db_id stringclasses 69
values | question stringlengths 24 476 | seed_question stringlengths 24 362 | evidence stringlengths 1 673 | sql stringlengths 23 1.42k | dsl unknown | reasoning stringlengths 0 729 | m_schema stringlengths 24 9.02k | verified bool 1
class | _dataset_source stringclasses 2
values | bird_schema stringclasses 69
values |
|---|---|---|---|---|---|---|---|---|---|---|
book_publishing_company | What is the price of the book that sells the best? | 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 | {
"tables": [
"sales",
"titles"
],
"dimensions": [
"price"
],
"order_by": [
{
"expr": "qty",
"desc": true
}
],
"limit": 1,
"_source": "sqlite",
"filters": [
"sales.title_id = titles.title_id"
]
} | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# sales ( stor_id, ord_num, ord_date, qty, payterms, title_id ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Please list the stores that ordered the book "Life Without Fear". | 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' | {
"tables": [
"sales",
"stores",
"titles"
],
"dimensions": [
"stor_name"
],
"_source": "sqlite",
"filters": [
"titles.title = 'Life Without Fear'",
"sales.stor_id = stores.stor_id",
"sales.title_id = titles.title_id"
]
} | # stores ( stor_id, stor_name, stor_address, city, state, zip )
# sales ( stor_id, ord_num, ord_date, qty, payterms, title_id )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Among the stores that have ordered the book "Life Without Fear", how many of them are located in Massachusetts? | 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' | {
"tables": [
"sales",
"stores",
"titles"
],
"measures": [
{
"agg": "COUNT",
"expr": "sales.stor_id",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"stores.state = 'Massachusetts'",
"sales.stor_id = stores.stor_id",
"sales.title_id = titles.title_id"
... | # stores ( stor_id, stor_name, stor_address, city, state, zip )
# sales ( stor_id, ord_num, ord_date, qty, payterms, title_id )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | In which country is the publisher of the book "Life Without Fear" located? | 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' | {
"tables": [
"publishers",
"titles"
],
"dimensions": [
"country"
],
"_source": "sqlite",
"filters": [
"titles.title = 'Life Without Fear'",
"titles.pub_id = publishers.pub_id"
]
} | # publishers ( pub_id, pub_name, city, state, country )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | What is the publisher that has published the most expensive book? | 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 | {
"tables": [
"publishers",
"titles"
],
"dimensions": [
"pub_name"
],
"order_by": [
{
"expr": "price",
"desc": true
}
],
"limit": 1,
"_source": "sqlite",
"filters": [
"titles.pub_id = publishers.pub_id"
]
} | # publishers ( pub_id, pub_name, city, state, country )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Among the publishers in the USA, how many of them have published books that are over $15? | 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 | {
"tables": [
"publishers",
"titles"
],
"measures": [
{
"agg": "COUNT_DISTINCT",
"expr": "titles.pub_id",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"publishers.country = 'USA'",
"titles.price > 15",
"titles.pub_id = publishers.pub_id"
]
} | # publishers ( pub_id, pub_name, city, state, country )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Please give more detailed information about the first three books that sell the best. | 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 | {
"tables": [
"sales",
"titles"
],
"dimensions": [
"notes"
],
"order_by": [
{
"expr": "qty",
"desc": true
}
],
"limit": 3,
"_source": "sqlite",
"filters": [
"titles.title_id = sales.title_id"
]
} | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# jobs ( job_id, job_desc, min_lvl, max_lvl )
# publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# pub_info ( pub_id, logo, pr_info )
# stores ( stor_id... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | How many books on business have the bookstores in Massachusetts ordered? | 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' | {
"tables": [
"sales",
"stores",
"titles"
],
"measures": [
{
"agg": "SUM",
"expr": "qty",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"stores.state = 'Massachusetts'",
"titles.type = 'business'",
"sales.stor_id = stores.stor_id",
"sales.title_id =... | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# jobs ( job_id, job_desc, min_lvl, max_lvl )
# publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# pub_info ( pub_id, logo, pr_info )
# stores ( stor_id... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | What is the average quantity of each order for the book "Life Without Fear"? | 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' | {
"tables": [
"sales",
"titles"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "simple_metric",
"agg": "SUM",
"field": "sales.qty"
},
{
"type": "simple_metric",
"agg"... | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# jobs ( job_id, job_desc, min_lvl, max_lvl )
# publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# pub_info ( pub_id, logo, pr_info )
# stores ( stor_id... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Which one is the cheapest business book? | 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 | {
"tables": [
"titles"
],
"dimensions": [
"title"
],
"order_by": [
{
"expr": "price",
"desc": false
}
],
"limit": 1,
"_source": "sqlite",
"filters": [
"type = 'business'"
]
} | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Which type of book had the most pre-paid amount? | 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 | {
"tables": [
"titles"
],
"dimensions": [
"type"
],
"order_by": [
{
"expr": "advance",
"desc": true
}
],
"limit": 1,
"_source": "sqlite"
} | # discounts ( discounttype, stor_id, lowqty, highqty, discount )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# titleauthor ( au_id, title_id, au_ord, royaltyper ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | What's the royalty for the bestseller book? | 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 | {
"tables": [
"titles"
],
"dimensions": [
"royalty"
],
"order_by": [
{
"expr": "ytd_sales",
"desc": true
}
],
"limit": 1,
"_source": "sqlite"
} | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# roysched ( title_id, lorange, hirange, royalty )
# titleauthor ( au_id, title_id, au_ord, royaltyper ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Which job level is O'Rourke at? | Which job level is O'Rourke at? | job level refers to job_lvl | SELECT job_lvl FROM employee WHERE lname = 'O''Rourke' | {
"tables": [
"employee"
],
"dimensions": [
"job_lvl"
],
"_source": "sqlite",
"filters": [
"lname = 'O''Rourke'"
]
} | # jobs ( job_id, job_desc, min_lvl, max_lvl )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Is the author of "Sushi, Anyone?" on the contract? | 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?' | {
"tables": [
"authors",
"titleauthor",
"titles"
],
"dimensions": [
"contract"
],
"_source": "sqlite",
"filters": [
"titles.title = 'Sushi, Anyone?'",
"authors.au_id = titleauthor.au_id",
"titleauthor.title_id = titles.title_id"
]
} | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Which publisher had the highest job level? Give his/her full name. | 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 | {
"tables": [
"employee",
"jobs"
],
"dimensions": [
"fname",
"minit",
"lname"
],
"order_by": [
{
"expr": "job_lvl",
"desc": true
}
],
"limit": 1,
"_source": "sqlite",
"filters": [
"employee.job_id = jobs.job_id"
]
} | # jobs ( job_id, job_desc, min_lvl, max_lvl )
# publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Tell me about the information of the French publisher. | 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' | {
"tables": [
"pub_info",
"publishers"
],
"dimensions": [
"pr_info"
],
"_source": "sqlite",
"filters": [
"publishers.country = 'France'",
"pub_info.pub_id = publishers.pub_id"
]
} | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# publishers ( pub_id, pub_name, city, state, country )
# stores ( stor_id, stor_name, stor_address, city, state, zip )
# pub_info ( pub_id, logo, pr_info ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | What's the publisher of the book "Silicon Valley Gastronomic Treats"? Give the publisher's name. | 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' | {
"tables": [
"publishers",
"titles"
],
"dimensions": [
"pub_name"
],
"_source": "sqlite",
"filters": [
"titles.title = 'Silicon Valley Gastronomic Treats'",
"titles.pub_id = publishers.pub_id"
]
} | # publishers ( pub_id, pub_name, city, state, country )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | How many sales did the store in Remulade make? | 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' | {
"tables": [
"sales",
"stores"
],
"measures": [
{
"agg": "COUNT",
"expr": "ord_num",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"stores.city = 'Remulade'",
"sales.stor_id = stores.stor_id"
]
} | # stores ( stor_id, stor_name, stor_address, city, state, zip )
# sales ( stor_id, ord_num, ord_date, qty, payterms, title_id )
# titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | For the quantities, what percent more did the store in Fremont sell than the store in Portland in 1993? | 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 =... | 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' | {
"tables": [
"sales",
"stores"
],
"measures": [
{
"agg": "CALCULATED",
"expr": "(CAST(SUM(CASE WHEN stores.city = 'Fremont' THEN qty END) - SUM(CASE WHEN stores.city = 'Portland' THEN qty END) AS REAL) / NULLIF(SUM(CASE WHEN stores.city = 'Fremont' THEN qty END), 0)) * 100"
}
],
"... | # stores ( stor_id, stor_name, stor_address, city, state, zip )
# sales ( stor_id, ord_num, ord_date, qty, payterms, title_id ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Among all the employees, how many percent more for the publishers than designers? | 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 | {
"tables": [
"employee",
"jobs"
],
"measures": [
{
"agg": "CALCULATED",
"expr": "(CAST(SUM(CASE WHEN job_desc = 'publisher' THEN 1 ELSE 0 END) - SUM(CASE WHEN job_desc = 'designer' THEN 1 ELSE 0 END) AS REAL) / NULLIF(COUNT(employee.job_id), 0)) * 100"
}
],
"_source": "sqlite",
... | # publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# jobs ( job_id, job_desc, min_lvl, max_lvl ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
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. | 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 | {
"tables": [
"employee"
],
"dimensions": [
"fname",
"minit",
"lname"
],
"order_by": [
{
"expr": "job_lvl",
"desc": true
}
],
"_source": "sqlite",
"filters": [
"STRFTIME('%Y', hire_date) BETWEEN '1990' AND '1995'"
]
} | # jobs ( job_id, job_desc, min_lvl, max_lvl )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# publishers ( pub_id, pub_name, city, state, country )
# stores ( stor_id, stor_name, stor_address, city, stat... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Which titles has above average royalty rate? Give those title's name, type and price? | 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 ) | {
"tables": [
"roysched",
"titles"
],
"dimensions": [
"title",
"type",
"price"
],
"_source": "sqlite",
"is_distinct": true,
"filters": [
{
"type": "subquery_comparison",
"left": "roysched.royalty",
"operator": ">",
"nested_subquery": {
"tables": [
... | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# discounts ( discounttype, stor_id, lowqty, highqty, discount )
# roysched ( title_id, lorange, hirange, royalty ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | In 1994 which title had less order quanty than the average order quantity? Find the title name, type and price. | 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 ) | {
"tables": [
"sales",
"titles"
],
"dimensions": [
"title",
"type",
"price"
],
"_source": "sqlite",
"is_distinct": true,
"filters": [
"sales.ord_date LIKE '1994%'",
{
"type": "subquery_comparison",
"left": "sales.Qty",
"operator": "<",
"nested_subquery":... | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# discounts ( discounttype, stor_id, lowqty, highqty, discount )
# roysched ( title_id, lorange, hirange, royalty )
# sales ( stor_id, ord_num, ord_date, qty, pa... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
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. | 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 | {
"tables": [
"publishers",
"titles"
],
"dimensions": [
"title",
"type",
"price"
],
"order_by": [
{
"expr": "price",
"desc": false
}
],
"_source": "sqlite",
"filters": [
"publishers.pub_name = 'New Moon Books'",
"titles.pub_id = publishers.pub_id"
]
} | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# roysched ( title_id, lorange, hirange, royalty )
# sales ( stor_id, ord_num, ord_date, qty, payterms, title_id, Qty )
# publishers ( pub_id, pub_name, city, st... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
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. | 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 | {
"tables": [
"publishers",
"roysched",
"titles"
],
"dimensions": [
"title"
],
"order_by": [
{
"expr": "titles.royalty",
"desc": true
}
],
"_source": "sqlite",
"filters": [
"publishers.country = 'USA'",
"titles.pub_id = publishers.pub_id",
"titles.title_id... | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# jobs ( job_id, job_desc, min_lvl, max_lvl )
# publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# pub_info ( pub_id, logo, pr_info )
# stores ( stor_id... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Find the difference between the average royalty of titles published by US and non US publishers? | 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 O... | {
"tables": [
"publishers",
"roysched",
"titles"
],
"measures": [
{
"type": "derived_metric",
"operator": "SUBTRACT",
"operands": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_... | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# roysched ( title_id, lorange, hirange, royalty )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# publishers ( pub_id, pub_name, city, state, country ) | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
book_publishing_company | Calculate the average level difference between the Marketing editors hired by the US and non-US publishers? | 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... | {
"tables": [
"employee",
"jobs",
"publishers"
],
"measures": [
{
"type": "derived_metric",
"operator": "SUBTRACT",
"operands": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_me... | # authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# jobs ( job_id, job_desc, min_lvl, max_lvl )
# publishers ( pub_id, pub_name, city, state, country )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# pub_info ( pub_id, logo, pr_info )
# stores ( stor_id... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
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? | 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.' | {
"tables": [
"publishers",
"titles"
],
"dimensions": [
"title",
"pub_name",
"price"
],
"_source": "sqlite",
"filters": [
"titles.notes = 'Helpful hints on how to use your electronic resources to the best advantage.'",
"titles.pub_id = publishers.pub_id"
]
} | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# publishers ( pub_id, pub_name, city, state, country )
# roysched ( title_id, lorange, hirange, royalty )
# sales ( stor_id, ord_num, ord_date, qty, payterms, t... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
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? | 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.' | {
"tables": [
"publishers",
"titles"
],
"dimensions": [
"title",
"pub_name",
"ytd_sales"
],
"_source": "sqlite",
"filters": [
"titles.notes = 'Carefully researched study of the effects of strong emotions on the body. Metabolic charts included.'",
"titles.pub_id = publishers.pub_i... | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# titleauthor ( au_id, title_id, au_ord, royaltyper )
