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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List name, dates active, and number of deaths for all storms with at least 1 death.</question>
[SQL]:
| <SQL_QUERY>SELECT name , dates_active , number_deaths FROM storm WHERE number_deaths >= 1</SQL_QUERY> | storm_record | SELECT name , dates_active , number_deaths FROM storm WHERE number_deaths >= 1 | List name, dates active, and number of deaths for all storms with at least 1 death. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names, dates active, and number of deaths for storms that had 1 or more death?</question>
[SQL]:
| <SQL_QUERY>SELECT name , dates_active , number_deaths FROM storm WHERE number_deaths >= 1</SQL_QUERY> | storm_record | SELECT name , dates_active , number_deaths FROM storm WHERE number_deaths >= 1 | What are the names, dates active, and number of deaths for storms that had 1 or more death? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average and maximum damage for all storms with max speed higher than 1000.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(damage_millions_USD) , max(damage_millions_USD) FROM storm WHERE max_speed > 1000</SQL_QUERY> | storm_record | SELECT avg(damage_millions_USD) , max(damage_millions_USD) FROM storm WHERE max_speed > 1000 | Show the average and maximum damage for all storms with max speed higher than 1000. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average and maximum damage in millions for storms that had a max speed over 1000?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(damage_millions_USD) , max(damage_millions_USD) FROM storm WHERE max_speed > 1000</SQL_QUERY> | storm_record | SELECT avg(damage_millions_USD) , max(damage_millions_USD) FROM storm WHERE max_speed > 1000 | What is the average and maximum damage in millions for storms that had a max speed over 1000? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total number of deaths and damage for all storms with a max speed greater than the average?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(number_deaths) , sum(damage_millions_USD) FROM storm WHERE max_speed > (SELECT avg(max_speed) FROM storm)</SQL_QUERY> | storm_record | SELECT sum(number_deaths) , sum(damage_millions_USD) FROM storm WHERE max_speed > (SELECT avg(max_speed) FROM storm) | What is the total number of deaths and damage for all storms with a max speed greater than the average? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the total number of deaths and total damange in millions for storms that had a max speed greater than the average.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(number_deaths) , sum(damage_millions_USD) FROM storm WHERE max_speed > (SELECT avg(max_speed) FROM storm)</SQL_QUERY> | storm_record | SELECT sum(number_deaths) , sum(damage_millions_USD) FROM storm WHERE max_speed > (SELECT avg(max_speed) FROM storm) | Return the total number of deaths and total damange in millions for storms that had a max speed greater than the average. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List name and damage for all storms in a descending order of max speed.</question>
[SQL]:
| <SQL_QUERY>SELECT name , damage_millions_USD FROM storm ORDER BY max_speed DESC</SQL_QUERY> | storm_record | SELECT name , damage_millions_USD FROM storm ORDER BY max_speed DESC | List name and damage for all storms in a descending order of max speed. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and damage in millions for storms, ordered by their max speeds descending?</question>
[SQL]:
| <SQL_QUERY>SELECT name , damage_millions_USD FROM storm ORDER BY max_speed DESC</SQL_QUERY> | storm_record | SELECT name , damage_millions_USD FROM storm ORDER BY max_speed DESC | What are the names and damage in millions for storms, ordered by their max speeds descending? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many regions are affected?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT region_id) FROM affected_region</SQL_QUERY> | storm_record | SELECT count(DISTINCT region_id) FROM affected_region | How many regions are affected? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of different affected regions.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT region_id) FROM affected_region</SQL_QUERY> | storm_record | SELECT count(DISTINCT region_id) FROM affected_region | Count the number of different affected regions. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name for regions not affected.</question>
[SQL]:
| <SQL_QUERY>SELECT region_name FROM region WHERE region_id NOT IN (SELECT region_id FROM affected_region)</SQL_QUERY> | storm_record | SELECT region_name FROM region WHERE region_id NOT IN (SELECT region_id FROM affected_region) | Show the name for regions not affected. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of regions that were not affected?</question>
[SQL]:
| <SQL_QUERY>SELECT region_name FROM region WHERE region_id NOT IN (SELECT region_id FROM affected_region)</SQL_QUERY> | storm_record | SELECT region_name FROM region WHERE region_id NOT IN (SELECT region_id FROM affected_region) | What are the names of regions that were not affected? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name for regions and the number of storms for each region.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.region_name , count(*) FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id</SQL_QUERY> | storm_record | SELECT T1.region_name , count(*) FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id | Show the name for regions and the number of storms for each region. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many storms occured in each region?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.region_name , count(*) FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id</SQL_QUERY> | storm_record | SELECT T1.region_name , count(*) FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id | How many storms occured in each region? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name for storms and the number of affected regions for each storm.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , count(*) FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id</SQL_QUERY> | storm_record | SELECT T1.name , count(*) FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id | List the name for storms and the number of affected regions for each storm. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many regions were affected by each storm?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , count(*) FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id</SQL_QUERY> | storm_record | SELECT T1.name , count(*) FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id | How many regions were affected by each storm? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the storm name and max speed which affected the greatest number of regions?