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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of items whose rating is higher than the average review rating of all items.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating > (SELECT avg(rating) FROM review)</SQL_QUERY> | epinions_1 | SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating > (SELECT avg(rating) FROM review) | Find the titles of items whose rating is higher than the average review rating of all items. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of items that received any rating below 5.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating < 5</SQL_QUERY> | epinions_1 | SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating < 5 | Find the titles of items that received any rating below 5. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the titles of items that received both a rating higher than 8 and a rating below 5.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating > 8 INTERSECT SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating < 5</SQL_QUERY> | epinions_1 | SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating > 8 INTERSECT SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rating < 5 | Find the titles of items that received both a rating higher than 8 and a rating below 5. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of items whose rank is higher than 3 and whose average rating is above 5.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rank > 3 INTERSECT SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id HAVING avg(T2.rating) > 5</SQL_QUERY> | epinions_1 | SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id WHERE T2.rank > 3 INTERSECT SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id HAVING avg(T2.rating) > 5 | Find the names of items whose rank is higher than 3 and whose average rating is above 5. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the item with the lowest average rating.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rating) LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.title FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rating) LIMIT 1 | Find the name of the item with the lowest average rating. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the titles of all items in alphabetic order .</question>
[SQL]:
| <SQL_QUERY>SELECT title FROM item ORDER BY title</SQL_QUERY> | epinions_1 | SELECT title FROM item ORDER BY title | List the titles of all items in alphabetic order . | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the user who gives the most reviews.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id GROUP BY T2.u_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.name FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id GROUP BY T2.u_id ORDER BY count(*) DESC LIMIT 1 | Find the name of the user who gives the most reviews. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and id of the item with the highest average rating.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title , T1.i_id FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rating) DESC LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.title , T1.i_id FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rating) DESC LIMIT 1 | Find the name and id of the item with the highest average rating. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and id of the good with the highest average rank.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.title , T1.i_id FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rank) DESC LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.title , T1.i_id FROM item AS T1 JOIN review AS T2 ON T1.i_id = T2.i_id GROUP BY T2.i_id ORDER BY avg(T2.rank) DESC LIMIT 1 | Find the name and id of the good with the highest average rank. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each user, return the name and the average rating of reviews given by them.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , avg(T2.rating) FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id GROUP BY T2.u_id</SQL_QUERY> | epinions_1 | SELECT T1.name , avg(T2.rating) FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id GROUP BY T2.u_id | For each user, return the name and the average rating of reviews given by them. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each user, find their name and the number of reviews written by them.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , count(*) FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id GROUP BY T2.u_id</SQL_QUERY> | epinions_1 | SELECT T1.name , count(*) FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id GROUP BY T2.u_id | For each user, find their name and the number of reviews written by them. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the user who gave the highest rating.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id ORDER BY T2.rating DESC LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.name FROM useracct AS T1 JOIN review AS T2 ON T1.u_id = T2.u_id ORDER BY T2.rating DESC LIMIT 1 | Find the name of the user who gave the highest rating. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the source user with the highest average trust score.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.source_u_id GROUP BY T2.source_u_id ORDER BY avg(trust) DESC LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.source_u_id GROUP BY T2.source_u_id ORDER BY avg(trust) DESC LIMIT 1 | Find the name of the source user with the highest average trust score. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find each target user's name and average trust score.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , avg(trust) FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.target_u_id GROUP BY T2.target_u_id</SQL_QUERY> | epinions_1 | SELECT T1.name , avg(trust) FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.target_u_id GROUP BY T2.target_u_id | Find each target user's name and average trust score. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the target user with the lowest trust score.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.target_u_id ORDER BY trust LIMIT 1</SQL_QUERY> | epinions_1 | SELECT T1.name FROM useracct AS T1 JOIN trust AS T2 ON T1.u_id = T2.target_u_id ORDER BY trust LIMIT 1 | Find the name of the target user with the lowest trust score. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of the items that did not receive any review.</question>