# publishers ( pub_id, pub_name, city, state, country )
# roysched ( title_id, lorange, hirange, royalty )
# sales ( stor_id, ord_num, ord_date, qty, payterms, t... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
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? | 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 | {
"tables": [
"publishers",
"sales",
"titles"
],
"dimensions": [
"title"
],
"order_by": [
{
"expr": "qty",
"desc": true
}
],
"limit": 5,
"_source": "sqlite",
"filters": [
{
"type": "subquery_comparison",
"left": "sales.qty",
"operator": ">",
... | # titles ( title_id, title, type, pub_id, price, advance, royalty, ytd_sales, notes, pubdate, title_ID )
# authors ( au_id, au_lname, au_fname, phone, address, city, state, zip, contract )
# employee ( emp_id, fname, minit, lname, job_id, job_lvl, pub_id, hire_date )
# sales ( stor_id, ord_num, ord_date, qty, payterms,... | true | simple | CREATE TABLE authors (
au_id TEXT,
au_lname TEXT,
au_fname TEXT,
phone TEXT,
address TEXT,
city TEXT,
state TEXT,
zip TEXT,
contract TEXT
);
CREATE TABLE discounts (
discounttype TEXT,
stor_id TEXT,
lowqty INTEGER,
highqty INTEGER,
discount REAL,
FOREIGN KEY ... | |
retail_complains | On which day was the most verbose complaint received? | 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 ) | {
"tables": [
"callcenterlogs"
],
"dimensions": [
"\"Date received\""
],
"_source": "sqlite",
"filters": [
{
"type": "subquery_comparison",
"left": "ser_time",
"operator": "=",
"nested_subquery": {
"tables": [
"callcenterlogs"
],
"measure... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
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? | 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' | {
"tables": [
"client",
"events"
],
"measures": [
{
"agg": "CALCULATED",
"expr": "CAST(COUNT(events.\"Complaint ID\") AS REAL) / NULLIF(3, 0)",
"alias": "average"
}
],
"_source": "sqlite",
"filters": [
"STRFTIME('%Y', events.\"Date received\") BETWEEN '2015' AND '2017'"... | # state ( StateCode, State, Region )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, add... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What was the serve time for the complaint call from client "C00007127" on 2017/2/22? | 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' | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"ser_time"
],
"_source": "sqlite",
"filters": [
"events.Client_ID = 'C00007127'",
"callcenterlogs.\"Date received\" = '2017-02-22'",
"callcenterlogs.\"Complaint ID\" = events.\"Complaint ID\""
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Which product received a review from Indianapolis on 2016/10/7? | 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' | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"reviews.Product"
],
"_source": "sqlite",
"filters": [
"district.city = 'Indianapolis'",
"reviews.Date = '2016-10-07'",
"reviews.district_id = district.district_id"
]
} | # reviews ( Date, Stars, Reviews, Product, district_id )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# ... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many stars did "Eagle Capital" received from Little Rock on 2013/4/4? | 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' | {
"tables": [
"district",
"reviews"
],
"measures": [
{
"agg": "COUNT",
"expr": "stars",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"reviews.Product = 'Eagle Capital'",
"district.city = 'Little Rock'",
"reviews.Date = '2013-04-04'",
"reviews.district_... | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | For the client who made the complaint call "CR0217298", what was his/her birthday？ | 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' | {
"tables": [
"client",
"events"
],
"dimensions": [
"month",
"day"
],
"_source": "sqlite",
"filters": [
"events.\"Complaint ID\" = 'CR0217298'",
"client.client_id = events.Client_ID"
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipco... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What was the phone of number of the client who made the complaint call "CR0100432" ？ | 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' | {
"tables": [
"client",
"events"
],
"dimensions": [
"phone"
],
"_source": "sqlite",
"filters": [
"events.\"Complaint ID\" = 'CR0100432'",
"client.client_id = events.Client_ID"
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipco... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many priority urgent complaints were received in march of 2017? List the complaint ID of these complaints. | 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 ) | {
"tables": [
"callcenterlogs"
],
"measures": [
{
"agg": "COUNT",
"expr": "\"Complaint ID\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"\"Date received\" LIKE '2017-01%'",
{
"type": "subquery_comparison",
"left": "priority",
"operator": "=",
... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List all the states in the South region. | List all the states in the South region. | N/A | SELECT state FROM state WHERE Region = 'South' | {
"tables": [
"state"
],
"dimensions": [
"state"
],
"_source": "sqlite",
"filters": [
"Region = 'South'"
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# state ( StateCode, State, Region ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Calculate the average age of clients from the Midwest region. | 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' | {
"tables": [
"client",
"district",
"state"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "simple_metric",
"agg": "SUM",
"field": "client.age"
},
{
"type": "simple_metric"... | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division )
# state ( StateCode, State, Region ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Find and list the names of districts which has below-average stars for Eagle Capital. | 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 ) | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"division"
],
"_source": "sqlite",
"filters": [
"reviews.Product = 'Eagle Capital'",
{
"type": "subquery_comparison",
"left": "reviews.Stars",
"operator": ">",
"nested_subquery": {
"tables": [
... | # reviews ( Date, Stars, Reviews, Product, district_id )
# district ( district_id, city, state_abbrev, division ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the medium through which most complaints are registered in Florida? | 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 | {
"tables": [
"callcenterlogs",
"client",
"events"
],
"dimensions": [
"events.\"Submitted via\""
],
"order_by": [
{
"expr": "COUNT(callcenterlogs.\"Complaint ID\")",
"desc": true
}
],
"limit": 1,
"group_by": [
"callcenterlogs.\"Complaint ID\""
],
"_source": "s... | # state ( StateCode, State, Region )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, add... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What percentage of consumers from Houston disputed complaints? | 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 | {
"tables": [
"client",
"events"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metric",
"agg": "SUM",
"field": "*",
"filter": {
"expression": "CASE WHEN events.\"Consume... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, da... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Find the number of service members who complained in Syracuse. | 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' | {
"tables": [
"client",
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "client.client_id",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"events.Tags = 'Servicemember'",
"client.city = 'Syracuse'",
"client.client_id = events.Client_ID"
]
} | # state ( StateCode, State, Region )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, add... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Among the calls from California, what percentage are priority 1? | 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 = 'Ca... | {
"tables": [
"callcenterlogs",
"client",
"district",
"state"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metric",
