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book_publishing_company

Please list the first names of the employees who work as Managing Editor.

Managing Editor is a job description which refers to job_desc

SELECT T1.fname FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T2.job_desc = 'Managing Editor'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What is the highest level of job to get to for the employee who got hired the earliest?

highest job level refers to MAX(job_lvl); hired the earliest refers to MIN(hire_date)

SELECT T2.max_lvl FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id ORDER BY T1.hire_date LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

In which city is the store with the highest total sales quantity located?

qty is abbreviation for quantity; highest sales quantity refers to MAX(qty)

SELECT T2.city FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id GROUP BY T2.city ORDER BY SUM(T1.qty) DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What is the price of the book that sells the best?

qty is abbreviation for quantity; sells the best mean with the most sales quantity; MAX(qty)

SELECT T2.price FROM sales AS T1 INNER JOIN titles AS T2 ON T1.title_id = T2.title_id ORDER BY T1.qty DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Please list the stores that ordered the book "Life Without Fear".

store name refers to stor_name

SELECT T2.stor_name FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id INNER JOIN titles AS T3 ON T1.title_id = T3.title_id WHERE T3.title = 'Life Without Fear'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Among the stores that have ordered the book "Life Without Fear", how many of them are located in Massachusetts?

Massachusetts is a state

SELECT COUNT(T1.stor_id) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id INNER JOIN titles AS T3 ON T1.title_id = T3.title_id WHERE T2.state = 'Massachusetts'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

In which country is the publisher of the book "Life Without Fear" located?

Life Without Fear is book title

SELECT T2.country FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.title = 'Life Without Fear'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What is the publisher that has published the most expensive book?

most expensive book refers to MAX(price)

SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id ORDER BY T1.price DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Among the publishers in the USA, how many of them have published books that are over $15?

are over $15 refers to price>15

SELECT COUNT(DISTINCT T1.pub_id) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country = 'USA' AND T1.price > 15

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Please give more detailed information about the first three books that sell the best.

qty is abbreviation for quantity; sells the best mean with the most sales quantity; MAX(qty)

SELECT T1.notes FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id ORDER BY T2.qty DESC LIMIT 3

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

How many books on business have the bookstores in Massachusetts ordered?

Massachusetts is a state; business books refers to type = 'business'

SELECT SUM(T1.qty) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id INNER JOIN titles AS T3 ON T1.title_id = T3.title_id WHERE T2.state = 'Massachusetts' AND T3.type = 'business'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What is the average quantity of each order for the book "Life Without Fear"?

qty is abbreviation for quantity; average quantity order = AVG(qty)

SELECT CAST(SUM(T2.qty) AS REAL) / COUNT(T1.title_id) FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE T1.title = 'Life Without Fear'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What is the average level employees working as Managing Editor are at? How many levels are there between the average level and the highest level?

Managing Editor is a job description which refers to job_desc; job level refers to job_lvl; highest level job refers to max_lvl; levels between the average level and the highest level = SUBTRACT(max_lvl; AVG(job_lvl))

SELECT AVG(T2.job_lvl), T1.max_lvl - AVG(T2.job_lvl) FROM jobs AS T1 INNER JOIN employee AS T2 ON T1.job_id = T2.job_id WHERE T1.job_desc = 'Managing Editor' GROUP BY T2.job_id, T1.max_lvl

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which one is the cheapest business book?

business books refers to type = 'business'; cheapest book refers to MIN(price)

SELECT title FROM titles WHERE type = 'business' ORDER BY price LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which type of book had the most pre-paid amount?

most pre-paid amount refers to MAX(advance)

SELECT type FROM titles ORDER BY advance DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What's the royalty for the bestseller book?

qty is abbreviation for quantity; bestseller means with the most sales quantity; MAX(qty)

SELECT royalty FROM titles ORDER BY ytd_sales DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which job level is O'Rourke at?

job level refers to job_lvl

SELECT job_lvl FROM employee WHERE lname = 'O''Rourke'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Show me the employ id of the highest employee who doesn't have a middle name.

highest employee refers to employee with the highest job level; MAX(job_lvl)

SELECT emp_id FROM employee WHERE minit = '' ORDER BY job_lvl DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Is the author of "Sushi, Anyone?" on the contract?

contract = 1 means on contract; contract = 0 means not on contract

SELECT T1.contract FROM authors AS T1 INNER JOIN titleauthor AS T2 ON T1.au_id = T2.au_id INNER JOIN titles AS T3 ON T2.title_id = T3.title_id WHERE T3.title = 'Sushi, Anyone?'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which publisher had the highest job level? Give his/her full name.

