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CREATE TABLE regions (region_id INT, region_name VARCHAR(50)); INSERT INTO regions (region_id, region_name) VALUES (1, 'North America'), (2, 'Europe'), (3, 'Asia'), (4, 'Africa'), (5, 'South America'); CREATE TABLE model_fairness (model_id INT, region_id INT, fairness_score FLOAT);
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What is the average fairness score of models trained on different geographical regions?
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SELECT AVG(mf.fairness_score) FROM model_fairness mf JOIN regions r ON mf.region_id = r.region_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE threat_intelligence (region VARCHAR(255), date DATE, metric1 FLOAT, metric2 FLOAT, metric3 FLOAT); INSERT INTO threat_intelligence (region, date, metric1, metric2, metric3) VALUES ('Northeast', '2020-01-01', 12.3, 45.6, 78.9), ('Midwest', '2020-01-01', 23.4, 56.7, 89.0), ('South', '2020-01-01', 34.5, 67.8, 90.1), ('West', '2020-01-01', 45.6, 78.9, 12.3);
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What are the average threat intelligence metrics for each region in 2020?
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SELECT region, AVG(metric1) as avg_metric1, AVG(metric2) as avg_metric2, AVG(metric3) as avg_metric3 FROM threat_intelligence WHERE date BETWEEN '2020-01-01' AND '2020-12-31' GROUP BY region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE WastewaterTreatment (id INT, facility VARCHAR, year INT, volume INT); INSERT INTO WastewaterTreatment (id, facility, year, volume) VALUES (1, 'Sacramento', 2018, 12000000), (2, 'Sacramento', 2019, 12500000), (3, 'San Diego', 2018, 14000000);
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What is the total volume of wastewater treated by the water treatment facility in Sacramento in 2018?
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SELECT SUM(volume) FROM WastewaterTreatment WHERE facility = 'Sacramento' AND year = 2018;
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gretelai_synthetic_text_to_sql
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CREATE TABLE hospitals (hospital_id INT, hospital_name VARCHAR(255)); CREATE TABLE doctors (doctor_id INT, doctor_name VARCHAR(255), hospital_id INT); INSERT INTO hospitals (hospital_id, hospital_name) VALUES (1, 'Hospital A'), (2, 'Hospital B'); INSERT INTO doctors (doctor_id, doctor_name, hospital_id) VALUES (1, 'Dr. Smith', 1), (2, 'Dr. Johnson', NULL), (3, 'Dr. Williams', 2);
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Delete the records of doctors who are not assigned to any hospital from the doctors table.
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DELETE FROM doctors WHERE hospital_id IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Warehouses (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255)); CREATE TABLE Freights (id INT PRIMARY KEY, warehouse_id INT, status VARCHAR(255), quantity INT, pickup_date DATETIME); CREATE VIEW PendingFreights AS SELECT * FROM Freights WHERE status = 'pending';
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What are the names of warehouses with no pending freights?
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SELECT w.name FROM Warehouses w LEFT JOIN PendingFreights p ON w.id = p.warehouse_id WHERE p.id IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA Biosensors; CREATE TABLE Patents (patent_name VARCHAR(50), grant_year INT); INSERT INTO Patents VALUES ('Patent1', 2018), ('Patent2', 2019);
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How many biosensor technology patents were granted in each year in the 'Patents' table?
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SELECT grant_year, COUNT(*) as num_patents FROM Biosensors.Patents GROUP BY grant_year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE if not exists VisitorContinents (Continent VARCHAR(50), Country VARCHAR(50), Visitors INT); INSERT INTO VisitorContinents (Continent, Country, Visitors) VALUES ('Africa', 'Egypt', 120000), ('Asia', 'Japan', 240000), ('Europe', 'France', 300000), ('South America', 'Brazil', 140000), ('North America', 'Canada', 170000), ('Oceania', 'Australia', 270000);
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What was the total number of visitors to each continent in 2021?
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SELECT a.Continent, SUM(a.Visitors) AS TotalVisitors FROM VisitorContinents a WHERE a.Year = 2021 GROUP BY a.Continent;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Infection_Rates (ID INT, Year INT, Disease TEXT, Region TEXT, Rate FLOAT); INSERT INTO Infection_Rates (ID, Year, Disease, Region, Rate) VALUES (1, 2017, 'Malaria', 'Tropical', 0.15); INSERT INTO Infection_Rates (ID, Year, Disease, Region, Rate) VALUES (2, 2018, 'Dengue Fever', 'Temperate', 0.07);
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What is the infection rate of Malaria and Dengue Fever in tropical and temperate regions over the past 5 years?
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SELECT Region, Disease, AVG(Rate) FROM Infection_Rates WHERE Year BETWEEN 2017 AND 2021 GROUP BY Region, Disease;
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gretelai_synthetic_text_to_sql
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CREATE TABLE product_complaints (complaint_id INT, brand_name VARCHAR(255), complaint_date DATE); CREATE TABLE brand_catalog (brand_id INT, brand_name VARCHAR(255));
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How many complaints were filed in the last 6 months for a specific brand?
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SELECT COUNT(*) FROM product_complaints JOIN brand_catalog ON product_complaints.brand_id = brand_catalog.brand_id WHERE brand_name = 'Example Brand' AND complaint_date >= DATE_SUB(CURRENT_DATE, INTERVAL 6 MONTH);
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gretelai_synthetic_text_to_sql
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CREATE TABLE news_agencies (id INT, name TEXT); INSERT INTO news_agencies VALUES (1, 'Acme News Agency'); INSERT INTO news_agencies VALUES (2, 'Global News'); CREATE TABLE articles (id INT, agency_id INT, title TEXT, location TEXT); INSERT INTO articles VALUES (1, 1, 'Article 1', 'Germany'); INSERT INTO articles VALUES (2, 1, 'Article 2', 'France'); INSERT INTO articles VALUES (3, 2, 'Article 3', 'USA');
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Find the number of articles published by 'Acme News Agency' in 'Germany' and 'France'?
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SELECT COUNT(articles.id) FROM articles INNER JOIN news_agencies ON articles.agency_id = news_agencies.id WHERE news_agencies.name = 'Acme News Agency' AND articles.location IN ('Germany', 'France');
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gretelai_synthetic_text_to_sql
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CREATE TABLE co2_emission (country VARCHAR(50), year INT, industry VARCHAR(50), co2_emission FLOAT); INSERT INTO co2_emission (country, year, industry, co2_emission) VALUES ('Canada', 2000, 'Oil', 100.0), ('Canada', 2001, 'Oil', 120.0), ('Norway', 2000, 'Gas', 80.0);
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What is the total CO2 emission in the Arctic by industry since 2000?
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SELECT c.country, c.industry, SUM(c.co2_emission) as total_emission FROM co2_emission c GROUP BY c.country, c.industry;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Locations (LocId INT, Type VARCHAR(50)); CREATE TABLE Crimes (CrimeId INT, LocId INT, Date DATE, Time TIME);
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What is the maximum number of crimes committed in a single day in each location type?
