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CREATE TABLE renewable_energy_projects (id INT, name TEXT, budget FLOAT); INSERT INTO renewable_energy_projects (id, name, budget) VALUES (1, 'Solar Farm', 5000000.00), (2, 'Wind Farm', 7000000.00);
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Increase the budget of a specific renewable energy project by 10%
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WITH project_update AS (UPDATE renewable_energy_projects SET budget = budget * 1.10 WHERE id = 1) SELECT * FROM project_update;
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gretelai_synthetic_text_to_sql
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CREATE TABLE policies (policy_number INT, policy_type VARCHAR(50), coverage_amount INT, state VARCHAR(2));
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Insert a new policy with policy number 222333, policy type 'Commercial', state 'NY', and coverage amount 400000.
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INSERT INTO policies (policy_number, policy_type, coverage_amount, state) VALUES (222333, 'Commercial', 400000, 'NY');
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gretelai_synthetic_text_to_sql
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CREATE TABLE Budget(Year INT, Service VARCHAR(20), Budget FLOAT); INSERT INTO Budget VALUES(2020, 'Education', 15000000), (2020, 'Healthcare', 20000000), (2021, 'Education', 14000000), (2021, 'Healthcare', 21000000), (2020, 'Public Transport', 10000000), (2021, 'Public Transport', 10500000);
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List the names of the services for which the budget has decreased in the last 2 years.
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SELECT DISTINCT Service FROM Budget WHERE (Budget - LAG(Budget, 1) OVER (PARTITION BY Service ORDER BY Year)) < 0 AND Year IN (2020, 2021);
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gretelai_synthetic_text_to_sql
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CREATE TABLE security_incidents (id INT, country VARCHAR(50), incident_count INT, incident_date DATE); CREATE TABLE ip_addresses (id INT, incident_id INT, ip_address VARCHAR(50), PRIMARY KEY (id, incident_id)); INSERT INTO security_incidents (id, country, incident_count, incident_date) VALUES (1, 'USA', 25, '2022-01-01'), (2, 'Canada', 10, '2022-01-02'); INSERT INTO ip_addresses (id, incident_id, ip_address) VALUES (1, 1, '192.168.1.1'), (2, 1, '192.168.1.2');
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What is the total number of security incidents and unique IP addresses involved in those incidents for each country in the last month?
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SELECT security_incidents.country, SUM(security_incidents.incident_count) as total_incidents, COUNT(DISTINCT ip_addresses.ip_address) as unique_ips FROM security_incidents INNER JOIN ip_addresses ON security_incidents.id = ip_addresses.incident_id WHERE security_incidents.incident_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH) GROUP BY security_incidents.country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Faculty (FacultyID INT, Name VARCHAR(50), Department VARCHAR(50), Gender VARCHAR(10), Salary INT); INSERT INTO Faculty (FacultyID, Name, Department, Gender, Salary) VALUES (1, 'Alice', 'Biology', 'Female', 80000); INSERT INTO Faculty (FacultyID, Name, Department, Gender, Salary) VALUES (2, 'Bob', 'Biology', 'Male', 85000); CREATE TABLE ResearchGrants (GrantID INT, FacultyID INT, Amount INT); INSERT INTO ResearchGrants (GrantID, FacultyID, Amount) VALUES (1, 1, 90000); INSERT INTO ResearchGrants (GrantID, FacultyID, Amount) VALUES (2, 2, 95000);
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What is the total amount of research grants awarded to faculty members in the Biology department?
|
SELECT SUM(rg.Amount) FROM ResearchGrants rg INNER JOIN Faculty f ON rg.FacultyID = f.FacultyID WHERE f.Department = 'Biology';
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gretelai_synthetic_text_to_sql
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CREATE TABLE peacekeeping_operations (id INT, name TEXT, start_date DATE, end_date DATE); CREATE TABLE peacekeeping_personnel (id INT, operation_id INT, year INT, personnel INT); INSERT INTO peacekeeping_operations (id, name, start_date, end_date) VALUES (1, 'Operation1', '2010-01-01', '2015-01-01'), (2, 'Operation2', '2015-01-01', '2020-01-01'), (3, 'Operation3', '2020-01-01', '2022-01-01'); INSERT INTO peacekeeping_personnel (id, operation_id, year, personnel) VALUES (1, 1, 2010, 1000), (2, 1, 2011, 1200), (3, 2, 2016, 1500), (4, 3, 2021, 2000);
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What is the maximum number of peacekeeping personnel deployed for each peacekeeping operation?
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SELECT peacekeeping_operations.name, MAX(peacekeeping_personnel.personnel) FROM peacekeeping_operations JOIN peacekeeping_personnel ON peacekeeping_operations.id = peacekeeping_personnel.operation_id GROUP BY peacekeeping_operations.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE SpaceX_Projects (project_id INT, name VARCHAR(50), type VARCHAR(50), expenses DECIMAL(10,2));CREATE TABLE NASA_Research (research_id INT, name VARCHAR(50), type VARCHAR(50), expenses DECIMAL(10,2)); INSERT INTO SpaceX_Projects (project_id, name, type, expenses) VALUES (1, 'Starlink', 'Satellite Deployment', 3000000.00), (2, 'Starship', 'Space Exploration', 5000000.00); INSERT INTO NASA_Research (research_id, name, type, expenses) VALUES (1, 'Mars Rover', 'Space Exploration', 2000000.00), (2, 'ISS Upgrades', 'Space Station', 1500000.00);
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What are the total expenses for the SpaceX satellite deployment projects and the NASA space exploration research programs?
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SELECT SUM(expenses) FROM SpaceX_Projects WHERE type IN ('Satellite Deployment', 'Space Exploration') UNION ALL SELECT SUM(expenses) FROM NASA_Research WHERE type IN ('Space Exploration', 'Space Station');
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA IF NOT EXISTS rural_development;CREATE TABLE IF NOT EXISTS rural_development.economic_diversification (name VARCHAR(255), id INT);INSERT INTO rural_development.economic_diversification (name, id) VALUES ('renewable_energy', 1), ('handicraft_promotion', 2), ('local_food_production', 3), ('tourism_development', 4);
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What are the names of all economic diversification efforts in the 'rural_development' schema, excluding those related to 'tourism'?
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SELECT name FROM rural_development.economic_diversification WHERE name NOT LIKE '%tourism%';
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gretelai_synthetic_text_to_sql
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CREATE TABLE construction_spending (spending_id INT, amount FLOAT, state VARCHAR(50), spend_date DATE); INSERT INTO construction_spending (spending_id, amount, state, spend_date) VALUES (9, 120000, 'Florida', '2019-01-01'); INSERT INTO construction_spending (spending_id, amount, state, spend_date) VALUES (10, 180000, 'Florida', '2019-02-01');
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What was the total construction spending for each month in the state of Florida in 2019?
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SELECT EXTRACT(MONTH FROM spend_date) AS month, SUM(amount) AS total_spending FROM construction_spending WHERE state = 'Florida' AND YEAR(spend_date) = 2019 GROUP BY month;
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gretelai_synthetic_text_to_sql
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CREATE TABLE accounts (customer_id INT, account_type VARCHAR(20), balance DECIMAL(10, 2));
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Determine the number of customers who have an account balance greater than the 75th percentile for their account type.