highest job level refers to MAX(job_lvl)

SELECT T1.fname, T1.minit, T1.lname FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id ORDER BY T1.job_lvl DESC LIMIT 1

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What's Pedro S Afonso's job title?

job title means job description which refers to job_desc

SELECT T2.job_desc FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.fname = 'Pedro' AND T1.minit = 'S' AND T1.lname = 'Afonso'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

How many levels are there left for Diego W Roel to reach if he/she could go to the max level for his/her position?

max level for his position refers to max_lvl; job level refers to job_lvl; level left to reach the max = SUBTRACT(max_lvl, job_lvl)

SELECT T2.max_lvl - T1.job_lvl FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id WHERE T1.fname = 'Diego' AND T1.minit = 'W' AND T1.lname = 'Roel'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What's on the notes for the order happened on 1994/9/14?

order happened on refers to ord_date

SELECT T1.notes FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE STRFTIME('%Y-%m-%d', T2.ord_date) = '1994-09-14'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

List the type of the book for the order which was sold on 1993/5/29.

sold on refers to ord_date

SELECT DISTINCT T1.type FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE STRFTIME('%Y-%m-%d', T2.ord_date) = '1993-05-29'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Tell me about the information of the French publisher.

French publisher means publisher in France where country = 'France'

SELECT T1.pr_info FROM pub_info AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.country = 'France'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

What's the publisher of the book "Silicon Valley Gastronomic Treats"? Give the publisher's name.

publisher name refers to pub_name; Silicon Valley Gastronomic Treats is the title of a book

SELECT T2.pub_name FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.title = 'Silicon Valley Gastronomic Treats'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which city did Victoria P Ashworth work in?

SELECT T2.city FROM employee AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.fname = 'Victoria' AND T1.minit = 'P' AND T1.lname = 'Ashworth'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

How many sales did the store in Remulade make?

Remulade is a city; sales in the store refers to ord_num

SELECT COUNT(T1.ord_num) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id WHERE T2.city = 'Remulade'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

For the quantities, what percent more did the store in Fremont sell than the store in Portland in 1993?

qty is abbreviation for quantity; Fremont and Portland are name of city; sell in 1993 refers to YEAR(ord_date) = 1993; percentage = DIVIDE( SUBTRACT(SUM(qty where city = ‘Fremont’ and year(ord_date = 1993)), SUM(qty where city = ‘Portland’ and year(ord_date = 1993))), SUM(qty where city = ‘Fremont’ and year(ord_date = 1993)) *100

SELECT CAST(SUM(CASE WHEN T2.city = 'Fremont' THEN qty END) - SUM(CASE WHEN T2.city = 'Portland' THEN qty END) AS REAL) * 100 / SUM(CASE WHEN T2.city = 'Fremont' THEN qty END) FROM sales AS T1 INNER JOIN stores AS T2 ON T1.stor_id = T2.stor_id WHERE STRFTIME('%Y', T1.ord_date) = '1993'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Among all the employees, how many percent more for the publishers than designers?

publisher and designer are job descriptions which refers to job_desc; percentage more = 100*(SUBTRACT(SUM(CASE WHERE job_desc = 'publisher), SUM(CASE WHERE job_desc = 'designer'))

SELECT CAST(SUM(CASE WHEN T2.job_desc = 'publisher' THEN 1 ELSE 0 END) - SUM(CASE WHEN T2.job_desc = 'designer' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.job_id) FROM employee AS T1 INNER JOIN jobs AS T2 ON T1.job_id = T2.job_id

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Find and list the full name of employees who were hired between 1990 and 1995. Also, arrange them in the descending order of job level.

job level refers to job_lvl; YEAR(hire_date) between 1990 and 1995

SELECT fname, minit, lname FROM employee WHERE STRFTIME('%Y', hire_date) BETWEEN '1990' AND '1995' ORDER BY job_lvl DESC

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which titles has above average royalty rate? Give those title's name, type and price?

average royalty rate = DIVIDE(SUM(royalty), COUNT(title_id))

SELECT DISTINCT T1.title, T1.type, T1.price FROM titles AS T1 INNER JOIN roysched AS T2 ON T1.title_id = T2.title_id WHERE T2.royalty > ( SELECT CAST(SUM(royalty) AS REAL) / COUNT(title_id) FROM roysched )

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

In 1994 which title had less order quanty than the average order quantity? Find the title name, type and price.

orders in 1994 refers to YEAR(ord_date) = 1994; order quantity refers to number of order expressed by ord_num; average order quantity = DIVIDE(SUM(ord_num), COUNT(title_id))

SELECT DISTINCT T1.title, T1.type, T1.price FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id WHERE T2.ord_date LIKE '1994%' AND T2.Qty < ( SELECT CAST(SUM(T4.qty) AS REAL) / COUNT(T3.title_id) FROM titles AS T3 INNER JOIN sales AS T4 ON T3.title_id = T4.title_id )

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

List the title name, type, and price of the titles published by New Moon Books. Arrange the list in ascending order of price.