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SELECT L.Type, MAX(C.Count) FROM Locations L INNER JOIN (SELECT LocId, COUNT(*) AS Count FROM Crimes GROUP BY LocId, Date, Time) C ON L.LocId = C.LocId GROUP BY L.Type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE aquatic_farms (id INT, country VARCHAR(50), biomass FLOAT); INSERT INTO aquatic_farms (id, country, biomass) VALUES (1, 'Norway', 350000), (2, 'Chile', 280000), (3, 'China', 740000);
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What is the total biomass of farmed fish in each country's aquatic farms?
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SELECT country, SUM(biomass) as total_biomass FROM aquatic_farms GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE donations (id INT, donation_date DATE, amount DECIMAL(10,2)); INSERT INTO donations (id, donation_date, amount) VALUES (1, '2021-01-01', 100.00), (2, '2021-01-15', 250.50), (3, '2021-03-01', 150.25);
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What was the total donation amount in Q1 2021?
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SELECT SUM(amount) FROM donations WHERE donation_date BETWEEN '2021-01-01' AND '2021-03-31';
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gretelai_synthetic_text_to_sql
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CREATE TABLE sites (id INT, name VARCHAR(255), annual_emission_limit INT); INSERT INTO sites (id, name, annual_emission_limit) VALUES (1, 'Site A', 1000), (2, 'Site B', 1200), (3, 'Site C', 1500); INSERT INTO sites (id, name, annual_emission_limit, yearly_emissions) VALUES (1, 'Site A', 1000, 1100), (2, 'Site B', 1200, 1150), (3, 'Site C', 1500, 1400);
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Which sites have exceeded their annual emission limits?
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SELECT name FROM (SELECT name, yearly_emissions, annual_emission_limit, ROW_NUMBER() OVER (PARTITION BY name ORDER BY yearly_emissions DESC) as row_num FROM sites) subquery WHERE row_num = 1 AND yearly_emissions > annual_emission_limit;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AlgorithmicFairness (ID INT, Algorithm VARCHAR(255), Category VARCHAR(255), Score FLOAT, Date DATE); INSERT INTO AlgorithmicFairness (ID, Algorithm, Category, Score, Date) VALUES (1, 'Algo1', 'CategoryA', 0.85, '2020-01-01'), (2, 'Algo2', 'CategoryB', 0.78, '2020-01-05'), (3, 'Algo3', 'CategoryA', 0.91, '2020-02-12'), (4, 'Algo4', 'CategoryB', 0.89, '2020-02-15'), (5, 'Algo5', 'CategoryA', 0.75, '2020-03-01');
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What is the minimum algorithmic fairness score for algorithms created in H1 2020, per category?
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SELECT Category, MIN(Score) as Min_Score FROM AlgorithmicFairness WHERE Date BETWEEN '2020-01-01' AND '2020-06-30' GROUP BY Category;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE hiv_data (id INT, city TEXT, year INT, cases INT); INSERT INTO hiv_data (id, city, year, cases) VALUES (1, 'Los Angeles', 2018, 500), (2, 'Los Angeles', 2019, 600);
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What is the change in the number of HIV cases between consecutive years, for each city?
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SELECT city, year, cases, LAG(cases) OVER (PARTITION BY city ORDER BY year) as prev_year_cases, cases - LAG(cases) OVER (PARTITION BY city ORDER BY year) as change FROM hiv_data;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Spacecraft (id INT, name VARCHAR(255), manufacturer VARCHAR(255), budget DECIMAL(10, 2)); INSERT INTO Spacecraft (id, name, manufacturer, budget) VALUES (1, 'Voyager I', 'AeroSpace Inc.', 800000000.00), (2, 'Voyager II', 'AeroSpace Inc.', 850000000.00), (3, 'Dragon C106', 'SpaceX', 150000000.00);
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What is the total budget for all spacecraft manufactured by 'AeroSpace Inc.' and 'SpaceX'?
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SELECT SUM(budget) FROM Spacecraft WHERE manufacturer IN ('AeroSpace Inc.', 'SpaceX');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE ticket_sales(ticket_id INT, game_id INT, location VARCHAR(50), tickets_sold INT);
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Identify the total number of tickets sold for games held in New York or Los Angeles.
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SELECT SUM(tickets_sold) FROM ticket_sales WHERE location IN ('New York', 'Los Angeles');
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gretelai_synthetic_text_to_sql
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CREATE TABLE spaceships (id INT, name VARCHAR(50), max_speed FLOAT, launch_date DATE); INSERT INTO spaceships (id, name, max_speed, launch_date) VALUES (1, 'Viking 1', 21000, '1975-08-20'); INSERT INTO spaceships (id, name, max_speed, launch_date) VALUES (2, 'Curiosity Rover', 13000, '2011-11-26');
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What is the average speed of spaceships that landed on Mars?
|
SELECT AVG(max_speed) FROM spaceships WHERE name IN ('Viking 1', 'Curiosity Rover') AND launch_date LIKE '19__-__-__' OR launch_date LIKE '20__-__-__';
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gretelai_synthetic_text_to_sql
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CREATE TABLE emissions (id INT, project_id INT, year INT, CO2_emissions_tonnes INT); INSERT INTO emissions (id, project_id, year, CO2_emissions_tonnes) VALUES (1, 1, 2018, 1000);
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How can I update the CO2 emissions for a specific project?
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UPDATE emissions SET CO2_emissions_tonnes = 1200 WHERE project_id = 1 AND year = 2018;
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gretelai_synthetic_text_to_sql
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CREATE TABLE years (year_id INT, year INT); CREATE TABLE projects (project_id INT, project_type VARCHAR(255), year_id INT);
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How many rural infrastructure projects were completed in 2021, categorized by project type?
|
SELECT p.project_type, COUNT(p.project_id) as project_count FROM projects p JOIN years y ON p.year_id = y.year_id WHERE y.year = 2021 GROUP BY p.project_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Employees (EmployeeID INT, Department VARCHAR(255), Salary FLOAT);
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Find the average salary of employees in the 'HumanResources' department who have a salary higher than the overall average salary.
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SELECT AVG(Salary) FROM Employees WHERE Department = 'HumanResources' AND Salary > (SELECT AVG(Salary) FROM Employees);
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gretelai_synthetic_text_to_sql
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CREATE TABLE MakeupProducts (product_id INT, product_name VARCHAR(255), price DECIMAL(5,2), is_organic BOOLEAN, country VARCHAR(50));
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What is the maximum price of organic makeup products sold in Australia?
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SELECT MAX(price) FROM MakeupProducts WHERE is_organic = TRUE AND country = 'Australia';
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gretelai_synthetic_text_to_sql
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CREATE TABLE vessels (id INT, name TEXT, speed FLOAT, departed_port TEXT, departed_date DATE); INSERT INTO vessels (id, name, speed, departed_port, departed_date) VALUES (1, 'VesselA', 15.2, 'Oakland', '2020-01-01'); INSERT INTO vessels (id, name, speed, departed_port, departed_date) VALUES (2, 'VesselB', 17.8, 'Oakland', '2020-01-15');
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What is the average speed of vessels that departed from the port of Oakland in January 2020?
|
SELECT AVG(speed) FROM vessels WHERE departed_port = 'Oakland' AND departed_date >= '2020-01-01' AND departed_date < '2020-02-01';
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gretelai_synthetic_text_to_sql
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CREATE TABLE carbon_offset_initiatives (id INT, name VARCHAR(255), description TEXT, total_carbon_offset FLOAT);
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Find the total carbon offset of all carbon offset initiatives in the database.
