London', 2), (2, 'London', 3), (3, 'New York', 1);
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How many art collections does each artist have in 'London'?
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SELECT city, collections FROM artists WHERE city = 'London';
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gretelai_synthetic_text_to_sql
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CREATE TABLE warehouse (warehouse_id VARCHAR(10), city VARCHAR(20), state VARCHAR(20), country VARCHAR(20));
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Insert records into the warehouse table for a new warehouse with warehouse_id '002', city 'Chicago', state 'IL', and country 'USA'
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INSERT INTO warehouse (warehouse_id, city, state, country) VALUES ('002', 'Chicago', 'IL', 'USA');
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA if not exists pharma; CREATE TABLE if not exists pharma.clinical_trials (drug VARCHAR(255), phase INT, result VARCHAR(255)); INSERT INTO pharma.clinical_trials (drug, phase, result) VALUES ('Drug A', 1, 'Completed'), ('Drug A', 2, 'Failed'), ('Drug B', 3, 'Completed'), ('Drug C', 3, 'Failed'), ('Drug D', 1, 'Completed'), ('Drug D', 2, 'Completed'), ('Drug D', 3, 'Completed');
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Which drugs had the highest clinical trial success rate in phase 3?
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SELECT drug, (SUM(CASE WHEN result = 'Completed' THEN 1 ELSE 0 END) / COUNT(*)) * 100.0 AS success_rate FROM pharma.clinical_trials WHERE phase = 3 GROUP BY drug ORDER BY success_rate DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE donors (donor_id INT, region VARCHAR(20), contributions DECIMAL(10,2), focus VARCHAR(20)); INSERT INTO donors (donor_id, region, contributions, focus) VALUES (1, 'Africa', 50000.00, 'accessibility'), (2, 'Europe', 100000.00, 'education'), (3, 'North America', 200000.00, 'policy'), (4, 'Africa', 75000.00, 'accessibility'), (5, 'Africa', 10000.00, 'accessibility');
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Who are the top 3 donors for accessibility-focused social good projects in Africa?
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SELECT donor_id, contributions FROM donors WHERE region = 'Africa' AND focus = 'accessibility' ORDER BY contributions DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE mobile_subscribers (subscriber_id INT, join_date DATE); INSERT INTO mobile_subscribers (subscriber_id, join_date) VALUES (1, '2021-01-01'), (2, '2021-02-01'), (3, '2020-12-01');
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List all mobile subscribers who joined after a specific date and their respective joining dates.
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SELECT * FROM mobile_subscribers WHERE join_date > '2021-01-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE workouts (id VARCHAR(10), member_id VARCHAR(10), duration INT, date DATE); INSERT INTO workouts (id, member_id, duration, date) VALUES ('001', '001', 60, '2022-01-01'), ('002', '002', 45, '2022-01-02'), ('003', '001', 90, '2022-01-03');
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Delete the workout with ID 003 from the workouts table.
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DELETE FROM workouts WHERE id = '003';
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gretelai_synthetic_text_to_sql
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CREATE TABLE MentalHealthParity (ID INT PRIMARY KEY, PatientID INT, Procedure VARCHAR(20), Cost INT);
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What is the total cost of mental health parity procedures performed on a specific date?
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SELECT SUM(Cost) as TotalCost FROM MentalHealthParity WHERE Date = '2022-01-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE riders (rider_id INT, rider_name TEXT); CREATE TABLE trips (trip_id INT, rider_id INT, trip_date DATE, trip_time TIME);
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What is the maximum number of trips taken by a single rider in a week?
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SELECT r.rider_name, MAX(COUNT(*)) as max_weekly_trips FROM riders r INNER JOIN trips t ON r.rider_id = t.rider_id GROUP BY r.rider_name, DATEPART(week, t.trip_date);
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gretelai_synthetic_text_to_sql
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CREATE TABLE BerlinExhibitions (id INT, visitorAge INT); INSERT INTO BerlinExhibitions (id, visitorAge) VALUES (1, 35), (2, 42), (3, 31), (4, 28), (5, 39), (6, 45);
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Calculate the median age of visitors who attended exhibitions in Berlin.
