1sf/bird-sql-train-with-schema huggingface dataset:
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: What is the medium through which most complaints are registered in Florida?
Evidence: medium refers to "Submitted via"; most complaints refers to MAX(Complaint ID); Florida refers to state = 'florida';
SQL: SELECT T3.`Submitted via` FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN events AS T3 ON T1.`Complaint ID` = T3.`Complaint ID` WHERE T2.state = 'FL' GROUP BY T1.`Complaint ID` ORDER BY COUNT(T1.`Complaint ID`) DESC LIMIT 1
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: Calculate the average number of complaints received from New Bedford each year which are closed with explanation.
Evidence: average = AVG("Complaint ID"); New Bedford refers to city = 'New Bedford'; closed with explanation refers to Company response to consumer = 'Closed with explanation';
SQL: SELECT STRFTIME('%Y', T3.`Date received`) , CAST(SUM(CASE WHEN T3.`Company response to consumer` = 'Closed with explanation' THEN 1 ELSE 0 END) AS REAL) / COUNT(T3.`Complaint ID`) AS average FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN events AS T3 ON T1.`Complaint ID` = T3.`Complaint ID` WHERE T2.city = 'New Bedford' GROUP BY strftime('%Y', T3.`Date received`)
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: What percentage of consumers from Houston disputed complaints?
Evidence: percentage = MULTIPLY(DIVIDE(SUM("Consumer disputed?" = 'Yes' AND city = 'Houston'), COUNT(client_id)), 1.0); Houston refers to city = 'Houston';
SQL: SELECT CAST(SUM(CASE WHEN T2.`Consumer disputed?` = 'Yes' AND T1.city = 'Houston' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: Find the number of service members who complained in Syracuse.
Evidence: service members refers to client.client_id; Syracuse refers to city = 'Syracuse';
SQL: SELECT COUNT(T1.client_id) FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.Tags = 'Servicemember' AND T1.city = 'Syracuse'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: Among the calls from California, what percentage are priority 1?
Evidence: California refers to state = 'California'; percentage = MULTIPLY(DIVIDE(SUM(priority = 1), COUNT("Complaint ID"), 1.0));
SQL: SELECT CAST(SUM(CASE WHEN T1.priority = 1 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.priority) FROM callcenterlogs AS T1 INNER JOIN client AS T2 ON T1.`rand client` = T2.client_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id INNER JOIN state AS T4 ON T3.state_abbrev = T4.StateCode WHERE T4.State = 'California'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: Calculate the difference in the average age of elderly and middle-aged clients in the Northeast region.
Evidence: 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;
SQL: SELECT (CAST(SUM(CASE WHEN T1.age BETWEEN 35 AND 55 THEN T1.age ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age BETWEEN 35 AND 55 THEN 1 ELSE 0 END)) - (CAST(SUM(CASE WHEN T1.age > 65 THEN T1.age ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.age > 65 THEN 1 ELSE 0 END)) AS difference FROM client AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T2.state_abbrev = T3.StateCode WHERE T3.Region = 'Northeast'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: List by their ID number the 3 longest complaints.
Evidence: ID number refers to "Complaint ID"; longest complaints refers to MAX(ser_time);
SQL: SELECT `Complaint ID` FROM callcenterlogs ORDER BY ser_time DESC LIMIT 3
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: How many clients have an email account other than gmail.com?
Evidence: email account other than gmail.com refers to email not like '%@gmail.com';
SQL: SELECT COUNT(email) FROM client WHERE email NOT LIKE '%@gmail.com'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: Identify by their ID all clients who did not give their consent permission.
Evidence: did not give their consent permission refers to Consumer consent provided is null, 'N/A', or empty;
SQL: SELECT Client_ID FROM events WHERE `Consumer consent provided?` = 'N/A' OR 'Consumer consent provided?' IS NULL OR 'Consumer consent provided?' = ''
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: List by their ID the complaints received by the company on 25/09/2014 that took the longest.
Evidence: 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"));
SQL: SELECT `Complaint ID` FROM events WHERE strftime('%J', `Date sent to company`) - strftime('%J', `Date received`) = ( SELECT MAX(strftime('%J', `Date sent to company`) - strftime('%J', `Date received`)) FROM events WHERE `Date sent to company` = '2014-09-25' ) AND `Date sent to company` = '2014-09-25'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: List priority 2 complaints by date received.