Eric the Read Books is a publisher which refers to pub_name;

SELECT T1.title, T1.type, T1.price FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T2.pub_name = 'New Moon Books' ORDER BY T1.price

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

In the books published by US publishers, which book has the highest royalty? List these books in the descending order of royalty.

US publisher refers publisher in the US where country = 'USA';

SELECT T1.title FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN roysched AS T3 ON T1.title_id = T3.title_id WHERE T2.country = 'USA' ORDER BY T1.royalty DESC

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Find the difference between the average royalty of titles published by US and non US publishers?

US publisher refers publisher in the US where country = 'USA'; non-US publishers refers publisher not in the US where country! = 'USA'; difference = SUBTRACT(AVG(royalty) where country = 'USA', AVG(royalty) where country! = 'USA'))

SELECT (CAST(SUM(CASE WHEN T2.country = 'USA' THEN T1.royalty ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.country = 'USA' THEN 1 ELSE 0 END)) - (CAST(SUM(CASE WHEN T2.country != 'USA' THEN T1.royalty ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.country != 'USA' THEN 1 ELSE 0 END)) FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id INNER JOIN roysched AS T3 ON T1.title_id = T3.title_id

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Calculate the average level difference between the Marketing editors hired by the US and non-US publishers?

Marketing manager is a job description which refers to job_desc; US publisher refers publisher in the US where country = 'USA'; non-US publishers refers publisher not in the US where country! = 'USA'; job level refers to job_lvl; average level = AVG(job_lvl)

SELECT (CAST(SUM(CASE WHEN T1.country = 'USA' THEN job_lvl ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.country = 'USA' THEN 1 ELSE 0 END)) - (CAST(SUM(CASE WHEN T1.country != 'USA' THEN job_lvl ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.country != 'USA' THEN 1 ELSE 0 END)) FROM publishers AS T1 INNER JOIN employee AS T2 ON T1.pub_id = T2.pub_id INNER JOIN jobs AS T3 ON T2.job_id = T3.job_id WHERE T3.job_desc = 'Managing Editor'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Which title is about helpful hints on how to use your electronic resources, which publisher published it and what is the price of this book?

publisher refers to pub_name; about the title refers to notes

SELECT T1.title, T2.pub_name, T1.price FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.notes = 'Helpful hints on how to use your electronic resources to the best advantage.'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Of the titles, which title is about the Carefully researched study of the effects of strong emotions on the body, which state-based publisher published this book, and what is the year-to-date sale?

year to date sales refers to ytd_sales; about the title refers to notes

SELECT T1.title, T2.pub_name, T1.ytd_sales FROM titles AS T1 INNER JOIN publishers AS T2 ON T1.pub_id = T2.pub_id WHERE T1.notes = 'Carefully researched study of the effects of strong emotions on the body. Metabolic charts included.'

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

book_publishing_company

Name the top five titles that sold more than average and list them in descending order of the number of sales in California stores?

qty is abbreviation for quantity; sold more than average refers to qty > AVG(qty); california refers to state = 'CA"

SELECT T1.title FROM titles AS T1 INNER JOIN sales AS T2 ON T1.title_id = T2.title_id INNER JOIN publishers AS T3 ON T1.pub_id = T3.pub_id WHERE T2.qty > ( SELECT CAST(SUM(qty) AS REAL) / COUNT(title_id) FROM sales ) AND T3.state = 'CA' ORDER BY T2.qty DESC LIMIT 5