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SELECT AVG(visitorAge) FROM (SELECT visitorAge FROM BerlinExhibitions t1 WHERE (SELECT COUNT(*) FROM BerlinExhibitions t2 WHERE t2.visitorAge <= t1.visitorAge) > (SELECT COUNT(*) / 2 FROM BerlinExhibitions)) t;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Players (PlayerID INT, Age INT, Platform VARCHAR(10));CREATE TABLE ESportsEvents (EventID INT, PlayerID INT);
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What is the average age of players who have participated in ESports events, categorized by the platform (PC, Console, Mobile)?
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SELECT Platform, AVG(Age) FROM Players p INNER JOIN ESportsEvents e ON p.PlayerID = e.PlayerID GROUP BY Platform;
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gretelai_synthetic_text_to_sql
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CREATE TABLE grad_students (id INT, name VARCHAR(50), race_ethnicity VARCHAR(50));CREATE TABLE papers (id INT, paper_id INT, title VARCHAR(100), year INT, author_id INT);
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What is the number of graduate students from historically marginalized racial and ethnic groups who have published 3 or more academic papers in the last 2 years?
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SELECT COUNT(DISTINCT gs.id) FROM grad_students gs JOIN papers p ON gs.id = p.author_id WHERE gs.race_ethnicity IN ('historically_marginalized_1', 'historically_marginalized_2') AND p.year BETWEEN YEAR(CURRENT_DATE) - 2 AND YEAR(CURRENT_DATE) GROUP BY gs.id HAVING COUNT(DISTINCT p.paper_id) >= 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ai_ethics_training (id INT PRIMARY KEY, employee_name VARCHAR(50), training_date DATE);
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Insert new records into the "ai_ethics_training" table for new employees from underrepresented communities
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INSERT INTO ai_ethics_training (employee_name, training_date) VALUES ('Mohamed Ali', '2023-03-15'), ('Juana Rodriguez', '2023-03-16'), ('Thanh Nguyen', '2023-03-17'), ('Rajesh Patel', '2023-03-18');
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gretelai_synthetic_text_to_sql
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CREATE TABLE workout_data(id INT, member_id INT, workout_type VARCHAR(20), workout_duration INT, country VARCHAR(20)); INSERT INTO workout_data(id, member_id, workout_type, workout_duration, country) VALUES (1, 1, 'Running', 60, 'USA'), (2, 2, 'Cycling', 45, 'Canada');
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Find the unique workout types for members who are older than 40 and from the United States.
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SELECT DISTINCT workout_type FROM workout_data WHERE country = 'USA' AND age > 40;
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gretelai_synthetic_text_to_sql
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CREATE TABLE public_services (id INT PRIMARY KEY, service VARCHAR(255), location VARCHAR(255), budget DECIMAL(10, 2), provider VARCHAR(255));
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List the total budget allocation for public services in each city, sorted by the total budget in descending order.
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SELECT location, SUM(budget) as total_budget FROM public_services GROUP BY location ORDER BY total_budget DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE inventory (product_id INT, last_sale_date DATE, ethical_source BOOLEAN); INSERT INTO inventory VALUES (1, '2022-01-01', false), (2, '2022-05-01', false), (3, '2021-12-31', true), (51, '2022-06-15', false);
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Update the ethical_source column to true for all products with a last_sale_date within the last month and product_id greater than 50.
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UPDATE inventory SET ethical_source = true WHERE last_sale_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH) AND product_id > 50;
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gretelai_synthetic_text_to_sql
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CREATE TABLE social_good (id INT, project_name TEXT, budget INT, region TEXT); INSERT INTO social_good (id, project_name, budget, region) VALUES (1, 'Tech4Good Initiative', 50000, 'Africa'), (2, 'SocialTech Program', 75000, 'North America'), (3, 'DigitalDivide Fund', 60000, 'Europe'); CREATE TABLE regions (id INT, region TEXT); INSERT INTO regions (id, region) VALUES (1, 'Asia'), (2, 'North America'), (3, 'Europe'), (4, 'Africa'), (5, 'South America');
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What is the average budget for technology for social good projects in each region?
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SELECT r.region, AVG(budget) as avg_budget FROM social_good sg JOIN regions r ON sg.region = r.region GROUP BY r.region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE WeatherData (temp FLOAT, time DATETIME, crop VARCHAR(255));
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What is the maximum temperature recorded for each crop type in the past week?