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SELECT SUM(total_carbon_offset) FROM carbon_offset_initiatives;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE drug_approval_2019 (drug VARCHAR(50), year INT, status VARCHAR(50)); INSERT INTO drug_approval_2019 (drug, year, status) VALUES ('DrugA', 2019, 'Approved'), ('DrugD', 2019, 'Approved'), ('DrugE', 2019, 'Approved'); CREATE TABLE drug_sales_q4_2020 (drug VARCHAR(50), quarter VARCHAR(5), year INT, revenue INT); INSERT INTO drug_sales_q4_2020 (drug, quarter, year, revenue) VALUES ('DrugA', 'Q4', 2020, 200000), ('DrugD', 'Q4', 2020, 150000), ('DrugF', 'Q4', 2020, 180000);
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List all drugs that were approved in 2019 and have sales revenue greater than $150,000 in Q4 2020?
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SELECT drug_sales_q4_2020.drug FROM drug_sales_q4_2020 INNER JOIN drug_approval_2019 ON drug_sales_q4_2020.drug = drug_approval_2019.drug WHERE drug_sales_q4_2020.quarter = 'Q4' AND drug_sales_q4_2020.year = 2020 AND drug_sales_q4_2020.revenue > 150000 AND drug_approval_2019.year = 2019 AND drug_approval_2019.status = 'Approved';
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gretelai_synthetic_text_to_sql
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CREATE TABLE if not exists dapps (dapp_id INT, dapp_name VARCHAR(255), country VARCHAR(255)); INSERT INTO dapps (dapp_id, dapp_name, country) VALUES (1, 'Uniswap', 'USA'), (2, 'Aave', 'UK'), (3, 'Compound', 'USA'), (4, 'Balancer', 'Switzerland'), (5, 'Yearn Finance', 'USA'), (6, 'Tether', 'Hong Kong'), (7, 'Binance DEX', 'Malta'), (8, 'Bitforex', 'China'), (9, 'IDEX', 'USA'), (10, 'Kyber Network', 'Singapore');
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Which decentralized applications have been banned in China?
|
SELECT dapp_name FROM dapps WHERE country = 'China';
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gretelai_synthetic_text_to_sql
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CREATE TABLE ArtistGrants (grantID INT, grantAmount DECIMAL(10,2), grantType VARCHAR(50)); INSERT INTO ArtistGrants (grantID, grantAmount, grantType) VALUES (1, 12000.00, 'Indigenous Artist Grant'), (2, 8000.00, 'Emerging Artist Grant'), (3, 15000.00, 'Established Artist Grant');
|
What is the maximum funding received by any Indigenous artist grant program?
|
SELECT MAX(grantAmount) FROM ArtistGrants WHERE grantType = 'Indigenous Artist Grant';
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gretelai_synthetic_text_to_sql
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CREATE TABLE ai_fairness (ai_category TEXT, fairness_metric TEXT, value FLOAT);
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How many algorithmic fairness entries have a value greater than 0.8 for each AI category in the 'ai_fairness' table?
|
SELECT ai_category, COUNT(*) FROM ai_fairness WHERE value > 0.8 GROUP BY ai_category;
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gretelai_synthetic_text_to_sql
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CREATE TABLE drought_impact_ca (sector VARCHAR(20), reduction FLOAT); INSERT INTO drought_impact_ca (sector, reduction) VALUES ('Industrial', 0.1), ('Agriculture', 0.2), ('Domestic', 0.15);
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What is the drought impact on industrial water usage in California in terms of water usage reduction?
|
SELECT reduction FROM drought_impact_ca WHERE sector = 'Industrial';
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gretelai_synthetic_text_to_sql
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CREATE TABLE virtual_tours (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255), tour_type VARCHAR(255)); INSERT INTO virtual_tours (id, name, location, tour_type) VALUES (1, 'Paris Virtual Tour', 'Paris', 'museum_tour'); INSERT INTO virtual_tours (id, name, location, tour_type) VALUES (2, 'Rome Virtual Tour', 'Rome', 'city_tour');
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Delete all records in the virtual_tours table where the tour_type is 'city_tour'
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DELETE FROM virtual_tours WHERE tour_type = 'city_tour';
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gretelai_synthetic_text_to_sql
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CREATE TABLE financial_capability_2 (id INT, country VARCHAR(20), capability DECIMAL(3, 2)); INSERT INTO financial_capability_2 (id, country, capability) VALUES (1, 'Switzerland', 0.87), (2, 'Denmark', 0.86), (3, 'Netherlands', 0.85);
|
Find the top 2 countries with the highest financial capability.
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SELECT country, capability FROM (SELECT country, capability, ROW_NUMBER() OVER (ORDER BY capability DESC) rn FROM financial_capability_2) t WHERE rn <= 2;
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gretelai_synthetic_text_to_sql
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CREATE TABLE military_sales (id INT, region VARCHAR, sale_value DECIMAL, sale_date DATE); INSERT INTO military_sales (id, region, sale_value, sale_date) VALUES (1, 'Canada', 12000, '2020-01-05'); INSERT INTO military_sales (id, region, sale_value, sale_date) VALUES (2, 'Canada', 15000, '2020-03-30');
|
What was the total value of military equipment sales to Canada in Q1 2020?
|
SELECT SUM(sale_value) FROM military_sales WHERE region = 'Canada' AND sale_date BETWEEN '2020-01-01' AND '2020-03-31';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE unions (id INT, name TEXT, region TEXT, collective_bargaining BOOLEAN, member_count INT);
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Show the names of unions with collective bargaining agreements in the 'southwest' region that have more than 100 members.
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SELECT name FROM unions WHERE region = 'southwest' AND collective_bargaining = true AND member_count > 100;
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gretelai_synthetic_text_to_sql
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CREATE TABLE clinical_trials (drug varchar(255), year int, trials int); INSERT INTO clinical_trials (drug, year, trials) VALUES ('DrugA', 2020, 1), ('DrugB', 2020, 3);
|
How many clinical trials were conducted for each drug in 2020?
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SELECT drug, SUM(trials) FROM clinical_trials WHERE year = 2020 GROUP BY drug;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE crimes (id INT, city VARCHAR(255), type VARCHAR(255), number_of_crimes INT); INSERT INTO crimes (id, city, type, number_of_crimes) VALUES (1, 'New_York_City', 'Theft', 50000), (2, 'New_York_City', 'Assault', 30000);
|
What is the most common type of crime in New York City?
|
SELECT type, COUNT(*) AS count FROM crimes WHERE city = 'New_York_City' GROUP BY type ORDER BY count DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE water_usage (practice VARCHAR(20), water_usage INT); INSERT INTO water_usage (practice, water_usage) VALUES ('Hydroponics', 500), ('Aquaponics', 400), ('Vertical Farming', 600), ('Rooftop Farming', 300), ('Urban Ranching', 700), ('Community Gardens', 200);
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List the urban farming practices utilizing the least amount of water.
