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CREATE TABLE brands (brand_id INT PRIMARY KEY, brand_name VARCHAR(255), brand_country VARCHAR(100), brand_status VARCHAR(20));
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Update 'brand_status' to 'Inactive' for 'brand_name' 'Nature's Beauty' in the 'brands' table
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UPDATE brands SET brand_status = 'Inactive' WHERE brand_name = 'Nature''s Beauty';
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gretelai_synthetic_text_to_sql
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CREATE TABLE donors (id INT, name VARCHAR(255)); INSERT INTO donors (id, name) VALUES (1, 'Effective Altruism Funds'); CREATE TABLE donations (id INT, donor_id INT, organization_id INT, amount DECIMAL(10,2), donation_date DATE); INSERT INTO donations (id, donor_id, organization_id, amount, donation_date) VALUES (1, 1, 3, 5000, '2021-06-15');
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List the names of all donors who have not donated in the past year.
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SELECT name FROM donors WHERE id NOT IN (SELECT donor_id FROM donations WHERE donation_date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 1 YEAR) AND CURRENT_DATE);
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gretelai_synthetic_text_to_sql
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CREATE TABLE international_bridges (id INT, name VARCHAR(50), country VARCHAR(50), length FLOAT); INSERT INTO international_bridges VALUES (1, 'Akashi Kaikyō', 'Japan', 3911), (2, 'Great Belt', 'Denmark', 6790), (3, 'Changhua-Kaohsiung', 'Taiwan', 1573);
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What is the maximum length of a bridge in each country?
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SELECT country, MAX(length) FROM international_bridges GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE cases (case_id INT, case_type VARCHAR(10), created_at TIMESTAMP); INSERT INTO cases (case_id, case_type, created_at) VALUES (1, 'civil', '2020-01-01 10:00:00'), (2, 'criminal', '2021-02-15 14:30:00'), (3, 'traffic', '2021-12-31 23:59:59');
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Delete records from the 'cases' table where the case_type is 'traffic' and created_at is in 2021
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DELETE FROM cases WHERE case_type = 'traffic' AND created_at >= '2021-01-01 00:00:00' AND created_at <= '2021-12-31 23:59:59';
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gretelai_synthetic_text_to_sql
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CREATE TABLE vulnerability_timeline(id INT, severity VARCHAR(50), vulnerability_date DATE, vulnerabilities INT);
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What is the maximum number of simultaneous high severity vulnerabilities that have been discovered in the past month?
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SELECT severity, MAX(vulnerabilities) as max_simultaneous_vulnerabilities FROM vulnerability_timeline WHERE severity = 'high' AND vulnerability_date > DATE(NOW()) - INTERVAL 30 DAY;
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gretelai_synthetic_text_to_sql
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CREATE TABLE bridges (id INT, name TEXT, region TEXT, resilience_score FLOAT, year_built INT); INSERT INTO bridges (id, name, region, resilience_score, year_built) VALUES (1, 'Golden Gate Bridge', 'West Coast', 85.2, 1937), (2, 'Brooklyn Bridge', 'East Coast', 76.3, 1883), (3, 'Bay Bridge', 'West Coast', 90.1, 1936), (4, 'George Washington Bridge', 'Northeast', 88.5, 1931), (5, 'Tappan Zee Bridge', 'Northeast', 82.7, 1955), (6, 'Sunshine Skyway Bridge', 'South', 89.6, 2005), (7, 'Ambassador Bridge', 'Midwest', 84.9, 1929);
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What is the minimum 'resilience_score' of bridges in the 'Midwest' region that were built before 2010?
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SELECT MIN(resilience_score) FROM bridges WHERE region = 'Midwest' AND year_built < 2010;
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gretelai_synthetic_text_to_sql
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CREATE TABLE funding (id INT, company_id INT, amount DECIMAL(10, 2), funding_year INT); CREATE TABLE company (id INT, name VARCHAR(255), founding_year INT); INSERT INTO company (id, name, founding_year) VALUES (1, 'Fintech Inc', 2018), (2, 'Startup Corp', 2019), (3, 'Green Inc', 2020); INSERT INTO funding (id, company_id, amount, funding_year) VALUES (1, 1, 500000.00, 2019), (2, 1, 750000.00, 2020), (3, 2, 250000.00, 2019), (4, 3, 300000.00, 2020), (5, 3, 400000.00, 2021);
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What is the total funding amount for companies founded in the year 2020?
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SELECT SUM(amount) FROM funding INNER JOIN company ON funding.company_id = company.id WHERE funding.funding_year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AISafetyIncidents (incident_id INTEGER, incident_date DATE, region TEXT); CREATE TABLE AIModels (model_id INTEGER, model_name TEXT); INSERT INTO AISafetyIncidents (incident_id, incident_date, region) VALUES (1, '2022-01-01', 'North America'), (2, '2022-04-01', 'North America'); INSERT INTO AIModels (model_id, model_name) VALUES (1, 'ModelA'), (2, 'ModelB');
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List AI safety incidents in North America, cross-joined with AI model details.
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SELECT AISafetyIncidents.incident_date, AIModels.model_name FROM AISafetyIncidents CROSS JOIN AIModels WHERE AISafetyIncidents.region = 'North America';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Aid_Donors (id INT, name TEXT, type TEXT); INSERT INTO Aid_Donors (id, name, type) VALUES (1, 'USA', 'Government'), (2, 'Germany', 'Government'), (3, 'Saudi Arabia', 'Government'), (4, 'UK', 'Government'); CREATE TABLE Aid_Contributions (id INT, donor_id INT, crisis TEXT, amount INT, contribution_date DATE); INSERT INTO Aid_Contributions (id, donor_id, crisis, amount, contribution_date) VALUES (1, 1, 'Rohingya Refugee Crisis', 15000000, '2018-01-01'), (2, 2, 'Rohingya Refugee Crisis', 12000000, '2018-02-15'), (3, 3, 'Rohingya Refugee Crisis', 18000000, '2018-03-30'), (4, 4, 'Rohingya Refugee Crisis', 10000000, '2018-04-15');
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What is the total amount of aid contributed by each government to the Rohingya refugee crisis, and the percentage of the total contribution made by each government?
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SELECT A.name as donor_name, SUM(AC.amount) as total_contribution, (SUM(AC.amount) / (SELECT SUM(amount) FROM Aid_Contributions WHERE crisis = 'Rohingya Refugee Crisis')) * 100 as contribution_percentage FROM Aid_Contributions AC INNER JOIN Aid_Donors A ON AC.donor_id = A.id WHERE AC.crisis = 'Rohingya Refugee Crisis' GROUP BY A.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE hotels_types (hotel_id INT, type TEXT); CREATE TABLE bookings (booking_id INT, hotel_id INT, revenue FLOAT);
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What is the average revenue per booking for 'Luxury' hotels in 'New York'?
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SELECT AVG(subquery.revenue) FROM (SELECT hotel_id, AVG(revenue) as revenue FROM bookings WHERE hotel_id IN (SELECT hotel_id FROM hotels_types WHERE type = 'Luxury') GROUP BY hotel_id) as subquery WHERE subquery.hotel_id IN (SELECT hotel_id FROM hotels WHERE city = 'New York');
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gretelai_synthetic_text_to_sql
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CREATE TABLE movie_ratings (user_id INT, movie_id INT, rating FLOAT);
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Insert records into the 'movie_ratings' table
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INSERT INTO movie_ratings (user_id, movie_id, rating) VALUES (1, 123, 4.5);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Geopolitical_Risk_Assessments (assessment_id INT, assessment_date DATE, country VARCHAR(50)); INSERT INTO Geopolitical_Risk_Assessments (assessment_id, assessment_date, country) VALUES (1, '2018-05-12', 'Egypt'), (2, '2019-07-03', 'Egypt'), (3, '2020-11-28', 'Egypt');
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How many geopolitical risk assessments have been conducted for Egypt since 2018?