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SELECT crop, MAX(temp) FROM WeatherData WHERE time > DATE_SUB(CURRENT_TIMESTAMP(), INTERVAL 1 WEEK) GROUP BY crop;
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gretelai_synthetic_text_to_sql
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CREATE TABLE programs (program_id INT, social_impact_score DECIMAL(10,2)); INSERT INTO programs (program_id, social_impact_score) VALUES (1, 8.5), (2, 9.0), (3, 7.5);
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What is the average social impact score for each program in the programs table?
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SELECT AVG(social_impact_score) as avg_social_impact_score, program_id FROM programs GROUP BY program_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Volunteers (VolunteerID int, Name varchar(50), Country varchar(50));
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Find the top 3 countries with the most volunteers and the total number of volunteers from each.
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SELECT Country, COUNT(*) as TotalVolunteers FROM Volunteers GROUP BY Country ORDER BY COUNT(*) DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE daily_production (well_id INT, date DATE, type VARCHAR(10), quantity INT); INSERT INTO daily_production (well_id, date, type, quantity) VALUES (1, '2022-01-01', 'Oil', 100), (1, '2022-01-02', 'Oil', 105), (2, '2022-01-01', 'Gas', 200), (2, '2022-01-02', 'Gas', 205);
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Show the daily production quantity per well in the Northern region
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SELECT well_id, date, type, quantity FROM daily_production WHERE region = 'Northern';
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gretelai_synthetic_text_to_sql
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CREATE TABLE virtual_tours (tour_id INT, region VARCHAR(20), bookings INT); INSERT INTO virtual_tours (tour_id, region, bookings) VALUES (1, 'North America', 500), (2, 'North America', 600), (3, 'Europe', 400), (4, 'Europe', 300);
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What is the number of virtual tours booked in each region?
|
SELECT region, SUM(bookings) FROM virtual_tours GROUP BY region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE employee_roster (id INT, country VARCHAR(50), employee VARCHAR(50)); INSERT INTO employee_roster (id, country, employee) VALUES (1, 'Canada', 'John Doe'), (2, 'Germany', 'Jane Smith'), (3, 'Canada', 'Jim Brown');
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Find the total number of employees in the manufacturing sector across all countries, excluding any duplicate entries.
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SELECT COUNT(DISTINCT employee) FROM employee_roster;
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gretelai_synthetic_text_to_sql
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CREATE TABLE renewable_energy (project_id INT, project_name VARCHAR(100), location VARCHAR(100), energy_type VARCHAR(50), installed_capacity FLOAT); INSERT INTO renewable_energy (project_id, project_name, location, energy_type, installed_capacity) VALUES (1, 'Solar Farm 1', 'Australia', 'Solar', 30.0), (2, 'Wind Farm 1', 'Sweden', 'Wind', 65.3);
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How many renewable energy projects are in the 'renewable_energy' table?
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SELECT COUNT(*) FROM renewable_energy;
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gretelai_synthetic_text_to_sql
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CREATE TABLE users (user_id INT, username VARCHAR(20), region VARCHAR(20));CREATE TABLE transactions (transaction_id INT, user_id INT, amount DECIMAL(10,2), transaction_time TIMESTAMP);
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Find users who made a transaction greater than $100 and less than $500?
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SELECT user_id FROM transactions WHERE amount > 100 AND amount < 500;
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gretelai_synthetic_text_to_sql
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CREATE TABLE renewable_energy (country VARCHAR(50), year INT, renewable_energy_share FLOAT); INSERT INTO renewable_energy (country, year, renewable_energy_share) VALUES ('Brazil', 2020, 44.3), ('Argentina', 2020, 9.5), ('Colombia', 2020, 73.4), ('Peru', 2020, 61.7), ('Chile', 2020, 41.7);
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What is the renewable energy share in South America in 2020?
|
SELECT country, AVG(renewable_energy_share) FROM renewable_energy WHERE year = 2020 AND country IN ('Brazil', 'Argentina', 'Colombia', 'Peru', 'Chile') GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE clinics (id INT, name TEXT, location TEXT, ambulances INT, rural BOOLEAN, added DATE); INSERT INTO clinics (id, name, location, ambulances, rural, added) VALUES (1, 'Clinic A', 'Iowa', 5, true, '2019-01-01'), (2, 'Clinic B', 'Iowa', 3, true, '2020-01-01');
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What is the minimum number of ambulances in rural clinics of Iowa that were added in 2020?