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SELECT COUNT(DISTINCT customer_id) FROM accounts WHERE balance > PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY balance) OVER (PARTITION BY account_type);
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gretelai_synthetic_text_to_sql
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CREATE TABLE housing_policies (id INT, city VARCHAR(50), eco_friendly BOOLEAN); INSERT INTO housing_policies VALUES (1, 'NYC', TRUE); INSERT INTO housing_policies VALUES (2, 'LA', FALSE); INSERT INTO housing_policies VALUES (3, 'Chicago', TRUE);
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List all eco-friendly housing policies in cities with a population over 1 million
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SELECT city FROM housing_policies WHERE eco_friendly = TRUE INTERSECT SELECT city FROM cities WHERE population > 1000000;
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gretelai_synthetic_text_to_sql
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CREATE TABLE public_consultations (consultation_id INT, consultation_date DATE, consultation_city VARCHAR(50)); INSERT INTO public_consultations (consultation_id, consultation_date, consultation_city) VALUES (1, '2022-02-01', 'Nairobi');
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How many public consultations were held in Nairobi, Kenya between January 1, 2022 and March 31, 2022?
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SELECT COUNT(*) FROM public_consultations WHERE consultation_city = 'Nairobi' AND consultation_date BETWEEN '2022-01-01' AND '2022-03-31';
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gretelai_synthetic_text_to_sql
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CREATE TABLE soil_samples (id INT, region_id INT, organic_matter_kg FLOAT, date DATE);
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What was the total organic matter (in kg) in soil samples from each region in 2020?
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SELECT region_id, SUM(organic_matter_kg) FROM soil_samples WHERE YEAR(date) = 2020 GROUP BY region_id;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE CountryProjects (ProjectID INT, ProjectName VARCHAR(255), Country VARCHAR(255), Capacity FLOAT); INSERT INTO CountryProjects (ProjectID, ProjectName, Country, Capacity) VALUES (1, 'SolarFarm1', 'USA', 5000), (2, 'WindFarm2', 'Germany', 7000), (3, 'HydroPlant3', 'Brazil', 6000), (4, 'GeoThermal4', 'China', 8000), (5, 'Biomass5', 'Canada', 4000);
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What is the total installed capacity of renewable energy projects for each country, ranked by the total capacity?
|
SELECT Country, SUM(Capacity) AS Total_Capacity FROM CountryProjects GROUP BY Country ORDER BY Total_Capacity DESC;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Digital_Initiatives (id INT, museum VARCHAR(255), initiative VARCHAR(255)); INSERT INTO Digital_Initiatives (id, museum, initiative) VALUES (1, 'National Museum of Australia', 'Virtual Tour'), (2, 'British Museum', 'Online Collection'), (3, 'Metropolitan Museum of Art', 'Digital Archive'), (4, 'National Museum of China', 'Interactive Exhibit');
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List all unique digital initiatives by museums located in the Asia-Pacific region.
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SELECT DISTINCT initiative FROM Digital_Initiatives WHERE museum LIKE 'National Museum%';
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gretelai_synthetic_text_to_sql
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CREATE TABLE reporters (id INT, city VARCHAR(255), salary DECIMAL(10,2)); INSERT INTO reporters (id, city, salary) VALUES (1, 'NYC', 80000.00), (2, 'LA', 70000.00), (3, 'Chicago', 75000.00), (4, 'Miami', 72000.00), (5, 'Dallas', 78000.00)
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Find the top 5 cities with the highest avg salary in the 'reporters' table
|
SELECT city, AVG(salary) as avg_salary FROM reporters GROUP BY city ORDER BY avg_salary DESC LIMIT 5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE public_trips (trip_id INT, trip_date DATE, trip_city VARCHAR(50)); INSERT INTO public_trips (trip_id, trip_date, trip_city) VALUES (1, '2020-01-01', 'New York City'), (2, '2020-01-02', 'New York City');
|
What is the total number of public transportation trips in New York City for the year 2020?
|
SELECT SUM(trips) FROM (SELECT COUNT(*) AS trips FROM public_trips WHERE trip_city = 'New York City' AND trip_date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY EXTRACT(MONTH FROM trip_date)) AS subquery;
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gretelai_synthetic_text_to_sql
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CREATE TABLE employees (employee_id INT, department TEXT, salary DECIMAL); INSERT INTO employees (employee_id, department, salary) VALUES (1, 'Marketing', 50000.00), (2, 'IT', 60000.00), (3, 'HR', 55000.00);
|
What is the average salary of employees in each department, excluding any departments with fewer than 5 employees?
|
SELECT department, AVG(salary) FROM employees GROUP BY department HAVING COUNT(*) >= 5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Volunteers (VolunteerID INT, ProgramID INT, SignUpDate DATE); CREATE TABLE Programs (ProgramID INT, ProgramName VARCHAR(255));
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How many volunteers signed up in each program in 2020?
|
SELECT ProgramID, ProgramName, COUNT(VolunteerID) as NumVolunteers FROM Volunteers INNER JOIN Programs ON Volunteers.ProgramID = Programs.ProgramID WHERE YEAR(SignUpDate) = 2020 GROUP BY ProgramID, ProgramName;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Suppliers (SupplierID INT, SupplierName VARCHAR(50), Country VARCHAR(50), Certification VARCHAR(50), Material VARCHAR(50)); INSERT INTO Suppliers (SupplierID, SupplierName, Country, Certification, Material) VALUES (1, 'Supplier A', 'Vietnam', 'Fair Trade', 'Organic Cotton'), (2, 'Supplier B', 'Bangladesh', 'Fair Trade', 'Organic Cotton'), (3, 'Supplier C', 'Vietnam', 'Certified Organic', 'Organic Cotton'), (4, 'Supplier D', 'India', 'Fair Trade', 'Recycled Polyester'), (5, 'Supplier E', 'China', 'Certified Organic', 'Recycled Polyester'), (6, 'Supplier F', 'Indonesia', 'Fair Trade', 'Hemp'), (7, 'Supplier G', 'India', 'Certified Organic', 'Hemp');
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Find the top 3 countries with the highest number of sustainable material suppliers?
|
SELECT Country, COUNT(*) AS NumberOfSuppliers FROM Suppliers GROUP BY Country ORDER BY NumberOfSuppliers DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE hotels (hotel_id INT, name TEXT, country TEXT, continent TEXT, eco_friendly BOOLEAN); INSERT INTO hotels (hotel_id, name, country, continent, eco_friendly) VALUES (1, 'Green Hotel', 'Brazil', 'South America', true), (2, 'Eco Lodge', 'France', 'Europe', true), (3, 'Polluting Hotel', 'USA', 'North America', false), (4, 'Sustainable Hotel', 'Japan', 'Asia', true);
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What is the total number of eco-friendly hotels in each continent?
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SELECT continent, COUNT(*) FROM hotels WHERE eco_friendly = true GROUP BY continent;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE dams (id INT, name TEXT, construction_date DATE); INSERT INTO dams (id, name, construction_date) VALUES (1, 'Dam A', '1950-05-15'), (2, 'Dam B', '1965-08-27');
|
Show the name and construction date of the oldest dam
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SELECT name, MIN(construction_date) FROM dams;
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gretelai_synthetic_text_to_sql
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CREATE TABLE drugs (drug_id INT, drug_name TEXT); INSERT INTO drugs (drug_id, drug_name) VALUES (1001, 'Ibuprofen'), (1002, 'Paracetamol'), (1003, 'Aspirin'); CREATE TABLE sales (sale_id INT, drug_id INT, sale_date DATE, revenue FLOAT); INSERT INTO sales (sale_id, drug_id, sale_date, revenue) VALUES (1, 1001, '2020-07-05', 1800.0), (2, 1002, '2020-08-10', 2300.0), (3, 1003, '2020-09-15', 1400.0), (4, 1001, '2020-10-20', 1900.0), (5, 1002, '2020-11-25', 2400.0);
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What are the total sales for each drug in Q3 2020?
|
SELECT drug_name, SUM(revenue) as total_sales FROM sales JOIN drugs ON sales.drug_id = drugs.drug_id WHERE sale_date BETWEEN '2020-07-01' AND '2020-09-30' GROUP BY drug_name;
|
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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Update the endangered status of the Polar Bear to true
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UPDATE species SET endangered = true WHERE common_name = 'Polar Bear';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE deep_sea_expeditions (leader VARCHAR(255), country VARCHAR(255)); INSERT INTO deep_sea_expeditions (leader, country) VALUES ('Dr. Shinsuke Kawagucci', 'Japan'), ('Dr. Makoto Kuwahara', 'Japan');
|
List all deep-sea expeditions led by Japanese researchers.