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SELECT practice FROM water_usage WHERE water_usage IN (SELECT MIN(water_usage) FROM water_usage);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Indian_TV (title TEXT, year INTEGER); INSERT INTO Indian_TV (title, year) VALUES ('TVShow1', 2016), ('TVShow2', 2017), ('TVShow3', 2018), ('TVShow4', 2019), ('TVShow5', 2020), ('TVShow6', 2021);
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How many TV shows were produced in India in the last 5 years?
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SELECT COUNT(*) FROM Indian_TV WHERE year BETWEEN 2016 AND 2021;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Digital_Divide (project_id INT, project_name VARCHAR(100), completion_year INT); INSERT INTO Digital_Divide (project_id, project_name, completion_year) VALUES (1, 'Project X', 2019), (2, 'Project Y', 2020), (3, 'Project Z', 2018);
|
Which digital divide initiatives were completed in 2020?
|
SELECT project_name FROM Digital_Divide WHERE completion_year = 2020;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Resilience_Measures (project_id INT, project_name VARCHAR(50), location VARCHAR(50)); INSERT INTO Resilience_Measures (project_id, project_name, location) VALUES (1, 'Levee Construction', 'Mississippi'); INSERT INTO Resilience_Measures (project_id, project_name, location) VALUES (2, 'Coastal Restoration', 'Florida');
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What are the names of the flood control projects in the 'Resilience_Measures' table?
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SELECT project_name FROM Resilience_Measures WHERE project_name LIKE '%Flood%';
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gretelai_synthetic_text_to_sql
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CREATE TABLE vessels (id INT, name TEXT, speed FLOAT, dock_date DATE);
|
What is the average speed of vessels that docked in the Port of Los Angeles in the last month?
|
SELECT AVG(speed) FROM vessels WHERE dock_date >= DATEADD(month, -1, GETDATE()) AND dock_port = 'Los Angeles';
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gretelai_synthetic_text_to_sql
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CREATE TABLE water_consumption (city VARCHAR(50), consumption FLOAT, month INT, year INT); INSERT INTO water_consumption (city, consumption, month, year) VALUES ('Miami', 12.3, 1, 2021), ('Miami', 13.1, 2, 2021), ('Miami', 11.9, 3, 2021);
|
Compute the moving average water consumption for the past 3 months in Miami.
|
SELECT city, AVG(consumption) OVER (PARTITION BY city ORDER BY year, month ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) FROM water_consumption;
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gretelai_synthetic_text_to_sql
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CREATE TABLE PrizePools (EventID INT, Region VARCHAR(50), PrizePool INT); INSERT INTO PrizePools (EventID, Region, PrizePool) VALUES (1, 'North America', 100000), (2, 'Europe', 150000), (4, 'Asia', 250000);
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What is the average prize pool for esports events in Asia?
|
SELECT AVG(PrizePool) FROM PrizePools WHERE Region = 'Asia';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE marine_trenches (name VARCHAR(255), location VARCHAR(255), depth FLOAT); INSERT INTO marine_trenches (name, location, depth) VALUES ('Mariana Trench', 'USA', 10994.0), ('Tonga Trench', 'Tonga', 10882.0), ('Kermadec Trench', 'New Zealand', 10047.0);
|
Identify the top three deepest marine trenches using window functions.
|
SELECT name, location, depth, ROW_NUMBER() OVER (ORDER BY depth DESC) as rn FROM marine_trenches WHERE rn <= 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Parks( park_id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255), area FLOAT, created_date DATE);
|
Add a new record to the 'Parks' table
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INSERT INTO Parks (park_id, name, location, area, created_date) VALUES (4, 'Stanley Park', 'Vancouver', 1001.00, '2000-01-04');
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gretelai_synthetic_text_to_sql
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CREATE TABLE cities (id INT, name TEXT, population INT);INSERT INTO cities (id, name, population) VALUES (1, 'CityA', 150000), (2, 'CityB', 80000), (3, 'CityC', 120000), (4, 'CityD', 200000);
|
What is the minimum population of any city in the cities table?
|
SELECT MIN(population) FROM cities;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE programs (id INT, program VARCHAR, community VARCHAR); INSERT INTO programs (id, program, community) VALUES (1, 'Youth Mentoring', 'Underrepresented'), (2, 'Women Empowerment', 'Underrepresented'), (3, 'Community Service', 'Underrepresented'), (4, 'Education Support', 'Underrepresented');
|
Delete the program 'Education Support' from the programs table
|
DELETE FROM programs WHERE program = 'Education Support';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE public_art (type VARCHAR(255), location VARCHAR(255), date DATE);
|
Insert a new record into the 'public_art' table for a new public art sculpture.
|
INSERT INTO public_art (type, location, date) VALUES ('Sculpture', 'City Park', '2023-02-14');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE ResearchVessels (VesselID INT, Name VARCHAR(50), SpeciesSpotted INT); INSERT INTO ResearchVessels (VesselID, Name, SpeciesSpotted) VALUES (1, 'RV1', 100), (2, 'RV2', 150), (3, 'RV3', 250), (4, 'RV4', 50);
|
What are the names of the vessels that have spotted more than 200 marine species?
|
SELECT Name FROM ResearchVessels WHERE SpeciesSpotted > 200;
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gretelai_synthetic_text_to_sql
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CREATE TABLE species ( id INT PRIMARY KEY, name VARCHAR(255) ); INSERT INTO species (id, name) VALUES (1, 'polar_bear'), (2, 'arctic_fox'); CREATE TABLE observations ( id INT PRIMARY KEY, species_id INT, observation_date DATE, FOREIGN KEY (species_id) REFERENCES species(id) ); INSERT INTO observations (id, species_id, observation_date) VALUES (1, 1, '2022-01-01'), (2, 2, '2022-01-02'), (3, 1, '2022-02-03');
|
What is the number of different species observed in 2022?
|
SELECT COUNT(DISTINCT species_id) FROM observations WHERE observation_date BETWEEN '2022-01-01' AND '2022-12-31';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE material_prices (id INT, material VARCHAR(50), price DECIMAL(10, 2)); INSERT INTO material_prices (id, material, price) VALUES (1, 'organic silk', 35.00), (2, 'organic linen', 18.50);
|
Which sustainable material has the highest average price?
|
SELECT material, AVG(price) as avg_price FROM material_prices GROUP BY material ORDER BY avg_price DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE language_preservation (id INT, country VARCHAR(50), program VARCHAR(50), region VARCHAR(50)); INSERT INTO language_preservation (id, country, program, region) VALUES (1, 'USA', 'Native American Language Program', 'North America'), (2, 'France', 'French Language Program', 'Europe');
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Compare the number of language preservation programs in North America and Europe.
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SELECT COUNT(*) FROM language_preservation WHERE region = 'North America' INTERSECT SELECT COUNT(*) FROM language_preservation WHERE region = 'Europe';
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gretelai_synthetic_text_to_sql
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CREATE TABLE solar_pv (id INT, country TEXT, year INT, capacity_mw FLOAT); INSERT INTO solar_pv (id, country, year, capacity_mw) VALUES (1, 'Japan', 2020, 60.5), (2, 'Japan', 2021, 65.6), (3, 'Germany', 2022, 70.7);
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What is the total installed solar PV capacity (MW) in Germany as of 2022?
