input stringlengths 667 7.62k | output stringlengths 41 600 | db_id stringlengths 3 31 | query stringlengths 18 577 | question stringlengths 3 224 | schema stringlengths 177 6.14k | primary_keys stringlengths 16 545 | foreign_keys stringlengths 16 1.48k |
|---|---|---|---|---|---|---|---|
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many branches where have more than average number of memberships are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM branch WHERE membership_amount > (SELECT avg(membership_amount) FROM branch)</SQL_QUERY> | shop_membership | SELECT count(*) FROM branch WHERE membership_amount > (SELECT avg(membership_amount) FROM branch) | How many branches where have more than average number of memberships are there? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the number of branches that have more than the average number of memberships?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM branch WHERE membership_amount > (SELECT avg(membership_amount) FROM branch)</SQL_QUERY> | shop_membership | SELECT count(*) FROM branch WHERE membership_amount > (SELECT avg(membership_amount) FROM branch) | What is the number of branches that have more than the average number of memberships? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show name, address road, and city for all branches sorted by open year.</question>
[SQL]:
| <SQL_QUERY>SELECT name , address_road , city FROM branch ORDER BY open_year</SQL_QUERY> | shop_membership | SELECT name , address_road , city FROM branch ORDER BY open_year | Show name, address road, and city for all branches sorted by open year. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names, address roads, and cities of the branches ordered by opening year?</question>
[SQL]:
| <SQL_QUERY>SELECT name , address_road , city FROM branch ORDER BY open_year</SQL_QUERY> | shop_membership | SELECT name , address_road , city FROM branch ORDER BY open_year | What are the names, address roads, and cities of the branches ordered by opening year? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are names for top three branches with most number of membership?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM branch ORDER BY membership_amount DESC LIMIT 3</SQL_QUERY> | shop_membership | SELECT name FROM branch ORDER BY membership_amount DESC LIMIT 3 | What are names for top three branches with most number of membership? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names for the 3 branches that have the most memberships?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM branch ORDER BY membership_amount DESC LIMIT 3</SQL_QUERY> | shop_membership | SELECT name FROM branch ORDER BY membership_amount DESC LIMIT 3 | What are the names for the 3 branches that have the most memberships? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all distinct city where branches with at least 100 memberships are located.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT city FROM branch WHERE membership_amount >= 100</SQL_QUERY> | shop_membership | SELECT DISTINCT city FROM branch WHERE membership_amount >= 100 | Show all distinct city where branches with at least 100 memberships are located. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different cities that have more than 100 memberships?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT city FROM branch WHERE membership_amount >= 100</SQL_QUERY> | shop_membership | SELECT DISTINCT city FROM branch WHERE membership_amount >= 100 | What are the different cities that have more than 100 memberships? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all open years when at least two shops are opened.</question>
[SQL]:
| <SQL_QUERY>SELECT open_year FROM branch GROUP BY open_year HAVING count(*) >= 2</SQL_QUERY> | shop_membership | SELECT open_year FROM branch GROUP BY open_year HAVING count(*) >= 2 | List all open years when at least two shops are opened. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the opening years in which at least two shops opened?</question>
[SQL]:
| <SQL_QUERY>SELECT open_year FROM branch GROUP BY open_year HAVING count(*) >= 2</SQL_QUERY> | shop_membership | SELECT open_year FROM branch GROUP BY open_year HAVING count(*) >= 2 | What are the opening years in which at least two shops opened? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show minimum and maximum amount of memberships for all branches opened in 2011 or located at city London.</question>
[SQL]:
| <SQL_QUERY>SELECT min(membership_amount) , max(membership_amount) FROM branch WHERE open_year = 2011 OR city = 'London'</SQL_QUERY> | shop_membership | SELECT min(membership_amount) , max(membership_amount) FROM branch WHERE open_year = 2011 OR city = 'London' | Show minimum and maximum amount of memberships for all branches opened in 2011 or located at city London. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the minimum and maximum membership amounts for all branches that either opened in 2011 or are located in London?</question>
[SQL]:
| <SQL_QUERY>SELECT min(membership_amount) , max(membership_amount) FROM branch WHERE open_year = 2011 OR city = 'London'</SQL_QUERY> | shop_membership | SELECT min(membership_amount) , max(membership_amount) FROM branch WHERE open_year = 2011 OR city = 'London' | What are the minimum and maximum membership amounts for all branches that either opened in 2011 or are located in London? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the city and the number of branches opened before 2010 for each city.</question>