|
SELECT MIN(ambulances) FROM clinics WHERE location = 'Iowa' AND rural = true AND added >= '2020-01-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE grants (id INT, department VARCHAR(255), year INT, status VARCHAR(255)); INSERT INTO grants (id, department, year, status) VALUES (1, 'Mathematics', 2018, 'approved'), (2, 'Physics', 2019, 'approved'), (3, 'Mathematics', 2020, 'rejected'), (4, 'Computer Science', 2017, 'approved');
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What is the average number of research grants approved per year for the Mathematics department?
|
SELECT department, AVG(year) as avg_year FROM (SELECT department, YEAR(CURDATE()) - year AS year, status FROM grants WHERE department = 'Mathematics' AND status = 'approved') subquery WHERE status = 'approved' GROUP BY department;
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gretelai_synthetic_text_to_sql
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CREATE TABLE savings (account_number INT, customer_rating INT, is_shariah_compliant BOOLEAN, balance DECIMAL(10, 2)); INSERT INTO savings (account_number, customer_rating, is_shariah_compliant, balance) VALUES (1, 5, true, 1500.00), (2, 3, false, 800.00), (3, 4, true, 1200.00), (4, 5, false, 2000.00), (5, 5, true, 2500.00);
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What is the average monthly balance for Shariah-compliant savings accounts with a customer rating above 4?
|
SELECT AVG(balance) FROM (SELECT account_number, customer_rating, is_shariah_compliant, balance, ROW_NUMBER() OVER (PARTITION BY customer_rating, is_shariah_compliant ORDER BY balance DESC) AS rn FROM savings) tmp WHERE rn = 1 AND customer_rating > 4 AND is_shariah_compliant = true;
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gretelai_synthetic_text_to_sql
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CREATE TABLE physician (physician_id INT, name VARCHAR(50), specialty VARCHAR(30)); CREATE TABLE visit (visit_id INT, physician_id INT, rural BOOLEAN);
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What is the name of the physician with the most rural patient visits?
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SELECT physician.name FROM physician JOIN (SELECT physician_id FROM visit WHERE rural = TRUE GROUP BY physician_id ORDER BY COUNT(*) DESC LIMIT 1) AS subquery ON physician.physician_id = subquery.physician_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE DestinationRatings (DestinationID INT, Destination VARCHAR(50), SustainableRating INT); INSERT INTO DestinationRatings (DestinationID, Destination, SustainableRating) VALUES (1, 'National Park', 5), (2, 'Beach Resort', 3);
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Find the top 3 destinations with the highest number of sustainable tourism certifications.
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SELECT Destination, SUM(SustainableRating) AS TotalRating FROM DestinationRatings GROUP BY Destination ORDER BY TotalRating DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE SpaceMissions (MissionID INT, MissionName VARCHAR(255), LaunchDate DATE); INSERT INTO SpaceMissions (MissionID, MissionName, LaunchDate) VALUES (100, 'Apollo 10', '1969-05-18'), (101, 'Apollo 11', '1969-07-16');
|
Delete the mission record with the MissionID 100 from the SpaceMissions table.
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DELETE FROM SpaceMissions WHERE MissionID = 100;
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gretelai_synthetic_text_to_sql
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CREATE TABLE teams (team_id INT, team_name VARCHAR(255)); CREATE TABLE games (game_id INT, team_id INT, game_date DATE); CREATE TABLE games_stats (game_id INT, team_id INT, points INT);
|
What is the highest scoring game for each team, from the teams, games, and games_stats tables?
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SELECT t.team_name, MAX(gs.points) AS highest_score FROM games g JOIN teams t ON g.team_id = t.team_id JOIN games_stats gs ON g.game_id = gs.game_id GROUP BY t.team_name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Infrastructure_Projects (Project_ID INT, Project_Type VARCHAR(255), Resilience_Score FLOAT, Year INT, State VARCHAR(255));
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What is the average resilience score for each type of infrastructure project in Texas for the year 2022?
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SELECT Year, Project_Type, AVG(Resilience_Score) FROM Infrastructure_Projects WHERE State = 'Texas' AND Year = 2022 GROUP BY Year, Project_Type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE mobile_usage (customer_id INT, city VARCHAR(20), data_usage FLOAT); INSERT INTO mobile_usage (customer_id, city, data_usage) VALUES (1, 'Sydney', 12), (2, 'Sydney', 8), (3, 'Melbourne', 15);
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What is the percentage of mobile customers in the city of Sydney who have used more than 10GB of data in the past month?