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SELECT COUNT(assessment_id) FROM Geopolitical_Risk_Assessments WHERE assessment_date >= '2018-01-01' AND country = 'Egypt';
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gretelai_synthetic_text_to_sql
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CREATE TABLE military_innovation (innovation_id SERIAL PRIMARY KEY, innovation_name VARCHAR(255), innovation_type VARCHAR(255), classification VARCHAR(255));
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Update the table 'military_innovation' and set the 'classification' to 'public' for all records where the 'innovation_type' is 'cybersecurity'
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WITH cte_cybersecurity AS (UPDATE military_innovation SET classification = 'public' WHERE innovation_type = 'cybersecurity' RETURNING innovation_id, innovation_name, innovation_type, classification) SELECT * FROM cte_cybersecurity;
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gretelai_synthetic_text_to_sql
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CREATE TABLE artists (id INT, name VARCHAR(255), year_of_birth INT); CREATE TABLE artworks (id INT, artist_id INT, category VARCHAR(255), year_of_creation INT);
|
What is the average age of artists who have created artworks in the abstract category?
|
SELECT AVG(YEAR(CURRENT_DATE) - year_of_birth) FROM artists a JOIN artworks aw ON a.id = aw.artist_id WHERE category = 'Abstract';
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gretelai_synthetic_text_to_sql
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CREATE TABLE shariah_compliant_loans (loan_id INT, customer_id INT, amount DECIMAL(10, 2), issue_date DATE); INSERT INTO shariah_compliant_loans (loan_id, customer_id, amount, issue_date) VALUES (1, 101, 5000.00, '2021-01-01'), (2, 102, 7000.00, '2021-02-01');
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What is the total amount of Shariah-compliant loans issued to customers in January 2021?
|
SELECT SUM(amount) FROM shariah_compliant_loans WHERE MONTH(issue_date) = 1 AND YEAR(issue_date) = 2021;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE unions (id INT, name VARCHAR(255), country VARCHAR(255));INSERT INTO unions (id, name, country) VALUES (1, 'UNI', 'Europe'), (2, 'CGT', 'France'), (3, 'UGT', 'Spain');CREATE TABLE members (id INT, union_id INT, joined DATE);INSERT INTO members (id, union_id, joined) VALUES (1, 1, '2018-01-01'), (2, 1, '2020-05-15'), (3, 2, '2017-08-28'), (4, 2, '2021-09-03'), (5, 3, '2019-12-31'), (6, 3, '2022-02-14');
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How many new union members joined from historically underrepresented communities in Europe in the last 5 years, and which unions were they?
|
SELECT unions.name, COUNT(members.id) as new_members FROM unions JOIN members ON unions.id = members.union_id WHERE unions.country = 'Europe' AND members.joined BETWEEN DATE_SUB(NOW(), INTERVAL 5 YEAR) AND NOW() AND unions.name IN ('UNI', 'CGT', 'UGT') GROUP BY unions.name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Visitors (id INT, race VARCHAR(20), city VARCHAR(20), num_visitors INT); INSERT INTO Visitors (id, race, city, num_visitors) VALUES (1, 'Black', 'Chicago', 200), (2, 'Indigenous', 'Detroit', 150), (3, 'Latinx', 'St. Louis', 250);
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What is the total number of visitors who identified as BIPOC and attended exhibitions in the Midwest?
|
SELECT SUM(num_visitors) FROM Visitors WHERE race IN ('Black', 'Indigenous', 'Latinx') AND city IN ('Chicago', 'Detroit', 'St. Louis');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE deep_sea_exploration (vessel TEXT, year INT);
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Insert a new record for a deep-sea exploration conducted by the Alvin in the year 2022
|
INSERT INTO deep_sea_exploration (vessel, year) VALUES ('Alvin', 2022);
|
gretelai_synthetic_text_to_sql
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CREATE TABLE Events (event_name TEXT, city TEXT, type TEXT); INSERT INTO Events (event_name, city, type) VALUES ('Art Exhibition', 'Los Angeles', 'Art'), ('Art Exhibition', 'San Francisco', 'Art');
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How many art exhibitions were held in Los Angeles and San Francisco combined?
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SELECT COUNT(*) FROM Events WHERE city IN ('Los Angeles', 'San Francisco') AND type = 'Art Exhibition';
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gretelai_synthetic_text_to_sql
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CREATE TABLE china_india_tourism (region TEXT, revenue FLOAT); INSERT INTO china_india_tourism (region, revenue) VALUES ('India', 3000000), ('China', 1500000);
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What is the average revenue of sustainable tourism in India and China?
|
SELECT AVG(revenue) FROM china_india_tourism WHERE region IN ('India', 'China');
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gretelai_synthetic_text_to_sql
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CREATE TABLE rd_expenditure (id INT PRIMARY KEY, drug_id INT, year INT, amount DECIMAL(10,2)); CREATE TABLE drugs (id INT PRIMARY KEY, name VARCHAR(255), manufacturer VARCHAR(255), approval_date DATE);
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What is the maximum R&D expenditure per year for drugs that were approved after 2017?
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SELECT MAX(amount) as max_annual_rd_expenditure FROM rd_expenditure JOIN drugs ON rd_expenditure.drug_id = drugs.id WHERE approval_date > '2017-01-01' GROUP BY rd_expenditure.year;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Members (Id INT, Name VARCHAR(50), Age INT, Nationality VARCHAR(50)); INSERT INTO Members (Id, Name, Age, Nationality) VALUES (8, 'Emma Wilson', 27, 'Australia'), (9, 'Liam Thompson', 38, 'New Zealand'); CREATE TABLE Workouts (Id INT, MemberId INT, WorkoutType VARCHAR(50), Duration INT, Date DATE); INSERT INTO Workouts (Id, MemberId, WorkoutType, Duration, Date) VALUES (9, 8, 'Running', 30, '2022-01-09'), (10, 9, 'Walking', 45, '2022-01-10'), (11, 8, 'Cycling', 60, '2022-01-11');
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What is the number of distinct workout types done by each member, excluding members who have only done 'Walking'?
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SELECT w.MemberId, COUNT(DISTINCT w.WorkoutType) as DistinctWorkoutTypes FROM Workouts w WHERE w.MemberId IN (SELECT m.Id FROM Members m EXCEPT (SELECT m.Id FROM Members m JOIN Workouts w ON m.Id = w.MemberId WHERE w.WorkoutType = 'Walking')) GROUP BY w.MemberId;
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gretelai_synthetic_text_to_sql
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CREATE TABLE RenewableEnergyProjects (id INT, name TEXT, location TEXT, category TEXT); INSERT INTO RenewableEnergyProjects (id, name, location, category) VALUES (1, 'SolarFarm1', 'Texas', 'Solar'), (2, 'WindFarm1', 'Oklahoma', 'Wind'), (3, 'SolarFarm2', 'Nevada', 'Solar');
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Identify the number of renewable energy projects in 'Solar' and 'Wind' categories.
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SELECT COUNT(*), category FROM RenewableEnergyProjects WHERE category IN ('Solar', 'Wind') GROUP BY category;
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gretelai_synthetic_text_to_sql
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CREATE TABLE menus (id INT, name VARCHAR(255), type VARCHAR(255), price DECIMAL(5,2)); INSERT INTO menus (id, name, type, price) VALUES (1, 'Veggie Burger', 'Vegan', 9.99); INSERT INTO menus (id, name, type, price) VALUES (2, 'Tofu Stir Fry', 'Vegan', 12.49);
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Find the average price of vegan menu items
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SELECT type, AVG(price) FROM menus WHERE type = 'Vegan';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE mining_sites (id INT, site_name TEXT); CREATE TABLE environmental_impact_scores (site_id INT, score FLOAT); INSERT INTO mining_sites (id, site_name) VALUES (1, 'siteA'), (2, 'siteB'), (3, 'siteC'); INSERT INTO environmental_impact_scores (site_id, score) VALUES (1, 85.0), (2, 78.0), (3, 92.0);
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Which mining sites have no recorded environmental impact scores?