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.max_speed FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | storm_record | SELECT T1.name , T1.max_speed FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id ORDER BY count(*) DESC LIMIT 1 | What is the storm name and max speed which affected the greatest number of regions? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the name and max speed of the storm that affected the most regions.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.max_speed FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | storm_record | SELECT T1.name , T1.max_speed FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id ORDER BY count(*) DESC LIMIT 1 | Return the name and max speed of the storm that affected the most regions. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of storms which don't have affected region in record.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM storm WHERE storm_id NOT IN (SELECT storm_id FROM affected_region)</SQL_QUERY> | storm_record | SELECT name FROM storm WHERE storm_id NOT IN (SELECT storm_id FROM affected_region) | Show the name of storms which don't have affected region in record. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of storms that did not affect any regions?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM storm WHERE storm_id NOT IN (SELECT storm_id FROM affected_region)</SQL_QUERY> | storm_record | SELECT name FROM storm WHERE storm_id NOT IN (SELECT storm_id FROM affected_region) | What are the names of storms that did not affect any regions? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show storm name with at least two regions and 10 cities affected.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2 INTERSECT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING sum(T2.number_city_affected) >= 10</SQL_QUERY> | storm_record | SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2 INTERSECT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING sum(T2.number_city_affected) >= 10 | Show storm name with at least two regions and 10 cities affected. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of storms that both affected two or more regions and affected a total of 10 or more cities?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2 INTERSECT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING sum(T2.number_city_affected) >= 10</SQL_QUERY> | storm_record | SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2 INTERSECT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING sum(T2.number_city_affected) >= 10 | What are the names of storms that both affected two or more regions and affected a total of 10 or more cities? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all storm names except for those with at least two affected regions.</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM storm EXCEPT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2</SQL_QUERY> | storm_record | SELECT name FROM storm EXCEPT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2 | Show all storm names except for those with at least two affected regions. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of storms that did not affect two or more regions?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM storm EXCEPT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2</SQL_QUERY> | storm_record | SELECT name FROM storm EXCEPT SELECT T1.name FROM storm AS T1 JOIN affected_region AS T2 ON T1.storm_id = T2.storm_id GROUP BY T1.storm_id HAVING count(*) >= 2 | What are the names of storms that did not affect two or more regions? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the region names affected by the storm with a number of deaths of least 10?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T3.number_deaths >= 10</SQL_QUERY> | storm_record | SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T3.number_deaths >= 10 | What are the region names affected by the storm with a number of deaths of least 10? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of the regions affected by storms that had a death count of at least 10.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T3.number_deaths >= 10</SQL_QUERY> | storm_record | SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T3.number_deaths >= 10 | Return the names of the regions affected by storms that had a death count of at least 10. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all storm names affecting region "Denmark".</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.region_name = 'Denmark'</SQL_QUERY> | storm_record | SELECT T3.name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.region_name = 'Denmark' | Show all storm names affecting region "Denmark". | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the storms that affected Denmark?</question>
[SQL]:
| <SQL_QUERY>SELECT T3.name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.region_name = 'Denmark'</SQL_QUERY> | storm_record | SELECT T3.name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.region_name = 'Denmark' | What are the names of the storms that affected Denmark? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the region name with at least two storms.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.region_name FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id HAVING count(*) >= 2</SQL_QUERY> | storm_record | SELECT T1.region_name FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id HAVING count(*) >= 2 | Show the region name with at least two storms. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of regions with two or more storms?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.region_name FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id HAVING count(*) >= 2</SQL_QUERY> | storm_record | SELECT T1.region_name FROM region AS T1 JOIN affected_region AS T2 ON T1.region_id = T2.region_id GROUP BY T1.region_id HAVING count(*) >= 2 | What are the names of regions with two or more storms? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of the regions which were affected by the storm that killed the greatest number of people.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id ORDER BY T3.Number_Deaths DESC LIMIT 1</SQL_QUERY> | storm_record | SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id ORDER BY T3.Number_Deaths DESC LIMIT 1 | Find the names of the regions which were affected by the storm that killed the greatest number of people. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of regions that were affected by the storm in which the most people died?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id ORDER BY T3.Number_Deaths DESC LIMIT 1</SQL_QUERY> | storm_record | SELECT T2.region_name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id ORDER BY T3.Number_Deaths DESC LIMIT 1 | What are the names of regions that were affected by the storm in which the most people died? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the storm that affected both Afghanistan and Albania regions.</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Afghanistan' INTERSECT SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Albania'</SQL_QUERY> | storm_record | SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Afghanistan' INTERSECT SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Albania' | Find the name of the storm that affected both Afghanistan and Albania regions. | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text);</schema>"