"agg": "SUM",
"field": "*",
"filter": {
"col... | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipco... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Calculate the difference in the average age of elderly and middle-aged clients in the Northeast region. | 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 O... | {
"tables": [
"client",
"district",
"state"
],
"measures": [
{
"type": "derived_metric",
"operator": "SUBTRACT",
"operands": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metri... | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division )
# state ( StateCode, State, Region ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List by their ID number the 3 longest complaints. | 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 | {
"tables": [
"callcenterlogs"
],
"dimensions": [
"\"Complaint ID\""
],
"order_by": [
{
"expr": "ser_time",
"desc": true
}
],
"limit": 3,
"_source": "sqlite"
} | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Identify by their ID all clients who did not give their consent permission. | 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?' = '' | {
"tables": [
"events"
],
"dimensions": [
"Client_ID"
],
"_source": "sqlite",
"filters": [
"\"Consumer consent provided?\" = 'N/A' OR 'Consumer consent provided?' IS NULL OR 'Consumer consent provided?' = ''"
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List by their ID the complaints received by the company on 25/09/2014 that took the longest. | 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' | {
"tables": [
"events"
],
"dimensions": [
"\"Complaint ID\""
],
"_source": "sqlite",
"filters": [
{
"type": "subquery_comparison",
"left": "STRFTIME('%J', \"Date sent to company\") - STRFTIME('%J', \"Date received\")",
"operator": "=",
"nested_subquery": {
"tables... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many complaints are not in process with an agent? | 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' | {
"tables": [
"callcenterlogs"
],
"measures": [
{
"agg": "COUNT",
"expr": "outcome",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"outcome <> 'AGENT'"
]
} | # state ( StateCode, State, Region )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, add... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many Credit Card complaints did Sharon handle? | 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' | {
"tables": [
"callcenterlogs",
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "callcenterlogs.\"Complaint ID\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"events.Product = 'Credit card'",
"callcenterlogs.server = 'SHARON'",
"callcenterlogs.\"Comp... | # state ( StateCode, State, Region )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, add... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | In which region have the most 1-star reviews been done? | 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 | {
"tables": [
"district",
"reviews",
"state"
],
"dimensions": [
"region"
],
"order_by": [
{
"expr": "COUNT(region)",
"desc": true
}
],
"limit": 1,
"group_by": [
"region"
],
"_source": "sqlite",
"filters": [
"reviews.Stars = 1",
"reviews.district_id =... | # reviews ( Date, Stars, Reviews, Product, district_id )
# state ( StateCode, State, Region )
# district ( district_id, city, state_abbrev, division ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | In what years were the clients who demanded more problems with Certificate of deposit born? | 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 | {
"tables": [
"client",
"events"
],
"dimensions": [
"year"
],
"order_by": [
{
"expr": "COUNT(year)",
"desc": true
}
],
"limit": 1,
"group_by": [
"year"
],
"_source": "sqlite",
"filters": [
"events.\"Sub-product\" = '(CD) Certificate of deposit'",
"client... | # state ( StateCode, State, Region )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, add... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many cases of billing dispute issues occurred in the Mountain division? | 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' | {
"tables": [
"client",
"district",
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "issue",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"events.Issue = 'Billing disputes'",
"district.division = 'Mountain'",
"events.Client_ID = client.client_id",
... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, da... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Lists the last name of all clients who made a PS-type complaint and were served by TOVA. | Lists the last name of all clients who made a PS-type complaint and were served by TOVA. | PS-type complaint refers to type = 'PS'; served by refers to server; | SELECT t1.last FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T2.type = 'PS' AND T2.server = 'TOVA' | {
"tables": [
"callcenterlogs",
"client"
],
"dimensions": [
"last"
],
"_source": "sqlite",
"filters": [
"callcenterlogs.type = 'PS'",
"callcenterlogs.server = 'TOVA'",
"client.client_id = callcenterlogs.\"rand client\""
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the name of the state in which there have been the largest number of complaints with priority 0? | What is the name of the state in which there have been the largest number of complaints with priority 0? | largest number of complaints refers to MAX(COUNT("Complaint ID") WHERE priority = 0); | SELECT T2.state 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 T1.priority = 0 GROUP BY T2.state ORDER BY COUNT(T2.state) DESC LIMIT 1 | {
"tables": [
"callcenterlogs",
"client",
"district",
"state"
],
"dimensions": [
"client.state"
],
"order_by": [
{
"expr": "COUNT(client.state)",
"desc": true
}
],
"limit": 1,
"group_by": [
"client.state"
],
"_source": "sqlite",
"filters": [
"callcen... | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many complaints were served in 5 minutes or less by DORIT and responded to the customer with an explanation, were made by phone? | How many complaints were served in 5 minutes or less by DORIT and responded to the customer with an explanation, were made by phone? | served in 5 minutes or less refers to ser_time < '00:05:00'; DORIT refers to server = 'DORIT'; responded with an explanation refers to "Company response to consumer" = 'Closed with explanation'; made by refers to "Submitted via"; | SELECT COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T1.ser_time < '00:05:00' AND T1.server = 'DORIT' AND T2.`Submitted via` = 'Phone' AND T2.`Company response to consumer` = 'Closed with explanation' | {
"tables": [
"callcenterlogs",
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "callcenterlogs.\"Complaint ID\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"callcenterlogs.ser_time < '00:05:00'",
"callcenterlogs.server = 'DORIT'",
"events.\"Submitt... | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many reviews by people between 30 and 50 years include the word 'great'? | How many reviews by people between 30 and 50 years include the word 'great'? | between 30 and 50 years refers to age BETWEEN 30 AND 50; include the word great refers to Review like '%Great%'; | SELECT COUNT(T1.Reviews) FROM reviews AS T1 INNER JOIN client AS T2 ON T1.district_id = T2.district_id WHERE T2.age BETWEEN 30 AND 50 AND T1.Reviews LIKE '%great%' | {
"tables": [
"client",
"reviews"
],
"measures": [
{
"agg": "COUNT",
"expr": "reviews",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"client.age BETWEEN 30 AND 50",
"reviews.Reviews LIKE '%great%'",
"reviews.district_id = client.district_id"
]
} | # reviews ( Date, Stars, Reviews, Product, district_id )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the average number of stars given by Oregon clients in their reviews? | What is the average number of stars given by Oregon clients in their reviews? | average = DIVIDE(SUM(State = 'Oregon'), COUNT(district_id)); Oregon refers to state = 'Oregon'; | SELECT CAST(SUM(T3.Stars) AS REAL) / COUNT(T3.Stars) AS average FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN reviews AS T3 ON T2.district_id = T3.district_id WHERE T1.State = 'Oregon' | {