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SELECT mining_sites.site_name FROM mining_sites LEFT JOIN environmental_impact_scores ON mining_sites.id = environmental_impact_scores.site_id WHERE environmental_impact_scores.score IS NULL;
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gretelai_synthetic_text_to_sql
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CREATE TABLE claims (id INT, underwriter_id INT, processed_date DATE); INSERT INTO claims (id, underwriter_id, processed_date) VALUES (1, 1, '2021-01-01'), (2, 2, '2021-02-01'), (3, 1, '2021-03-01');
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What is the total number of claims processed for each underwriter?
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SELECT underwriter_id, COUNT(*) FROM claims GROUP BY underwriter_id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE startups(id INT, name TEXT, founder_lgbtqia INT, industry TEXT, funding FLOAT); INSERT INTO startups VALUES (1, 'StartupG', 1, 'Biotech', 7000000);
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What is the average funding amount for startups founded by individuals who identify as LGBTQIA+ in the Biotech sector?
|
SELECT AVG(funding) FROM startups WHERE industry = 'Biotech' AND founder_lgbtqia = 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE athletes (athlete_id INT, name VARCHAR(50), age INT, sport VARCHAR(20));
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Show the number of athletes in each age group (0-20, 21-30, 31-40, 41-50, 51+) from the 'athletes' table.
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SELECT CASE WHEN age BETWEEN 0 AND 20 THEN '0-20' WHEN age BETWEEN 21 AND 30 THEN '21-30' WHEN age BETWEEN 31 AND 40 THEN '31-40' WHEN age BETWEEN 41 AND 50 THEN '41-50' ELSE '51+' END AS age_group, COUNT(*) FROM athletes GROUP BY age_group;
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gretelai_synthetic_text_to_sql
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CREATE TABLE customer_size_diversity (id INT PRIMARY KEY, customer_id INT, size VARCHAR(10), height INT, weight INT);
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Display all customers with size 'L' from 'customer_size_diversity' table
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SELECT * FROM customer_size_diversity WHERE size = 'L';
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gretelai_synthetic_text_to_sql
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CREATE TABLE CityVisitors (id INT, city VARCHAR(50), year INT, num_visitors INT);
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Which cities had more than 100,000 visitors in 2021?
|
SELECT city, SUM(num_visitors) FROM CityVisitors WHERE year = 2021 GROUP BY city HAVING SUM(num_visitors) > 100000;
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gretelai_synthetic_text_to_sql
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CREATE SCHEMA community_development; Use community_development; CREATE TABLE comm_dev_initiatives (initiative_code VARCHAR(20), start_date DATE); INSERT INTO comm_dev_initiatives (initiative_code, start_date) VALUES ('CD1', '2022-01-01'), ('CD2', '2021-05-15'), ('CD3', '2022-07-20');
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List all unique community development initiative codes and their corresponding start dates in the 'community_development' schema, sorted by start date in ascending order.
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SELECT DISTINCT initiative_code, start_date FROM community_development.comm_dev_initiatives ORDER BY start_date ASC;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE hospitals (id INT, name VARCHAR(50), location VARCHAR(20)); INSERT INTO hospitals (id, name, location) VALUES (1, 'Hospital A', 'rural Alabama');
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How many hospitals are there in rural Alabama?
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SELECT COUNT(*) FROM hospitals WHERE location = 'rural Alabama';
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gretelai_synthetic_text_to_sql
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CREATE TABLE buildings (id INT, name TEXT, city TEXT, state TEXT, is_green_certified BOOLEAN);
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How many green-certified buildings are in Seattle?
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SELECT COUNT(*) FROM buildings WHERE city = 'Seattle' AND is_green_certified = TRUE;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE climate_adaptation_projects ( id INT, name VARCHAR(255), location VARCHAR(255), strategy VARCHAR(255) ); INSERT INTO climate_adaptation_projects (id, name, location, strategy) VALUES (1, 'Project B', 'Pacific Islands', 'Educational outreach'); INSERT INTO climate_adaptation_projects (id, name, location, strategy) VALUES (2, 'Project C', 'Fiji', 'Community workshops');
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List all unique communication strategies used in climate adaptation projects in the Pacific region, not including those in small island states.
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SELECT DISTINCT strategy FROM climate_adaptation_projects WHERE location NOT IN ('Pacific Islands', 'Small Island States');
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gretelai_synthetic_text_to_sql
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CREATE TABLE investments(id INT, region VARCHAR(10), investment_date DATE, amount INT);
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What is the average investment in network infrastructure for the current quarter in each region?
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SELECT investments.region, AVG(investments.amount) FROM investments WHERE QUARTER(investments.investment_date) = QUARTER(CURRENT_DATE) GROUP BY investments.region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE marine_research_funding (id INT PRIMARY KEY, project_name VARCHAR(50), location VARCHAR(50), amount DECIMAL(10,2), start_date DATE, end_date DATE);
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How much research funding is allocated for projects in the Pacific region?
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SELECT SUM(amount) as total_funding FROM marine_research_funding WHERE location = 'Pacific';
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gretelai_synthetic_text_to_sql
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CREATE TABLE tv_shows (id INT, title VARCHAR(100), release_year INT, runtime INT, genre VARCHAR(20)); INSERT INTO tv_shows (id, title, release_year, runtime, genre) VALUES (1, 'TVShow1', 2018, 600, 'Drama'); INSERT INTO tv_shows (id, title, release_year, runtime, genre) VALUES (2, 'TVShow2', 2019, 720, 'Drama'); INSERT INTO tv_shows (id, title, release_year, runtime, genre) VALUES (3, 'TVShow3', 2020, 500, 'Comedy'); INSERT INTO tv_shows (id, title, release_year, runtime, genre) VALUES (4, 'TVShow4', 2021, 800, 'Action'); INSERT INTO tv_shows (id, title, release_year, runtime, genre) VALUES (5, 'TVShow5', 2019, 650, 'Korean Drama');
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What's the total runtime for Korean dramas released in 2019?
|
SELECT SUM(runtime) FROM tv_shows WHERE release_year = 2019 AND genre = 'Korean Drama';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE forest_timber (id INT, region VARCHAR(20), year INT, volume FLOAT);
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Find the percentage of total timber volume that comes from boreal forests in the last 3 years.
|
SELECT region, (SUM(volume) / (SELECT SUM(volume) FROM forest_timber WHERE year BETWEEN 2019 AND 2021) * 100) as pct_volume FROM forest_timber WHERE region = 'Boreal' AND year BETWEEN 2019 AND 2021 GROUP BY region;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Members (id INT, state VARCHAR(2), zip INT); INSERT INTO Members (id, state, zip) VALUES (1, 'CA', 90001), (2, 'CA', 90002); CREATE TABLE Workouts (member_id INT, duration INT, calories INT, workout_date DATE); INSERT INTO Workouts (member_id, duration, calories, workout_date) VALUES (1, 60, 250, '2022-01-01'), (1, 45, 200, '2022-01-02'), (2, 90, 400, '2022-01-01');
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List the total workout time and calories burned for members in California, per ZIP code.