[SQL]:
| <SQL_QUERY>SELECT title FROM item WHERE i_id NOT IN (SELECT i_id FROM review)</SQL_QUERY> | epinions_1 | SELECT title FROM item WHERE i_id NOT IN (SELECT i_id FROM review) | Find the names of the items that did not receive any review. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of users who did not leave any review.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM useracct WHERE u_id NOT IN (SELECT u_id FROM review)</SQL_QUERY> | epinions_1 | SELECT name FROM useracct WHERE u_id NOT IN (SELECT u_id FROM review) | Find the names of users who did not leave any review. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of users who did not write any review.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM useracct WHERE u_id NOT IN (SELECT u_id FROM review)</SQL_QUERY> | epinions_1 | SELECT count(*) FROM useracct WHERE u_id NOT IN (SELECT u_id FROM review) | Find the number of users who did not write any review. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text);</schema>"
<primary_keys>[Primary Keys]: item : i_id, review : a_id, useracct : u_id</primary_keys>"
<foreign_keys>[Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of items without any review.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM item WHERE i_id NOT IN (SELECT i_id FROM review)</SQL_QUERY> | epinions_1 | SELECT count(*) FROM item WHERE i_id NOT IN (SELECT i_id FROM review) | Find the number of items without any review. | [Schema (values) (types)]: | epinions_1 | item : i_id (text) , title (number) | review : a_id (text) , u_id (number) , i_id (text) , rating (number) , rank (number) | useracct : u_id (text) , name (number) | trust : source_u_id (text) , target_u_id (number) , trust (text); | [Primary Keys]: item : i_id, review : a_id, useracct : u_id | [Foreign Keys]: review : i_id = item : i_id | review : u_id = useracct : u_id | trust : target_u_id = useracct : u_id | trust : source_u_id = useracct : u_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many players are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM player</SQL_QUERY> | riding_club | SELECT count(*) FROM player | How many players are there? | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of players in ascending order of votes.</question>
[SQL]:
| <SQL_QUERY>SELECT Player_name FROM player ORDER BY Votes ASC</SQL_QUERY> | riding_club | SELECT Player_name FROM player ORDER BY Votes ASC | List the names of players in ascending order of votes. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the gender and occupation of players?</question>
[SQL]:
| <SQL_QUERY>SELECT Gender , Occupation FROM player</SQL_QUERY> | riding_club | SELECT Gender , Occupation FROM player | What are the gender and occupation of players? | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name and residence for players whose occupation is not "Researcher".</question>
[SQL]:
| <SQL_QUERY>SELECT Player_name , residence FROM player WHERE Occupation != "Researcher"</SQL_QUERY> | riding_club | SELECT Player_name , residence FROM player WHERE Occupation != "Researcher" | List the name and residence for players whose occupation is not "Researcher". | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of sponsors of players whose residence is either "Brandon" or "Birtle".</question>
[SQL]:
| <SQL_QUERY>SELECT Sponsor_name FROM player WHERE Residence = "Brandon" OR Residence = "Birtle"</SQL_QUERY> | riding_club | SELECT Sponsor_name FROM player WHERE Residence = "Brandon" OR Residence = "Birtle" | Show the names of sponsors of players whose residence is either "Brandon" or "Birtle". | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the player with the largest number of votes?</question>
[SQL]:
| <SQL_QUERY>SELECT Player_name FROM player ORDER BY Votes DESC LIMIT 1</SQL_QUERY> | riding_club | SELECT Player_name FROM player ORDER BY Votes DESC LIMIT 1 | What is the name of the player with the largest number of votes? | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show different occupations along with the number of players in each occupation.</question>
[SQL]:
| <SQL_QUERY>SELECT Occupation , COUNT(*) FROM player GROUP BY Occupation</SQL_QUERY> | riding_club | SELECT Occupation , COUNT(*) FROM player GROUP BY Occupation | Show different occupations along with the number of players in each occupation. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Please show the most common occupation of players.</question>
[SQL]:
| <SQL_QUERY>SELECT Occupation FROM player GROUP BY Occupation ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | riding_club | SELECT Occupation FROM player GROUP BY Occupation ORDER BY COUNT(*) DESC LIMIT 1 | Please show the most common occupation of players. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the residences that have at least two players.</question>
[SQL]:
| <SQL_QUERY>SELECT Residence FROM player GROUP BY Residence HAVING COUNT(*) >= 2</SQL_QUERY> | riding_club | SELECT Residence FROM player GROUP BY Residence HAVING COUNT(*) >= 2 | Show the residences that have at least two players. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of players and names of their coaches.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Player_name , T2.coach_name FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID</SQL_QUERY> | riding_club | SELECT T3.Player_name , T2.coach_name FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID | Show the names of players and names of their coaches. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of players coached by the rank 1 coach.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Player_name FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID WHERE T2.Rank = 1</SQL_QUERY> | riding_club | SELECT T3.Player_name FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID WHERE T2.Rank = 1 | Show the names of players coached by the rank 1 coach. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names and genders of players with a coach starting after 2011.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Player_name , T3.gender FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID WHERE T1.Starting_year > 2011</SQL_QUERY> | riding_club | SELECT T3.Player_name , T3.gender FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID WHERE T1.Starting_year > 2011 | Show the names and genders of players with a coach starting after 2011. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of players and names of their coaches in descending order of the votes of players.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Player_name , T2.coach_name FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID ORDER BY T3.Votes DESC</SQL_QUERY> | riding_club | SELECT T3.Player_name , T2.coach_name FROM player_coach AS T1 JOIN coach AS T2 ON T1.Coach_ID = T2.Coach_ID JOIN player AS T3 ON T1.Player_ID = T3.Player_ID ORDER BY T3.Votes DESC | Show the names of players and names of their coaches in descending order of the votes of players. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of players that do not have coaches.</question>
[SQL]:
| <SQL_QUERY>SELECT Player_name FROM player WHERE Player_ID NOT IN (SELECT Player_ID FROM player_coach)</SQL_QUERY> | riding_club | SELECT Player_name FROM player WHERE Player_ID NOT IN (SELECT Player_ID FROM player_coach) | List the names of players that do not have coaches. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the residences that have both a player of gender "M" and a player of gender "F".</question>
[SQL]:
| <SQL_QUERY>SELECT Residence FROM player WHERE gender = "M" INTERSECT SELECT Residence FROM player WHERE gender = "F"</SQL_QUERY> | riding_club | SELECT Residence FROM player WHERE gender = "M" INTERSECT SELECT Residence FROM player WHERE gender = "F" | Show the residences that have both a player of gender "M" and a player of gender "F". | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many coaches does each club has? List the club id, name and the number of coaches.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.club_id , T1.club_name, count(*) FROM club AS T1 JOIN coach AS T2 ON T1.club_id = T2.club_id GROUP BY T1.club_id</SQL_QUERY> | riding_club | SELECT T1.club_id , T1.club_name, count(*) FROM club AS T1 JOIN coach AS T2 ON T1.club_id = T2.club_id GROUP BY T1.club_id | How many coaches does each club has? List the club id, name and the number of coaches. | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text);</schema>"
<primary_keys>[Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank</primary_keys>"
<foreign_keys>[Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many gold medals has the club with the most coaches won?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.club_id , T1.gold FROM match_result AS T1 JOIN coach AS T2 ON T1.club_id = T2.club_id GROUP BY T1.club_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | riding_club | SELECT T1.club_id , T1.gold FROM match_result AS T1 JOIN coach AS T2 ON T1.club_id = T2.club_id GROUP BY T1.club_id ORDER BY count(*) DESC LIMIT 1 | How many gold medals has the club with the most coaches won? | [Schema (values) (types)]: | riding_club | player : player_id (text) , sponsor_name (number) , player_name (text) , gender (text) , residence (text) , occupation (text) , votes (text) , rank (number) | club : club_id (text) , club_name (number) , region (text) , start_year (text) | coach : coach_id (text) , coach_name (number) , gender (text) , club_id (text) , rank (text) | player_coach : player_id (text) , coach_id (number) , starting_year (text) | match_result : rank (text) , club_id (number) , gold (text) , big_silver (text) , small_silver (text) , bronze (text) , points (text); | [Primary Keys]: player : player_id, club : club_id, coach : coach_id, player_coach : player_id, match_result : rank | [Foreign Keys]: coach : club_id = club : club_id | player_coach : coach_id = coach : coach_id | player_coach : player_id = player : player_id | match_result : club_id = club : club_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many gymnasts are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM gymnast</SQL_QUERY> | gymnast | SELECT count(*) FROM gymnast | How many gymnasts are there? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of gymnasts.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM gymnast</SQL_QUERY> | gymnast | SELECT count(*) FROM gymnast | Count the number of gymnasts. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the total points of gymnasts in descending order.</question>
[SQL]:
| <SQL_QUERY>SELECT Total_Points FROM gymnast ORDER BY Total_Points DESC</SQL_QUERY> | gymnast | SELECT Total_Points FROM gymnast ORDER BY Total_Points DESC | List the total points of gymnasts in descending order. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the total points for all gymnasts, ordered by total points descending?</question>
[SQL]:
| <SQL_QUERY>SELECT Total_Points FROM gymnast ORDER BY Total_Points DESC</SQL_QUERY> | gymnast | SELECT Total_Points FROM gymnast ORDER BY Total_Points DESC | What are the total points for all gymnasts, ordered by total points descending? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the total points of gymnasts in descending order of floor exercise points.</question>
[SQL]:
| <SQL_QUERY>SELECT Total_Points FROM gymnast ORDER BY Floor_Exercise_Points DESC</SQL_QUERY> | gymnast | SELECT Total_Points FROM gymnast ORDER BY Floor_Exercise_Points DESC | List the total points of gymnasts in descending order of floor exercise points. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the total points of gymnasts, ordered by their floor exercise points descending?</question>
[SQL]:
| <SQL_QUERY>SELECT Total_Points FROM gymnast ORDER BY Floor_Exercise_Points DESC</SQL_QUERY> | gymnast | SELECT Total_Points FROM gymnast ORDER BY Floor_Exercise_Points DESC | What are the total points of gymnasts, ordered by their floor exercise points descending? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average horizontal bar points for all gymnasts?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Horizontal_Bar_Points) FROM gymnast</SQL_QUERY> | gymnast | SELECT avg(Horizontal_Bar_Points) FROM gymnast | What is the average horizontal bar points for all gymnasts? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the average horizontal bar points across all gymnasts.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Horizontal_Bar_Points) FROM gymnast</SQL_QUERY> | gymnast | SELECT avg(Horizontal_Bar_Points) FROM gymnast | Return the average horizontal bar points across all gymnasts. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of people in ascending alphabetical order?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM People ORDER BY Name ASC</SQL_QUERY> | gymnast | SELECT Name FROM People ORDER BY Name ASC | What are the names of people in ascending alphabetical order? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of people, ordered alphabetically.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM People ORDER BY Name ASC</SQL_QUERY> | gymnast | SELECT Name FROM People ORDER BY Name ASC | Return the names of people, ordered alphabetically. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of gymnasts?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID</SQL_QUERY> | gymnast | SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID | What are the names of gymnasts? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of the gymnasts.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID</SQL_QUERY> | gymnast | SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID | Return the names of the gymnasts. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of gymnasts whose hometown is not "Santo Domingo"?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T2.Hometown != "Santo Domingo"</SQL_QUERY> | gymnast | SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T2.Hometown != "Santo Domingo" | What are the names of gymnasts whose hometown is not "Santo Domingo"? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of gymnasts who did not grow up in Santo Domingo.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T2.Hometown != "Santo Domingo"</SQL_QUERY> | gymnast | SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T2.Hometown != "Santo Domingo" | Return the names of gymnasts who did not grow up in Santo Domingo. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the age of the tallest person?</question>
[SQL]:
| <SQL_QUERY>SELECT Age FROM people ORDER BY Height DESC LIMIT 1</SQL_QUERY> | gymnast | SELECT Age FROM people ORDER BY Height DESC LIMIT 1 | What is the age of the tallest person? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the age of the person with the greatest height.</question>
[SQL]:
| <SQL_QUERY>SELECT Age FROM people ORDER BY Height DESC LIMIT 1</SQL_QUERY> | gymnast | SELECT Age FROM people ORDER BY Height DESC LIMIT 1 | Return the age of the person with the greatest height. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of the top 5 oldest people.</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM People ORDER BY Age DESC LIMIT 5</SQL_QUERY> | gymnast | SELECT Name FROM People ORDER BY Age DESC LIMIT 5 | List the names of the top 5 oldest people. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the five oldest people?</question>
[SQL]:
| <SQL_QUERY>SELECT Name FROM People ORDER BY Age DESC LIMIT 5</SQL_QUERY> | gymnast | SELECT Name FROM People ORDER BY Age DESC LIMIT 5 | What are the names of the five oldest people? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total point count of the youngest gymnast?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Total_Points FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Age ASC LIMIT 1</SQL_QUERY> | gymnast | SELECT T1.Total_Points FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Age ASC LIMIT 1 | What is the total point count of the youngest gymnast? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the total points of the gymnast with the lowest age.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Total_Points FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Age ASC LIMIT 1</SQL_QUERY> | gymnast | SELECT T1.Total_Points FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Age ASC LIMIT 1 | Return the total points of the gymnast with the lowest age. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average age of all gymnasts?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T2.Age) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID</SQL_QUERY> | gymnast | SELECT avg(T2.Age) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID | What is the average age of all gymnasts? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the average age across all gymnasts.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(T2.Age) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID</SQL_QUERY> | gymnast | SELECT avg(T2.Age) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID | Return the average age across all gymnasts. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct hometowns of gymnasts with total points more than 57.5?