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SELECT * FROM deep_sea_expeditions WHERE country = 'Japan';
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gretelai_synthetic_text_to_sql
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CREATE TABLE users (id INT, name VARCHAR(255), city VARCHAR(255)); CREATE TABLE posts (id INT, post_text TEXT, post_date DATETIME);
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List the top 5 cities where most users posted about vegan food in the past month.
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SELECT city, COUNT(*) AS post_count FROM posts p JOIN users u ON p.user_id = u.id WHERE p.post_text LIKE '%vegan food%' AND DATE(p.post_date) > DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH) GROUP BY city ORDER BY post_count DESC LIMIT 5;
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gretelai_synthetic_text_to_sql
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CREATE TABLE tickets (ticket_id INT, game_id INT, price INT, sale_date DATE); INSERT INTO tickets (ticket_id, game_id, price, sale_date) VALUES (1, 1, 50, '2021-09-01'), (2, 2, 60, '2021-10-01'); CREATE TABLE games (game_id INT, sport VARCHAR(20), city VARCHAR(20), game_date DATE); INSERT INTO games (game_id, sport, city, game_date) VALUES (1, 'Basketball', 'Los Angeles', '2021-09-01'), (2, 'Basketball', 'Chicago', '2021-10-01');
|
How many tickets were sold for basketball games in Los Angeles and Chicago in the last quarter?
|
SELECT COUNT(tickets.ticket_id) FROM tickets INNER JOIN games ON tickets.game_id = games.game_id WHERE games.sport = 'Basketball' AND (games.city = 'Los Angeles' OR games.city = 'Chicago') AND tickets.sale_date >= DATEADD(quarter, -1, GETDATE());
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gretelai_synthetic_text_to_sql
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CREATE TABLE CommunityHealthWorkers (WorkerID INT, Age INT, GenderIdentity VARCHAR(255)); INSERT INTO CommunityHealthWorkers (WorkerID, Age, GenderIdentity) VALUES (1, 35, 'Transgender Woman'); INSERT INTO CommunityHealthWorkers (WorkerID, Age, GenderIdentity) VALUES (2, 42, 'Cisgender Man'); INSERT INTO CommunityHealthWorkers (WorkerID, Age, GenderIdentity) VALUES (3, 50, 'Non-binary'); INSERT INTO CommunityHealthWorkers (WorkerID, Age, GenderIdentity) VALUES (4, 30, 'Genderqueer');
|
What is the average age of community health workers by their gender identity?
|
SELECT GenderIdentity, AVG(Age) FROM CommunityHealthWorkers GROUP BY GenderIdentity;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE satellites (id INT, name VARCHAR(50), launch_status VARCHAR(50), manufacturer VARCHAR(50), launch_date DATE);
|
Find the number of successful satellite launches by company ABC
|
SELECT COUNT(*) FROM satellites WHERE launch_status = 'Success' AND manufacturer = 'ABC';
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gretelai_synthetic_text_to_sql
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CREATE TABLE wind_farms (name VARCHAR(50), location VARCHAR(50), capacity FLOAT, production_mwh FLOAT); INSERT INTO wind_farms (name, location, capacity, production_mwh) VALUES ('Farm I', 'Texas', 300, 5000), ('Farm J', 'Oklahoma', 250, 4500), ('Farm K', 'Kansas', 350, 5200), ('Farm L', 'Iowa', 280, 4800);
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What is the monthly energy production (in MWh) for each wind farm, ranked by the highest production?
|
SELECT name, production_mwh, ROW_NUMBER() OVER (ORDER BY production_mwh DESC) as rank FROM wind_farms;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE mental_health_parity_violations (id INT, state VARCHAR(50), violation_count INT); INSERT INTO mental_health_parity_violations (id, state, violation_count) VALUES (1, 'California', 10), (2, 'Florida', 5), (3, 'Illinois', 15);
|
Identify the number of mental health parity violations by state?
|
SELECT state, SUM(violation_count) as total_violations FROM mental_health_parity_violations GROUP BY state;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE providers (provider_id INT, name VARCHAR(50), zip_code VARCHAR(10));
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Update the "providers" table to add a new column for "email" and update the "name" column to "full_name"
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ALTER TABLE providers ADD COLUMN email VARCHAR(50); UPDATE providers SET full_name = name;
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gretelai_synthetic_text_to_sql
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CREATE VIEW urban_neighborhoods AS SELECT * FROM properties WHERE neighborhood_type = 'urban';
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What is the average walkability score for properties in the urban_neighborhoods view?
|
SELECT AVG(walkability_score) FROM urban_neighborhoods;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Flu_Shots (ID INT, Quantity INT, Location VARCHAR(50), Year INT); INSERT INTO Flu_Shots (ID, Quantity, Location, Year) VALUES (1, 500, 'Los Angeles County', 2019); INSERT INTO Flu_Shots (ID, Quantity, Location, Year) VALUES (2, 300, 'Los Angeles County', 2019);
|
What is the total number of flu shots administered in Los Angeles County in 2019?
|
SELECT SUM(Quantity) FROM Flu_Shots WHERE Location = 'Los Angeles County' AND Year = 2019;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Spacecraft (SpacecraftID INT, Name VARCHAR(50), ManufacturingCountry VARCHAR(50)); INSERT INTO Spacecraft (SpacecraftID, Name, ManufacturingCountry) VALUES (1, 'Space Shuttle Atlantis', 'USA'); INSERT INTO Spacecraft (SpacecraftID, Name, ManufacturingCountry) VALUES (2, 'Space Shuttle Discovery', 'USA'); INSERT INTO Spacecraft (SpacecraftID, Name, ManufacturingCountry) VALUES (3, 'Space Shuttle Endeavour', 'USA'); INSERT INTO Spacecraft (SpacecraftID, Name, ManufacturingCountry) VALUES (4, 'Soyuz TMA-14M', 'Russia'); INSERT INTO Spacecraft (SpacecraftID, Name, ManufacturingCountry) VALUES (5, 'Shenzhou 11', 'China');
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Find the top 3 countries with the highest number of spacecraft manufactured, along with the number of spacecraft manufactured by each.
|
SELECT ManufacturingCountry, COUNT(*) AS SpacecraftCount FROM Spacecraft GROUP BY ManufacturingCountry ORDER BY SpacecraftCount DESC LIMIT 3;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE risk (id INT PRIMARY KEY, investment_id INT, type VARCHAR(255), level VARCHAR(255)); INSERT INTO risk (id, investment_id, type, level) VALUES (3, 3, 'Operational Risk', 'High'); CREATE TABLE investment (id INT PRIMARY KEY, organization_id INT, amount FLOAT, date DATE); INSERT INTO investment (id, organization_id, amount, date) VALUES (3, 3, 12000, '2020-05-15'); CREATE TABLE organization (id INT PRIMARY KEY, name VARCHAR(255), sector VARCHAR(255), location VARCHAR(255)); INSERT INTO organization (id, name, sector, location) VALUES (3, 'Code to Inspire', 'Nonprofit', 'New York, NY');
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What is the total amount invested in organizations located in 'New York, NY' with a 'High' operational risk level?