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SELECT (COUNT(*) * 100.0 / (SELECT COUNT(*) FROM mobile_usage WHERE city = 'Sydney')) FROM mobile_usage WHERE city = 'Sydney' AND data_usage > 10;
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gretelai_synthetic_text_to_sql
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CREATE TABLE uk_garment_sales (garment_type VARCHAR(255), geography VARCHAR(255), sales_quantity INT, quarter INT, year INT); INSERT INTO uk_garment_sales (garment_type, geography, sales_quantity, quarter, year) VALUES ('T-Shirt', 'United Kingdom', 1000, 1, 2021), ('Jeans', 'United Kingdom', 1500, 1, 2021), ('Hoodie', 'United Kingdom', 1200, 1, 2021);
|
How many men's garments were sold in the United Kingdom in Q1 2021?
|
SELECT SUM(sales_quantity) FROM uk_garment_sales WHERE geography = 'United Kingdom' AND quarter = 1 AND year = 2021;
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gretelai_synthetic_text_to_sql
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CREATE TABLE meals (user_id INT, meal_date DATE, calories INT); INSERT INTO meals (user_id, meal_date, calories) VALUES (1, '2022-01-01', 600), (1, '2022-01-02', 800), (2, '2022-01-01', 500);
|
What is the average calorie intake per meal by users in Canada?
|
SELECT AVG(calories) FROM (SELECT user_id, meal_date, SUM(calories) OVER (PARTITION BY user_id ORDER BY meal_date) as calories FROM meals) t WHERE t.user_id IN (SELECT user_id FROM users WHERE country = 'Canada');
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gretelai_synthetic_text_to_sql
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CREATE TABLE Players (PlayerID INT, Age INT, Gender VARCHAR(10), Country VARCHAR(20), FavoriteGame VARCHAR(10)); INSERT INTO Players (PlayerID, Age, Gender, Country, FavoriteGame) VALUES (1, 22, 'Female', 'India', 'Mobile'); INSERT INTO Players (PlayerID, Age, Gender, Country, FavoriteGame) VALUES (2, 28, 'Male', 'Australia', 'Mobile'); INSERT INTO Players (PlayerID, Age, Gender, Country, FavoriteGame) VALUES (3, 35, 'Female', 'Brazil', 'Mobile');
|
Find the top 2 countries with the highest number of female players who prefer Mobile games.
|
SELECT Country, COUNT(PlayerID) as NumberOfPlayers FROM Players WHERE Gender = 'Female' AND FavoriteGame = 'Mobile' GROUP BY Country ORDER BY NumberOfPlayers DESC LIMIT 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE MentalHealthClinics (ClinicID INT, Location VARCHAR(50), Type VARCHAR(20)); CREATE TABLE DisadvantagedNeighborhoods (NeighborhoodID INT, Location VARCHAR(50)); INSERT INTO MentalHealthClinics (ClinicID, Location, Type) VALUES (1, '123 Main St', 'Psychiatric'); INSERT INTO DisadvantagedNeighborhoods (NeighborhoodID, Location) VALUES (1, '456 Elm St');
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List all mental health clinics located in disadvantaged neighborhoods?
|
SELECT MentalHealthClinics.Location FROM MentalHealthClinics INNER JOIN DisadvantagedNeighborhoods ON MentalHealthClinics.Location = DisadvantagedNeighborhoods.Location;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Exhibitions (exhibition_id INT, location VARCHAR(20), entry_fee INT); INSERT INTO Exhibitions (exhibition_id, location, entry_fee) VALUES (1, 'Beijing', 12), (2, 'Beijing', 20), (3, 'Beijing', 30); CREATE TABLE Visitors (visitor_id INT, exhibition_id INT); INSERT INTO Visitors (visitor_id, exhibition_id) VALUES (1, 1), (2, 1), (3, 2), (4, 3);
|
What is the total entry fee collected in Beijing for exhibitions with an entry fee above 10?
|
SELECT SUM(entry_fee) FROM Exhibitions WHERE location = 'Beijing' AND entry_fee > 10;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE transportation_projects (id INT, project_name TEXT, budget INT);INSERT INTO transportation_projects (id, project_name, budget) VALUES (1, 'ProjectA', 8000000), (2, 'ProjectB', 5000000), (3, 'ProjectC', 10000000);
|
What is the maximum budget allocated for any project in the transportation projects table?