[SQL]:
| <SQL_QUERY>SELECT city , count(*) FROM branch WHERE open_year < 2010 GROUP BY city</SQL_QUERY> | shop_membership | SELECT city , count(*) FROM branch WHERE open_year < 2010 GROUP BY city | Show the city and the number of branches opened before 2010 for each city. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each city, how many branches opened before 2010?</question>
[SQL]:
| <SQL_QUERY>SELECT city , count(*) FROM branch WHERE open_year < 2010 GROUP BY city</SQL_QUERY> | shop_membership | SELECT city , count(*) FROM branch WHERE open_year < 2010 GROUP BY city | For each city, how many branches opened before 2010? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different levels do members have?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT LEVEL) FROM member</SQL_QUERY> | shop_membership | SELECT count(DISTINCT LEVEL) FROM member | How many different levels do members have? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different membership levels?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT LEVEL) FROM member</SQL_QUERY> | shop_membership | SELECT count(DISTINCT LEVEL) FROM member | What are the different membership levels? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show card number, name, and hometown for all members in a descending order of level.</question>
[SQL]:
| <SQL_QUERY>SELECT card_number , name , hometown FROM member ORDER BY LEVEL DESC</SQL_QUERY> | shop_membership | SELECT card_number , name , hometown FROM member ORDER BY LEVEL DESC | Show card number, name, and hometown for all members in a descending order of level. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the card numbers, names, and hometowns of every member ordered by descending level?</question>
[SQL]:
| <SQL_QUERY>SELECT card_number , name , hometown FROM member ORDER BY LEVEL DESC</SQL_QUERY> | shop_membership | SELECT card_number , name , hometown FROM member ORDER BY LEVEL DESC | What are the card numbers, names, and hometowns of every member ordered by descending level? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the membership level with most number of members.</question>
[SQL]:
| <SQL_QUERY>SELECT LEVEL FROM member GROUP BY LEVEL ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | shop_membership | SELECT LEVEL FROM member GROUP BY LEVEL ORDER BY count(*) DESC LIMIT 1 | Show the membership level with most number of members. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the membership level with the most people?</question>
[SQL]:
| <SQL_QUERY>SELECT LEVEL FROM member GROUP BY LEVEL ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | shop_membership | SELECT LEVEL FROM member GROUP BY LEVEL ORDER BY count(*) DESC LIMIT 1 | What is the membership level with the most people? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all member names and registered branch names sorted by register year.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name , T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id ORDER BY T1.register_year</SQL_QUERY> | shop_membership | SELECT T3.name , T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id ORDER BY T1.register_year | Show all member names and registered branch names sorted by register year. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the members and branches at which they are registered sorted by year of registration?</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name , T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id ORDER BY T1.register_year</SQL_QUERY> | shop_membership | SELECT T3.name , T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id ORDER BY T1.register_year | What are the names of the members and branches at which they are registered sorted by year of registration? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all branch names with the number of members in each branch registered after 2015.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , count(*) FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year > 2015 GROUP BY T2.branch_id</SQL_QUERY> | shop_membership | SELECT T2.name , count(*) FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year > 2015 GROUP BY T2.branch_id | Show all branch names with the number of members in each branch registered after 2015. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each branch id, what are the names of the branches that were registered after 2015?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , count(*) FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year > 2015 GROUP BY T2.branch_id</SQL_QUERY> | shop_membership | SELECT T2.name , count(*) FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year > 2015 GROUP BY T2.branch_id | For each branch id, what are the names of the branches that were registered after 2015? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show member names without any registered branch.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM member WHERE member_id NOT IN (SELECT member_id FROM membership_register_branch)</SQL_QUERY> | shop_membership | SELECT name FROM member WHERE member_id NOT IN (SELECT member_id FROM membership_register_branch) | Show member names without any registered branch. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the members that have never registered at any branch?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM member WHERE member_id NOT IN (SELECT member_id FROM membership_register_branch)</SQL_QUERY> | shop_membership | SELECT name FROM member WHERE member_id NOT IN (SELECT member_id FROM membership_register_branch) | What are the names of the members that have never registered at any branch? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the branch name and city without any registered members.</question>