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SELECT investment.amount FROM investment INNER JOIN organization ON investment.organization_id = organization.id INNER JOIN risk ON investment.id = risk.investment_id WHERE organization.location = 'New York, NY' AND risk.type = 'Operational Risk' AND risk.level = 'High';
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gretelai_synthetic_text_to_sql
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CREATE TABLE vulnerabilities (id INT, severity FLOAT); INSERT INTO vulnerabilities (id, severity) VALUES (1, 7.5);
|
What is the minimum severity of vulnerabilities found in the last week?
|
SELECT MIN(severity) FROM vulnerabilities WHERE vulnerabilities.id IN (SELECT MAX(id) FROM vulnerabilities WHERE incident_date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 WEEK));
|
gretelai_synthetic_text_to_sql
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CREATE TABLE artworks (id INT, art_name VARCHAR(50), style VARCHAR(50), artist_name VARCHAR(50)); CREATE TABLE sales (id INT, artwork_id INT, price DECIMAL(10, 2));
|
List all abstract expressionist artists and their highest-selling artwork.
|
SELECT a.artist_name, MAX(s.price) as highest_selling_price FROM artworks a JOIN sales s ON a.id = s.artwork_id WHERE a.style = 'Abstract Expressionism' GROUP BY a.artist_name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE energy_production (source VARCHAR(255), month INT, year INT, production FLOAT);
|
What is the average monthly energy production (in MWh) for each renewable energy source in 2019?
|
SELECT source, AVG(production) FROM energy_production WHERE year = 2019 GROUP BY source, month;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE performing_arts_events (id INT, event_name VARCHAR(255), event_date DATE, attendee_gender VARCHAR(255));
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Which performing arts events had the highest and lowest attendance by gender?
|
SELECT event_name, attendee_gender, COUNT(attendee_gender) as attendance FROM performing_arts_events GROUP BY event_name, attendee_gender ORDER BY attendance DESC, event_name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE cases (case_id INT, case_number VARCHAR(50), client_name VARCHAR(50), attorney_id INT);
|
Count the number of cases in 'cases' table for each attorney
|
SELECT attorney_id, COUNT(*) FROM cases GROUP BY attorney_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE nuclear_plants (country VARCHAR(50), operational BOOLEAN, year INT); INSERT INTO nuclear_plants (country, operational, year) VALUES ('France', true, 2020), ('Russia', true, 2020), ('United Kingdom', true, 2020), ('Germany', false, 2020);
|
List the number of nuclear power plants in France, Russia, and the United Kingdom, as of 2020.
|
SELECT country, COUNT(*) FROM nuclear_plants WHERE country IN ('France', 'Russia', 'United Kingdom') AND operational = true GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE CriminalJustice (case_id INT, case_status VARCHAR(10)); INSERT INTO CriminalJustice (case_id, case_status) VALUES (1, 'pending'), (2, 'closed'), (3, 'pending'), (4, 'in_progress'), (5, 'closed'), (6, 'in_progress');
|
Find the total number of cases in the 'CriminalJustice' table and the number of cases with 'case_status' of 'pending' or 'in_progress'
|
SELECT COUNT(*) AS total_cases, SUM(CASE WHEN case_status IN ('pending', 'in_progress') THEN 1 ELSE 0 END) AS pending_or_in_progress_cases FROM CriminalJustice;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE water_usage (id INT, usage FLOAT, purpose VARCHAR(20), date DATE); INSERT INTO water_usage (id, usage, purpose, date) VALUES (1, 50, 'residential', '2021-09-01'); INSERT INTO water_usage (id, usage, purpose, date) VALUES (2, 60, 'residential', '2021-09-02');
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Determine the average daily water usage for 'residential' purposes in 'September 2021' from the 'water_usage' table
|
SELECT AVG(usage) FROM (SELECT usage FROM water_usage WHERE purpose = 'residential' AND date BETWEEN '2021-09-01' AND '2021-09-30' GROUP BY date) as daily_usage;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Athletes (athlete_id INT, athlete_name VARCHAR(255), age INT, team VARCHAR(255)); CREATE VIEW WellbeingPrograms AS SELECT athlete_id, team FROM Programs WHERE program_type IN ('NHL', 'NBA');
|
Who are the top 2 oldest athletes in 'NHL' and 'NBA' wellbeing programs?
|
SELECT Athletes.athlete_name, Athletes.age FROM Athletes INNER JOIN WellbeingPrograms ON Athletes.athlete_id = WellbeingPrograms.athlete_id WHERE (Athletes.team = 'NHL' OR Athletes.team = 'NBA') GROUP BY Athletes.athlete_name ORDER BY Athletes.age DESC LIMIT 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE vendors(vendor_id INT, vendor_name TEXT, circular_supply_chain BOOLEAN); INSERT INTO vendors(vendor_id, vendor_name, circular_supply_chain) VALUES (1, 'VendorA', TRUE), (2, 'VendorB', FALSE), (3, 'VendorC', TRUE);
|
What is the maximum price of a product sold by vendors with a circular supply chain?
|
SELECT MAX(transactions.price) FROM transactions JOIN vendors ON transactions.vendor_id = vendors.vendor_id WHERE vendors.circular_supply_chain = TRUE;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE impact_projects (id INT, focus_area VARCHAR(20), investment_amount FLOAT); INSERT INTO impact_projects (id, focus_area, investment_amount) VALUES (1, 'gender_equality', 45000), (2, 'gender_equality', 52000), (3, 'gender_equality', 39000);
|
What is the maximum investment amount for 'gender_equality' focused projects?
|
SELECT MAX(investment_amount) FROM impact_projects WHERE focus_area = 'gender_equality';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE financial_institutions (name TEXT, region TEXT); INSERT INTO financial_institutions (name, region) VALUES ('Bank of America', 'USA'), ('Barclays Bank', 'UK');
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Insert a new financial institution 'Green Finance Corporation' in the 'Canada' region.
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INSERT INTO financial_institutions (name, region) VALUES ('Green Finance Corporation', 'Canada');
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gretelai_synthetic_text_to_sql
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CREATE TABLE healthcare_providers (id INT, name VARCHAR(50), gender VARCHAR(10), location VARCHAR(50)); INSERT INTO healthcare_providers (id, name, gender, location) VALUES (1, 'Dr. Smith', 'Female', 'Rural India'); INSERT INTO healthcare_providers (id, name, gender, location) VALUES (2, 'Dr. Johnson', 'Male', 'Urban New York');
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What is the percentage of female healthcare providers in rural India?
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SELECT ROUND(100.0 * COUNT(*) / (SELECT COUNT(*) FROM healthcare_providers WHERE location = 'Rural India'), 2) FROM healthcare_providers WHERE location = 'Rural India' AND gender = 'Female';
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gretelai_synthetic_text_to_sql
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CREATE TABLE vaccinations (id INT, state VARCHAR(2), vaccine VARCHAR(50), rate DECIMAL(5,2)); INSERT INTO vaccinations (id, state, vaccine, rate) VALUES (1, 'NY', 'Measles', 0.95), (2, 'CA', 'Measles', 0.96), (3, 'TX', 'Measles', 0.92), (4, 'FL', 'Measles', 0.94), (5, 'AK', 0.98), (6, 'MS', 0.91);
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Which states have the highest and lowest vaccination rates for measles?