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SELECT SUM(capacity_mw) FROM solar_pv WHERE country = 'Germany' AND year = 2022;
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gretelai_synthetic_text_to_sql
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CREATE TABLE companies (id INT, name VARCHAR(50), industry VARCHAR(50), founding_year INT, founder_gender VARCHAR(10)); INSERT INTO companies (id, name, industry, founding_year, founder_gender) VALUES (1, 'Delta Inc', 'Retail', 2016, 'Female'), (2, 'Echo Corp', 'Tech', 2017, 'Male'), (3, 'Foxtrot LLC', 'Retail', 2018, 'Female'), (4, 'Gamma Inc', 'Healthcare', 2015, 'Male'); CREATE TABLE funding_rounds (company_id INT, round_amount DECIMAL(10,2), round_type VARCHAR(20), year INT); INSERT INTO funding_rounds (company_id, round_amount, round_type, year) VALUES (1, 2000000, 'Seed', 2016), (2, 5000000, 'Series A', 2017), (3, 3000000, 'Seed', 2018), (4, 6000000, 'Series B', 2019);
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What is the total funding raised for companies with a female founder?
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SELECT SUM(f.round_amount) FROM companies c JOIN funding_rounds f ON c.id = f.company_id WHERE c.founder_gender = 'Female';
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gretelai_synthetic_text_to_sql
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CREATE TABLE players (id INT, name VARCHAR(100), country VARCHAR(100)); CREATE TABLE purchases (id INT, player_id INT, purchase_date DATE); INSERT INTO players (id, name, country) VALUES (1, 'John Doe', 'USA'), (2, 'Jane Smith', 'USA'), (3, 'Alex Brown', 'Canada'); INSERT INTO purchases (id, player_id, purchase_date) VALUES (1, 1, '2022-01-01'), (2, 2, '2022-02-01'), (3, 1, '2021-01-01');
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Delete players from the US who haven't made any purchases in the last year?
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DELETE FROM players WHERE id IN (SELECT p.id FROM players p JOIN purchases pu ON p.id = pu.player_id WHERE p.country = 'USA' AND pu.purchase_date < (CURRENT_DATE - INTERVAL '1 year'));
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gretelai_synthetic_text_to_sql
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CREATE TABLE staff (id INT, name VARCHAR(50), position VARCHAR(50), salary INT); INSERT INTO staff (id, name, position, salary) VALUES (1, 'Jane Smith', 'Editor', 70000), (2, 'Mike Johnson', 'Reporter', 50000);
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What is the maximum salary of editors in the "staff" table?
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SELECT MAX(salary) FROM staff WHERE position = 'Editor';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Ingredient_Sourcing (SupplierID INT, ProductID INT, Organic BOOLEAN, Country VARCHAR(50)); INSERT INTO Ingredient_Sourcing (SupplierID, ProductID, Organic, Country) VALUES (1001, 101, TRUE, 'Brazil'), (1002, 102, FALSE, 'Brazil'), (1003, 101, TRUE, 'Argentina'), (1004, 103, FALSE, 'Argentina'), (1005, 102, TRUE, 'Chile');
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Which country sources the most organic ingredients for cosmetic products?
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SELECT Country, SUM(Organic) as TotalOrganic FROM Ingredient_Sourcing GROUP BY Country ORDER BY TotalOrganic DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE cargos (id INT PRIMARY KEY, name VARCHAR(50), date_received DATE);
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Delete all cargos from the 'cargos' table that are over 10 years old.
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DELETE FROM cargos WHERE date_received < DATE_SUB(CURDATE(), INTERVAL 10 YEAR);
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gretelai_synthetic_text_to_sql
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CREATE TABLE la_prop(id INT, owner1 VARCHAR(20), owner2 VARCHAR(20), lease_exp DATE); INSERT INTO la_prop VALUES (1, 'Ivy', 'Jack', '2023-03-01'), (2, 'Karen', 'Luke', '2023-01-15');
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Find the unique property co-owners in Los Angeles with a lease expiration date in the next 3 months.
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SELECT DISTINCT owner1, owner2 FROM la_prop WHERE (owner1 <> owner2) AND (lease_exp BETWEEN CURDATE() AND DATE_ADD(CURDATE(), INTERVAL 3 MONTH));
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gretelai_synthetic_text_to_sql
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CREATE TABLE SafetyIncidents(IncidentID INT, VesselID INT, IncidentType TEXT, IncidentDate DATETIME); INSERT INTO SafetyIncidents(IncidentID, VesselID, IncidentType, IncidentDate) VALUES (1, 1, 'Collision', '2022-03-05 11:00:00'), (2, 2, 'Grounding', '2022-03-15 09:00:00'), (3, 3, 'Mechanical Failure', '2022-03-30 16:30:00');
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List all safety incidents recorded in the last 30 days
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SELECT * FROM SafetyIncidents WHERE IncidentDate BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY) AND CURRENT_DATE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE GeopoliticalRiskAssessments (AssessmentID INT, Country VARCHAR(50), RiskRating VARCHAR(10), AssessmentDate DATE); INSERT INTO GeopoliticalRiskAssessments (AssessmentID, Country, RiskRating, AssessmentDate) VALUES (1, 'Iran', 'High', '2021-06-01'), (2, 'India', 'Medium', '2022-08-12');
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Retrieve the most recent geopolitical risk rating for India.
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SELECT Country, RiskRating FROM GeopoliticalRiskAssessments WHERE AssessmentDate = (SELECT MAX(AssessmentDate) FROM GeopoliticalRiskAssessments WHERE Country = 'India');
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gretelai_synthetic_text_to_sql
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CREATE TABLE MilitaryAircrafts(id INT PRIMARY KEY, name VARCHAR(50), model VARCHAR(50), country VARCHAR(50));INSERT INTO MilitaryAircrafts(id, name, model, country) VALUES (1, 'F-15 Eagle', 'F-15EX', 'USA');
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What is the name and model of military aircrafts manufactured in the USA?
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SELECT name, model FROM MilitaryAircrafts WHERE country = 'USA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE pollution_initiatives (initiative_id INT, site_id INT, initiative_date DATE, initiative_description TEXT); INSERT INTO pollution_initiatives (initiative_id, site_id, initiative_date, initiative_description) VALUES (1, 1, '2022-08-01', 'Installed new filters'), (2, 3, '2022-07-15', 'Regular cleaning schedule established');
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What is the earliest pollution control initiative date for each site?
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SELECT site_id, MIN(initiative_date) FROM pollution_initiatives GROUP BY site_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Districts (DistrictID INT, Name VARCHAR(50)); CREATE TABLE EmergencyCalls (CallID INT, DistrictID INT, ResponseTime FLOAT);
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What is the maximum response time for emergency calls in each district?