database name:db_id book_publishing_company authors table authors Cols: author id dtype text, author last name dtype text, author first name dtype text, phone dtype text, address dtype text, city dtype text, state dtype text, zip dtype text, contract dtype text, jobs table jobs Cols: job id dtype integer, job description dtype text, min level dtype integer, max level dtype integer, publishers table publishers Cols: publisher id dtype text, publisher name dtype text, city dtype text, state dtype text, country dtype text, employee table employee Cols: employee id dtype text, first name dtype text, minit dtype text, last name dtype text, job id dtype integer, job level dtype integer, publisher id dtype text, hire_date dtype datetime, pub_info table pub_info Cols: publication id dtype text, logo dtype blob, publisher's information dtype text, stores table stores Cols: store id dtype text, store name dtype text, store address dtype text, city dtype text, state dtype text, zip dtype text, discounts table discounts Cols: discount type dtype text, store id dtype text, low quantity dtype integer, high quantity dtype integer, discount dtype real, titles table titles Cols: title id dtype text, title dtype text, type dtype text, publisher id dtype text, price dtype real, advance dtype real, royalty dtype integer, year to date sales dtype integer, notes dtype text, publication date dtype datetime, roysched table roysched Cols: title_id dtype text, low range dtype integer, high range dtype integer, royalty dtype integer, sales table sales Cols: store id dtype text, order number dtype text, order date dtype datetime, quantity dtype integer, payterms dtype text, title id dtype text, titleauthor table titleauthor Cols: author id dtype text, title id dtype text, author ordering dtype integer, royaltyper dtype integer,

retail_complains

On which day was the most verbose complaint received?

day received refers to "Date received"; most verbose complaint refers to MAX(ser_time);

SELECT `Date received` FROM callcenterlogs WHERE ser_time = ( SELECT MAX(ser_time) FROM callcenterlogs )

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

When did the earliest complaint start on 2017/3/22?

earliest complaint refers to oldest ser_start; on 2017/3/22 refers to "Date received" = '2017-03-22';

SELECT MIN(ser_time) FROM callcenterlogs WHERE `Date received` = '2017-03-22'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which complaint is more urgent, complaint ID CR2400594 or ID CR2405641?

more urgent refers to MAX(priority);

SELECT CASE WHEN SUM(CASE WHEN `Complaint ID` = 'CR2400594' THEN priority END) > SUM(CASE WHEN `Complaint ID` = 'CR2405641' THEN priority END) THEN 'CR2400594' ELSE 'CR2405641' END FROM callcenterlogs

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Please list the full names of all the male clients born after the year 1990.

full names = first, middle, last; male refers to sex = 'Male'; year > 1990;

SELECT first, middle, last FROM client WHERE year > 1990

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many complaints have the client Diesel Galloway filed?

SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Diesel' AND T1.last = 'Galloway'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the detailed product of the complaint filed by Diesel Galloway on 2014/7/3?

detailed product refers to "sub-product"; on 2014/7/3 refers to "Date received" = '2014-07-03';

SELECT T2.`Sub-product` FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Diesel' AND T1.last = 'Galloway' AND T2.`Date received` = '2014-07-03'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Was the tag in the complaint filed by Matthew Pierce on 2016/10/28 approved by himself?

on 2016/10/28 refers to Date received = '2016-10-28'; "Consumer consent provided?" in (null, 'N/A', 'Empty') means that the company didn't get the permission of consent; "Consumer consent provided?" not in (null, 'N/A', 'Empty') means that customers provide the consent for this tag;

SELECT CASE WHEN T2.`Consumer consent provided?` IN (NULL, 'N/A', 'Empty') THEN 'No' ELSE 'Yes' END FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Matthew' AND T1.last = 'Pierce' AND T2.`Date received` = '2016-10-28'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

For how long was the complaint filed by Matthew Pierce on 2016/10/28 delayed?

on 2016/10/28 refers to "Date received" = '2016-10-28'; delayed = SUBTRACT("Date sent to company', 'Date received");

SELECT 365 * (strftime('%Y', T2.`Date sent to company`) - strftime('%Y', T2.`Date received`)) + 30 * (strftime('%M', T2.`Date sent to company`) - strftime('%M', T2.`Date received`)) + (strftime('%d', T2.`Date sent to company`) - strftime('%d', T2.`Date received`)) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Matthew' AND T1.last = 'Pierce' AND T2.`Date received` = '2016-10-28'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the full name of the client whose complaint on 2017/3/27 was received by MICHAL?

full names = first, middle, last; on 2017/3/27 refers to "Date received" = '2017-03-27'; MICHAL refers to server = 'MICHAL';

SELECT T1.first, T1.middle, T1.last FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.`Date received` = '2017-03-27' AND T2.server = 'MICHAL'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

For how long did the complaint filed on 2017/3/27 by Rachel Hicks last?

how long did the complaint filed last refers to ser_time; on 2017/3/27 refers to "Date received" = '2017-03-27';

SELECT T2.ser_time FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T1.first = 'Rachel' AND T1.last = 'Hicks' AND T2.`Date received` = '2017-03-27'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Among all the clients from the New York city, how many of them have filed a complaint on the issue of Deposits and withdrawals?