"tables": [
"district",
"reviews",
"state"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "simple_metric",
"agg": "SUM",
"field": "reviews.Stars"
},
{
"type": "simple_met... | # reviews ( Date, Stars, Reviews, Product, district_id )
# district ( district_id, city, state_abbrev, division )
# state ( StateCode, State, Region, state ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What percentage of clients who sent their complaints by postal mail are age 50 and older? | What percentage of clients who sent their complaints by postal mail are age 50 and older? | percentage = MULTIPLY(DIVIDE(SUM("Submitted via" = 'Postal mail'), COUNT(client_id)), 1.0); sent their complaints by refers to "Submitted via"; age > 50; | SELECT CAST(SUM(CASE WHEN T1.age > 50 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.`Submitted via`) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Submitted via` = 'Postal mail' | {
"tables": [
"client",
"events"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metric",
"agg": "SUM",
"field": "*",
"filter": {
"column": "client.age",
"oper... | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many clients who live in Kansas City provided a 1-star review? | How many clients who live in Kansas City provided a 1-star review? | 1-star review refers stars = 1; | SELECT COUNT(T1.Stars) FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T2.city = 'Kansas City' AND T1.Stars = 1 | {
"tables": [
"district",
"reviews"
],
"measures": [
{
"agg": "COUNT",
"expr": "stars",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"district.city = 'Kansas City'",
"reviews.Stars = 1",
"reviews.district_id = district.district_id"
]
} | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complai... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Which state has the highest number of clients who gave a 5-star review? | Which state has the highest number of clients who gave a 5-star review? | highest number of clients refers to MAX(COUNT(client_id)); 5-star review refers to stars = 5; | SELECT T2.state_abbrev FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Stars = 5 GROUP BY T2.state_abbrev ORDER BY COUNT(T2.state_abbrev) DESC LIMIT 1 | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"state_abbrev"
],
"order_by": [
{
"expr": "COUNT(state_abbrev)",
"desc": true
}
],
"limit": 1,
"group_by": [
"state_abbrev"
],
"_source": "sqlite",
"filters": [
"reviews.Stars = 5",
"reviews.district... | # state ( StateCode, State, Region, state )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division )
# reviews ( Date, Stars, Reviews, Prod... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What are the products that people who were born after 2005 complain about? | What are the products that people who were born after 2005 complain about? | year > 2005; | SELECT DISTINCT T2.Product FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.year > 2005 | {
"tables": [
"client",
"events"
],
"dimensions": [
"events.Product"
],
"_source": "sqlite",
"is_distinct": true,
"filters": [
"client.year > 2005",
"client.client_id = events.Client_ID"
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What was the issue that the client with the longest server time faced? | What was the issue that the client with the longest server time faced? | longest server time refers to MAX(ser_time); | SELECT T2.Issue FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T1.ser_time = ( SELECT MAX(ser_time) FROM callcenterlogs ) | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"issue"
],
"_source": "sqlite",
"filters": [
{
"type": "subquery_comparison",
"left": "callcenterlogs.ser_time",
"operator": "=",
"nested_subquery": {
"tables": [
"callcenterlogs"
],... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many clients who live in New York City submitted their complaints via fax? | How many clients who live in New York City submitted their complaints via fax? | submitted complaints via fax refers to "Submitted via" = 'Fax'; | SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T1.city = 'New York City' AND T2.`Submitted via` = 'Fax' | {
"tables": [
"client",
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "client.client_id",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"client.city = 'New York City'",
"events.\"Submitted via\" = 'Fax'",
"client.client_id = events.Client_ID"
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, da... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the birth date of the youngest client? | What is the birth date of the youngest client? | birth date refers to year, month, day; youngest client refers to max(year, month, day) | SELECT day, month, year FROM client ORDER BY year DESC, month DESC, day DESC LIMIT 1 | {
"tables": [
"client"
],
"dimensions": [
"day",
"month",
"year"
],
"order_by": [
{
"expr": "year",
"desc": true
},
{
"expr": "month",
"desc": true
},
{
"expr": "day",
"desc": true
}
],
"limit": 1,
"_source": "sqlite"
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many times does the consumer have no dispute over a non-timely response from the company? | How many times does the consumer have no dispute over a non-timely response from the company? | no dispute refers to Consumer disputed? = 'No'; non-timely response refers to Timely response? = 'No' | SELECT COUNT(`Timely response?`) FROM events WHERE `Timely response?` = 'No' AND `Consumer disputed?` = 'No' | {
"tables": [
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "\"Timely response?\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"\"Timely response?\" = 'No'",
"\"Consumer disputed?\" = 'No'"
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many of the complaints are longer than 15 minutes? | How many of the complaints are longer than 15 minutes? | longer than 15 minutes refers to ser_time > '00:15:00' | SELECT COUNT(ser_time) FROM callcenterlogs WHERE strftime('%M', ser_time) > '15' | {
"tables": [
"callcenterlogs"
],
"measures": [
{
"agg": "COUNT",
"expr": "ser_time",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"DATE_EXTRACT('minute', ser_time) > '15'"
]
} | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the most common issue for the highest priority complaints? | What is the most common issue for the highest priority complaints? | most common refers to max(count(issue)); highest priority refers to priority = 2 | SELECT T1.Issue FROM events AS T1 INNER JOIN callcenterlogs AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.priority = 2 GROUP BY T1.Issue ORDER BY COUNT(T1.Issue) DESC LIMIT 1 | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"issue"
],
"order_by": [
{
"expr": "COUNT(issue)",
"desc": true
}
],
"limit": 1,
"group_by": [
"issue"
],
"_source": "sqlite",
"filters": [
"callcenterlogs.priority = 2",
"events.\"Complaint ID\... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the social number of the person who made the most complaints? | What is the social number of the person who made the most complaints? | social number refers to social; most complaints refers to max(count(event.Client_ID)) | SELECT T1.social FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID GROUP BY T1.client_id ORDER BY COUNT(T1.client_id) DESC LIMIT 1 | {
"tables": [
"client",
"events"
],
"dimensions": [
"social"
],
"order_by": [
{
"expr": "COUNT(client.client_id)",
"desc": true
}
],
"limit": 1,
"group_by": [
"client.client_id"
],
"_source": "sqlite",
"filters": [
"client.client_id = events.Client_ID"
]
} | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Which is the city where most of the 1 star reviews come from? | Which is the city where most of the 1 star reviews come from? | most refers to max(count(state_abbrev)); 1 star review refers to Stars = 1 | SELECT T2.city FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Stars = 1 GROUP BY T2.city ORDER BY COUNT(T2.city) DESC LIMIT 1 | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"district.city"
],
"order_by": [
{
"expr": "COUNT(district.city)",
"desc": true
}
],
"limit": 1,
"group_by": [