[SQL]:
| <SQL_QUERY>SELECT name , city FROM branch WHERE branch_id NOT IN (SELECT branch_id FROM membership_register_branch)</SQL_QUERY> | shop_membership | SELECT name , city FROM branch WHERE branch_id NOT IN (SELECT branch_id FROM membership_register_branch) | List the branch name and city without any registered members. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and cities of the branches that do not have any registered members?</question>
[SQL]:
| <SQL_QUERY>SELECT name , city FROM branch WHERE branch_id NOT IN (SELECT branch_id FROM membership_register_branch)</SQL_QUERY> | shop_membership | SELECT name , city FROM branch WHERE branch_id NOT IN (SELECT branch_id FROM membership_register_branch) | What are the names and cities of the branches that do not have any registered members? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name and open year for the branch with most number of memberships registered in 2016?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , T2.open_year FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year = 2016 GROUP BY T2.branch_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | shop_membership | SELECT T2.name , T2.open_year FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year = 2016 GROUP BY T2.branch_id ORDER BY count(*) DESC LIMIT 1 | What is the name and open year for the branch with most number of memberships registered in 2016? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name and opening year for the branch that registered the most members in 2016?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , T2.open_year FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year = 2016 GROUP BY T2.branch_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | shop_membership | SELECT T2.name , T2.open_year FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T1.register_year = 2016 GROUP BY T2.branch_id ORDER BY count(*) DESC LIMIT 1 | What is the name and opening year for the branch that registered the most members in 2016? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the member name and hometown who registered a branch in 2016.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , T2.hometown FROM membership_register_branch AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T1.register_year = 2016</SQL_QUERY> | shop_membership | SELECT T2.name , T2.hometown FROM membership_register_branch AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T1.register_year = 2016 | Show the member name and hometown who registered a branch in 2016. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the member names and hometowns of those who registered at a branch in 2016?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name , T2.hometown FROM membership_register_branch AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T1.register_year = 2016</SQL_QUERY> | shop_membership | SELECT T2.name , T2.hometown FROM membership_register_branch AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T1.register_year = 2016 | What are the member names and hometowns of those who registered at a branch in 2016? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all city with a branch opened in 2001 and a branch with more than 100 membership.</question>
[SQL]:
| <SQL_QUERY>SELECT city FROM branch WHERE open_year = 2001 AND membership_amount > 100</SQL_QUERY> | shop_membership | SELECT city FROM branch WHERE open_year = 2001 AND membership_amount > 100 | Show all city with a branch opened in 2001 and a branch with more than 100 membership. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the cities that have a branch that opened in 2001 and a branch with more than 100 members?</question>
[SQL]:
| <SQL_QUERY>SELECT city FROM branch WHERE open_year = 2001 AND membership_amount > 100</SQL_QUERY> | shop_membership | SELECT city FROM branch WHERE open_year = 2001 AND membership_amount > 100 | What are the cities that have a branch that opened in 2001 and a branch with more than 100 members? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all cities without a branch having more than 100 memberships.</question>
[SQL]:
| <SQL_QUERY>SELECT city FROM branch EXCEPT SELECT city FROM branch WHERE membership_amount > 100</SQL_QUERY> | shop_membership | SELECT city FROM branch EXCEPT SELECT city FROM branch WHERE membership_amount > 100 | Show all cities without a branch having more than 100 memberships. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the cities that do not have any branches with more than 100 members?</question>
[SQL]:
| <SQL_QUERY>SELECT city FROM branch EXCEPT SELECT city FROM branch WHERE membership_amount > 100</SQL_QUERY> | shop_membership | SELECT city FROM branch EXCEPT SELECT city FROM branch WHERE membership_amount > 100 | What are the cities that do not have any branches with more than 100 members? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the sum of total pounds of purchase in year 2018 for all branches in London?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(total_pounds) FROM purchase AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T2.city = 'London' AND T1.year = 2018</SQL_QUERY> | shop_membership | SELECT sum(total_pounds) FROM purchase AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T2.city = 'London' AND T1.year = 2018 | What is the sum of total pounds of purchase in year 2018 for all branches in London? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many total pounds were purchased in the year 2018 at all London branches?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(total_pounds) FROM purchase AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T2.city = 'London' AND T1.year = 2018</SQL_QUERY> | shop_membership | SELECT sum(total_pounds) FROM purchase AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id WHERE T2.city = 'London' AND T1.year = 2018 | How many total pounds were purchased in the year 2018 at all London branches? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total number of purchases for members with level 6?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM purchase AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T2.level = 6</SQL_QUERY> | shop_membership | SELECT count(*) FROM purchase AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T2.level = 6 | What is the total number of purchases for members with level 6? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the total purchases for members rated at level 6?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM purchase AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T2.level = 6</SQL_QUERY> | shop_membership | SELECT count(*) FROM purchase AS T1 JOIN member AS T2 ON T1.member_id = T2.member_id WHERE T2.level = 6 | What are the total purchases for members rated at level 6? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of branches where have some members whose hometown is in Louisville, Kentucky and some in Hiram, Georgia.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Louisville , Kentucky' INTERSECT SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Hiram , Georgia'</SQL_QUERY> | shop_membership | SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Louisville , Kentucky' INTERSECT SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Hiram , Georgia' | Find the name of branches where have some members whose hometown is in Louisville, Kentucky and some in Hiram, Georgia. | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the branches that have some members with a hometown in Louisville, Kentucky and also those from Hiram, Goergia?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Louisville , Kentucky' INTERSECT SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Hiram , Georgia'</SQL_QUERY> | shop_membership | SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Louisville , Kentucky' INTERSECT SELECT T2.name FROM membership_register_branch AS T1 JOIN branch AS T2 ON T1.branch_id = T2.branch_id JOIN member AS T3 ON T1.member_id = T3.member_id WHERE T3.Hometown = 'Hiram , Georgia' | What are the names of the branches that have some members with a hometown in Louisville, Kentucky and also those from Hiram, Goergia? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>list the card number of all members whose hometown address includes word "Kentucky".</question>
[SQL]:
| <SQL_QUERY>SELECT card_number FROM member WHERE Hometown LIKE "%Kentucky%"</SQL_QUERY> | shop_membership | SELECT card_number FROM member WHERE Hometown LIKE "%Kentucky%" | list the card number of all members whose hometown address includes word "Kentucky". | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text);</schema>"
<primary_keys>[Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id</primary_keys>"
<foreign_keys>[Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the card numbers of members from Kentucky?</question>
[SQL]:
| <SQL_QUERY>SELECT card_number FROM member WHERE Hometown LIKE "%Kentucky%"</SQL_QUERY> | shop_membership | SELECT card_number FROM member WHERE Hometown LIKE "%Kentucky%" | What are the card numbers of members from Kentucky? | [Schema (values) (types)]: | shop_membership | member : member_id (text) , card_number (number) , name (text) , hometown (text) , level (text) | branch : branch_id (text) , name (number) , open_year (text) , address_road (text) , city (text) , membership_amount (number) | membership_register_branch : member_id (text) , branch_id (number) , register_year (text) | purchase : member_id (text) , branch_id (number) , year (text) , total_pounds (text); | [Primary Keys]: member : member_id, branch : branch_id, membership_register_branch : member_id, purchase : member_id | [Foreign Keys]: membership_register_branch : branch_id = branch : branch_id | membership_register_branch : member_id = member : member_id | purchase : branch_id = branch : branch_id | purchase : member_id = member : member_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of students in total.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM STUDENT</SQL_QUERY> | voter_2 | SELECT count(*) FROM STUDENT | Find the number of students in total. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students are there in total?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM STUDENT</SQL_QUERY> | voter_2 | SELECT count(*) FROM STUDENT | How many students are there in total? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of voting records in total.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT count(*) FROM VOTING_RECORD | Find the number of voting records in total. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many voting records do we have?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT count(*) FROM VOTING_RECORD | How many voting records do we have? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct number of president votes.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT President_Vote) FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT count(DISTINCT President_Vote) FROM VOTING_RECORD | Find the distinct number of president votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct president votes are recorded?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT President_Vote) FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT count(DISTINCT President_Vote) FROM VOTING_RECORD | How many distinct president votes are recorded? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the maximum age of all the students.</question>
[SQL]:
| <SQL_QUERY>SELECT max(Age) FROM STUDENT</SQL_QUERY> | voter_2 | SELECT max(Age) FROM STUDENT | Find the maximum age of all the students. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the oldest age among the students?</question>
[SQL]:
| <SQL_QUERY>SELECT max(Age) FROM STUDENT</SQL_QUERY> | voter_2 | SELECT max(Age) FROM STUDENT | What is the oldest age among the students? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the last names of students with major 50.</question>
[SQL]:
| <SQL_QUERY>SELECT LName FROM STUDENT WHERE Major = 50</SQL_QUERY> | voter_2 | SELECT LName FROM STUDENT WHERE Major = 50 | Find the last names of students with major 50. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the last names of students studying major 50?</question>
[SQL]:
| <SQL_QUERY>SELECT LName FROM STUDENT WHERE Major = 50</SQL_QUERY> | voter_2 | SELECT LName FROM STUDENT WHERE Major = 50 | What are the last names of students studying major 50? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the first names of students with age above 22.</question>
[SQL]:
| <SQL_QUERY>SELECT Fname FROM STUDENT WHERE Age > 22</SQL_QUERY> | voter_2 | SELECT Fname FROM STUDENT WHERE Age > 22 | Find the first names of students with age above 22. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the first names of all the students aged above 22?</question>
[SQL]:
| <SQL_QUERY>SELECT Fname FROM STUDENT WHERE Age > 22</SQL_QUERY> | voter_2 | SELECT Fname FROM STUDENT WHERE Age > 22 | What are the first names of all the students aged above 22? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the majors of male (sex is M) students?</question>
[SQL]:
| <SQL_QUERY>SELECT Major FROM STUDENT WHERE Sex = "M"</SQL_QUERY> | voter_2 | SELECT Major FROM STUDENT WHERE Sex = "M" | What are the majors of male (sex is M) students? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the major of each male student.</question>
[SQL]:
| <SQL_QUERY>SELECT Major FROM STUDENT WHERE Sex = "M"</SQL_QUERY> | voter_2 | SELECT Major FROM STUDENT WHERE Sex = "M" | List the major of each male student. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average age of female (sex is F) students?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Age) FROM STUDENT WHERE Sex = "F"</SQL_QUERY> | voter_2 | SELECT avg(Age) FROM STUDENT WHERE Sex = "F" | What is the average age of female (sex is F) students? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average age of female students.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Age) FROM STUDENT WHERE Sex = "F"</SQL_QUERY> | voter_2 | SELECT avg(Age) FROM STUDENT WHERE Sex = "F" | Find the average age of female students. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the maximum and minimum age of students with major 600?</question>
[SQL]:
| <SQL_QUERY>SELECT max(Age) , min(Age) FROM STUDENT WHERE Major = 600</SQL_QUERY> | voter_2 | SELECT max(Age) , min(Age) FROM STUDENT WHERE Major = 600 | What are the maximum and minimum age of students with major 600? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Tell me the ages of the oldest and youngest students studying major 600.</question>
[SQL]:
| <SQL_QUERY>SELECT max(Age) , min(Age) FROM STUDENT WHERE Major = 600</SQL_QUERY> | voter_2 | SELECT max(Age) , min(Age) FROM STUDENT WHERE Major = 600 | Tell me the ages of the oldest and youngest students studying major 600. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who are the advisors for students that live in a city with city code "BAL"?</question>
[SQL]:
| <SQL_QUERY>SELECT Advisor FROM STUDENT WHERE city_code = "BAL"</SQL_QUERY> | voter_2 | SELECT Advisor FROM STUDENT WHERE city_code = "BAL" | Who are the advisors for students that live in a city with city code "BAL"? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the advisors of the students whose city of residence has city code "BAL".</question>
[SQL]:
| <SQL_QUERY>SELECT Advisor FROM STUDENT WHERE city_code = "BAL"</SQL_QUERY> | voter_2 | SELECT Advisor FROM STUDENT WHERE city_code = "BAL" | Show the advisors of the students whose city of residence has city code "BAL". | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct secretary votes in the fall election cycle?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Secretary_Vote FROM VOTING_RECORD WHERE ELECTION_CYCLE = "Fall"</SQL_QUERY> | voter_2 | SELECT DISTINCT Secretary_Vote FROM VOTING_RECORD WHERE ELECTION_CYCLE = "Fall" | What are the distinct secretary votes in the fall election cycle? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return all the distinct secretary votes made in the fall election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Secretary_Vote FROM VOTING_RECORD WHERE ELECTION_CYCLE = "Fall"</SQL_QUERY> | voter_2 | SELECT DISTINCT Secretary_Vote FROM VOTING_RECORD WHERE ELECTION_CYCLE = "Fall" | Return all the distinct secretary votes made in the fall election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct president votes on 08/30/2015?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT PRESIDENT_Vote FROM VOTING_RECORD WHERE Registration_Date = "08/30/2015"</SQL_QUERY> | voter_2 | SELECT DISTINCT PRESIDENT_Vote FROM VOTING_RECORD WHERE Registration_Date = "08/30/2015" | What are the distinct president votes on 08/30/2015? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all the distinct president votes made on 08/30/2015.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT PRESIDENT_Vote FROM VOTING_RECORD WHERE Registration_Date = "08/30/2015"</SQL_QUERY> | voter_2 | SELECT DISTINCT PRESIDENT_Vote FROM VOTING_RECORD WHERE Registration_Date = "08/30/2015" | Show all the distinct president votes made on 08/30/2015. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Report the distinct registration date and the election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Registration_Date , Election_Cycle FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT DISTINCT Registration_Date , Election_Cycle FROM VOTING_RECORD | Report the distinct registration date and the election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct registration dates and the election cycles?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Registration_Date , Election_Cycle FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT DISTINCT Registration_Date , Election_Cycle FROM VOTING_RECORD | What are the distinct registration dates and the election cycles? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Report the distinct president vote and the vice president vote.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT President_Vote , VICE_President_Vote FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT DISTINCT President_Vote , VICE_President_Vote FROM VOTING_RECORD | Report the distinct president vote and the vice president vote. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the distinct president votes and the vice president votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT President_Vote , VICE_President_Vote FROM VOTING_RECORD</SQL_QUERY> | voter_2 | SELECT DISTINCT President_Vote , VICE_President_Vote FROM VOTING_RECORD | List all the distinct president votes and the vice president votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct last names of the students who have class president votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_President_VOTE</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_President_VOTE | Find the distinct last names of the students who have class president votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct last names of the students who have class president votes?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_President_VOTE</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_President_VOTE | What are the distinct last names of the students who have class president votes? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct first names of the students who have class senator votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_Senator_VOTE</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_Senator_VOTE | Find the distinct first names of the students who have class senator votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct first names of the students who have class president votes?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_Senator_VOTE</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.CLASS_Senator_VOTE | What are the distinct first names of the students who have class president votes? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct ages of students who have secretary votes in the fall election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Age FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Secretary_Vote WHERE T2.Election_Cycle = "Fall"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Age FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Secretary_Vote WHERE T2.Election_Cycle = "Fall" | Find the distinct ages of students who have secretary votes in the fall election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct ages of students who have secretary votes in the fall election cycle?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Age FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Secretary_Vote WHERE T2.Election_Cycle = "Fall"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Age FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Secretary_Vote WHERE T2.Election_Cycle = "Fall" | What are the distinct ages of students who have secretary votes in the fall election cycle? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct Advisor of students who have treasurer votes in the spring election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Advisor FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote WHERE T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Advisor FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote WHERE T2.Election_Cycle = "Spring" | Find the distinct Advisor of students who have treasurer votes in the spring election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who served as an advisor for students who have treasurer votes in the spring election cycle?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Advisor FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote WHERE T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Advisor FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote WHERE T2.Election_Cycle = "Spring" | Who served as an advisor for students who have treasurer votes in the spring election cycle? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct majors of students who have treasurer votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Major FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Major FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote | Find the distinct majors of students who have treasurer votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct majors that students with treasurer votes are studying?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Major FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Major FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.Treasurer_Vote | What are the distinct majors that students with treasurer votes are studying? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the first and last names of all the female (sex is F) students who have president votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.President_VOTE WHERE T1.sex = "F"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.President_VOTE WHERE T1.sex = "F" | Find the first and last names of all the female (sex is F) students who have president votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the first and last names of all the female students who have president votes?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.President_VOTE WHERE T1.sex = "F"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.President_VOTE WHERE T1.sex = "F" | What are the first and last names of all the female students who have president votes? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the first and last name of all the students of age 18 who have vice president votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_President_VOTE WHERE T1.age = 18</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_President_VOTE WHERE T1.age = 18 | Find the first and last name of all the students of age 18 who have vice president votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the first names and last names of the students who are 18 years old and have vice president votes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_President_VOTE WHERE T1.age = 18</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname , T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_President_VOTE WHERE T1.age = 18 | What are the first names and last names of the students who are 18 years old and have vice president votes. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many male (sex is M) students have class senator votes in the fall election cycle?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.Sex = "M" AND T2.Election_Cycle = "Fall"</SQL_QUERY> | voter_2 | SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.Sex = "M" AND T2.Election_Cycle = "Fall" | How many male (sex is M) students have class senator votes in the fall election cycle? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of male students who had class senator votes in the fall election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.Sex = "M" AND T2.Election_Cycle = "Fall"</SQL_QUERY> | voter_2 | SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.Sex = "M" AND T2.Election_Cycle = "Fall" | Count the number of male students who had class senator votes in the fall election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of students whose city code is NYC and who have class senator votes in the spring election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring" | Find the number of students whose city code is NYC and who have class senator votes in the spring election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which students live in the city with code "NYC" and have class senator votes in the spring election cycle? Count the numbers.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT count(*) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = Class_Senator_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring" | Which students live in the city with code "NYC" and have class senator votes in the spring election cycle? Count the numbers. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average age of students who live in the city with code "NYC" and have secretary votes in the spring election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring" | Find the average age of students who live in the city with code "NYC" and have secretary votes in the spring election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average age of students who have city code "NYC" and have secretary votes for the spring election cycle?