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SELECT state, rate FROM vaccinations WHERE vaccine = 'Measles' ORDER BY rate DESC, state ASC LIMIT 1; SELECT state, rate FROM vaccinations WHERE vaccine = 'Measles' ORDER BY rate ASC, state ASC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Songs (song_id INT, title TEXT, genre TEXT, release_date DATE, price DECIMAL(5,2));
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Update the price of jazz songs released before 2000 to $1.99
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UPDATE Songs SET price = 1.99 WHERE genre = 'jazz' AND release_date < '2000-01-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE beauty_products_italy (product_cruelty_free BOOLEAN, sales_quantity INT); INSERT INTO beauty_products_italy (product_cruelty_free, sales_quantity) VALUES (TRUE, 800), (FALSE, 1200);
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What is the percentage of cruelty-free beauty products in the overall beauty product sales in Italy?
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SELECT (SUM(CASE WHEN product_cruelty_free = TRUE THEN sales_quantity ELSE 0 END) / SUM(sales_quantity)) * 100 AS cruelty_free_percentage FROM beauty_products_italy;
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gretelai_synthetic_text_to_sql
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CREATE TABLE program_impact (program_id INT, country VARCHAR(50), impact INT); INSERT INTO program_impact VALUES (1, 'India', 100), (2, 'Brazil', 150), (3, 'USA', 200), (4, 'India', 120), (5, 'Brazil', 180);
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Find the top 2 countries with the most program impact in 2022?
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SELECT country, SUM(impact) as total_impact FROM program_impact WHERE program_id IN (SELECT program_id FROM program_impact WHERE program_id IN (SELECT program_id FROM program_impact WHERE year = 2022 GROUP BY country HAVING COUNT(*) > 1) GROUP BY country HAVING COUNT(*) > 1) GROUP BY country ORDER BY total_impact DESC LIMIT 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE mining_operations (id INT, location VARCHAR(50), operation_type VARCHAR(50), monthly_co2_emission INT); INSERT INTO mining_operations (id, location, operation_type, monthly_co2_emission) VALUES (1, 'USA', 'Coal', 12000), (2, 'China', 'Coal', 18000), (3, 'Canada', 'Gold', 8000);
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What is the total CO2 emission from coal mining operations in the USA and China?
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SELECT SUM(CASE WHEN operation_type = 'Coal' AND location IN ('USA', 'China') THEN monthly_co2_emission ELSE 0 END) as total_coal_emission FROM mining_operations;
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gretelai_synthetic_text_to_sql
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CREATE TABLE virtual_tourism_extended_2 (country TEXT, revenue FLOAT, date DATE); INSERT INTO virtual_tourism_extended_2 (country, revenue, date) VALUES ('Spain', 25000.0, '2022-03-01'), ('Spain', 28000.0, '2022-04-01'), ('Italy', 18000.0, '2022-03-01'), ('Italy', 20000.0, '2022-04-01'), ('Germany', 30000.0, '2022-02-01'), ('Germany', 35000.0, '2022-03-01'), ('France', 40000.0, '2022-01-01'), ('France', 42000.0, '2022-02-01'), ('Japan', 50000.0, '2022-01-01'), ('Japan', 52000.0, '2022-02-01'), ('South Korea', 60000.0, '2022-02-01'), ('South Korea', 62000.0, '2022-03-01');
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Virtual tourism revenue by quarter for each country?
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SELECT country, DATE_TRUNC('quarter', date) AS quarter, SUM(revenue) FROM virtual_tourism_extended_2 GROUP BY country, quarter;
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gretelai_synthetic_text_to_sql
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CREATE TABLE future_trends (country VARCHAR(50), year INT, projected_visitors INT); INSERT INTO future_trends (country, year, projected_visitors) VALUES ('France', 2025, 25000000), ('Spain', 2025, 20000000), ('Italy', 2025, 18000000), ('Japan', 2025, 16000000), ('Germany', 2025, 15000000);
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List the top 3 countries with the most tourists in 2025 based on current trends.
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SELECT country, projected_visitors FROM future_trends WHERE year = 2025 ORDER BY projected_visitors DESC LIMIT 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Loans (Id INT, Lender VARCHAR(20), Location VARCHAR(20), LoanType VARCHAR(20), LoanAmount DECIMAL(10,2), LoanYear INT); INSERT INTO Loans (Id, Lender, Location, LoanType, LoanAmount, LoanYear) VALUES (1, 'LenderA', 'Asia', 'Socially Responsible', 500.00, 2020), (2, 'LenderB', 'Asia', 'Socially Responsible', 700.00, 2020), (3, 'LenderC', 'Asia', 'Socially Responsible', 600.00, 2021);
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What is the average loan amount for socially responsible lenders in Asia, grouped by year?
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SELECT AVG(LoanAmount) AS Avg_Loan_Amount, LoanYear FROM Loans WHERE LoanType = 'Socially Responsible' AND Location = 'Asia' GROUP BY LoanYear;
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gretelai_synthetic_text_to_sql
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CREATE TABLE smart_city_initiatives (initiative_id INT, initiative_name VARCHAR(50), location VARCHAR(50), carbon_offsets FLOAT); INSERT INTO smart_city_initiatives (initiative_id, initiative_name, location, carbon_offsets) VALUES (1, 'Smart Grid 1', 'CityC', 1000.0), (2, 'Smart Lighting 1', 'CityD', 500.0), (3, 'Smart Waste Management 1', 'CityC', 1500.0);
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What is the number of smart city initiatives and their average carbon offsets by location?
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SELECT location, COUNT(*), AVG(carbon_offsets) FROM smart_city_initiatives GROUP BY location;
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gretelai_synthetic_text_to_sql
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cars (id, make, model, year, fuel_type)
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Delete records of cars with no fuel type specified in the cars table.
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DELETE FROM cars WHERE cars.fuel_type IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE production (country VARCHAR(255), element VARCHAR(255), quantity INT, year INT); INSERT INTO production (country, element, quantity, year) VALUES ('China', 'Europium', 2000, 2018), ('China', 'Europium', 2500, 2018), ('United States', 'Europium', 1000, 2018), ('United States', 'Europium', 1200, 2018);
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What is the average production of Europium per country in 2018?
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SELECT country, AVG(quantity) as avg_production FROM production WHERE element = 'Europium' AND year = 2018 GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE IF NOT EXISTS carbon_offset_initiatives ( initiative_id INT, initiative_name VARCHAR(255), co2_offset FLOAT, PRIMARY KEY (initiative_id)); INSERT INTO carbon_offset_initiatives (initiative_id, initiative_name, co2_offset) VALUES (1, 'Tree Planting', 50), (2, 'Solar Power Installation', 100), (3, 'Wind Farm Development', 150);
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What is the average CO2 offset for each carbon offset initiative in the carbon_offset_initiatives table?
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SELECT AVG(co2_offset) FROM carbon_offset_initiatives;
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales_by_region (region VARCHAR(20), quarter VARCHAR(2), year INT, sales_amount FLOAT); INSERT INTO sales_by_region (region, quarter, year, sales_amount) VALUES ('Europe', 'Q3', 2022, 90000.0), ('Asia', 'Q3', 2022, 85000.0), ('Africa', 'Q3', 2022, 95000.0);
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Which region had the highest sales in Q3 2022?