"district.city"
],
"_source": "sqlite",
"filters": [
"reviews.Stars = 1",
"reviews.distr... | # reviews ( Date, Stars, Reviews, Product, district_id )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, las... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List all the server of the phone complaints with a late response from the company. | List all the server of the phone complaints with a late response from the company. | phone complaint refers to Submitted via = 'Phone'; late response refers to Timely response? = 'No' | SELECT DISTINCT T2.server FROM events AS T1 INNER JOIN callcenterlogs AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T1.`Submitted via` = 'Phone' AND T1.`Timely response?` = 'No' | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"server"
],
"_source": "sqlite",
"is_distinct": true,
"filters": [
"events.\"Submitted via\" = 'Phone'",
"events.\"Timely response?\" = 'No'",
"events.\"Complaint ID\" = callcenterlogs.\"Complaint ID\""
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Which region has the second most clients? | Which region has the second most clients? | region refers to division; second most refers to second max(client_id) | SELECT T2.division FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id GROUP BY T2.division ORDER BY COUNT(T2.division) DESC LIMIT 1, 1 | {
"tables": [
"client",
"district"
],
"dimensions": [
"division"
],
"order_by": [
{
"expr": "COUNT(division)",
"desc": true
}
],
"limit": [
1,
1
],
"group_by": [
"division"
],
"_source": "sqlite",
"filters": [
"client.district_id = district.distric... | # state ( StateCode, State, Region, state )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Compute the average time in minute for each age group | Compute the average time in minute for each age group | teenager refers to 13 < age < = 19; adult refers to 19 < age < = 65; elder refers to age < = 65; highest average time per complaint = max(divide(sum(ser_time), count(ser_time))) | SELECT CAST(SUM(CASE WHEN T1.age > 13 AND T1.age <= 19 THEN 60 * strftime('%H', ser_time) + strftime('%M', ser_time) + strftime('%S', ser_time) / 60 ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age > 13 AND T1.age <= 19 THEN 1 ELSE 0 END) AS teenagerAverageMins, CAST(SUM(CASE WHEN T1.age > 19 AND T1.age <= 65 THEN 60 * strf... | {
"tables": [
"callcenterlogs",
"client"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metric",
"agg": "SUM",
"field": "60 * STRFTIME('%H', ser_time) + STRFTIME('%M', ser_time) + STRFTIME('%S... | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipco... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Calculate the percentage of male clients from Indianapolis City. | Calculate the percentage of male clients from Indianapolis City. | male refers to sex = 'Male'; Indianapolis City refers to city = 'Indianapolis'; percentage = divide(count(client_id where sex = 'Male' and city = 'Indianapolis') , count(client_id where city = 'Indianapolis')) * 100% | SELECT CAST(SUM(CASE WHEN sex = 'Male' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(client_id) FROM client WHERE city = 'Indianapolis' | {
"tables": [
"client"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metric",
"agg": "SUM",
"field": "*",
"filter": {
"column": "sex",
"operator": "=",
... | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Among the teenager clients who use Google account and Microsoft account, which group of client is more than the other? | Among the teenager clients who use Google account and Microsoft account, which group of client is more than the other? | teenager refers to 13 < age < = 19; Google account refers to email like '%@gmail.com'; Microsoft account refers to email like '%@outlook.com' | SELECT CASE WHEN SUM(CASE WHEN email LIKE '%@gmail.com' THEN 1 ELSE 0 END) > SUM(CASE WHEN email LIKE '%@outlook.com' THEN 1 ELSE 0 END) THEN 'Google account' ELSE 'Microsoft account' END FROM client WHERE age BETWEEN 13 AND 19 | {
"tables": [
"client"
],
"measures": [
{
"agg": "CALCULATED",
"expr": "CASE WHEN SUM(CASE WHEN email LIKE '%@gmail.com' THEN 1 ELSE 0 END) > SUM(CASE WHEN email LIKE '%@outlook.com' THEN 1 ELSE 0 END) THEN 'Google account' ELSE 'Microsoft account' END",
"alias": ""
}
],
"_source... | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many clients who live in New York City have the complaint outcome as "AGENT"? | How many clients who live in New York City have the complaint outcome as "AGENT"? | New York City refers to city = 'New York City' | SELECT COUNT(T2.`rand client`) FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T1.city = 'New York City' AND T2.outcome = 'AGENT' | {
"tables": [
"callcenterlogs",
"client"
],
"measures": [
{
"agg": "COUNT",
"expr": "callcenterlogs.\"rand client\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"client.city = 'New York City'",
"callcenterlogs.outcome = 'AGENT'",
"client.client_id = call... | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipco... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What are the complaint id of client who were born in 1931? | What are the complaint id of client who were born in 1931? | in 1931 refers to year = 1931 | SELECT T2.`Complaint ID` FROM client AS T1 INNER JOIN callcenterlogs AS T2 ON T1.client_id = T2.`rand client` WHERE T1.year = 1931 | {
"tables": [
"callcenterlogs",
"client"
],
"dimensions": [
"callcenterlogs.\"Complaint ID\""
],
"_source": "sqlite",
"filters": [
"client.year = 1931",
"client.client_id = callcenterlogs.\"rand client\""
]
} | # client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Complaint about Credit Card mostly came from clients of which age group? | Complaint about Credit Card mostly came from clients of which age group? | about Credit Card refers to Product = 'Credit Card'; teenager refers to 13 < age < = 19; adult refers to 19 < age < = 65; elder refers to age < = 65 | SELECT SUM(CASE WHEN T1.age > 13 AND T1.age <= 19 THEN 1 ELSE 0 END), SUM(CASE WHEN T1.age > 19 AND T1.age <= 65 THEN 1 ELSE 0 END) AS adult , SUM(CASE WHEN T1.age > 65 THEN 1 ELSE 0 END) AS elder FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.Product = 'Credit card' | {
"tables": [
"client",
"events"
],
"measures": [
{
"agg": "SUM",
"expr": "CASE WHEN age > 13 AND age <= 19 THEN 1 ELSE 0 END",
"alias": ""
},
{
"agg": "SUM",
"expr": "CASE WHEN age > 19 AND age <= 65 THEN 1 ELSE 0 END",
"alias": "adult"
},
{
"... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List down the issues for complaint with server time of below 10 minutes. | List down the issues for complaint with server time of below 10 minutes. | server time of below 10 minutes refers to ser_time < '00:10:00' | SELECT T2.Issue FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE strftime('%M', T1.ser_time) < '10' | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"issue"
],
"_source": "sqlite",
"filters": [
"DATE_EXTRACT('minute', callcenterlogs.ser_time) < '10'",
"callcenterlogs.\"Complaint ID\" = events.\"Complaint ID\""
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Write down the date received of complaints sent via Fax. | Write down the date received of complaints sent via Fax. | sent via Fax refers to Submitted via = 'Fax' | SELECT T1.`Date received` FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.`Submitted via` = 'Fax' | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"callcenterlogs.\"Date received\""
],
"_source": "sqlite",
"filters": [
"events.\"Submitted via\" = 'Fax'",
"callcenterlogs.\"Complaint ID\" = events.\"Complaint ID\""
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Write the complaint ID, call ID, and final phone number of complaints through AVIDAN server from 1/1/2014 to 12/30/2014. | Write the complaint ID, call ID, and final phone number of complaints through AVIDAN server from 1/1/2014 to 12/30/2014. | final phone number refers to phonefinal; from 1/1/2014 to 12/30/2014 refers to Date received between '2014-01-01' and '2014-12-30' | SELECT `Complaint ID`, call_id, phonefinal FROM callcenterlogs WHERE strftime('%Y', `Date received`) = '2014' AND server = 'AVIDAN' | {