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SELECT D.Name, MAX(E.ResponseTime) as MaxResponseTime FROM Districts D INNER JOIN EmergencyCalls E ON D.DistrictID = E.DistrictID GROUP BY D.Name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ethical_manufacturing (id INT PRIMARY KEY, certification VARCHAR(100), certification_date DATE);
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Insert new records into the 'ethical_manufacturing' table with the following data: (1, 'Fair Trade Certified', '2021-01-01')
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INSERT INTO ethical_manufacturing (id, certification, certification_date) VALUES (1, 'Fair Trade Certified', '2021-01-01');
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gretelai_synthetic_text_to_sql
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CREATE TABLE enrollments (id INT, enrollment_date DATE, student_id INT, program VARCHAR(50)); INSERT INTO enrollments (id, enrollment_date, student_id, program) VALUES (1, '2021-07-01', 1001, 'Open Pedagogy'), (2, '2021-08-15', 1002, 'Open Pedagogy'), (3, '2022-01-10', 1003, 'Traditional Program'), (4, '2022-02-01', 1004, 'Open Pedagogy');
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How many students have enrolled in the open pedagogy program in the past 6 months?
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SELECT COUNT(DISTINCT student_id) as num_enrolled FROM enrollments WHERE program = 'Open Pedagogy' AND enrollment_date >= DATEADD(month, -6, GETDATE());
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gretelai_synthetic_text_to_sql
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player (player_id, name, email, age, gender, country, total_games_played)
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Update email of players from 'US' to 'new_email@usa.com'
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UPDATE player SET email = 'new_email@usa.com' WHERE country = 'US'
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gretelai_synthetic_text_to_sql
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CREATE TABLE Accidents (AccidentID INT, Date DATE, Location VARCHAR(50), AircraftType VARCHAR(50), Description TEXT, Fatalities INT); INSERT INTO Accidents (AccidentID, Date, Location, AircraftType, Description, Fatalities) VALUES (7, '2018-05-05', 'Moscow', 'Boeing 737', 'Electrical issues', 1), (8, '2020-06-06', 'Tokyo', 'Boeing 737', 'Pressurization problems', 0);
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Determine the most common aircraft type involved in accidents and its count.
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SELECT AircraftType, COUNT(*) AS Count FROM Accidents GROUP BY AircraftType ORDER BY COUNT(*) DESC FETCH FIRST 1 ROW ONLY;
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gretelai_synthetic_text_to_sql
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CREATE TABLE legal_aid_organizations (org_id INT, name VARCHAR(50), cases_handled INT, state VARCHAR(2)); INSERT INTO legal_aid_organizations (org_id, name, cases_handled, state) VALUES (1, 'California Legal Aid', 200, 'CA'), (2, 'New York Legal Aid', 300, 'NY'), (3, 'Texas Legal Aid', 150, 'TX'), (4, 'Florida Legal Aid', 250, 'FL'), (5, 'Los Angeles Legal Aid', 400, 'CA');
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Identify the legal aid organization with the most cases in California
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SELECT name, MAX(cases_handled) FROM legal_aid_organizations WHERE state = 'CA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE menu (dish_name TEXT, category TEXT, price DECIMAL); INSERT INTO menu VALUES ('Margherita Pizza', 'Pizza', 9.99), ('Pepperoni Pizza', 'Pizza', 10.99), ('Vegetarian Pizza', 'Pizza', 11.99);
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Find the dish with the highest price in the 'Pizza' category
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SELECT dish_name, MAX(price) FROM menu WHERE category = 'Pizza' GROUP BY category;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Customers (CustomerID INT, Size VARCHAR(10), Country VARCHAR(255)); INSERT INTO Customers (CustomerID, Size, Country) VALUES (1, 'XS', 'Brazil'), (2, 'S', 'Argentina'), (3, 'M', 'Chile'), (4, 'L', 'Peru'), (5, 'XL', 'Colombia'), (6, 'XS', 'Argentina'), (7, 'L', 'Brazil');
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Which size has the most customers in the 'South America' region?
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SELECT Size, COUNT(*) AS Count FROM Customers WHERE Country = 'South America' GROUP BY Size ORDER BY Count DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE claims (id INT, policyholder_id INT, amount DECIMAL(10, 2), risk_category VARCHAR(25));
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What is the total claim amount per risk assessment category?
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SELECT risk_category, SUM(amount) as total_claim_amount FROM claims GROUP BY risk_category;
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gretelai_synthetic_text_to_sql
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CREATE TABLE suppliers (supp_id INT, name VARCHAR(50), country VARCHAR(50)); INSERT INTO suppliers VALUES (1, 'Green Earth', 'Germany'); INSERT INTO suppliers VALUES (2, 'EcoVita', 'Germany'); CREATE TABLE products (product_id INT, name VARCHAR(50), type VARCHAR(20), price DECIMAL(5,2)); INSERT INTO products VALUES (1, 'Tofu Steaks', 'vegan', 6.99); INSERT INTO products VALUES (2, 'Almond Milk', 'vegan', 3.49);
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List the suppliers and their respective total revenue for vegan products in Germany.
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SELECT s.name, SUM(p.price) FROM suppliers s JOIN products p ON s.name = p.name WHERE s.country = 'Germany' AND p.type = 'vegan' GROUP BY s.name;
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gretelai_synthetic_text_to_sql
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create table PressureData (Device varchar(255), Pressure int, Timestamp datetime); insert into PressureData values ('Device1', 50, '2022-01-01 01:00:00'), ('Device2', 70, '2022-01-01 02:00:00'), ('Device1', 60, '2022-01-01 03:00:00');
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What is the maximum pressure recorded per device per hour?
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select Device, DATE_PART('hour', Timestamp) as Hour, MAX(Pressure) as MaxPressure from PressureData group by Device, Hour;
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales (sale_id INT, product_id INT, quantity INT, sale_date DATE, is_small_business BOOLEAN); INSERT INTO sales (sale_id, product_id, quantity, sale_date, is_small_business) VALUES (1, 1, 5, '2021-01-01', true); CREATE TABLE products (product_id INT, product_name VARCHAR(255)); INSERT INTO products (product_id, product_name) VALUES (1, 'Handmade Jewelry');
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What is the maximum quantity of products sold by small businesses, pivoted by day?
|
SELECT EXTRACT(DAY FROM sale_date) AS day, is_small_business, MAX(quantity) AS max_quantity FROM sales JOIN products ON sales.product_id = products.product_id WHERE is_small_business = true GROUP BY day, is_small_business;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Players (PlayerID INT, PlayerName VARCHAR(50), Country VARCHAR(50)); INSERT INTO Players (PlayerID, PlayerName, Country) VALUES (1, 'John Doe', 'USA'), (2, 'Jane Smith', 'Canada'); CREATE TABLE EsportsEvents (EventID INT, PlayerID INT, EventName VARCHAR(50)); INSERT INTO EsportsEvents (EventID, PlayerID, EventName) VALUES (1, 3, 'GameX Championship'), (2, 4, 'Battle Royale Cup');
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Which players from the United States and Canada have not participated in any esports events?
|
(SELECT Players.PlayerName FROM Players WHERE Players.Country IN ('USA', 'Canada') EXCEPT SELECT EsportsEvents.PlayerName FROM EsportsEvents)
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gretelai_synthetic_text_to_sql
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CREATE TABLE time_series_data (incident_id INT, incident_type VARCHAR(50), incident_year INT); INSERT INTO time_series_data (incident_id, incident_type, incident_year) VALUES (1, 'Data Privacy', 2021), (2, 'Model Malfunction', 2020), (3, 'Data Privacy', 2021);
|
What is the distribution of AI safety incidents by type in the last 3 years?