SELECT COUNT(T2.Issue) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.Issue = 'Deposits and withdrawals' AND T1.city = 'New York City'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Please list the full names of all the clients whose complaints are still in progress.

full name = first, middle, last; complaints are still in progress refers to "Company response to consumer" = 'In progress';

SELECT T1.first, T1.middle, T1.last FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Company response to consumer` = 'In progress'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Among the clients who did receive a timely response for their complaint, how many of them are from New York?

did not receive a timely response refers to "Timely response?" = 'No'; New York refers to city = 'New York';

SELECT COUNT(T1.city) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Timely response?` = 'No' AND T1.city = 'New York City'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many complaints on credit cards in the year 2016 were filed by male clients?

credit cards refers to Product = 'Credit card'; 2016 refers to year(Date received) = 2016; male refers to sex = 'Male';

SELECT COUNT(T1.sex) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE strftime('%Y', T2.`Date received`) = '2016' AND T1.sex = 'Male' AND T2.Product = 'Credit card'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which division is Diesel Galloway in?

SELECT T2.division FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.first = 'Diesel' AND T1.last = 'Galloway'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Please list the full names of all the male clients in the Pacific division.

full names = first, middle, last; male refers to sex = 'Male';

SELECT T1.first, T1.middle, T1.last FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.division = 'Pacific' AND T1.sex = 'Male'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the average number of complaints on credit cards filed by clients from New York in the 3 consecutive years starting from 2015?

average = AVG(Complaint ID); credit cards refers to Product = 'Credit card'; New York refers to city = 'New York'; 3 consecutive years starting from 2015 refers to "Date received" BETWEEN 2015 AND 2017;

SELECT CAST(COUNT(T2.`Complaint ID`) AS REAL) / 3 AS average FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE strftime('%Y', T2.`Date received`) BETWEEN '2015' AND '2017' AND T1.city = 'New York City' AND T2.Product = 'Credit card'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the percentage of the increase of complaints filed by the clients from New York from the year 2016 to the year 2017?

percentage of increase = MULTIPLY(DIVIDE(SUBTRACT(SUM(year("Date received") = 2017), SUM(year("Date received") = 2016)), SUM(year("Date received") = 2016)), 1.0); New York refers to city = 'New York'; year("Date received") BETWEEN 2016 AND 2017;

SELECT 100.0 * (SUM(CASE WHEN strftime('%Y', T2.`Date received`) = '2017' THEN 1 ELSE 0 END) - SUM(CASE WHEN strftime('%Y', T2.`Date received`) = '2016' THEN 1 ELSE 0 END)) / SUM(CASE WHEN strftime('%Y', T2.`Date received`) = '2016' THEN 1 ELSE 0 END) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.city = 'New York City'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What was the serve time for the complaint call from client "C00007127" on 2017/2/22?

serve time refers to ser_time; longer ser_time means more verbose or longer complaint; on 2017/2/22 refers to "Date received" = '2017-02-22';

SELECT T1.ser_time FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.Client_ID = 'C00007127' AND T1.`Date received` = '2017-02-22'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which state does the owner of "[email protected]" live in? Give the full name of the state.

full name of the state refers to state_name;

SELECT T1.state FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.email = '[email protected]'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which detailed product did Mr Lennox Oliver Drake complain about?

detailed product refers to "Sub-product"; Mr refers to sex = 'Male';

SELECT DISTINCT T2.`Sub-product` FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Lennox' AND T1.middle = 'Oliver' AND T1.last = 'Drake' AND T1.sex = 'Male'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What was the detailed issue did Mr Gunner Omer Fuller complain about?

detailed issue refers to Sub-issue; Mr refers to sex = 'Male';

SELECT T2.`Sub-issue` FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Gunner' AND T1.middle = 'Omer' AND T1.last = 'Fuller' AND T1.sex = 'Male'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Did Ms. Lyric Emely Taylor provide the consent for result of the complaint call on 2016/5/20?