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SELECT m.zip, SUM(w.duration) as total_time, SUM(w.calories) as total_calories FROM Members m JOIN Workouts w ON m.id = w.member_id WHERE m.state = 'CA' GROUP BY m.zip;
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gretelai_synthetic_text_to_sql
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CREATE TABLE drought_impact(region VARCHAR(50), year INT, score INT); INSERT INTO drought_impact(region, year, score) VALUES ('Texas', 2019, 80), ('Texas', 2020, 85), ('Texas', 2021, 90);
|
What is the average drought impact score for Texas in the last 3 years?
|
SELECT AVG(score) FROM drought_impact WHERE region = 'Texas' AND year BETWEEN (YEAR(CURRENT_DATE)-3) AND YEAR(CURRENT_DATE);
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gretelai_synthetic_text_to_sql
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CREATE TABLE subscriber_data (subscriber_id INT, plan_type VARCHAR(20), data_usage FLOAT); INSERT INTO subscriber_data VALUES (1, 'Basic', 2.5), (2, 'Premium', 4.7), (3, 'Basic', 3.2);
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What is the average data usage for each mobile plan in the 'subscriber_data' table, grouped by plan type?
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SELECT plan_type, AVG(data_usage) FROM subscriber_data GROUP BY plan_type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE ocean_floor_mapping(id INT, region VARCHAR(20), depth FLOAT); INSERT INTO ocean_floor_mapping(id, region, depth) VALUES (1, 'Pacific', 5000.5), (2, 'Atlantic', 4500.3), (3, 'Pacific', 6200.7), (4, 'Indian', 4200.0);
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What is the minimum depth of ocean floor mapping projects in the Atlantic region?
|
SELECT MIN(depth) FROM ocean_floor_mapping WHERE region = 'Atlantic';
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gretelai_synthetic_text_to_sql
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CREATE TABLE satellite_deployments (id INT, satellite_id INT, country VARCHAR(255), altitude INT); INSERT INTO satellite_deployments (id, satellite_id, country, altitude) VALUES (1, 1, 'China', 50000000);
|
What is the maximum altitude reached by any satellite deployed by China?
|
SELECT MAX(altitude) FROM satellite_deployments WHERE country = 'China';
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gretelai_synthetic_text_to_sql
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CREATE TABLE songs (song_id INT, genre VARCHAR(20), release_year INT, streams INT); INSERT INTO songs (song_id, genre, release_year, streams) VALUES (1, 'rock', 2022, 4000); INSERT INTO songs (song_id, genre, release_year, streams) VALUES (2, 'rock', 2022, 5000); INSERT INTO songs (song_id, genre, release_year, streams) VALUES (3, 'rock', 2022, 6000);
|
What is the minimum number of streams for rock songs released in 2022?
|
SELECT MIN(streams) FROM songs WHERE genre = 'rock' AND release_year = 2022;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE articles (title VARCHAR(255), author VARCHAR(255), date DATE, topic VARCHAR(255));
|
Update the articles table to set the topic to 'disinformation' for articles published by 'Dan' with the date 2022-03-14.
|
UPDATE articles SET topic = 'disinformation' WHERE author = 'Dan' AND date = '2022-03-14';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Players (PlayerID INT, Age INT, Gender VARCHAR(10)); INSERT INTO Players (PlayerID, Age, Gender) VALUES (1, 25, 'Male'); INSERT INTO Players (PlayerID, Age, Gender) VALUES (2, 30, 'Female');
|
Show players' gender distribution in the 'Players' table.
|
SELECT Gender, COUNT(*) as Count FROM Players GROUP BY Gender;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE hospitals (city VARCHAR(50), year INT, count INT);
|
How many hospitals are there in Tokyo, Japan as of 2020?
|
SELECT count FROM hospitals WHERE city = 'Tokyo' AND year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE posts (id INT, user_id INT, brand_mentioned VARCHAR(255), likes INT, shares INT, post_time DATETIME);
|
What is the total number of likes and shares on posts mentioning the brand "Google" in the technology industry, in India, in the past month?
|
SELECT SUM(likes + shares) FROM posts WHERE brand_mentioned = 'Google' AND industry = 'technology' AND country = 'India' AND post_time > DATE_SUB(NOW(), INTERVAL 1 MONTH);
|
gretelai_synthetic_text_to_sql
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CREATE TABLE space_missions (mission_id INT, mission_name VARCHAR(50), launch_date DATE, return_date DATE, mission_company VARCHAR(50));
|
What is the earliest launch date for a space mission for SpaceX?
|
SELECT MIN(launch_date) AS earliest_launch_date FROM space_missions WHERE mission_company = 'SpaceX';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE transport (id INT, method VARCHAR(50), frequency INT); INSERT INTO transport (id, method, frequency) VALUES (1, 'Bicycle', 1500), (2, 'Private Car', 8000), (3, 'Public Bus', 4000), (4, 'Subway', 3500), (5, 'Motorcycle', 600), (6, 'Tram', 2000);
|
Show the transportation methods in the 'city_transport' database that have a frequency higher than 'Bus' and 'Subway'.
|
SELECT method FROM transport WHERE frequency > (SELECT frequency FROM transport WHERE method = 'Bus') AND frequency > (SELECT frequency FROM transport WHERE method = 'Subway');
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gretelai_synthetic_text_to_sql
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CREATE TABLE Vessels (VesselID INT, VesselName VARCHAR(100), VesselType VARCHAR(100), PortID INT); INSERT INTO Vessels (VesselID, VesselName, VesselType, PortID) VALUES (1, 'Kota Pertama', 'Container Ship', 1); CREATE TABLE Cargo (CargoID INT, CargoName VARCHAR(100), Quantity INT, VesselID INT); INSERT INTO Cargo (CargoID, CargoName, Quantity, VesselID) VALUES (1, 'Textiles', 8000, 1); INSERT INTO Cargo (CargoID, CargoName, Quantity, VesselID) VALUES (2, 'Machinery', 6000, 2); CREATE TABLE VesselTypes (VesselTypeID INT, VesselType VARCHAR(100)); INSERT INTO VesselTypes (VesselTypeID, VesselType) VALUES (1, 'Container Ship'); INSERT INTO VesselTypes (VesselTypeID, VesselType) VALUES (2, 'Ro-Ro Ship');
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What is the total quantity of textiles transported by container ships?
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SELECT SUM(Cargo.Quantity) FROM Cargo INNER JOIN Vessels ON Cargo.VesselID = Vessels.VesselID INNER JOIN VesselTypes ON Vessels.VesselType = VesselTypes.VesselType WHERE VesselTypes.VesselType = 'Container Ship' AND Cargo.CargoName = 'Textiles';
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gretelai_synthetic_text_to_sql
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CREATE TABLE conferences (id INT, country VARCHAR(50), conference_year INT, conference_type VARCHAR(50)); INSERT INTO conferences (id, country, conference_year, conference_type) VALUES (1, 'Japan', 2022, 'Sustainable Tourism'), (2, 'Japan', 2021, 'Sustainable Tourism'), (3, 'Japan', 2020, 'Sustainable Tourism'), (4, 'Japan', 2019, 'Sustainable Tourism');
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How many sustainable tourism conferences were held in Japan in 2022?
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SELECT COUNT(*) FROM conferences WHERE country = 'Japan' AND conference_year = 2022 AND conference_type = 'Sustainable Tourism';
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gretelai_synthetic_text_to_sql
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CREATE TABLE cosmetics.eyeshadow_data (eyeshadow_id INT, finish VARCHAR(20), country VARCHAR(50)); INSERT INTO cosmetics.eyeshadow_data (eyeshadow_id, finish, country) VALUES (1, 'Matte', 'Germany'), (2, 'Shimmer', 'Germany'), (3, 'Glitter', 'Germany'), (4, 'Matte', 'Spain'), (5, 'Shimmer', 'France');
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What is the most popular eyeshadow finish among consumers in Germany?