|
SELECT incident_type, COUNT(*) as num_incidents, incident_year FROM time_series_data WHERE incident_year >= 2019 GROUP BY incident_type, incident_year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE yearly_acidification (year INT, level FLOAT); INSERT INTO yearly_acidification (year, level) VALUES (2015, 7.6), (2016, 7.7), (2017, 7.8), (2018, 7.8), (2019, 7.7), (2020, 7.6);
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What was the minimum ocean acidification level by year?
|
SELECT year, MIN(level) FROM yearly_acidification;
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gretelai_synthetic_text_to_sql
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CREATE TABLE projects (id INT, name VARCHAR(50), country VARCHAR(50), techniques VARCHAR(50), costs FLOAT); INSERT INTO projects (id, name, country, techniques, costs) VALUES (1, 'ProjectX', 'UK', 'Biosensor technology, bioinformatics', 20000); INSERT INTO projects (id, name, country, techniques, costs) VALUES (2, 'ProjectY', 'UK', 'PCR, bioinformatics', 15000); INSERT INTO projects (id, name, country, techniques, costs) VALUES (3, 'ProjectZ', 'UK', 'Biosensor technology, DNA sequencing', 25000);
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What is the total biosensor technology development cost for projects in the UK?
|
SELECT SUM(costs) FROM projects WHERE country = 'UK' AND techniques LIKE '%Biosensor technology%';
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gretelai_synthetic_text_to_sql
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CREATE TABLE mining_operations (id INT, name TEXT, location TEXT, num_employees INT); INSERT INTO mining_operations (id, name, location, num_employees) VALUES (1, 'Operation X', 'Australia-NSW', 250), (2, 'Operation Y', 'Australia-QLD', 300), (3, 'Operation Z', 'Australia-NSW', 200);
|
What is the average number of employees per mining operation in Australia, partitioned by state?
|
SELECT location, AVG(num_employees) FROM mining_operations WHERE location LIKE 'Australia-%' GROUP BY location;
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gretelai_synthetic_text_to_sql
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CREATE TABLE matches (id INT, player_id INT, opponent_id INT, winner_id INT); INSERT INTO matches VALUES (1, 1, 2, 1); INSERT INTO matches VALUES (2, 2, 1, 2); INSERT INTO matches VALUES (3, 1, 3, 1); INSERT INTO matches VALUES (4, 3, 1, 3);
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What is the win rate for each player in the 'matches' table?
|
SELECT player_id, COUNT(*) * 100.0 / SUM(CASE WHEN player_id IN (player_id, opponent_id) THEN 1 ELSE 0 END) as win_rate FROM matches GROUP BY player_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE union_advocacy_tx (id INT, union_name TEXT, state TEXT, involved_in_advocacy BOOLEAN, members INT); INSERT INTO union_advocacy_tx (id, union_name, state, involved_in_advocacy, members) VALUES (1, 'Union A', 'Texas', true, 500), (2, 'Union B', 'Texas', true, 600), (3, 'Union C', 'Texas', false, 400);
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What is the number of members in unions advocating for labor rights in Texas?
|
SELECT SUM(members) FROM union_advocacy_tx WHERE state = 'Texas' AND involved_in_advocacy = true;
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gretelai_synthetic_text_to_sql
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CREATE TABLE platformD (genre TEXT, revenue INT); CREATE TABLE platformE (genre TEXT, revenue INT); CREATE TABLE platformF (genre TEXT, revenue INT);
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Display the total revenue for the "jazz" genre from all platforms, excluding any platforms that have a revenue lower than $5,000 for that genre.
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SELECT genre, SUM(revenue) FROM (SELECT genre, revenue FROM platformD WHERE genre = 'jazz' AND revenue >= 5000 UNION ALL SELECT genre, revenue FROM platformE WHERE genre = 'jazz' AND revenue >= 5000 UNION ALL SELECT genre, revenue FROM platformF WHERE genre = 'jazz' AND revenue >= 5000) AS combined_platforms GROUP BY genre;
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gretelai_synthetic_text_to_sql
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CREATE TABLE atlantic_ocean (id INT, year INT, species TEXT, sightings INT); INSERT INTO atlantic_ocean (id, year, species, sightings) VALUES (1, 2020, 'Blue Whale', 250);
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How many whales have been spotted in the Atlantic Ocean in 2020?
|
SELECT SUM(sightings) FROM atlantic_ocean WHERE year = 2020 AND species = 'Blue Whale';
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gretelai_synthetic_text_to_sql
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CREATE TABLE menu_engineering(dish VARCHAR(255), category VARCHAR(255), price DECIMAL(5,2), restaurant VARCHAR(255));
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Update the 'Organic Chicken' dish price to $14.00 in the 'Bistro' restaurant.
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UPDATE menu_engineering SET price = 14.00 WHERE dish = 'Organic Chicken' AND restaurant = 'Bistro';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Waste_Production (Plant VARCHAR(255), Waste_Amount INT, Waste_Date DATE); INSERT INTO Waste_Production (Plant, Waste_Amount, Waste_Date) VALUES ('Plant1', 50, '2022-06-01'), ('Plant1', 60, '2022-06-02'), ('Plant2', 30, '2022-06-01'), ('Plant2', 40, '2022-06-02');
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Calculate the average amount of waste produced per day for each manufacturing plant, for the past month, and rank them in descending order.
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SELECT Plant, AVG(Waste_Amount) AS Avg_Waste_Per_Day, RANK() OVER (ORDER BY AVG(Waste_Amount) DESC) AS Rank FROM Waste_Production WHERE Waste_Date >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH) GROUP BY Plant;
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gretelai_synthetic_text_to_sql
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CREATE TABLE fare (fare_id INT, amount DECIMAL, collected_date DATE, route_id INT); INSERT INTO fare VALUES (1, 2.50, '2022-07-01', 1); INSERT INTO fare VALUES (2, 3.00, '2022-07-01', 1); INSERT INTO fare VALUES (3, 2.00, '2022-07-02', 2); INSERT INTO fare VALUES (4, 4.00, '2022-07-02', 2); CREATE TABLE route (route_id INT, name TEXT); INSERT INTO route VALUES (1, 'Route 1'); INSERT INTO route VALUES (2, 'Route 2');
|
Find the average fare for each route
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SELECT r.name, AVG(f.amount) FROM fare f JOIN route r ON f.route_id = r.route_id GROUP BY f.route_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE genetic_research (id INT, project_name VARCHAR(50), location VARCHAR(50)); INSERT INTO genetic_research (id, project_name, location) VALUES (1, 'Project K', 'USA'); INSERT INTO genetic_research (id, project_name, location) VALUES (2, 'Project L', 'Canada');
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Calculate the total number of genetic research projects in the USA.