Ms refers to sex = 'Female'; "Consumer consent provided?" in (null, 'N/A', 'Empty') means that the company didn't get the permission of consent; "Consumer consent provided?" not in (null, 'N/A', 'Empty') means the customers provide the consent; on 2016/5/20 refers to Date received = '2016-05-20';

SELECT CASE WHEN T2.`Consumer consent provided?` IN (NULL, 'N/A', '') THEN 'No' ELSE 'Yes' END FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.first = 'Lyric' AND T1.middle = 'Emely' AND T1.last = 'Taylor' AND T1.sex = 'Female' AND T2.`Date received` = '2016-05-20'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many days delay for the complaint call from Mr. Brantley Julian Stanley on 2012/5/18?

days delay for the complaint = SUBTRACT("date sent to company", "Date received"); Mr refers to sex = 'Male'; on 2012/5/18 refers to "Date received" = '2012-05-18';

SELECT 365 * (strftime('%Y', T2.`Date sent to company`) - strftime('%Y', T2.`Date received`)) + 30 * (strftime('%M', T2.`Date sent to company`) - strftime('%M', T2.`Date received`)) + (strftime('%d', T2.`Date sent to company`) - strftime('%d', T2.`Date received`)) AS days FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Date received` = '2012-05-18' AND T1.sex = 'Male' AND T1.first = 'Brantley' AND T1.middle = 'Julian' AND T1.last = 'Stanley'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which district did the review on 2018/9/11 come from? Give the name of the city.

on 2018/9/11 refers to Date = '2017-07-22';

SELECT T2.district_id, T2.city FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Date = '2018-09-11'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What was the review context from Jacksonville on 2017/7/22?

Jacksonville refers to city = 'Jacksonville'; on 2017/7/22 refers to Date = '2017-07-22';

SELECT T1.Reviews FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.city = 'Jacksonville' AND T1.Date = '2017-07-22'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which product received a review from Indianapolis on 2016/10/7?

Indianapolis refers to state = 'Indianapolis'; on 2016/10/7 refers to Date = '2013-04-04';

SELECT T1.Product FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.city = 'Indianapolis' AND T1.Date = '2016-10-07'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many stars did "Eagle Capital" received from Little Rock on 2013/4/4?

Eagle Capital refers to Product = 'Eagle Capital'; Little Rock is a city; on 2013/4/4 refers to Date = '2013-04-04';

SELECT COUNT(T1.Stars) FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Product = 'Eagle Capital' AND T2.city = 'Little Rock' AND T1.Date = '2013-04-04'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

For the client who made the complaint call "CR0217298", what was his/her birthday？

complaint call refers to Complaint ID; birthday = year, month, day;

SELECT T1.month, T1.day FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Complaint ID` = 'CR0217298'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What was the phone of number of the client who made the complaint call "CR0100432" ？

complaint call refers to Complaint ID;

SELECT T1.phone FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Complaint ID` = 'CR0100432'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

For all the complaint callers on 2017/3/27, what percentage of the clients are females?

on 2017/3/27 refers to "Date received" = '2017-03-27'; percentage = MULTIPLY(DIVIDE(SUM(sex = 'Female' ), COUNT(client_id)), 1.0); females refers to sex = 'Female';

SELECT CAST(SUM(CASE WHEN T1.sex = 'Female' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.sex) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Date received` = '2017-03-27'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the percentage of the complaint calls from Mr Mason Javen Lopez has got the consent provided by the customer?

percentage = MULTIPLY(DIVIDE(SUM("Consumer consent provided?" = 'Consent provided'), COUNT(client_id)), 1.0); Mr refers to sex = 'Male'; consent provided by the customer refers to "Consumer consent provided?" = 'Consent provided';

SELECT CAST(SUM(CASE WHEN T2.`Consumer consent provided?` = 'Consent provided' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.`Consumer consent provided?`) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.sex = 'Male' AND T1.first = 'Mason' AND T1.middle = 'Javen' AND T1.last = 'Lopez'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many priority urgent complaints were received in march of 2017? List the complaint ID of these complaints.

urgent complaints refers to priority = 2; march of 2017 refers to "Date received" BETWEEN '2017-01-01' AND '2017-01-31';

SELECT COUNT(`Complaint ID`) FROM callcenterlogs WHERE `Date received` LIKE '2017-01%' AND priority = ( SELECT MAX(priority) FROM callcenterlogs )

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Please list the full name, date of birth, and email id of the elderly clients in descending order of age.

full name = first, middle, last; date of birth = year, month, day; elderly clients refers to age > 65;

SELECT first, middle, last, year, month , day, email FROM client WHERE age > 65 ORDER BY age DESC

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Which product got the most five stars, and how many?

most five stars refers to MAX(COUNT(stars = 5));

SELECT T.Product, MAX(T.num) FROM ( SELECT Product, COUNT(Stars) AS num FROM reviews WHERE Stars = 5 GROUP BY Product ) T

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

List all the states in the South region.