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SELECT region, MAX(sales_amount) FROM sales_by_region WHERE quarter = 'Q3' AND year = 2022 GROUP BY region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE export_info (id INT, element TEXT, location TEXT, company TEXT, date DATE, quantity INT, revenue INT); INSERT INTO export_info (id, element, location, company, date, quantity, revenue) VALUES (1, 'dysprosium', 'Africa', 'Company A', '2019-01-01', 500, 2000000000), (2, 'dysprosium', 'Africa', 'Company B', '2020-01-01', 600, 3000000000);
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What is the total amount of dysprosium exported to Africa in the past 3 years by companies with a revenue greater than $1 billion?
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SELECT SUM(quantity) FROM export_info WHERE element = 'dysprosium' AND location = 'Africa' AND company IN (SELECT company FROM export_info WHERE revenue > 1000000000) AND extract(year from date) >= 2019;
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gretelai_synthetic_text_to_sql
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CREATE TABLE MentalHealthParity (Region VARCHAR(255), ParityIndexScore INT); INSERT INTO MentalHealthParity (Region, ParityIndexScore) VALUES ('North', 80), ('South', 85), ('East', 70), ('West', 90);
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List the top 3 regions with the highest mental health parity index scores, along with their corresponding scores.
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SELECT Region, ParityIndexScore FROM (SELECT Region, ParityIndexScore, ROW_NUMBER() OVER (ORDER BY ParityIndexScore DESC) as Rank FROM MentalHealthParity) as RankedData WHERE Rank <= 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AutoShows (name VARCHAR(20), country VARCHAR(10), year INT); INSERT INTO AutoShows (name, country, year) VALUES ('Tokyo Auto Salon', 'Japan', 2023);
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List the auto show events happening in Japan in 2023.
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SELECT name FROM AutoShows WHERE country = 'Japan' AND year = 2023;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ContractValues (company TEXT, contract_date DATE, contract_value FLOAT); INSERT INTO ContractValues (company, contract_date, contract_value) VALUES ('Contractor D', '2022-03-01', 3000000), ('Contractor E', '2022-07-15', 4000000), ('Contractor F', '2022-11-30', 2500000);
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What is the maximum contract value awarded to a defense contractor in Texas in 2022?
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SELECT MAX(contract_value) FROM ContractValues WHERE company LIKE '%defense%' AND contract_date BETWEEN '2022-01-01' AND '2022-12-31' AND state = 'Texas';
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gretelai_synthetic_text_to_sql
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CREATE TABLE beneficiaries (program VARCHAR(10), gender VARCHAR(6), date DATE); INSERT INTO beneficiaries (program, gender, date) VALUES ('ProgA', 'Female', '2020-01-01'), ('ProgA', 'Male', '2020-01-05'), ('ProgB', 'Female', '2020-03-02');
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How many female and male beneficiaries were served by each program in 2020?
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SELECT program, gender, COUNT(*) FROM beneficiaries WHERE YEAR(date) = 2020 GROUP BY program, gender;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Performances (id INT, name TEXT, year INT, location TEXT, type TEXT); INSERT INTO Performances (id, name, year, location, type) VALUES (1, 'Performance1', 2015, 'Japan', 'dance'), (2, 'Performance2', 2005, 'USA', 'theater'), (3, 'Performance3', 2018, 'Australia', 'music');
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How many performances were held in Asia or Oceania between 2010 and 2020?
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SELECT COUNT(*) FROM Performances WHERE location IN ('Asia', 'Oceania') AND year BETWEEN 2010 AND 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Feedback (Date DATE, Region VARCHAR(50), Service VARCHAR(50), Comment TEXT); INSERT INTO Feedback (Date, Region, Service, Comment) VALUES ('2021-01-01', 'Central', 'Healthcare', 'Great service'), ('2021-01-02', 'Central', 'Healthcare', 'Poor service'), ('2021-02-01', 'North', 'Education', 'Excellent education'), ('2022-03-01', 'East', 'Housing', 'Adequate conditions');
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What is the total number of citizen feedback records received for the 'Housing' service?
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SELECT COUNT(*) FROM Feedback WHERE Service = 'Housing';
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gretelai_synthetic_text_to_sql
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CREATE TABLE defense_spending (country VARCHAR(50), continent VARCHAR(50), amount DECIMAL(10,2)); INSERT INTO defense_spending (country, continent, amount) VALUES ('USA', 'North America', 73200000000), ('China', 'Asia', 26100000000), ('Russia', 'Europe', 61000000000), ('Japan', 'Asia', 50500000000), ('India', 'Asia', 57000000000);
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What is the total defense spending for each continent?
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SELECT continent, SUM(amount) as total_defense_spending FROM defense_spending GROUP BY continent;
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gretelai_synthetic_text_to_sql
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CREATE TABLE users (id INT, username VARCHAR(255), followers INT, follow_date DATE);
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Get the number of new followers for each user in the last month, pivoted by day of the week in the "users" table
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SELECT username, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Monday' THEN 1 ELSE 0 END) AS Monday, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Tuesday' THEN 1 ELSE 0 END) AS Tuesday, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Wednesday' THEN 1 ELSE 0 END) AS Wednesday, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Thursday' THEN 1 ELSE 0 END) AS Thursday, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Friday' THEN 1 ELSE 0 END) AS Friday, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Saturday' THEN 1 ELSE 0 END) AS Saturday, SUM(CASE WHEN DATE_FORMAT(follow_date, '%W') = 'Sunday' THEN 1 ELSE 0 END) AS Sunday FROM users WHERE follow_date >= DATE_SUB(CURDATE(), INTERVAL 1 MONTH) GROUP BY username;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Humanitarian_Assistance_Missions (id INT, organization VARCHAR(50), year INT, missions INT);
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What is the average number of humanitarian assistance missions carried out by each organization in the last 2 years?
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SELECT organization, AVG(missions) as avg_missions FROM Humanitarian_Assistance_Missions WHERE year BETWEEN (YEAR(CURRENT_DATE) - 2) AND YEAR(CURRENT_DATE) GROUP BY organization;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Cases (id INT, case_number INT, opened_date DATE);
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How many cases were opened for each month in the year 2020?
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SELECT MONTH(opened_date) AS Month, COUNT(*) AS NumberOfCases FROM Cases WHERE YEAR(opened_date) = 2020 GROUP BY Month;
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gretelai_synthetic_text_to_sql
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CREATE TABLE VolunteerDonors (VolunteerID INT, VolunteerName TEXT, DonationAmount DECIMAL(10,2), DonationDate DATE); INSERT INTO VolunteerDonors (VolunteerID, VolunteerName, DonationAmount, DonationDate) VALUES (1, 'Ravi Patel', 1200.00, '2022-06-01');
|
Show the details of volunteers who have donated more than $1000?