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SELECT finish, COUNT(*) as countOfFinish FROM cosmetics.eyeshadow_data WHERE country = 'Germany' GROUP BY finish ORDER BY countOfFinish DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE marine_species (id INT, name TEXT, region TEXT); CREATE TABLE conservation_status (id INT, species_id INT, status TEXT); INSERT INTO marine_species (id, name, region) VALUES (1, 'Beluga Whale', 'Arctic'); INSERT INTO conservation_status (id, species_id, status) VALUES (1, 1, 'Vulnerable');
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List all marine species and their conservation status in the Arctic region.
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SELECT marine_species.name, conservation_status.status FROM marine_species INNER JOIN conservation_status ON marine_species.id = conservation_status.species_id WHERE marine_species.region = 'Arctic';
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gretelai_synthetic_text_to_sql
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CREATE TABLE spacecrafts (manufacturer VARCHAR(255), mass FLOAT, manufacture_date DATE); INSERT INTO spacecrafts (manufacturer, mass, manufacture_date) VALUES ('SpaceCorp', 10000, '2010-01-01'); INSERT INTO spacecrafts (manufacturer, mass, manufacture_date) VALUES ('SpaceCorp', 12000, '2012-03-14'); INSERT INTO spacecrafts (manufacturer, mass, manufacture_date) VALUES ('Galactic Inc', 15000, '2015-06-28');
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Find the average mass of spacecrafts manufactured by SpaceCorp between 2010 and 2015
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SELECT AVG(mass) FROM spacecrafts WHERE manufacturer = 'SpaceCorp' AND manufacture_date BETWEEN '2010-01-01' AND '2015-12-31';
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gretelai_synthetic_text_to_sql
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CREATE TABLE collective_bargaining (bargaining_id INT, union_name VARCHAR(50), company_name VARCHAR(50), contract_start_date DATE, contract_end_date DATE);CREATE VIEW union_region AS SELECT union_name, 'Southeast' as region FROM collective_bargaining GROUP BY union_name;
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What is the average contract length for unions in the Southeast region?
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SELECT AVG(DATEDIFF(contract_end_date, contract_start_date)) as avg_contract_length FROM collective_bargaining cb JOIN union_region ur ON cb.union_name = ur.union_name WHERE ur.region = 'Southeast';
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gretelai_synthetic_text_to_sql
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CREATE TABLE meals (user_id INT, meal_date DATE, calories INT); INSERT INTO meals (user_id, meal_date, calories) VALUES (1, '2022-01-01', 1200), (1, '2022-01-02', 800), (2, '2022-01-01', 600); CREATE TABLE users (user_id INT, country VARCHAR(255)); INSERT INTO users (user_id, country) VALUES (1, 'Brazil'), (2, 'USA'), (3, 'Brazil');
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Show the percentage of meals in Brazil with more than 1000 calories.
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SELECT 100.0 * COUNT(*) / (SELECT COUNT(*) FROM meals JOIN users ON meals.user_id = users.user_id WHERE users.country = 'Brazil') as pct_meals FROM meals JOIN users ON meals.user_id = users.user_id WHERE users.country = 'Brazil' AND calories > 1000;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Crop (id INT, farm_id INT, crop_type VARCHAR(255), location VARCHAR(255)); INSERT INTO Crop (id, farm_id, crop_type, location) VALUES (1, 1001, 'Wheat', 'AU-WA');
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List all the unique crop types grown in "AU-WA" and "ZA-WC".
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SELECT DISTINCT crop_type FROM Crop WHERE location IN ('AU-WA', 'ZA-WC');
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gretelai_synthetic_text_to_sql
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CREATE TABLE staff_details (id INT, name VARCHAR(50), department VARCHAR(50), salary FLOAT); INSERT INTO staff_details (id, name, department, salary) VALUES (1, 'Alex Jones', 'human_resources', 65000.00), (2, 'Jessica Lee', 'human_resources', 70000.00), (3, 'Taylor Garcia', 'environmental_compliance', 68000.00);
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What is the average salary for employees in the 'human_resources' and 'environmental_compliance' departments?
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SELECT department, AVG(salary) as avg_salary FROM (SELECT department, salary FROM staff_details WHERE department = 'human_resources' UNION SELECT department, salary FROM staff_details WHERE department = 'environmental_compliance') AS combined_departments GROUP BY department;
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gretelai_synthetic_text_to_sql
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CREATE TABLE species_density (id INT, species VARCHAR(255), density FLOAT);
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List the names and average stocking density of fish species with density > 25
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SELECT species, AVG(density) FROM species_density WHERE density > 25 GROUP BY species;
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gretelai_synthetic_text_to_sql
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CREATE TABLE media_content (content_id INT, country VARCHAR(50), genre VARCHAR(50), coverage INT); INSERT INTO media_content (content_id, country, genre, coverage) VALUES (1, 'USA', 'News', 500), (2, 'Canada', 'Entertainment', 300), (3, 'Mexico', 'Sports', 400);
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What is the minimum coverage of news media in the media_content table?
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SELECT MIN(coverage) as min_coverage FROM media_content WHERE genre = 'News';
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gretelai_synthetic_text_to_sql
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CREATE TABLE MonitoringStation (ID INT, Name VARCHAR(100), Location VARCHAR(100), Elevation FLOAT, AnnualTemp FLOAT); INSERT INTO MonitoringStation (ID, Name, Location, Elevation, AnnualTemp) VALUES (1, 'Station X', 'Svalbard', 150, 2.5); INSERT INTO MonitoringStation (ID, Name, Location, Elevation, AnnualTemp) VALUES (2, 'Station Y', 'Greenland', 250, 3.0);
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What is the average temperature change in the past 3 years for each monitoring station?
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SELECT Name, AVG(AnnualTemp) OVER (PARTITION BY Name ORDER BY Name ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS AvgAnnualTemp FROM MonitoringStation WHERE YEAR(CurrentDate) - YEAR(DateInstalled) BETWEEN 1 AND 3;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Museums (Name VARCHAR(50), Attendance INT, Year INT);
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Add a new museum with attendance of 8000 in 2021
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INSERT INTO Museums (Name, Attendance, Year) VALUES ('New Museum', 8000, 2021)
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gretelai_synthetic_text_to_sql
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CREATE TABLE Infrastructure_Projects (Project_ID INT, Project_Name VARCHAR(50), Project_Type VARCHAR(50), Completion_Date DATE); INSERT INTO Infrastructure_Projects (Project_ID, Project_Name, Project_Type, Completion_Date) VALUES (1, 'Seawall', 'Resilience', '2021-02-28'), (2, 'Floodgate', 'Resilience', '2020-12-31'), (3, 'Bridge_Replacement', 'Transportation', '2021-01-31');
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What are the names and completion dates of all resilience projects in the infrastructure database?
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SELECT Project_Name, Completion_Date FROM Infrastructure_Projects WHERE Project_Type = 'Resilience';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Producers (ProducerID INT PRIMARY KEY, Name TEXT, ProductionYear INT, RareEarth TEXT, Quantity INT, Location TEXT);
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Display the names of companies that reduced their Europium production quantity between 2019 and 2020 by more than 20%.
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SELECT DISTINCT p1.Name FROM Producers p1, Producers p2 WHERE p1.ProductionYear = 2020 AND p2.ProductionYear = 2019 AND p1.RareEarth = 'Europium' AND p2.RareEarth = 'Europium' AND p1.Name = p2.Name AND p1.Quantity < p2.Quantity * 0.8;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Employees (EmployeeID INT, FirstName VARCHAR(50), LastName VARCHAR(50), Department VARCHAR(50), Salary DECIMAL(10,2)); INSERT INTO Employees (EmployeeID, FirstName, LastName, Department, Salary) VALUES (1, 'John', 'Doe', 'Engineering', 75000.00), (2, 'Jane', 'Doe', 'Engineering', 80000.00), (3, 'Mike', 'Smith', 'Marketing', 60000.00), (4, 'Samantha', 'Johnson', 'Engineering', 70000.00), (5, 'David', 'Brown', 'Marketing', 65000.00);
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Who are the employees with the lowest salary in each department?