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T1.Total_Points > 57.5</SQL_QUERY> | gymnast | SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T1.Total_Points > 57.5 | What are the distinct hometowns of gymnasts with total points more than 57.5? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the different hometowns of gymnasts that have a total point score of above 57.5.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T1.Total_Points > 57.5</SQL_QUERY> | gymnast | SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID WHERE T1.Total_Points > 57.5 | Give the different hometowns of gymnasts that have a total point score of above 57.5. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the hometowns of gymnasts and the corresponding number of gymnasts?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Hometown , COUNT(*) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown</SQL_QUERY> | gymnast | SELECT T2.Hometown , COUNT(*) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown | What are the hometowns of gymnasts and the corresponding number of gymnasts? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many gymnasts are from each hometown?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Hometown , COUNT(*) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown</SQL_QUERY> | gymnast | SELECT T2.Hometown , COUNT(*) FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown | How many gymnasts are from each hometown? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the most common hometown of gymnasts?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | gymnast | SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown ORDER BY COUNT(*) DESC LIMIT 1 | What is the most common hometown of gymnasts? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the hometown that is most common among gymnasts.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | gymnast | SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown ORDER BY COUNT(*) DESC LIMIT 1 | Return the hometown that is most common among gymnasts. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the hometowns that are shared by at least two gymnasts?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown HAVING COUNT(*) >= 2</SQL_QUERY> | gymnast | SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown HAVING COUNT(*) >= 2 | What are the hometowns that are shared by at least two gymnasts? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give the hometowns from which two or more gymnasts are from.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown HAVING COUNT(*) >= 2</SQL_QUERY> | gymnast | SELECT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID GROUP BY T2.Hometown HAVING COUNT(*) >= 2 | Give the hometowns from which two or more gymnasts are from. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the names of gymnasts in ascending order by their heights.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Height ASC</SQL_QUERY> | gymnast | SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Height ASC | List the names of gymnasts in ascending order by their heights. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of gymnasts, ordered by their heights ascending?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Height ASC</SQL_QUERY> | gymnast | SELECT T2.Name FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T2.Height ASC | What are the names of gymnasts, ordered by their heights ascending? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the distinct hometowns that are not associated with any gymnast.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Hometown FROM people EXCEPT SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID</SQL_QUERY> | gymnast | SELECT DISTINCT Hometown FROM people EXCEPT SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID | List the distinct hometowns that are not associated with any gymnast. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>From which hometowns did no gymnasts come from?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT Hometown FROM people EXCEPT SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID</SQL_QUERY> | gymnast | SELECT DISTINCT Hometown FROM people EXCEPT SELECT DISTINCT T2.Hometown FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID | From which hometowns did no gymnasts come from? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the hometowns shared by people older than 23 and younger than 20.</question>
[SQL]:
| <SQL_QUERY>SELECT Hometown FROM people WHERE Age > 23 INTERSECT SELECT Hometown FROM people WHERE Age < 20</SQL_QUERY> | gymnast | SELECT Hometown FROM people WHERE Age > 23 INTERSECT SELECT Hometown FROM people WHERE Age < 20 | Show the hometowns shared by people older than 23 and younger than 20. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>From which hometowns did both people older than 23 and younger than 20 come from?</question>
[SQL]:
| <SQL_QUERY>SELECT Hometown FROM people WHERE Age > 23 INTERSECT SELECT Hometown FROM people WHERE Age < 20</SQL_QUERY> | gymnast | SELECT Hometown FROM people WHERE Age > 23 INTERSECT SELECT Hometown FROM people WHERE Age < 20 | From which hometowns did both people older than 23 and younger than 20 come from? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct hometowns did these people have?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Hometown) FROM people</SQL_QUERY> | gymnast | SELECT count(DISTINCT Hometown) FROM people | How many distinct hometowns did these people have? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of different hometowns of these people.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Hometown) FROM people</SQL_QUERY> | gymnast | SELECT count(DISTINCT Hometown) FROM people | Count the number of different hometowns of these people. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the ages of gymnasts in descending order of total points.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Age FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T1.Total_Points DESC</SQL_QUERY> | gymnast | SELECT T2.Age FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T1.Total_Points DESC | Show the ages of gymnasts in descending order of total points. | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number);</schema>"