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.city_code = "NYC" AND T2.Election_Cycle = "Spring" | What is the average age of students who have city code "NYC" and have secretary votes for the spring election cycle? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average age of female (sex is F) students who have secretary votes in the spring election cycle.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.Sex = "F" AND T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.Sex = "F" AND T2.Election_Cycle = "Spring" | Find the average age of female (sex is F) students who have secretary votes in the spring election cycle. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average age of the female students with secretary votes in the spring election cycle?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.Sex = "F" AND T2.Election_Cycle = "Spring"</SQL_QUERY> | voter_2 | SELECT avg(T1.Age) FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = SECRETARY_Vote WHERE T1.Sex = "F" AND T2.Election_Cycle = "Spring" | What is the average age of the female students with secretary votes in the spring election cycle? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct first names of all the students who have vice president votes and whose city code is not PIT.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_PRESIDENT_Vote EXCEPT SELECT DISTINCT Fname FROM STUDENT WHERE city_code = "PIT"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_PRESIDENT_Vote EXCEPT SELECT DISTINCT Fname FROM STUDENT WHERE city_code = "PIT" | Find the distinct first names of all the students who have vice president votes and whose city code is not PIT. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct first names of the students who have vice president votes and reside in a city whose city code is not PIT?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_PRESIDENT_Vote EXCEPT SELECT DISTINCT Fname FROM STUDENT WHERE city_code = "PIT"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.Fname FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = T2.VICE_PRESIDENT_Vote EXCEPT SELECT DISTINCT Fname FROM STUDENT WHERE city_code = "PIT" | What are the distinct first names of the students who have vice president votes and reside in a city whose city code is not PIT? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct last names of all the students who have president votes and whose advisor is not 2192.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote EXCEPT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "2192"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote EXCEPT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "2192" | Find the distinct last names of all the students who have president votes and whose advisor is not 2192. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct last names of the students who have president votes but do not have 2192 as the advisor?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote EXCEPT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "2192"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote EXCEPT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "2192" | What are the distinct last names of the students who have president votes but do not have 2192 as the advisor? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct last names of all the students who have president votes and whose advisor is 8741.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote INTERSECT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "8741"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote INTERSECT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "8741" | Find the distinct last names of all the students who have president votes and whose advisor is 8741. | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text);</schema>"
<primary_keys>[Primary Keys]: student : stuid</primary_keys>"
<foreign_keys>[Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct last names of the students who have president votes and have 8741 as the advisor?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote INTERSECT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "8741"</SQL_QUERY> | voter_2 | SELECT DISTINCT T1.LName FROM STUDENT AS T1 JOIN VOTING_RECORD AS T2 ON T1.StuID = PRESIDENT_Vote INTERSECT SELECT DISTINCT LName FROM STUDENT WHERE Advisor = "8741" | What are the distinct last names of the students who have president votes and have 8741 as the advisor? | [Schema (values) (types)]: | voter_2 | Student : stuid (text) , lname (number) , fname (text) , age (text) , sex (number) , major (text) , advisor (number) , city_code (number) | Voting_record : stuid (text) , registration_date (number) , election_cycle (text) , president_vote (text) , vice_president_vote (number) , secretary_vote (text) , treasurer_vote (number) , class_president_vote (number) , class_senator_vote (text); | [Primary Keys]: student : stuid | [Foreign Keys]: voting_record : class_senator_vote = student : stuid | voting_record : class_president_vote = student : stuid | voting_record : treasurer_vote = student : stuid | voting_record : secretary_vote = student : stuid | voting_record : vice_president_vote = student : stuid | voting_record : president_vote = student : stuid | voting_record : stuid = student : stuid |
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