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SELECT EmployeeID, FirstName, LastName, Department, Salary, RANK() OVER (PARTITION BY Department ORDER BY Salary) AS Rank FROM Employees;
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gretelai_synthetic_text_to_sql
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CREATE TABLE whale_sightings (id INT PRIMARY KEY, species VARCHAR(255), location VARCHAR(255), sighting_date DATE); INSERT INTO whale_sightings (id, species, location, sighting_date) VALUES (1, 'Beluga Whale', 'Arctic Ocean', '2023-03-10');
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Delete all records of whale sightings in the Arctic Ocean
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DELETE FROM whale_sightings WHERE location = 'Arctic Ocean';
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gretelai_synthetic_text_to_sql
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CREATE TABLE ProductionMaterials (id INT, name TEXT, co2_emissions INT, quantity INT); INSERT INTO ProductionMaterials (id, name, co2_emissions, quantity) VALUES (1, 'Organic Cotton', 4, 1000), (2, 'Recycled Polyester', 7, 2000), (3, 'Hemp', 2, 1500), (4, 'Tencel', 3, 2500);
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Which materials are used the most in production, and what are their CO2 emissions?
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SELECT name, SUM(quantity) AS total_quantity, AVG(co2_emissions) AS avg_co2_emissions FROM ProductionMaterials GROUP BY name ORDER BY total_quantity DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE factories (id INT PRIMARY KEY, name VARCHAR(255), location VARCHAR(255), capacity INT); INSERT INTO factories (id, name, location, capacity) VALUES (1, 'Ethical Fabrications', 'Bangladesh', 500), (2, 'Fair Factories', 'Cambodia', 300); CREATE TABLE labor_practices (id INT PRIMARY KEY, factory_id INT, worker_count INT, wage_level VARCHAR(255)); INSERT INTO labor_practices (id, factory_id, worker_count, wage_level) VALUES (1, 1, 100, 'Fair'), (2, 2, 120, 'Living');
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Find the factories with the lowest and highest worker counts and their corresponding wage levels.
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SELECT f.name, lp.wage_level, MIN(lp.worker_count) AS min_workers, MAX(lp.worker_count) AS max_workers FROM factories f INNER JOIN labor_practices lp ON f.id = lp.factory_id GROUP BY f.id;
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gretelai_synthetic_text_to_sql
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CREATE TABLE attorneys (attorney_id INT, name TEXT); CREATE TABLE cases (case_id INT, attorney_id INT);
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What is the number of cases handled by each attorney, grouped by attorney name?
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SELECT a.name, COUNT(c.attorney_id) AS case_count FROM attorneys a JOIN cases c ON a.attorney_id = c.attorney_id GROUP BY a.name
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gretelai_synthetic_text_to_sql
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CREATE TABLE Infrastructure_Projects (Project_ID INT, Project_Name VARCHAR(255), Project_Type VARCHAR(255), Resilience_Score FLOAT, Year INT, State VARCHAR(255));
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What is the maximum resilience score for each type of infrastructure project in California for the year 2020?
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SELECT Project_Type, MAX(Resilience_Score) FROM Infrastructure_Projects WHERE Year = 2020 AND State = 'California' GROUP BY Project_Type;
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gretelai_synthetic_text_to_sql
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CREATE TABLE support_programs (id INT, program_name VARCHAR(50), budget INT); INSERT INTO support_programs (id, program_name, budget) VALUES (1, 'Mentorship Program', 10000), (2, 'Tutoring Program', 15000), (3, 'Accessibility Improvements', 20000);
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Update the budget for the 'Accessibility Improvements' program to 25000.
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UPDATE support_programs SET budget = 25000 WHERE program_name = 'Accessibility Improvements';
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gretelai_synthetic_text_to_sql
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CREATE TABLE SubwayFares (id INT, city VARCHAR(255), fare DECIMAL(10, 2), accessibility VARCHAR(255), fare_date DATE);
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What is the total fare collected for accessible subway rides in Tokyo in 2022?
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SELECT SUM(fare) FROM SubwayFares WHERE city = 'Tokyo' AND accessibility = 'Accessible' AND YEAR(fare_date) = 2022;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Artists (id INT, name VARCHAR(100), country VARCHAR(50)); INSERT INTO Artists (id, name, country) VALUES (1, 'Artist 1', 'Nigeria'), (2, 'Artist 2', 'France'), (3, 'Artist 3', 'Egypt'); CREATE TABLE Paintings (id INT, name VARCHAR(100), artist_id INT, price DECIMAL(10,2)); INSERT INTO Paintings (id, name, artist_id, price) VALUES (1, 'Painting 1', 1, 10000.00), (2, 'Painting 2', 2, 20000.00), (3, 'Painting 3', 3, 15000.00);
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Find the highest price of a painting from an African artist.
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SELECT MAX(price) FROM Paintings JOIN Artists ON Paintings.artist_id = Artists.id WHERE Artists.country = 'Africa';
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gretelai_synthetic_text_to_sql
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CREATE TABLE emergency_incidents (id INT, city VARCHAR(20), month INT, year INT, incidents INT); INSERT INTO emergency_incidents (id, city, month, year, incidents) VALUES (1, 'Phoenix', 5, 2022, 100); INSERT INTO emergency_incidents (id, city, month, year, incidents) VALUES (2, 'Phoenix', 5, 2022, 110);
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What is the total number of emergency incidents in the city of Phoenix in the month of May 2022?
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SELECT SUM(incidents) FROM emergency_incidents WHERE city = 'Phoenix' AND month = 5 AND year = 2022;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Volunteers (VolunteerID int, VolunteerName varchar(50), VolunteerDOB date, VolunteerSignUpDate date); INSERT INTO Volunteers (VolunteerID, VolunteerName, VolunteerDOB, VolunteerSignUpDate) VALUES (1, 'James Brown', '1990-01-01', '2020-02-01'), (2, 'Emma White', '1985-06-15', '2020-04-20'), (3, 'Robert Green', '1979-12-31', '2020-11-05');
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How many volunteers signed up in each month of 2020?
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SELECT DATEPART(mm, VolunteerSignUpDate) as Month, COUNT(*) as VolunteersSignedUp FROM Volunteers WHERE VolunteerSignUpDate >= '2020-01-01' AND VolunteerSignUpDate < '2021-01-01' GROUP BY DATEPART(mm, VolunteerSignUpDate);
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gretelai_synthetic_text_to_sql
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CREATE TABLE Contracts (contract_id INT, region VARCHAR(50), original_timeline DATE, revised_timeline DATE); INSERT INTO Contracts (contract_id, region, original_timeline, revised_timeline) VALUES (1, 'Asia-Pacific', '2017-01-01', '2017-06-30');
|
List all contracts that had delays in the Asia-Pacific region and their revised timelines.
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SELECT contract_id, region, revised_timeline FROM Contracts WHERE region = 'Asia-Pacific' AND original_timeline < revised_timeline
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gretelai_synthetic_text_to_sql
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CREATE TABLE Members (MemberID INT, Age INT, FavoriteExercise VARCHAR(20)); INSERT INTO Members (MemberID, Age, FavoriteExercise) VALUES (1, 35, 'Cycling'); INSERT INTO Members (MemberID, Age, FavoriteExercise) VALUES (2, 28, 'Running'); INSERT INTO Members (MemberID, Age, FavoriteExercise) VALUES (3, 45, 'Strength Training');
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What is the maximum age of members who do strength training workouts?