<primary_keys>[Primary Keys]: gymnast : gymnast_id, people : people_id</primary_keys>"
<foreign_keys>[Foreign Keys]: gymnast : gymnast_id = people : people_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ages of the gymnasts, ordered descending by their total points?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Age FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T1.Total_Points DESC</SQL_QUERY> | gymnast | SELECT T2.Age FROM gymnast AS T1 JOIN people AS T2 ON T1.Gymnast_ID = T2.People_ID ORDER BY T1.Total_Points DESC | What are the ages of the gymnasts, ordered descending by their total points? | [Schema (values) (types)]: | gymnast | gymnast : gymnast_id (text) , floor_exercise_points (number) , pommel_horse_points (number) , rings_points (number) , vault_points (number) , parallel_bars_points (number) , horizontal_bar_points (number) , total_points (number) | people : people_id (text) , name (number) , age (number) , height (number) , hometown (number); | [Primary Keys]: gymnast : gymnast_id, people : people_id | [Foreign Keys]: gymnast : gymnast_id = people : people_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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total savings balance of all accounts except the account with name ‘Brown’.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(T2.balance) FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T1.name != 'Brown'</SQL_QUERY> | small_bank_1 | SELECT sum(T2.balance) FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T1.name != 'Brown' | Find the total savings balance of all accounts except the account with name ‘Brown’. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total balance of savings accounts not belonging to someone with the name Brown?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(T2.balance) FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T1.name != 'Brown'</SQL_QUERY> | small_bank_1 | SELECT sum(T2.balance) FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T1.name != 'Brown' | What is the total balance of savings accounts not belonging to someone with the name Brown? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many accounts are there in total?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM accounts</SQL_QUERY> | small_bank_1 | SELECT count(*) FROM accounts | How many accounts are there in total? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of accounts.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM accounts</SQL_QUERY> | small_bank_1 | SELECT count(*) FROM accounts | Count the number of accounts. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total checking balance in all accounts?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(balance) FROM checking</SQL_QUERY> | small_bank_1 | SELECT sum(balance) FROM checking | What is the total checking balance in all accounts? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total balance across checking accounts.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(balance) FROM checking</SQL_QUERY> | small_bank_1 | SELECT sum(balance) FROM checking | Find the total balance across checking accounts. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the average checking balance.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(balance) FROM checking</SQL_QUERY> | small_bank_1 | SELECT avg(balance) FROM checking | Find the average checking balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average balance in checking accounts?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(balance) FROM checking</SQL_QUERY> | small_bank_1 | SELECT avg(balance) FROM checking | What is the average balance in checking accounts? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many accounts have a savings balance above the average savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM savings WHERE balance > (SELECT avg(balance) FROM savings)</SQL_QUERY> | small_bank_1 | SELECT count(*) FROM savings WHERE balance > (SELECT avg(balance) FROM savings) | How many accounts have a savings balance above the average savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of accounts with a savings balance that is higher than the average savings balance.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM savings WHERE balance > (SELECT avg(balance) FROM savings)</SQL_QUERY> | small_bank_1 | SELECT count(*) FROM savings WHERE balance > (SELECT avg(balance) FROM savings) | Find the number of accounts with a savings balance that is higher than the average savings balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and id of accounts whose checking balance is below the maximum checking balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.custid , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT max(balance) FROM checking)</SQL_QUERY> | small_bank_1 | SELECT T1.custid , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT max(balance) FROM checking) | Find the name and id of accounts whose checking balance is below the maximum checking balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the customer id and name corresponding to accounts with a checking balance less than the largest checking balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.custid , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT max(balance) FROM checking)</SQL_QUERY> | small_bank_1 | SELECT T1.custid , T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT max(balance) FROM checking) | What are the customer id and name corresponding to accounts with a checking balance less than the largest checking balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the checking balance of the account whose owner’s name contains the substring ‘ee’?