"tables": [
"callcenterlogs"
],
"dimensions": [
"\"Complaint ID\"",
"call_id",
"phonefinal"
],
"_source": "sqlite",
"filters": [
{
"type": "time_filter",
"field": "\"Date received\"",
"unit": "YEAR",
"operator": "EQ",
"value": "2014"
},
"server = '... | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Between 1/1/2017 and 4/1/2017, what is the average server time of calls under the server DARMON? | Between 1/1/2017 and 4/1/2017, what is the average server time of calls under the server DARMON? | between 1/1/2017 and 4/1/2017 refers to Date received between '2017-01-01' and '2017-04-01'; average server time refers to avg(ser_time) | SELECT AVG(CAST(SUBSTR(ser_time, 4, 2) AS REAL)) FROM callcenterlogs WHERE `Date received` BETWEEN '2017-01-01' AND '2017-04-01' | {
"tables": [
"callcenterlogs"
],
"measures": [
{
"agg": "AVG",
"expr": "CAST(SUBSTRING(ser_time, 4, 2) AS REAL)",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"\"Date received\" BETWEEN '2017-01-01' AND '2017-04-01'"
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | How many times per year does a credit card customer complain about overlimit fees? | How many times per year does a credit card customer complain about overlimit fees? | credit card customer refers to product = 'Credit card'; about overlimit fees refers to issue = 'Overlimit fee' | SELECT strftime('%Y', `Date received`), COUNT(`Date received`) FROM events WHERE product = 'Credit card' AND issue = 'Overlimit fee' GROUP BY strftime('%Y', `Date received`) HAVING COUNT(`Date received`) | {
"tables": [
"events"
],
"dimensions": [
"DATE_EXTRACT('year', \"Date received\")"
],
"measures": [
{
"agg": "COUNT",
"expr": "\"Date received\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"product = 'Credit card'",
"issue = 'Overlimit fee'",
"COUN... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID )
# callcenterlogs ( Date received, Complaint ID, rand client... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List the top five cities in terms of the number of 5-star ratings in 2016 reviews, in descending order. | List the top five cities in terms of the number of 5-star ratings in 2016 reviews, in descending order. | 5-star rating refers to Stars = 5; in 2016 refers to Date like '2016%'; most reviews refers to max(count(city)) | SELECT T2.city FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id WHERE T1.Stars = 5 AND T1.Date LIKE '2016%' ORDER BY T1.Date DESC LIMIT 5 | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"district.city"
],
"order_by": [
{
"expr": "date",
"desc": true
}
],
"limit": 5,
"_source": "sqlite",
"filters": [
"reviews.Stars = 5",
"reviews.Date LIKE '2016%'",
"reviews.district_id = district.distri... | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the longest server time when the call is about the issue of arbitration? | What is the longest server time when the call is about the issue of arbitration? | longest server time refers to max(ser_time) | SELECT MAX(T1.ser_time) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.issue = 'Arbitration' | {
"tables": [
"callcenterlogs",
"events"
],
"measures": [
{
"agg": "MAX",
"expr": "ser_time",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"events.issue = 'Arbitration'",
"callcenterlogs.\"Complaint ID\" = events.\"Complaint ID\""
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Please calculate the number of clients by each division. | Please calculate the number of clients by each division. | N/A | SELECT T2.division, COUNT(T2.division) FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id GROUP BY T2.division | {
"tables": [
"client",
"district"
],
"dimensions": [
"division"
],
"measures": [
{
"agg": "COUNT",
"expr": "division",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"client.district_id = district.district_id"
]
} | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Which city in the Midwest region has the least number of clients? | Which city in the Midwest region has the least number of clients? | least number of clients refers to min(count(client_id)) | SELECT T2.city 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' GROUP BY T2.city ORDER BY COUNT(T2.city) LIMIT 1 | {
"tables": [
"client",
"district",
"state"
],
"dimensions": [
"district.city"
],
"order_by": [
{
"expr": "COUNT(district.city)",
"desc": false
}
],
"limit": 1,
"group_by": [
"district.city"
],
"_source": "sqlite",
"filters": [
"state.Region = 'Midwest'"... | # state ( StateCode, State, Region, state )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | What is the percentage of complaints about the late fee issue whose priority is 2 in 2017? | What is the percentage of complaints about the late fee issue whose priority is 2 in 2017? | percentage = divide(count(Complaint ID where priority = 2) , count(Complaint ID)) * 100%; in 2017 refers to year(Date received) = 2017 | SELECT CAST(SUM(CASE WHEN T1.priority = 2 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE strftime('%Y', T1.`Date received`) = '2017' | {
"tables": [
"callcenterlogs",
"events"
],
"measures": [
{
"type": "derived_metric",
"operator": "DIVIDE",
"operands": [
{
"type": "filtered_metric",
"agg": "SUM",
"field": "*",
"filter": {
"column": "callcenterlogs.priorit... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, issue )
# callcenterlogs ( Date received, Complaint ID, rand... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Which state has the most cities? | Which state has the most cities? | state refers to state_abbrev; most cities refers to max(count(city)) | SELECT state_abbrev FROM district GROUP BY state_abbrev ORDER BY COUNT(city) DESC LIMIT 1 | {
"tables": [
"district"
],
"dimensions": [
"state_abbrev"
],
"order_by": [
{
"expr": "COUNT(city)",
"desc": true
}
],
"limit": 1,
"group_by": [
"state_abbrev"
],
"_source": "sqlite"
} | # state ( StateCode, State, Region, state )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, email, address_1, address_2, city, state, zipcode, district_id )
# district ( district_id, city, state_abbrev, division ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Please list all clients' phone numbers and complaint IDs which are still in progress. | Please list all clients' phone numbers and complaint IDs which are still in progress. | in progress refers to Company response to consumer = 'In progress' | SELECT T1.phone, T2.`Complaint ID` FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Company response to consumer` = 'In progress' | {
"tables": [
"client",
"events"
],
"dimensions": [
"phone",
"events.\"Complaint ID\""
],
"_source": "sqlite",
"filters": [
"events.\"Company response to consumer\" = 'In progress'",
"client.client_id = events.Client_ID"
]
} | # callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to compa... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | In 2014, what is the percentage of complaints from consumers in Houston that the delay was over 5 days? | In 2014, what is the percentage of complaints from consumers in Houston that the delay was over 5 days? | in 2014 refers to Date received LIKE'2014%'; Houston refers to city = 'Houston'; delay over 5 days refers to subtract(Date sent to company, Date received) > 5; percentage = divide(count(Complaint ID where subtract(Date sent to company , Date received) > 5) , count(Complaint ID)) * 100% | SELECT CAST((SUM(CASE WHEN strftime('%J', T2.`Date sent to company`) - strftime('%J', T2.`Date received`) > 5 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 WHERE T1.city = 'Houston' AND strftime('%Y', T2.`Date received`) = '2014' | {
"tables": [
"client",
"events"
],
"measures": [
{
"agg": "CALCULATED",
"expr": "(CAST((SUM(CASE WHEN STRFTIME('%J', events.\"Date sent to company\") - STRFTIME('%J', events.\"Date received\") > 5 THEN 1 ELSE 0 END)) AS REAL) / NULLIF(COUNT(client.client_id), 0)) * 100"
}
],