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SELECT MAX(Age) FROM Members WHERE FavoriteExercise = 'Strength Training';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Concerts (ConcertID INT, ConcertName VARCHAR(100), Genre VARCHAR(50), Year INT, Revenue INT); INSERT INTO Concerts VALUES (1, 'Concert1', 'Pop', 2020, 10000); INSERT INTO Concerts VALUES (2, 'Concert2', 'Rock', 2021, 15000); INSERT INTO Concerts VALUES (3, 'Concert3', 'Jazz', 2019, 12000);
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What is the total revenue from each genre of concert ticket sales?
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SELECT Genre, SUM(Revenue) FROM Concerts GROUP BY Genre;
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gretelai_synthetic_text_to_sql
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CREATE TABLE energy_emissions (country VARCHAR(50), year INT, co2_emissions FLOAT); INSERT INTO energy_emissions (country, year, co2_emissions) VALUES ('USA', 2020, 5135.2), ('China', 2020, 10031.2), ('Germany', 2020, 712.4);
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Find the total CO2 emissions for each country in 2020 from the energy sector
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SELECT country, SUM(co2_emissions) as total_emissions FROM energy_emissions WHERE year = 2020 GROUP BY country;
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gretelai_synthetic_text_to_sql
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CREATE TABLE landfill_capacity (city VARCHAR(20), year INT, landfill_capacity FLOAT, waste_generated FLOAT);INSERT INTO landfill_capacity (city, year, landfill_capacity, waste_generated) VALUES ('Jakarta', 2019, 6000000, 3500000), ('Jakarta', 2020, 6000000, 3700000), ('Jakarta', 2021, 6000000, 3900000), ('Bangkok', 2019, 5000000, 3000000), ('Bangkok', 2020, 5000000, 3200000), ('Bangkok', 2021, 5000000, 3400000);
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Calculate the landfill capacity utilization for the city of Jakarta in 2020
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SELECT (waste_generated / landfill_capacity) * 100 FROM landfill_capacity WHERE city = 'Jakarta' AND year = 2020;
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gretelai_synthetic_text_to_sql
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CREATE TABLE CommunityIncidents (community VARCHAR(255), incident_year INT, incident_type VARCHAR(255)); INSERT INTO CommunityIncidents (community, incident_year, incident_type) VALUES ('Indigenous', 2022, 'Algorithmic bias'), ('LGBTQ+', 2021, 'Data privacy'), ('Women in Tech', 2022, 'Model explainability');
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Which AI safety incidents were reported by the Indigenous community in 2022?
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SELECT community, incident_type FROM CommunityIncidents WHERE community = 'Indigenous' AND incident_year = 2022;
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gretelai_synthetic_text_to_sql
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CREATE TABLE countries (country_id INT, country_name VARCHAR(100));CREATE TABLE satellites (satellite_id INT, country_id INT, launch_date DATE);
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List all countries with at least one satellite launched by 2022?
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SELECT countries.country_name FROM countries INNER JOIN satellites ON countries.country_id = satellites.country_id WHERE satellites.launch_date <= '2022-01-01' GROUP BY countries.country_name HAVING COUNT(satellites.satellite_id) >= 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE AIModels (id INT, model_name VARCHAR(50), organization VARCHAR(50), application_type VARCHAR(50), safety_rating INT); INSERT INTO AIModels (id, model_name, organization, application_type, safety_rating) VALUES (1, 'AI4Welfare', 'Microsoft', 'Social Welfare', 85), (2, 'AI4Empowerment', 'Google', 'Social Welfare', 90), (3, 'AI4Assistance', 'IBM', 'Social Welfare', 88), (4, 'AI4Support', 'Alibaba', 'Social Welfare', 92), (5, 'AI4Access', 'Tencent', 'Social Welfare', 80);
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Who is the TOP 1 organization with the highest number of AI models developed for social welfare applications, and what is the median safety rating of their models?
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SELECT organization, COUNT(model_name) as model_count FROM AIModels WHERE application_type = 'Social Welfare' GROUP BY organization ORDER BY model_count DESC LIMIT 1; SELECT AVG(safety_rating) as median_safety_rating FROM (SELECT safety_rating FROM AIModels WHERE organization = (SELECT organization FROM AIModels WHERE application_type = 'Social Welfare' GROUP BY organization ORDER BY COUNT(model_name) DESC LIMIT 1) LIMIT 2 OFFSET 1) as subquery;
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gretelai_synthetic_text_to_sql
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CREATE TABLE soldiers_personal_data (soldier_id INT, name VARCHAR(50), rank VARCHAR(50), departure_date DATE);
|
Update the rank of soldier with ID 3001 to Captain in the soldiers_personal_data table
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UPDATE soldiers_personal_data SET rank = 'Captain' WHERE soldier_id = 3001;
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gretelai_synthetic_text_to_sql
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CREATE TABLE niger_delta_operators (operator_id INT, operator_name VARCHAR(50), location VARCHAR(50), operational_status VARCHAR(15)); INSERT INTO niger_delta_operators VALUES (1, 'Shell', 'Niger Delta', 'Active'); INSERT INTO niger_delta_operators VALUES (2, 'Chevron', 'Niger Delta', 'Active'); CREATE TABLE oil_production (operator_id INT, platform_id INT, year INT, production FLOAT); INSERT INTO oil_production VALUES (1, 1, 2019, 1200000); INSERT INTO oil_production VALUES (1, 1, 2019, 1500000); INSERT INTO oil_production VALUES (2, 2, 2019, 800000); INSERT INTO oil_production VALUES (2, 2, 2019, 900000);
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What is the total oil production for each operator in the Niger Delta for the year 2019?
|
SELECT operator_name, SUM(production) FROM oil_production JOIN niger_delta_operators ON oil_production.operator_id = niger_delta_operators.operator_id WHERE year = 2019 AND location = 'Niger Delta' GROUP BY operator_name;
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gretelai_synthetic_text_to_sql
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CREATE TABLE patient (patient_id INT, name VARCHAR(50), age INT, gender VARCHAR(10), condition VARCHAR(50)); INSERT INTO patient (patient_id, name, age, gender, condition) VALUES (1, 'John Doe', 45, 'Male', 'Anxiety'), (2, 'Jane Smith', 35, 'Female', 'Depression'); CREATE TABLE treatment (treatment_id INT, patient_id INT, treatment_name VARCHAR(50), start_date DATE, end_date DATE, completed BOOLEAN); INSERT INTO treatment (treatment_id, patient_id, treatment_name, start_date, end_date, completed) VALUES (1, 1, 'Dialectical Behavior Therapy', '2021-01-01', '2021-03-31', TRUE), (2, 2, 'Dialectical Behavior Therapy', '2021-04-01', '2021-06-30', FALSE);
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How many patients have completed the Dialectical Behavior Therapy program?
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SELECT COUNT(patient_id) FROM treatment WHERE treatment_name = 'Dialectical Behavior Therapy' AND completed = TRUE;
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gretelai_synthetic_text_to_sql
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CREATE TABLE videos (id INT, title VARCHAR(100), topic VARCHAR(50), views INT, platform VARCHAR(50)); INSERT INTO videos (id, title, topic, views, platform) VALUES (1, 'Video1', 'technology', 5000, 'ABC News'), (2, 'Video2', 'politics', 7000, 'ABC News'), (3, 'Video3', 'technology', 6000, 'ABC News');
|
What is the average number of views for videos on the topic "technology" on the media platform "ABC News"?
|
SELECT AVG(views) FROM videos WHERE topic = 'technology' AND platform = 'ABC News';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Disinformation (ID INT, Topic TEXT, Date DATE); INSERT INTO Disinformation (ID, Topic, Date) VALUES (1, 'Politics', '2022-01-01'), (2, 'Health', '2022-01-05'), (3, 'Politics', '2022-01-07');
|
Identify the most common disinformation topics in the past month.