<primary_keys>[Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id</primary_keys>"
<foreign_keys>[Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the storms that affected both the regions of Afghanistan and Albania?</question>
[SQL]:
| <SQL_QUERY>SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Afghanistan' INTERSECT SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Albania'</SQL_QUERY> | storm_record | SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Afghanistan' INTERSECT SELECT T3.Name FROM affected_region AS T1 JOIN region AS T2 ON T1.region_id = T2.region_id JOIN storm AS T3 ON T1.storm_id = T3.storm_id WHERE T2.Region_name = 'Albania' | What are the names of the storms that affected both the regions of Afghanistan and Albania? | [Schema (values) (types)]: | storm_record | storm : storm_id (text) , name (number) , dates_active (text) , max_speed (text) , damage_millions_usd (number) , number_deaths (number) | region : region_id (text) , region_code (number) , region_name (text) | affected_region : region_id (text) , storm_id (number) , number_city_affected (text); | [Primary Keys]: storm : storm_id, region : region_id, affected_region : region_id | [Foreign Keys]: affected_region : storm_id = storm : storm_id | affected_region : region_id = region : region_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many counties are there in total?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM county</SQL_QUERY> | election | SELECT count(*) FROM county | How many counties are there in total? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the total number of counties.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM county</SQL_QUERY> | election | SELECT count(*) FROM county | Count the total number of counties. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the county name and population of all counties.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name , Population FROM county</SQL_QUERY> | election | SELECT County_name , Population FROM county | Show the county name and population of all counties. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the name and population of each county?</question>
[SQL]:
| <SQL_QUERY>SELECT County_name , Population FROM county</SQL_QUERY> | election | SELECT County_name , Population FROM county | What are the name and population of each county? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the average population of all counties.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Population) FROM county</SQL_QUERY> | election | SELECT avg(Population) FROM county | Show the average population of all counties. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>On average how large is the population of the counties?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(Population) FROM county</SQL_QUERY> | election | SELECT avg(Population) FROM county | On average how large is the population of the counties? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the maximum and minimum population among all counties.</question>
[SQL]:
| <SQL_QUERY>SELECT max(Population) , min(Population) FROM county</SQL_QUERY> | election | SELECT max(Population) , min(Population) FROM county | Return the maximum and minimum population among all counties. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the maximum and minimum population of the counties?</question>
[SQL]:
| <SQL_QUERY>SELECT max(Population) , min(Population) FROM county</SQL_QUERY> | election | SELECT max(Population) , min(Population) FROM county | What are the maximum and minimum population of the counties? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all the distinct districts for elections.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT District FROM election</SQL_QUERY> | election | SELECT DISTINCT District FROM election | Show all the distinct districts for elections. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the distinct districts for elections?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT District FROM election</SQL_QUERY> | election | SELECT DISTINCT District FROM election | What are the distinct districts for elections? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the zip code of the county with name "Howard".</question>
[SQL]:
| <SQL_QUERY>SELECT Zip_code FROM county WHERE County_name = "Howard"</SQL_QUERY> | election | SELECT Zip_code FROM county WHERE County_name = "Howard" | Show the zip code of the county with name "Howard". | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the zip code the county named "Howard" is located in?</question>
[SQL]:
| <SQL_QUERY>SELECT Zip_code FROM county WHERE County_name = "Howard"</SQL_QUERY> | election | SELECT Zip_code FROM county WHERE County_name = "Howard" | What is the zip code the county named "Howard" is located in? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the delegate from district 1 in election.</question>
[SQL]:
| <SQL_QUERY>SELECT Delegate FROM election WHERE District = 1</SQL_QUERY> | election | SELECT Delegate FROM election WHERE District = 1 | Show the delegate from district 1 in election. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who is the delegate of district 1 in the elections?</question>
[SQL]:
| <SQL_QUERY>SELECT Delegate FROM election WHERE District = 1</SQL_QUERY> | election | SELECT Delegate FROM election WHERE District = 1 | Who is the delegate of district 1 in the elections? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the delegate and committee information of elections.</question>
[SQL]:
| <SQL_QUERY>SELECT Delegate , Committee FROM election</SQL_QUERY> | election | SELECT Delegate , Committee FROM election | Show the delegate and committee information of elections. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the delegate and committee information for each election record?</question>
[SQL]:
| <SQL_QUERY>SELECT Delegate , Committee FROM election</SQL_QUERY> | election | SELECT Delegate , Committee FROM election | What are the delegate and committee information for each election record? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct governors are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Governor) FROM party</SQL_QUERY> | election | SELECT count(DISTINCT Governor) FROM party | How many distinct governors are there? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of distinct governors.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT Governor) FROM party</SQL_QUERY> | election | SELECT count(DISTINCT Governor) FROM party | Count the number of distinct governors. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the lieutenant governor and comptroller from the democratic party.</question>
[SQL]:
| <SQL_QUERY>SELECT Lieutenant_Governor , Comptroller FROM party WHERE Party = "Democratic"</SQL_QUERY> | election | SELECT Lieutenant_Governor , Comptroller FROM party WHERE Party = "Democratic" | Show the lieutenant governor and comptroller from the democratic party. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who are the lieutenant governor and comptroller from the democratic party?</question>
[SQL]:
| <SQL_QUERY>SELECT Lieutenant_Governor , Comptroller FROM party WHERE Party = "Democratic"</SQL_QUERY> | election | SELECT Lieutenant_Governor , Comptroller FROM party WHERE Party = "Democratic" | Who are the lieutenant governor and comptroller from the democratic party? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>In which distinct years was the governor "Eliot Spitzer"?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT YEAR FROM party WHERE Governor = "Eliot Spitzer"</SQL_QUERY> | election | SELECT DISTINCT YEAR FROM party WHERE Governor = "Eliot Spitzer" | In which distinct years was the governor "Eliot Spitzer"? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the distinct years when the governor was named "Eliot Spitzer".</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT YEAR FROM party WHERE Governor = "Eliot Spitzer"</SQL_QUERY> | election | SELECT DISTINCT YEAR FROM party WHERE Governor = "Eliot Spitzer" | Find the distinct years when the governor was named "Eliot Spitzer". | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show all the information about election.</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM election</SQL_QUERY> | election | SELECT * FROM election | Show all the information about election. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return all the information for each election record.</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM election</SQL_QUERY> | election | SELECT * FROM election | Return all the information for each election record. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the delegates and the names of county they belong to.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Delegate , T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District</SQL_QUERY> | election | SELECT T2.Delegate , T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District | Show the delegates and the names of county they belong to. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the delegate and name of the county they belong to, for each county?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Delegate , T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District</SQL_QUERY> | election | SELECT T2.Delegate , T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District | What are the delegate and name of the county they belong to, for each county? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which delegates are from counties with population smaller than 100000?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Delegate FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population < 100000</SQL_QUERY> | election | SELECT T2.Delegate FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population < 100000 | Which delegates are from counties with population smaller than 100000? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the delegates who are from counties with population below 100000.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Delegate FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population < 100000</SQL_QUERY> | election | SELECT T2.Delegate FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population < 100000 | Find the delegates who are from counties with population below 100000. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many distinct delegates are from counties with population larger than 50000?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT T2.Delegate) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population > 50000</SQL_QUERY> | election | SELECT count(DISTINCT T2.Delegate) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population > 50000 | How many distinct delegates are from counties with population larger than 50000? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of distinct delegates who are from counties with population above 50000.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT T2.Delegate) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population > 50000</SQL_QUERY> | election | SELECT count(DISTINCT T2.Delegate) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T1.Population > 50000 | Count the number of distinct delegates who are from counties with population above 50000. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the county that the delegates on "Appropriations" committee belong to?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T2.Committee = "Appropriations"</SQL_QUERY> | election | SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T2.Committee = "Appropriations" | What are the names of the county that the delegates on "Appropriations" committee belong to? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which county do the delegates on "Appropriations" committee belong to? Give me the county names.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T2.Committee = "Appropriations"</SQL_QUERY> | election | SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District WHERE T2.Committee = "Appropriations" | Which county do the delegates on "Appropriations" committee belong to? Give me the county names. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the delegates and the names of the party they belong to.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Delegate , T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID</SQL_QUERY> | election | SELECT T1.Delegate , T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID | Show the delegates and the names of the party they belong to. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each delegate, find the names of the party they are part of.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Delegate , T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID</SQL_QUERY> | election | SELECT T1.Delegate , T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID | For each delegate, find the names of the party they are part of. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who were the governors of the parties associated with delegates from district 1?