SELECT state FROM state WHERE Region = 'South'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the email id of clients whose calls were hung?

email id refers to email; calls were hung refers to outcome = 'Hang';

SELECT T1.email FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.outcome = 'HANG'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Calculate the average age of clients from the Midwest region.

average age = AVG(age);

SELECT CAST(SUM(T1.age) AS REAL) / COUNT(T3.Region) AS average FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T2.state_abbrev = T3.StateCode WHERE T3.Region = 'Midwest'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

List the full name and phone number of clients who submitted the complaint via fax.

full name = first, middle, last; submitted the complaint via fax refers to "Submitted via" = 'fax';

SELECT T1.first, T1.middle, T1.last, T1.phone FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Submitted via` = 'Fax'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Find and list the names of districts which has below-average stars for Eagle Capital.

below average = AVG(stars) < Stars; Eagle Capital refers to Product = 'Eagle Capital';

SELECT T2.division FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Product = 'Eagle Capital' AND T1.Stars > ( SELECT AVG(Stars) FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id )

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

In the calls from the mountain division, how many are from teenage clients?

teenage refers to age BETWEEN 12 AND 20;

SELECT COUNT(T1.age) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.age BETWEEN 12 AND 20 AND T2.division = 'Mountain'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the number of complaints related to Credit cards came from female clients?

Credit cards refers to Product = 'Credit card'; female refers to sex = 'female';

SELECT COUNT(T1.sex) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.sex = 'Female' AND T2.Product = 'Credit card'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Among the clients born between 1980 and 2000, list the name of male clients who complained through referral.

born between 1980 and 2000 refers to year BETWEEN 1980 AND 2000; name = first, middle, last; male refers to sex = 'Male'; complained through refers to "Submitted via";

SELECT T1.first, T1.middle, T1.last FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.year BETWEEN 1980 AND 2000 AND T1.sex = 'Male' AND T2.`Submitted via` = 'Referral'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What is the medium through which most complaints are registered in Florida?

medium refers to "Submitted via"; most complaints refers to MAX(Complaint ID); Florida refers to state = 'florida';

SELECT T3.`Submitted via` FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN events AS T3 ON T1.`Complaint ID` = T3.`Complaint ID` WHERE T2.state = 'FL' GROUP BY T1.`Complaint ID` ORDER BY COUNT(T1.`Complaint ID`) DESC LIMIT 1

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Calculate the average number of complaints received from New Bedford each year which are closed with explanation.

average = AVG("Complaint ID"); New Bedford refers to city = 'New Bedford'; closed with explanation refers to Company response to consumer = 'Closed with explanation';

SELECT STRFTIME('%Y', T3.`Date received`) , CAST(SUM(CASE WHEN T3.`Company response to consumer` = 'Closed with explanation' THEN 1 ELSE 0 END) AS REAL) / COUNT(T3.`Complaint ID`) AS average FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN events AS T3 ON T1.`Complaint ID` = T3.`Complaint ID` WHERE T2.city = 'New Bedford' GROUP BY strftime('%Y', T3.`Date received`)

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

What percentage of consumers from Houston disputed complaints?

percentage = MULTIPLY(DIVIDE(SUM("Consumer disputed?" = 'Yes' AND city = 'Houston'), COUNT(client_id)), 1.0); Houston refers to city = 'Houston';

SELECT CAST(SUM(CASE WHEN T2.`Consumer disputed?` = 'Yes' AND T1.city = 'Houston' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Find the number of service members who complained in Syracuse.

service members refers to client.client_id; Syracuse refers to city = 'Syracuse';

SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.Tags = 'Servicemember' AND T1.city = 'Syracuse'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Among the calls from California, what percentage are priority 1?

California refers to state = 'California'; percentage = MULTIPLY(DIVIDE(SUM(priority = 1), COUNT("Complaint ID"), 1.0));

SELECT CAST(SUM(CASE WHEN T1.priority = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.priority) FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id INNER JOIN state AS T4 ON T3.state_abbrev = T4.StateCode WHERE T4.State = 'California'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Calculate the difference in the average age of elderly and middle-aged clients in the Northeast region.

difference in the average = SUBTRACT(AVG(age BETWEEN 35 AND 55), AVG( age > 65)); elderly refers to age > 65; middle-aged refers to age BETWEEN 35 AND 55;

SELECT (CAST(SUM(CASE WHEN T1.age BETWEEN 35 AND 55 THEN T1.age ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age BETWEEN 35 AND 55 THEN 1 ELSE 0 END)) - (CAST(SUM(CASE WHEN T1.age > 65 THEN T1.age ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age > 65 THEN 1 ELSE 0 END)) AS difference FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T2.state_abbrev = T3.StateCode WHERE T3.Region = 'Northeast'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

List by their ID number the 3 longest complaints.