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name LIKE '%ee%'</SQL_QUERY> | small_bank_1 | SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name LIKE '%ee%' | What is the checking balance of the account whose owner’s name contains the substring ‘ee’? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the balance of the checking account belonging to an owner whose name contains 'ee'.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name LIKE '%ee%'</SQL_QUERY> | small_bank_1 | SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name LIKE '%ee%' | Find the balance of the checking account belonging to an owner whose name contains 'ee'. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the checking balance and saving balance in the Brown’s account.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T1.name = 'Brown'</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T1.name = 'Brown' | Find the checking balance and saving balance in the Brown’s account. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the checking and savings balances in accounts belonging to Brown?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance , T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T1.name = 'Brown'</SQL_QUERY> | small_bank_1 | SELECT T2.balance , T3.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid WHERE T1.name = 'Brown' | What are the checking and savings balances in accounts belonging to Brown? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of accounts whose checking balance is above the average checking balance, but savings balance is below the average savings balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM checking) INTERSECT SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM savings)</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM checking) INTERSECT SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM savings) | Find the names of accounts whose checking balance is above the average checking balance, but savings balance is below the average savings balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of accounts with checking balances greater than the average checking balance and savings balances below the average savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM checking) INTERSECT SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM savings)</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM checking) INTERSECT SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance < (SELECT avg(balance) FROM savings) | What are the names of accounts with checking balances greater than the average checking balance and savings balances below the average savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the checking balance of the accounts whose savings balance is higher than the average savings balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name IN (SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM savings))</SQL_QUERY> | small_bank_1 | SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name IN (SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM savings)) | Find the checking balance of the accounts whose savings balance is higher than the average savings balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the balances of checking accounts belonging to people with savings balances greater than the average savings balance?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name IN (SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM savings))</SQL_QUERY> | small_bank_1 | SELECT T2.balance FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid WHERE T1.name IN (SELECT T1.name FROM accounts AS T1 JOIN savings AS T2 ON T1.custid = T2.custid WHERE T2.balance > (SELECT avg(balance) FROM savings)) | What are the balances of checking accounts belonging to people with savings balances greater than the average savings balance? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all customers’ names in the alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM accounts ORDER BY name</SQL_QUERY> | small_bank_1 | SELECT name FROM accounts ORDER BY name | List all customers’ names in the alphabetical order. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all the customers in alphabetical order?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM accounts ORDER BY name</SQL_QUERY> | small_bank_1 | SELECT name FROM accounts ORDER BY name | What are the names of all the customers in alphabetical order? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of account that has the lowest total checking and saving balance.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance LIMIT 1 | Find the name of account that has the lowest total checking and saving balance. | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number);</schema>"
<primary_keys>[Primary Keys]: accounts : custid, savings : custid, checking : custid</primary_keys>"
<foreign_keys>[Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name corresponding to the accoung with the lowest sum of checking and savings balances?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance LIMIT 1</SQL_QUERY> | small_bank_1 | SELECT T1.name FROM accounts AS T1 JOIN checking AS T2 ON T1.custid = T2.custid JOIN savings AS T3 ON T1.custid = T3.custid ORDER BY T2.balance + T3.balance LIMIT 1 | What is the name corresponding to the accoung with the lowest sum of checking and savings balances? | [Schema (values) (types)]: | small_bank_1 | ACCOUNTS : custid (text) , name (number) | SAVINGS : custid (text) , balance (number) | CHECKING : custid (text) , balance (number); | [Primary Keys]: accounts : custid, savings : custid, checking : custid | [Foreign Keys]: savings : custid = accounts : custid | checking : custid = accounts : custid |
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