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Governor FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1</SQL_QUERY> | election | SELECT T2.Governor FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1 | Who were the governors of the parties associated with delegates from district 1? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the parties associated with the delegates from district 1. Who served as governors of the parties?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Governor FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1</SQL_QUERY> | election | SELECT T2.Governor FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1 | Find the parties associated with the delegates from district 1. Who served as governors of the parties? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who were the comptrollers of the parties associated with the delegates from district 1 or district 2?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Comptroller FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1 OR T1.District = 2</SQL_QUERY> | election | SELECT T2.Comptroller FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1 OR T1.District = 2 | Who were the comptrollers of the parties associated with the delegates from district 1 or district 2? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the parties associated with the delegates from district 1 or 2. Who served as comptrollers of the parties?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Comptroller FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1 OR T1.District = 2</SQL_QUERY> | election | SELECT T2.Comptroller FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.District = 1 OR T1.District = 2 | Find the parties associated with the delegates from district 1 or 2. Who served as comptrollers of the parties? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return all the committees that have delegates from Democratic party.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic"</SQL_QUERY> | election | SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic" | Return all the committees that have delegates from Democratic party. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which committees have delegates from the Democratic party?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic"</SQL_QUERY> | election | SELECT T1.Committee FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T2.Party = "Democratic" | Which committees have delegates from the Democratic party? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of each county along with the corresponding number of delegates from that county.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.County_name , COUNT(*) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id</SQL_QUERY> | election | SELECT T1.County_name , COUNT(*) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id | Show the name of each county along with the corresponding number of delegates from that county. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each county, find the name of the county and the number of delegates from that county.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.County_name , COUNT(*) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id</SQL_QUERY> | election | SELECT T1.County_name , COUNT(*) FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id | For each county, find the name of the county and the number of delegates from that county. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of each party and the corresponding number of delegates from that party.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party</SQL_QUERY> | election | SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party | Show the name of each party and the corresponding number of delegates from that party. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each party, return the name of the party and the number of delegates from that party.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party</SQL_QUERY> | election | SELECT T2.Party , COUNT(*) FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party | For each party, return the name of the party and the number of delegates from that party. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of all counties sorted by population in ascending order.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY Population ASC</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY Population ASC | Return the names of all counties sorted by population in ascending order. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Sort the names of all counties in ascending order of population.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY Population ASC</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY Population ASC | Sort the names of all counties in ascending order of population. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the names of all counties sorted by county name in descending alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY County_name DESC</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY County_name DESC | Return the names of all counties sorted by county name in descending alphabetical order. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Sort the names of all counties in descending alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY County_name DESC</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY County_name DESC | Sort the names of all counties in descending alphabetical order. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of the county with the biggest population.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY Population DESC LIMIT 1</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY Population DESC LIMIT 1 | Show the name of the county with the biggest population. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which county has the largest population? Give me the name of the county.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY Population DESC LIMIT 1</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY Population DESC LIMIT 1 | Which county has the largest population? Give me the name of the county. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the 3 counties with the smallest population.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY Population ASC LIMIT 3</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY Population ASC LIMIT 3 | Show the 3 counties with the smallest population. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the 3 counties that have the smallest population? Give me the county names.</question>
[SQL]:
| <SQL_QUERY>SELECT County_name FROM county ORDER BY Population ASC LIMIT 3</SQL_QUERY> | election | SELECT County_name FROM county ORDER BY Population ASC LIMIT 3 | What are the 3 counties that have the smallest population? Give me the county names. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the names of counties that have at least two delegates.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id HAVING COUNT(*) >= 2</SQL_QUERY> | election | SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id HAVING COUNT(*) >= 2 | Show the names of counties that have at least two delegates. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which counties have two or more delegates? Give me the county names.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id HAVING COUNT(*) >= 2</SQL_QUERY> | election | SELECT T1.County_name FROM county AS T1 JOIN election AS T2 ON T1.County_id = T2.District GROUP BY T1.County_id HAVING COUNT(*) >= 2 | Which counties have two or more delegates? Give me the county names. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of the party that has at least two records.</question>
[SQL]:
| <SQL_QUERY>SELECT Party FROM party GROUP BY Party HAVING COUNT(*) >= 2</SQL_QUERY> | election | SELECT Party FROM party GROUP BY Party HAVING COUNT(*) >= 2 | Show the name of the party that has at least two records. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which party has two or more records?</question>
[SQL]:
| <SQL_QUERY>SELECT Party FROM party GROUP BY Party HAVING COUNT(*) >= 2</SQL_QUERY> | election | SELECT Party FROM party GROUP BY Party HAVING COUNT(*) >= 2 | Which party has two or more records? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the name of the party that has the most delegates.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | election | SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party ORDER BY COUNT(*) DESC LIMIT 1 | Show the name of the party that has the most delegates. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which party has the largest number of delegates?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | election | SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID GROUP BY T1.Party ORDER BY COUNT(*) DESC LIMIT 1 | Which party has the largest number of delegates? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the people that have been governor the most times.</question>
[SQL]:
| <SQL_QUERY>SELECT Governor FROM party GROUP BY Governor ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | election | SELECT Governor FROM party GROUP BY Governor ORDER BY COUNT(*) DESC LIMIT 1 | Show the people that have been governor the most times. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which people severed as governor most frequently?</question>
[SQL]:
| <SQL_QUERY>SELECT Governor FROM party GROUP BY Governor ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | election | SELECT Governor FROM party GROUP BY Governor ORDER BY COUNT(*) DESC LIMIT 1 | Which people severed as governor most frequently? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Show the people that have been comptroller the most times and the corresponding number of times.</question>
[SQL]:
| <SQL_QUERY>SELECT Comptroller , COUNT(*) FROM party GROUP BY Comptroller ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | election | SELECT Comptroller , COUNT(*) FROM party GROUP BY Comptroller ORDER BY COUNT(*) DESC LIMIT 1 | Show the people that have been comptroller the most times and the corresponding number of times. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which people severed as comptroller most frequently? Give me the name of the person and the frequency count.</question>
[SQL]:
| <SQL_QUERY>SELECT Comptroller , COUNT(*) FROM party GROUP BY Comptroller ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | election | SELECT Comptroller , COUNT(*) FROM party GROUP BY Comptroller ORDER BY COUNT(*) DESC LIMIT 1 | Which people severed as comptroller most frequently? Give me the name of the person and the frequency count. | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of parties that do not have delegates in election?</question>
[SQL]:
| <SQL_QUERY>SELECT Party FROM party WHERE Party_ID NOT IN (SELECT Party FROM election)</SQL_QUERY> | election | SELECT Party FROM party WHERE Party_ID NOT IN (SELECT Party FROM election) | What are the names of parties that do not have delegates in election? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which parties did not have any delegates in elections?</question>
[SQL]:
| <SQL_QUERY>SELECT Party FROM party WHERE Party_ID NOT IN (SELECT Party FROM election)</SQL_QUERY> | election | SELECT Party FROM party WHERE Party_ID NOT IN (SELECT Party FROM election) | Which parties did not have any delegates in elections? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of parties that have both delegates on "Appropriations" committee and</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Appropriations" INTERSECT SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Economic Matters"</SQL_QUERY> | election | SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Appropriations" INTERSECT SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Economic Matters" | What are the names of parties that have both delegates on "Appropriations" committee and | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_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)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number);</schema>"
<primary_keys>[Primary Keys]: county : county_id, party : party_id, election : election_id</primary_keys>"
<foreign_keys>[Foreign Keys]: election : district = county : county_id | election : party = party : party_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which parties have delegates in both the "Appropriations" committee and the "Economic Matters" committee?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Appropriations" INTERSECT SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Economic Matters"</SQL_QUERY> | election | SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Appropriations" INTERSECT SELECT T2.Party FROM election AS T1 JOIN party AS T2 ON T1.Party = T2.Party_ID WHERE T1.Committee = "Economic Matters" | Which parties have delegates in both the "Appropriations" committee and the "Economic Matters" committee? | [Schema (values) (types)]: | election | county : county_id (text) , county_name (number) , population (text) , zip_code (number) | party : party_id (text) , year (number) , party (text) , governor (number) , lieutenant_governor (text) , comptroller (number) , attorney_general (number) , us_senate (text) | election : election_id (text) , counties_represented (number) , district (text) , delegate (number) , party (text) , first_elected (number) , committee (number); | [Primary Keys]: county : county_id, party : party_id, election : election_id | [Foreign Keys]: election : district = county : county_id | election : party = party : party_id |
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