|
SELECT Topic, COUNT(*) as Count FROM Disinformation WHERE Date >= DATEADD(month, -1, CURRENT_DATE) GROUP BY Topic ORDER BY Count DESC LIMIT 1;
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gretelai_synthetic_text_to_sql
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CREATE TABLE Voyage (id INT, vessel VARCHAR(255), time_in_port INT, country VARCHAR(255), time DATETIME); INSERT INTO Voyage (id, vessel, time_in_port, country, time) VALUES (1, 'African Explorer', 12, 'South Africa', '2021-01-01 10:00:00'), (2, 'Sea Titan', 10, 'Morocco', '2021-02-15 15:30:00');
|
What is the average time spent in port by vessels that have transported containers to Africa in the year 2021?
|
SELECT AVG(time_in_port) FROM Voyage V WHERE country = 'South Africa' OR country = 'Morocco';
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gretelai_synthetic_text_to_sql
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CREATE TABLE Cases (CaseID int, ClientID int, Category varchar(50)); INSERT INTO Cases (CaseID, ClientID, Category) VALUES (401, 4, 'Divorce'); CREATE TABLE Billing (CaseID int, AttorneyID int, HoursFraction decimal(3,2), HourlyRate decimal(5,2)); INSERT INTO Billing (CaseID, AttorneyID, HoursFraction, HourlyRate) VALUES (401, 5, 2.5, 200);
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What is the total billing amount for 'divorce' cases?
|
SELECT SUM(B.HoursFraction * B.HourlyRate) as TotalBillingAmount FROM Cases CA INNER JOIN Billing B ON CA.CaseID = B.CaseID WHERE CA.Category = 'Divorce';
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gretelai_synthetic_text_to_sql
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CREATE TABLE accessible_tech_2 (product_id INT, product_release_year INT, company_region VARCHAR(20));INSERT INTO accessible_tech_2 (product_id, product_release_year, company_region) VALUES (1, 2023, 'Latin America'), (2, 2022, 'Asia'), (3, 2021, 'Pacific Islands');
|
Find the number of accessible technology products released in 2023 that were developed by companies based in Latin America or the Pacific Islands.
|
SELECT COUNT(*) FROM accessible_tech_2 WHERE product_release_year = 2023 AND company_region IN ('Latin America', 'Pacific Islands');
|
gretelai_synthetic_text_to_sql
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CREATE TABLE clients (id INT, name TEXT, assets FLOAT); CREATE TABLE investments (id INT, client_id INT, product_code TEXT); INSERT INTO clients (id, name, assets) VALUES (1, 'John Doe', 50000.00), (2, 'Jane Smith', 75000.00), (3, 'Alice Johnson', 100000.00), (4, 'Bob Brown', 120000.00); INSERT INTO investments (id, client_id, product_code) VALUES (1, 1, 'AAPL'), (2, 1, 'GOOG'), (3, 2, 'MSFT'), (4, 4, 'FB');
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What is the total assets value for clients who own investment product 'MSFT'?
|
SELECT SUM(c.assets) FROM clients c JOIN investments i ON c.id = i.client_id WHERE i.product_code = 'MSFT';
|
gretelai_synthetic_text_to_sql
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CREATE TABLE restaurant_info (restaurant_id INT, name VARCHAR(50), address VARCHAR(100), city VARCHAR(50), state VARCHAR(2), has_vegan_options BOOLEAN);
|
Update the restaurant_info table to set the has_vegan_options field to true for restaurant ID 34
|
UPDATE restaurant_info SET has_vegan_options = true WHERE restaurant_id = 34;
|
gretelai_synthetic_text_to_sql
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CREATE TABLE explainability_scores (model_id INT, model_type VARCHAR(20), score INT); INSERT INTO explainability_scores (model_id, model_type, score) VALUES (1, 'Generative', 7), (2, 'Transformer', 8), (3, 'Reinforcement', 9), (4, 'Generative2', 6), (5, 'Transformer2', 10), (6, 'Reinforcement2', 7), (7, 'Generative3', 8), (8, 'Transformer3', 6), (9, 'Reinforcement3', 9);
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What is the explainability score distribution for each AI model type, ordered by average explainability score in descending order?
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SELECT model_type, AVG(score) as avg_explainability_score, STDDEV(score) as stddev_explainability_score FROM explainability_scores GROUP BY model_type ORDER BY avg_explainability_score DESC;
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gretelai_synthetic_text_to_sql
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CREATE TABLE policyholders (id INT, age INT, state VARCHAR(2), policy_type VARCHAR(10)); INSERT INTO policyholders (id, age, state, policy_type) VALUES (1, 35, 'NY', 'car'), (2, 45, 'CA', 'home'), (3, 28, 'NY', 'car');
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What is the average age of policyholders who live in 'NY' and have a car insurance policy?
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SELECT AVG(age) FROM policyholders WHERE state = 'NY' AND policy_type = 'car';
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gretelai_synthetic_text_to_sql
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CREATE TABLE climate_mitigation(project_name TEXT, country TEXT, num_trees INTEGER); INSERT INTO climate_mitigation(project_name, country, num_trees) VALUES ('Project A', 'Kenya', 1000), ('Project B', 'Brazil', 1500);
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What is the total number of trees planted for climate mitigation projects in Africa and South America?
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SELECT SUM(num_trees) FROM climate_mitigation WHERE country IN ('Africa', 'South America');
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gretelai_synthetic_text_to_sql
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CREATE TABLE sales (drug_name TEXT, year INT, region TEXT, revenue FLOAT); INSERT INTO sales (drug_name, year, region, revenue) VALUES ('DrugA', 2020, 'US', 5000000);
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What was the total sales revenue for 'DrugA' in the year 2020 in the US market?
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SELECT revenue FROM sales WHERE drug_name = 'DrugA' AND year = 2020 AND region = 'US';
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gretelai_synthetic_text_to_sql
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CREATE TABLE brands (id INT, brand VARCHAR(255)); INSERT INTO brands (id, brand) VALUES (1, 'Lush'), (2, 'Burt’s Bees'), (3, 'Maybelline'), (4, 'Estée Lauder'), (5, 'MAC'); CREATE TABLE brand_products (id INT, brand VARCHAR(255), product VARCHAR(255), has_natural_ingredients BOOLEAN); INSERT INTO brand_products (id, brand, product, has_natural_ingredients) VALUES (1, 'Lush', 'Lip Balm', true), (2, 'Burt’s Bees', 'Face Cream', true), (3, 'Maybelline', 'Mascara', false), (4, 'Estée Lauder', 'Foundation', false), (5, 'MAC', 'Lipstick', false);
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List brands that have no products with natural ingredients.
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SELECT brand FROM brands WHERE id NOT IN (SELECT brand FROM brand_products WHERE has_natural_ingredients = true);
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gretelai_synthetic_text_to_sql
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CREATE TABLE diversity_training (id INT, mine_id INT, training_type VARCHAR(50), PRIMARY KEY(id), FOREIGN KEY (mine_id) REFERENCES mine_operations(id)); INSERT INTO diversity_training (id, mine_id, training_type) VALUES (1, 1, 'Diversity Training'); CREATE TABLE workforce_demographics (id INT, mine_id INT, gender VARCHAR(10), percentage FLOAT, PRIMARY KEY(id), FOREIGN KEY (mine_id) REFERENCES mine_operations(id)); INSERT INTO workforce_demographics (id, mine_id, gender, percentage) VALUES (1, 1, 'Female', 35.6);
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Which mines have a diversity training program and have a workforce that is at least 30% female?
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SELECT m.mine_name FROM mine_operations m JOIN diversity_training dt ON m.id = dt.mine_id JOIN workforce_demographics wd ON m.id = wd.mine_id WHERE dt.training_type = 'Diversity Training' AND wd.gender = 'Female' AND wd.percentage >= 30 GROUP BY m.mine_name;
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gretelai_synthetic_text_to_sql
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