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SELECT * FROM VolunteerDonors WHERE DonationAmount > 1000;
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gretelai_synthetic_text_to_sql
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CREATE VIEW JobTitlesDepartments AS SELECT JobTitle, Department FROM TalentAcquisition;
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Display the view JobTitlesDepartments
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SELECT * FROM JobTitlesDepartments;
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gretelai_synthetic_text_to_sql
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CREATE TABLE diversity (id INT, company_id INT, founder_race VARCHAR(255)); INSERT INTO diversity SELECT 1, 1, 'Hispanic'; INSERT INTO diversity SELECT 2, 2, 'Asian'; INSERT INTO diversity SELECT 3, 3, 'Black'; INSERT INTO companies (id, industry, founding_date) SELECT 2, 'Finance', '2005-01-01'; INSERT INTO companies (id, industry, founding_date) SELECT 3, 'Retail', '2008-01-01'; INSERT INTO companies (id, industry, founding_date) SELECT 4, 'IT', '2012-01-01'; INSERT INTO funding (company_id, amount) SELECT 2, 1000000; INSERT INTO funding (company_id, amount) SELECT 3, 750000; INSERT INTO funding (company_id, amount) SELECT 4, 1250000;
|
List the number of unique industries and total funding for companies founded by people of color before 2010
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SELECT diversity.founder_race, COUNT(DISTINCT companies.industry) AS unique_industries, SUM(funding.amount) AS total_funding FROM diversity JOIN companies ON diversity.company_id = companies.id JOIN funding ON companies.id = funding.company_id WHERE companies.founding_date < '2010-01-01' AND diversity.founder_race IN ('Hispanic', 'Asian', 'Black') GROUP BY diversity.founder_race;
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gretelai_synthetic_text_to_sql
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CREATE TABLE malware_activity (id INT, ip_address VARCHAR(15), malware_type VARCHAR(255), region VARCHAR(100), last_seen DATE); INSERT INTO malware_activity (id, ip_address, malware_type, region, last_seen) VALUES (1, '192.168.1.1', 'ransomware', 'Asia-Pacific', '2021-11-01'), (2, '10.0.0.1', 'virut', 'North America', '2021-12-05'), (3, '192.168.1.1', 'ransomware', 'Asia-Pacific', '2021-12-12'), (4, '10.0.0.2', 'wannacry', 'South America', '2021-12-08');
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Find the number of unique IP addresses associated with malware activity in the 'South America' region in the past month.
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SELECT COUNT(DISTINCT ip_address) FROM malware_activity WHERE region = 'South America' AND last_seen >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Brands (Brand_ID INT PRIMARY KEY, Brand_Name TEXT); CREATE TABLE Certifications (Certification_ID INT PRIMARY KEY, Certification_Name TEXT, Brand_ID INT); INSERT INTO Brands (Brand_ID, Brand_Name) VALUES (1, 'Ethical Beauty'), (2, 'Pure Cosmetics'), (3, 'Green Earth'), (4, 'Eco Living'), (5, 'Sustainable Solutions'); INSERT INTO Certifications (Certification_ID, Certification_Name, Brand_ID) VALUES (1, 'Leaping Bunny', 1), (2, 'Cruelty Free International', 1), (3, 'People for the Ethical Treatment of Animals (PETA)', 2), (4, 'Leaping Bunny', 2), (5, 'Cruelty Free International', 3), (6, 'Leaping Bunny', 3), (7, 'People for the Ethical Treatment of Animals (PETA)', 4), (8, 'Leaping Bunny', 4), (9, 'Cruelty Free International', 5), (10, 'People for the Ethical Treatment of Animals (PETA)', 5);
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Which brands have received the most cruelty-free certifications?
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SELECT b.Brand_Name, COUNT(c.Certification_ID) AS Cruelty_Free_Certifications_Count FROM Brands b JOIN Certifications c ON b.Brand_ID = c.Brand_ID GROUP BY b.Brand_ID;
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gretelai_synthetic_text_to_sql
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CREATE TABLE bali_tourism (id INT, year INT, revenue INT); INSERT INTO bali_tourism (id, year, revenue) VALUES (1, 2019, 10000000), (2, 2020, 5000000);
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What is the total revenue generated by tourism in Bali in 2020?
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SELECT SUM(revenue) FROM bali_tourism WHERE year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE companies (id INT, name TEXT); CREATE TABLE fundings (id INT, company_id INT, round TEXT); INSERT INTO companies (id, name) VALUES (1, 'Acme Inc'), (2, 'Zebra Corp'), (3, 'Dino Tech'), (4, 'Elephant Inc'); INSERT INTO fundings (id, company_id, round) VALUES (1, 1, 'Seed'), (2, 1, 'Series A'), (3, 2, 'Seed'), (4, 2, 'Series A');
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List the companies that have not received any funding.
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SELECT companies.name FROM companies LEFT JOIN fundings ON companies.id = fundings.company_id WHERE fundings.id IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE monthly_donations_category (id INT, donor_category VARCHAR(50), donor_name VARCHAR(50), donation_amount DECIMAL(10,2), donation_date DATE); INSERT INTO monthly_donations_category (id, donor_category, donor_name, donation_amount, donation_date) VALUES (1, 'Regular', 'John Doe', 50, '2022-01-01'), (2, 'One-time', 'Jane Smith', 75, '2022-01-15'), (3, 'Regular', 'John Doe', 60, '2022-02-01');
|
What is the average monthly donation per donor category?
|
SELECT donor_category, AVG(donation_amount) as avg_monthly_donation FROM monthly_donations_category GROUP BY donor_category;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Sales (sale_id INT PRIMARY KEY, sale_date DATE, item_sold VARCHAR(255), quantity INT, sale_price DECIMAL(5,2));
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What is the average revenue per day for the month of January for a given year?
|
SELECT AVG(SUM(quantity * sale_price)) FROM Sales WHERE sale_date BETWEEN '2022-01-01' AND '2022-01-31';
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gretelai_synthetic_text_to_sql
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CREATE TABLE researchers (id INT, name VARCHAR(50), project VARCHAR(50)); INSERT INTO researchers (id, name, project) VALUES (1, 'Alice', 'gene sequencing'), (2, 'Bob', 'biosensor development'), (3, 'Charlie', 'gene sequencing');
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Insert a new row with id '4', name 'Dana', project 'protein folding' into the 'researchers' table.
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INSERT INTO researchers (id, name, project) VALUES (4, 'Dana', 'protein folding');
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gretelai_synthetic_text_to_sql
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CREATE TABLE Vessels_4 (id INT, name VARCHAR(255), region VARCHAR(255), year INT); INSERT INTO Vessels_4 (id, name, region, year) VALUES (1, 'African Wave', 'Africa', 2021); INSERT INTO Vessels_4 (id, name, region, year) VALUES (2, 'Ocean Splash', 'Africa', 2022); INSERT INTO Vessels_4 (id, name, region, year) VALUES (3, 'Marine Journey', 'Africa', 2021); INSERT INTO Vessels_4 (id, name, region, year) VALUES (4, 'Sea Explorer', 'Africa', 2022);
|
List all vessels inspected in 'Africa' during 2021 and 2022.
|
SELECT name FROM Vessels_4 WHERE region = 'Africa' AND year IN (2021, 2022);
|
gretelai_synthetic_text_to_sql
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CREATE TABLE programs (name VARCHAR(25), budget INT, funding_source VARCHAR(15));
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Insert new records of art programs for underrepresented communities, each with a budget of 10000 and a public funding source.