SQL: SELECT DISTINCT `Complaint ID` FROM callcenterlogs WHERE priority = 2 ORDER BY `Date received` DESC
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: How many complaints are not in process with an agent?
Evidence: not in process with an agent refers to outcome ! = 'AGENT';
SQL: SELECT COUNT(outcome) FROM callcenterlogs WHERE outcome != 'AGENT'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: How many Credit Card complaints did Sharon handle?
Evidence: Credit Card refers to Product = 'Credit Card'; Sharon refers to server = 'SHARON';
SQL: SELECT COUNT(T1.`Complaint ID`) FROM callcenterlogs AS T1 INNER JOIN events AS T2 ON T1.`Complaint ID` = T2.`Complaint ID` WHERE T2.Product = 'Credit card' AND T1.server = 'SHARON'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: In which region have the most 1-star reviews been done?
Evidence: most 1-star reviews refers to MAX(COUNT(stars = 1));
SQL: SELECT T3.Region FROM reviews AS T1 INNER JOIN district AS T2 ON T1.district_id = T2.district_id INNER JOIN state AS T3 ON T2.state_abbrev = T3.StateCode WHERE T1.Stars = 1 GROUP BY T3.Region ORDER BY COUNT(T3.Region) DESC LIMIT 1
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: In what years were the clients who demanded more problems with Certificate of deposit born?
Evidence: more problems with Certificate refers to MAX(COUNT("Sub-product" = '(CD) Certificate of deposit'));
SQL: SELECT T1.year FROM client AS T1 INNER JOIN events AS T2 ON T1.client_id = T2.Client_ID WHERE T2.`Sub-product` = '(CD) Certificate of deposit' GROUP BY T1.year ORDER BY COUNT(T1.year) DESC LIMIT 1
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: How many cases of billing dispute issues occurred in the Mountain division?
Evidence: billing dispute refers to issue = 'Billing disputes';
SQL: SELECT COUNT(T1.Issue) FROM events AS T1 INNER JOIN client AS T2 ON T1.Client_ID = T2.client_id INNER JOIN district AS T3 ON T2.district_id = T3.district_id WHERE T1.Issue = 'Billing disputes' AND T3.division = 'Mountain'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: How many male clients are from the state of Massachusetts?
Evidence: male refers to sex = 'Male';
SQL: SELECT COUNT(T3.sex) FROM state AS T1 INNER JOIN district AS T2 ON T1.StateCode = T2.state_abbrev INNER JOIN client AS T3 ON T2.district_id = T3.district_id WHERE T1.state = 'Massachusetts' AND T3.sex = 'Male'
Database: retail_complains
Tables: state, callcenterlogs, client, district, events, reviews
Columns (table index, column name): -1, *, 0, StateCode, 0, State, 0, Region, 1, Date received, 1, Complaint ID, 1, rand client, 1, phonefinal, 1, vru+line, 1, call_id, 1, priority, 1, type, 1, outcome, 1, server, 1, ser_start, 1, ser_exit, 1, ser_time, 2, client_id, 2, sex, 2, day, 2, month, 2, year, 2, age, 2, social, 2, first, 2, middle, 2, last, 2, phone, 2, email, 2, address_1, 2, address_2, 2, city, 2, state, 2, zipcode, 2, district_id, 3, district_id, 3, city, 3, state_abbrev, 3, division, 4, Date received, 4, Product, 4, Sub-product, 4, Issue, 4, Sub-issue, 4, Consumer complaint narrative, 4, Tags, 4, Consumer consent provided?, 4, Submitted via, 4, Date sent to company, 4, Company response to consumer, 4, Timely response?, 4, Consumer disputed?, 4, Complaint ID, 4, Client_ID, 5, Date, 5, Stars, 5, Reviews, 5, Product, 5, district_id
Question: Lists the last name of all clients who made a PS-type complaint and were served by TOVA.
Evidence: PS-type complaint refers to type = 'PS'; served by refers to server;


SQL: 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'