|
SELECT MAX(budget) FROM transportation_projects;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE temperature_data (id INT, fish_id INT, record_date DATE, water_temp DECIMAL(5,2)); INSERT INTO temperature_data (id, fish_id, record_date, water_temp) VALUES (1, 1, '2022-03-01', 27.5), (2, 1, '2022-03-15', 28.2), (3, 2, '2022-03-01', 8.3), (4, 2, '2022-03-15', 8.9);
|
Update the water temperature for record ID 3 to 9.0 degrees.
|
UPDATE temperature_data SET water_temp = 9.0 WHERE id = 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE marine_protected_areas (year INT, area_size FLOAT); INSERT INTO marine_protected_areas (year, area_size) VALUES (2010, 25000), (2011, 30000), (2012, 20000), (2013, 35000), (2014, 15000), (2015, 40000);
|
What was the maximum marine protected area size created each year?
|
SELECT year, MAX(area_size) OVER(PARTITION BY (year - MOD(year, 5))) as max_area_per_5_years FROM marine_protected_areas;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE installations (exhibition_id INT, installation_type VARCHAR(10)); INSERT INTO installations (exhibition_id, installation_type) VALUES (1, 'Interactive'), (1, 'Projection');
|
How many digital interactive installations were available for each exhibition category?
|
SELECT exhibition_category, COUNT(DISTINCT exhibition_id) AS num_interactive_installations FROM installations JOIN exhibitions ON installations.exhibition_id = exhibitions.id GROUP BY exhibition_category;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE manufacturers (manufacturer_id INT, manufacturer_name TEXT); CREATE TABLE labor_reports (report_id INT, manufacturer_id INT, violation_count INT); INSERT INTO manufacturers (manufacturer_id, manufacturer_name) VALUES (1, 'Ethical Clothing'), (2, 'Fast Fashion Inc.'); INSERT INTO labor_reports (report_id, manufacturer_id, violation_count) VALUES (1, 1, 0), (2, 1, 2), (3, 2, 5), (4, 2, 3);
|
How many labor violations have been reported for each manufacturer?
|
SELECT manufacturer_id, SUM(violation_count) FROM labor_reports GROUP BY manufacturer_id;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE sector_incidents (id INT, incident_type VARCHAR(255), sector VARCHAR(255), incident_date DATE, affected_assets INT); INSERT INTO sector_incidents (id, incident_type, sector, incident_date, affected_assets) VALUES (1, 'Ransomware', 'Transportation', '2022-01-01', 50);
|
What is the total number of cybersecurity incidents and their types that have occurred in the transportation sector in the past year?
|
SELECT incident_type, COUNT(*) as total_occurrences FROM sector_incidents WHERE sector = 'Transportation' AND incident_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR) GROUP BY incident_type;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Farm (id INT, name VARCHAR(50), country VARCHAR(50)); CREATE TABLE Measurement (id INT, farm_id INT, dissolved_oxygen FLOAT, timestamp TIMESTAMP);
|
Find the top 3 countries with the highest average dissolved oxygen levels in their aquaculture farms.
|
SELECT f.country, AVG(m.dissolved_oxygen) FROM Farm f JOIN Measurement m ON f.id = m.farm_id GROUP BY f.country ORDER BY AVG(m.dissolved_oxygen) DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE content_creators (id INT, name TEXT, country TEXT, media_literacy_score INT); INSERT INTO content_creators (id, name, country, media_literacy_score) VALUES (1, 'Alice', 'Brazil', 90), (2, 'Bob', 'Argentina', 95);
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Who are the top 5 content creators with the highest media literacy scores in Latin American countries?
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SELECT name, media_literacy_score FROM content_creators WHERE country IN ('Brazil', 'Argentina', 'Colombia', 'Chile', 'Mexico') ORDER BY media_literacy_score DESC LIMIT 5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE healthcare_providers_income (income_area VARCHAR(20), provider_count INT); INSERT INTO healthcare_providers_income (income_area, provider_count) VALUES ('Low-income', 500), ('High-income', 200);
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How many healthcare providers are there in low-income and high-income areas?
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SELECT income_area, provider_count, NTILE(4) OVER (ORDER BY provider_count) AS tier FROM healthcare_providers_income;
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gretelai_synthetic_text_to_sql
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