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INSERT INTO programs (name, budget, funding_source) VALUES ('Art for Indigenous Youth', 10000, 'public'), ('Art for Disability Community', 10000, 'public');
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gretelai_synthetic_text_to_sql
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CREATE TABLE asia_lang_progs (id INT, org_name TEXT, year INT, num_progs INT); INSERT INTO asia_lang_progs (id, org_name, year, num_progs) VALUES (1, 'Shanghai Language Institute', 2015, 100), (2, 'Tokyo Language School', 2016, 120), (3, 'Beijing Language University', 2017, 150), (4, 'New Delhi Language Academy', 2018, 180), (5, 'Seoul Language Institute', 2019, 210), (6, 'Hong Kong Language School', 2020, 240);
|
What is the percentage change in the number of language preservation programs offered in Asia between 2015 and 2020?
|
SELECT (SUM(CASE WHEN year = 2020 THEN num_progs ELSE 0 END) - SUM(CASE WHEN year = 2015 THEN num_progs ELSE 0 END)) * 100.0 / SUM(CASE WHEN year = 2015 THEN num_progs ELSE 0 END) as pct_change FROM asia_lang_progs WHERE org_name IN ('Shanghai Language Institute', 'Tokyo Language School', 'Beijing Language University', 'New Delhi Language Academy', 'Seoul Language Institute', 'Hong Kong Language School') AND year IN (2015, 2020);
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gretelai_synthetic_text_to_sql
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CREATE TABLE users (user_id INT, user_country VARCHAR(255)); CREATE TABLE streams (stream_id INT, song_id INT, user_id INT, stream_date DATE);
|
Find the number of unique users who have streamed a song on each day in the US.
|
SELECT stream_date, COUNT(DISTINCT user_id) as unique_users FROM streams st JOIN users u ON st.user_id = u.user_id WHERE u.user_country = 'United States' GROUP BY stream_date;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE carbon_storage (country VARCHAR(50), operational BOOLEAN, year INT); INSERT INTO carbon_storage (country, operational, year) VALUES ('United States', true, 2020), ('Germany', true, 2020), ('Saudi Arabia', true, 2020), ('Norway', false, 2020);
|
List the number of carbon capture and storage facilities in the United States, Germany, and Saudi Arabia, as of 2020.
|
SELECT country, COUNT(*) FROM carbon_storage WHERE country IN ('United States', 'Germany', 'Saudi Arabia') AND operational = true GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE immigrants (id INT, name VARCHAR(100), education VARCHAR(50)); INSERT INTO immigrants (id, name, education) VALUES (1, 'Immigrant 1', 'High School'); INSERT INTO immigrants (id, name, education) VALUES (2, 'Immigrant 2', 'Bachelor’s Degree');
|
What is the highest level of education achieved by immigrants in Germany?
|
SELECT education FROM (SELECT education, ROW_NUMBER() OVER (ORDER BY education DESC) as row_num FROM immigrants) immigrants_ranked WHERE row_num = 1;
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA if not exists mining;CREATE TABLE mining.impact (id INT, site STRING, ias_score INT);INSERT INTO mining.impact (id, site, ias_score) VALUES (1, 'site Z', 65), (2, 'site W', 75), (3, 'site X', 85);
|
Show environmental impact score for site 'Z' and 'W'.
|
SELECT ias_score FROM mining.impact WHERE site IN ('site Z', 'site W');
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gretelai_synthetic_text_to_sql
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CREATE TABLE socially_responsible_lending (id INT, loan_amount FLOAT, country VARCHAR(255)); INSERT INTO socially_responsible_lending (id, loan_amount, country) VALUES (1, 5000, 'USA'), (2, 7000, 'USA'), (3, 8000, 'USA');
|
What is the maximum loan amount for socially responsible lending in the United States?
|
SELECT MAX(loan_amount) FROM socially_responsible_lending WHERE country = 'USA';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE r_d_expenditure (drug VARCHAR(20), division VARCHAR(20), date DATE, expenditure NUMERIC(12, 2)); INSERT INTO r_d_expenditure (drug, division, date, expenditure) VALUES ('DrugA', 'Oncology', '2023-01-01', 150000.00), ('DrugB', 'Cardiology', '2023-01-01', 120000.00), ('DrugA', 'Neurology', '2023-01-01', 90000.00), ('DrugB', 'Oncology', '2023-01-01', 155000.00), ('DrugA', 'Cardiology', '2023-01-01', 123000.00), ('DrugB', 'Neurology', '2023-01-01', 915000.00);
|
What was the R&D expenditure for each drug in Q1 2023, pivoted by division?
|
SELECT drug, SUM(CASE WHEN division = 'Oncology' THEN expenditure ELSE 0 END) AS oncology_expenditure, SUM(CASE WHEN division = 'Cardiology' THEN expenditure ELSE 0 END) AS cardiology_expenditure FROM r_d_expenditure WHERE date BETWEEN '2023-01-01' AND '2023-03-31' GROUP BY drug;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE TrainingData (EmployeeID INT, Department TEXT, Training TEXT); INSERT INTO TrainingData (EmployeeID, Department, Training) VALUES (1, 'Sales', 'Diversity');
|
How many employees have undergone diversity training in the Sales department?
|
SELECT COUNT(*) FROM TrainingData WHERE Department = 'Sales' AND Training = 'Diversity';
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gretelai_synthetic_text_to_sql
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CREATE TABLE food_products (id INT PRIMARY KEY, name TEXT, safety_recall BOOLEAN);
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Update the name of food product with id 1 to 'Organic Quinoa Puffs'
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UPDATE food_products SET name = 'Organic Quinoa Puffs' WHERE id = 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Ratings (hotel_id INT, ota TEXT, city TEXT, hotel_class TEXT, rating FLOAT); INSERT INTO Ratings (hotel_id, ota, city, hotel_class, rating) VALUES (1, 'Agoda', 'Sydney', 'boutique', 4.7), (2, 'Agoda', 'Sydney', 'boutique', 4.6), (3, 'Agoda', 'Sydney', 'non-boutique', 4.3);
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What is the average rating for 'boutique' hotels in 'Sydney' on 'Agoda'?
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SELECT AVG(rating) FROM Ratings WHERE ota = 'Agoda' AND city = 'Sydney' AND hotel_class = 'boutique';
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gretelai_synthetic_text_to_sql
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CREATE TABLE cases (id INT, caseworker_id INT, date DATE); INSERT INTO cases (id, caseworker_id, date) VALUES (1, 101, '2020-01-01'), (2, 101, '2020-01-10'), (3, 102, '2020-02-01');
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How many cases were handled by each caseworker in the justice department, with the total number of cases and cases per caseworker?
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SELECT COUNT(*) OVER (PARTITION BY caseworker_id) AS cases_per_caseworker, COUNT(*) AS total_cases FROM cases;
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gretelai_synthetic_text_to_sql
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CREATE TABLE language_preservation (id INT PRIMARY KEY, name TEXT, location TEXT);
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Add a new language preservation project in 'Mexico'
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INSERT INTO language_preservation (id, name, location) VALUES (1, 'Mixtec Language', 'Mexico');
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gretelai_synthetic_text_to_sql
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CREATE TABLE ingredient (product_id INT, ingredient TEXT, origin TEXT);
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Find brands that use ingredients from 'India' and have no safety records after 2022-01-01
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SELECT brand FROM ingredient INNER JOIN (SELECT product_id FROM safety_record WHERE report_date > '2022-01-01' EXCEPT SELECT product_id FROM safety_record) ON ingredient.product_id = product_id WHERE origin = 'India';
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gretelai_synthetic_text_to_sql
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CREATE TABLE sustainable_projects (project_id SERIAL PRIMARY KEY, square_footage INTEGER, is_sustainable BOOLEAN); INSERT INTO sustainable_projects (project_id, square_footage, is_sustainable) VALUES (1, 15000, true), (2, 20000, false), (3, 25000, true);
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What is the total square footage of sustainable building projects?
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SELECT SUM(square_footage) FROM sustainable_projects WHERE is_sustainable = true;
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gretelai_synthetic_text_to_sql
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CREATE TABLE SpaceAgency (ID INT, Name VARCHAR(50), Country VARCHAR(50)); CREATE TABLE SpaceMission (AgencyID INT, Name VARCHAR(50), LaunchDate DATE, Duration INT);
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What is the average duration of space missions per agency?
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SELECT sa.Name, AVG(sm.Duration) AS AvgDuration FROM SpaceAgency sa JOIN SpaceMission sm ON sa.ID = sm.AgencyID GROUP BY sa.Name;
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gretelai_synthetic_text_to_sql
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