"_sou... | # state ( StateCode, State, Region, state )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, last, phone, ema... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | In the complains received in 2012, how many of them are submitted through email? | In the complains received in 2012, how many of them are submitted through email? | received in 2012 refers to Date received LIKE '2012%'; submitted through email refers to Submitted via = 'Email' | SELECT COUNT(`Submitted via`) FROM events WHERE strftime('%Y', `Date received`) = '2012' AND `Submitted via` = 'Email' | {
"tables": [
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "\"Submitted via\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
{
"type": "time_filter",
"field": "\"Date received\"",
"unit": "YEAR",
"operator": "EQ",
"value": "2012"
... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, issue )
# callcenterlogs ( Date received, Complaint ID, rand... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Give the client ID of the complaint received on April 16, 2014 and submitted through fax. | Give the client ID of the complaint received on April 16, 2014 and submitted through fax. | April 16, 2014 refers to Date received = '2014-04-16'; submitted through fax refers to Submitted via = 'Fax' | SELECT T2.Client_ID FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.`Submitted via` = 'Fax' AND T1.`Date received` = '2014-04-16' | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"events.Client_ID"
],
"_source": "sqlite",
"filters": [
"events.\"Submitted via\" = 'Fax'",
"callcenterlogs.\"Date received\" = '2014-04-16'",
"callcenterlogs.\"Complaint ID\" = events.\"Complaint ID\""
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, issue )
# client ( client_id ( e.g., `alias: name`, etc. ), ... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List date of the review of the Eagle Capital from Indianapolis, Indiana. | List date of the review of the Eagle Capital from Indianapolis, Indiana. | Eagle Capital refers to Product = 'Eagle Capital'; Indianapolis refers to city = 'Indianapolis'; Indiana refers to state_abbrev = 'IN' | SELECT T2.Date FROM district AS T1 INNER JOIN reviews AS T2 ON T1.district_id = T2.district_id WHERE T2.Product = 'Eagle Capital' AND T1.city = 'Indianapolis' AND T1.state_abbrev = 'IN' | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"date"
],
"_source": "sqlite",
"filters": [
"reviews.Product = 'Eagle Capital'",
"district.city = 'Indianapolis'",
"district.state_abbrev = 'IN'",
"district.district_id = reviews.district_id"
]
} | # reviews ( Date, Stars, Reviews, Product, district_id )
# events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, iss... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Among the complaints received in year 2015, what is total number of complaints timely response and closed with an explanation? | Among the complaints received in year 2015, what is total number of complaints timely response and closed with an explanation? | in year 2015 refers to Date received LIKE '2015%'; timely response refers to Timely response?" = 'Yes'; closed with an explanation refers to Company response to consumer = 'Closed with explanation' | SELECT COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE strftime('%Y', T1.`Date received`) = '2015' AND T2.`Timely response?` = 'Yes' AND T2.`Company response to consumer` = 'Closed with explanation' | {
"tables": [
"callcenterlogs",
"events"
],
"measures": [
{
"agg": "COUNT",
"expr": "callcenterlogs.\"Complaint ID\"",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
{
"type": "time_filter",
"field": "callcenterlogs.\"Date received\"",
"unit": "YEA... | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, issue )
# callcenterlogs ( Date received, Complaint ID, rand... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List the product reviewed with 1 star on March 14, 2016 from Newton, Massachusetts. | List the product reviewed with 1 star on March 14, 2016 from Newton, Massachusetts. | 1 star refers to Stars = 1; on March 14, 2016 refers to Date = '2016-03-14'; Newton refers to city = 'Newton'; Massachusetts refers to state_abbrev = 'MA' | SELECT T2.Product FROM district AS T1 INNER JOIN reviews AS T2 ON T1.district_id = T2.district_id WHERE T1.city = 'Newton' AND T1.state_abbrev = 'MA' AND T2.Date = '2016-03-14' AND T2.Stars = 1 | {
"tables": [
"district",
"reviews"
],
"dimensions": [
"reviews.Product"
],
"_source": "sqlite",
"filters": [
"district.city = 'Newton'",
"district.state_abbrev = 'MA'",
"reviews.Date = '2016-03-14'",
"reviews.Stars = 1",
"district.district_id = reviews.district_id"
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, issue )
# reviews ( Date, Stars, Reviews, Product, district_... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | In reviews for the Eagle National Bank product, how many of the 5 star reviews where from Nashville, Tennessee? | In reviews for the Eagle National Bank product, how many of the 5 star reviews where from Nashville, Tennessee? | 5 star refers to Stars = 5; Nashville refers to city = 'Nashville'; Tennessee refers to state_abbrev = 'TN' | SELECT COUNT(T2.Stars) FROM district AS T1 INNER JOIN reviews AS T2 ON T1.district_id = T2.district_id WHERE T1.city = 'Nashville' AND T1.state_abbrev = 'TN' AND T2.Product = 'Eagle National Mortgage' AND T2.Stars = 5 | {
"tables": [
"district",
"reviews"
],
"measures": [
{
"agg": "COUNT",
"expr": "stars",
"alias": ""
}
],
"_source": "sqlite",
"filters": [
"district.city = 'Nashville'",
"district.state_abbrev = 'TN'",
"reviews.Product = 'Eagle National Mortgage'",
"reviews.... | # reviews ( Date, Stars, Reviews, Product, district_id )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# district ( district_id, city, state_abbrev, division ) | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | Among the reviews from midwest region, what are the products that received 1 star? | Among the reviews from midwest region, what are the products that received 1 star? | 1 star refers to Stars = 1 | SELECT DISTINCT T3.Product FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN reviews AS T3 ON T2.district_id = T3.district_id WHERE T1.Region = 'Midwest' AND T3.Stars = 1 | {
"tables": [
"district",
"reviews",
"state"
],
"dimensions": [
"reviews.Product"
],
"_source": "sqlite",
"is_distinct": true,
"filters": [
"state.Region = 'Midwest'",
"reviews.Stars = 1",
"state.StateCode = district.state_abbrev",
"district.district_id = reviews.district_i... | # reviews ( Date, Stars, Reviews, Product, district_id )
# callcenterlogs ( Date received, Complaint ID, rand client, phonefinal, vru+line, call_id, priority, type, outcome, server, ser_start, ser_exit, ser_time )
# client ( client_id ( e.g., `alias: name`, etc. ), sex, day, month, year, age, social, first, middle, las... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... | |
retail_complains | List the products involved in the complaints received on March 2017 via TOVA server. | List the products involved in the complaints received on March 2017 via TOVA server. | on March 2017 refers to Date received LIKE '%03%' AND Date received LIKE '2017%' | SELECT DISTINCT T2.Product FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T1.server = 'TOVA' AND T2.`Date received` LIKE '2017-03%' | {
"tables": [
"callcenterlogs",
"events"
],
"dimensions": [
"events.Product"
],
"_source": "sqlite",
"is_distinct": true,
"filters": [
"callcenterlogs.server = 'TOVA'",
"events.\"Date received\" LIKE '2017-03%'",
"callcenterlogs.\"Complaint ID\" = events.\"Complaint ID\""
]
} | # events ( Date received, Product, Sub-product, Issue, Sub-issue, Consumer complaint narrative, Tags, Consumer consent provided?, Submitted via, Date sent to company, Company response to consumer, Timely response?, Consumer disputed?, Complaint ID, Client_ID, issue )
# callcenterlogs ( Date received, Complaint ID, rand... | true | simple | CREATE TABLE callcenterlogs (
`Date received` DATE,
`Complaint ID` TEXT,
`rand client` TEXT,
phonefinal TEXT,
`vru+line` TEXT,
call_id INTEGER,
priority INTEGER,
type TEXT,
outcome TEXT,
server TEXT,
ser_start TEXT,
ser_exit TEXT,
ser_time TEXT,
FOREIGN KEY (`rand... |
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