ID number refers to "Complaint ID"; longest complaints refers to MAX(ser_time);

SELECT `Complaint ID` FROM callcenterlogs ORDER BY ser_time DESC LIMIT 3

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many clients have an email account other than gmail.com?

email account other than gmail.com refers to email not like '%@gmail.com';

SELECT COUNT(email) FROM client WHERE email NOT LIKE '%@gmail.com'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

Identify by their ID all clients who did not give their consent permission.

did not give their consent permission refers to Consumer consent provided is null, 'N/A', or empty;

SELECT Client_ID FROM events WHERE `Consumer consent provided?` = 'N/A' OR 'Consumer consent provided?' IS NULL OR 'Consumer consent provided?' = ''

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

List by their ID the complaints received by the company on 25/09/2014 that took the longest.

ID of the complaints refers to "Complaint ID"; on 25/09/2014 refers to "Date sent to company" = '2014-09-25'; took the longest = MAX(SUBTRACT("Date sent to company", "Date received"));

SELECT `Complaint ID` FROM events WHERE strftime('%J', `Date sent to company`) - strftime('%J', `Date received`) = ( SELECT MAX(strftime('%J', `Date sent to company`) - strftime('%J', `Date received`)) FROM events WHERE `Date sent to company` = '2014-09-25' ) AND `Date sent to company` = '2014-09-25'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

List priority 2 complaints by date received.

SELECT DISTINCT `Complaint ID` FROM callcenterlogs WHERE priority = 2 ORDER BY `Date received` DESC

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many complaints are not in process with an agent?

not in process with an agent refers to outcome ! = 'AGENT';

SELECT COUNT(outcome) FROM callcenterlogs WHERE outcome != 'AGENT'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many Credit Card complaints did Sharon handle?

Credit Card refers to Product = 'Credit Card'; Sharon refers to server = 'SHARON';

SELECT COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.Product = 'Credit card' AND T1.server = 'SHARON'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

In which region have the most 1-star reviews been done?

most 1-star reviews refers to MAX(COUNT(stars = 1));

SELECT T3.Region FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T2.state_abbrev = T3.StateCode WHERE T1.Stars = 1 GROUP BY T3.Region ORDER BY COUNT(T3.Region) DESC LIMIT 1

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

In what years were the clients who demanded more problems with Certificate of deposit born?

more problems with Certificate refers to MAX(COUNT("Sub-product" = '(CD) Certificate of deposit'));

SELECT T1.year FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Sub-product` = '(CD) Certificate of deposit' GROUP BY T1.year ORDER BY COUNT(T1.year) DESC LIMIT 1

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many cases of billing dispute issues occurred in the Mountain division?

billing dispute refers to issue = 'Billing disputes';

SELECT COUNT(T1.Issue) FROM events AS T1 INNER JOIN client AS T2 ON T1.Client_ID = T2.client_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id WHERE T1.Issue = 'Billing disputes' AND T3.division = 'Mountain'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,

retail_complains

How many male clients are from the state of Massachusetts?

male refers to sex = 'Male';

SELECT COUNT(T3.sex) FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN client AS T3 ON T2.district_id = T3.district_id WHERE T1.state = 'Massachusetts' AND T3.sex = 'Male'

database name:db_id retail_complains state table state Cols: StateCode dtype text, State dtype text, Region dtype text, callcenterlogs table callcenterlogs Cols: Date received dtype date, Complaint ID dtype text, rand client dtype text, phone final dtype text, voice response unit line dtype text, call id dtype integer, priority dtype integer, type dtype text, outcome dtype text, server dtype text, server start dtype text, server exit dtype text, server time dtype text, client table client Cols: client id dtype text, sex dtype text, day dtype integer, month dtype integer, year dtype integer, age dtype integer, social dtype text, first dtype text, middle dtype text, last dtype text, phone dtype text, email dtype text, address_1 dtype text, address_2 dtype text, city dtype text, state dtype text, zipcode dtype integer, district id dtype integer, district table district Cols: district id dtype integer, city dtype text, state_abbrev dtype text, division dtype text, events table events Cols: Date received dtype date, Product dtype text, Sub-product dtype text, Issue dtype text, Sub-issue dtype text, Consumer complaint narrative dtype text, Tags dtype text, Tags Consumer consent provided? dtype text, Submitted via dtype text, Date sent to company dtype text, Company response to consumer dtype text, Timely response? dtype text, Consumer disputed? dtype text, Complaint ID dtype text, Client ID dtype text, reviews table reviews Cols: Date dtype date, Stars dtype integer, Reviews dtype text, Product dtype text, district_id dtype integer,