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SELECT COUNT(*) FROM genetic_research WHERE location = 'USA';
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gretelai_synthetic_text_to_sql
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CREATE TABLE projects (id INT, category VARCHAR(20), volunteer_id INT); INSERT INTO projects (id, category, volunteer_id) VALUES (1, 'Education', 100), (2, 'Environment', 100), (3, 'Health', 200), (4, 'Education', 300);
|
What are the names of volunteers who have worked on projects in both 'Education' and 'Environment' categories?
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SELECT volunteer_id FROM projects WHERE category = 'Education' INTERSECT SELECT volunteer_id FROM projects WHERE category = 'Environment';
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gretelai_synthetic_text_to_sql
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CREATE TABLE carbon_sequestration (id INT, country VARCHAR(255), year INT, sequestration FLOAT, hectares FLOAT); INSERT INTO carbon_sequestration (id, country, year, sequestration, hectares) VALUES (1, 'Canada', 2018, 1000.2, 12000000.5), (2, 'Australia', 2019, 1100.1, 15000000.3), (3, 'Brazil', 2018, 1300.0, 20000000.7), (4, 'Indonesia', 2019, 1500.0, 17500000.6), (5, 'USA', 2020, 1200.8, 13000000.8), (6, 'Canada', 2020, 1150.9, 14000000.9), (7, 'Australia', 2020, 1400.0, 15000000.0);
|
Update the carbon sequestration values for Canada in 2020 by 5%
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UPDATE carbon_sequestration SET sequestration = sequestration * 1.05 WHERE country = 'Canada' AND year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Brands (brand_id INT, brand_name VARCHAR(50), ethical BOOLEAN, region VARCHAR(50)); CREATE TABLE Deliveries (delivery_id INT, delivery_date DATE, brand_id INT);
|
What is the average delivery time for each fair labor practice brand in Asia?
|
SELECT B.brand_name, AVG(DATEDIFF(delivery_date, order_date)) as avg_delivery_time FROM Deliveries D INNER JOIN Orders O ON D.delivery_id = O.order_id INNER JOIN Brands B ON D.brand_id = B.brand_id WHERE B.ethical = TRUE AND B.region = 'Asia' GROUP BY B.brand_name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Naval_Ships (id INT, country VARCHAR(50), type VARCHAR(50), acquisition_date DATE, maintenance_cost FLOAT);
|
What is the average maintenance cost per month for naval ships in Canada?
|
SELECT AVG(maintenance_cost/MONTHS_BETWEEN(acquisition_date, CURRENT_DATE)) FROM Naval_Ships WHERE country = 'Canada';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE genetics_investment(id INT, investment VARCHAR(50), date DATE, amount DECIMAL(10,2)); INSERT INTO genetics_investment VALUES (1, 'InvestmentA', '2022-03-15', 1000000.00), (2, 'InvestmentB', '2022-01-30', 1200000.00), (3, 'InvestmentC', '2022-02-28', 1500000.00);
|
What is the total investment in genetics research in Q1 2022?
|
SELECT SUM(amount) FROM genetics_investment WHERE date BETWEEN '2022-01-01' AND '2022-03-31';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE organizations (id INT, name VARCHAR(50), type VARCHAR(50), country VARCHAR(50)); INSERT INTO organizations (id, name, type, country) VALUES (1, 'Greenpeace Africa', 'NGO', 'Africa'); INSERT INTO organizations (id, name, type, country) VALUES (2, 'Friends of the Earth Africa', 'NGO', 'Africa'); INSERT INTO organizations (id, name, type, country) VALUES (3, 'WildlifeDirect', 'NGO', 'Africa'); INSERT INTO organizations (id, name, type, country) VALUES (4, 'Earthlife Africa', 'NGO', 'Africa'); INSERT INTO organizations (id, name, type, country) VALUES (5, 'African Wildlife Foundation', 'NGO', 'Africa');
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What's the total funding received by environmental NGOs based in Africa since 2015?
|
SELECT o.name, o.country, sum(f.funding) as total_funding FROM organizations o INNER JOIN funding_received f ON o.id = f.organization_id WHERE o.type = 'NGO' AND o.country = 'Africa' AND f.year >= 2015 GROUP BY o.name, o.country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ethical_ai_projects (project_id INT, country VARCHAR(20), completion_year INT); INSERT INTO ethical_ai_projects (project_id, country, completion_year) VALUES (1, 'USA', 2020), (2, 'Canada', 2019), (3, 'Mexico', 2021), (4, 'USA', 2018);
|
How many ethical AI projects were completed in North America last year?
|
SELECT COUNT(*) FROM ethical_ai_projects WHERE country IN ('USA', 'Canada') AND completion_year = 2020;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE visitor_stats (visitor_id INT, city TEXT, visit_date DATE); INSERT INTO visitor_stats (visitor_id, city, visit_date) VALUES (1, 'Paris', '2020-01-01'), (2, 'Paris', '2020-02-14'), (3, 'London', '2020-03-03'), (4, 'Paris', '2020-04-20');
|
How many international visitors arrived in Paris by month in 2020?
|
SELECT city, EXTRACT(MONTH FROM visit_date) AS month, COUNT(DISTINCT visitor_id) AS num_visitors FROM visitor_stats WHERE city = 'Paris' AND EXTRACT(YEAR FROM visit_date) = 2020 GROUP BY city, month ORDER BY month;
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gretelai_synthetic_text_to_sql
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CREATE TABLE security_incidents (id INT, department VARCHAR(20), incident_date DATE); INSERT INTO security_incidents (id, department, incident_date) VALUES (1, 'HR', '2022-01-15'), (2, 'Finance', '2022-02-07'), (3, 'HR', '2022-03-20'), (4, 'HR', '2022-01-01');
|
What is the average number of security incidents per month for the 'HR' department in 2022?
|
SELECT AVG(COUNT(*)) FROM security_incidents WHERE department = 'HR' AND YEAR(incident_date) = 2022 GROUP BY MONTH(incident_date);
|
gretelai_synthetic_text_to_sql
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CREATE TABLE emissions (country VARCHAR(50), year INT, co2_emissions INT); INSERT INTO emissions (country, year, co2_emissions) VALUES ('USA', 2020, 5135), ('China', 2020, 10096), ('India', 2020, 2720), ('Russia', 2020, 2653), ('Japan', 2020, 1140), ('Germany', 2020, 736), ('Iran', 2020, 551), ('Saudi Arabia', 2020, 531), ('South Korea', 2020, 601), ('Indonesia', 2020, 600), ('Canada', 2020, 554), ('Mexico', 2020, 493);
|
Calculate the total CO2 emissions for each country in 2020 from the 'emissions' table
|
SELECT country, SUM(co2_emissions) as total_emissions FROM emissions WHERE year = 2020 GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ca_renewable_energy (id INT, source TEXT, capacity_mw FLOAT); INSERT INTO ca_renewable_energy (id, source, capacity_mw) VALUES (1, 'Wind', 500.0), (2, 'Solar', 1000.0), (3, 'Geothermal', 750.0);
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What is the total installed capacity (MW) of renewable energy sources in California?
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SELECT SUM(capacity_mw) FROM ca_renewable_energy WHERE source IN ('Wind', 'Solar', 'Geothermal');
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gretelai_synthetic_text_to_sql
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