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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the distinct district names ordered by city area in descending.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT District_name FROM district ORDER BY city_area DESC</SQL_QUERY> | store_product | SELECT DISTINCT District_name FROM district ORDER BY city_area DESC | Find all the distinct district names ordered by city area in descending. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different district names in order of descending city area?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT District_name FROM district ORDER BY city_area DESC</SQL_QUERY> | store_product | SELECT DISTINCT District_name FROM district ORDER BY city_area DESC | What are the different district names in order of descending city area? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the list of page size which have more than 3 product listed</question>
[SQL]:
| <SQL_QUERY>SELECT max_page_size FROM product GROUP BY max_page_size HAVING count(*) > 3</SQL_QUERY> | store_product | SELECT max_page_size FROM product GROUP BY max_page_size HAVING count(*) > 3 | Find the list of page size which have more than 3 product listed | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the maximum page size for everything that has more than 3 products listed?</question>
[SQL]:
| <SQL_QUERY>SELECT max_page_size FROM product GROUP BY max_page_size HAVING count(*) > 3</SQL_QUERY> | store_product | SELECT max_page_size FROM product GROUP BY max_page_size HAVING count(*) > 3 | What is the maximum page size for everything that has more than 3 products listed? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and population of district with population between 200000 and 2000000</question>
[SQL]:
| <SQL_QUERY>SELECT District_name , City_Population FROM district WHERE City_Population BETWEEN 200000 AND 2000000</SQL_QUERY> | store_product | SELECT District_name , City_Population FROM district WHERE City_Population BETWEEN 200000 AND 2000000 | Find the name and population of district with population between 200000 and 2000000 | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the district names and city populations for all districts that between 200,000 and 2,000,000 residents?</question>
[SQL]:
| <SQL_QUERY>SELECT District_name , City_Population FROM district WHERE City_Population BETWEEN 200000 AND 2000000</SQL_QUERY> | store_product | SELECT District_name , City_Population FROM district WHERE City_Population BETWEEN 200000 AND 2000000 | What are the district names and city populations for all districts that between 200,000 and 2,000,000 residents? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name all districts with city area greater than 10 or population larger than 100000</question>
[SQL]:
| <SQL_QUERY>SELECT district_name FROM district WHERE city_area > 10 OR City_Population > 100000</SQL_QUERY> | store_product | SELECT district_name FROM district WHERE city_area > 10 OR City_Population > 100000 | Find the name all districts with city area greater than 10 or population larger than 100000 | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all districts with a city area greater than 10 or have more than 100000 people living there?</question>
[SQL]:
| <SQL_QUERY>SELECT district_name FROM district WHERE city_area > 10 OR City_Population > 100000</SQL_QUERY> | store_product | SELECT district_name FROM district WHERE city_area > 10 OR City_Population > 100000 | What are the names of all districts with a city area greater than 10 or have more than 100000 people living there? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which district has the largest population?</question>
[SQL]:
| <SQL_QUERY>SELECT district_name FROM district ORDER BY city_population DESC LIMIT 1</SQL_QUERY> | store_product | SELECT district_name FROM district ORDER BY city_population DESC LIMIT 1 | Which district has the largest population? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the district with the most residents?</question>
[SQL]:
| <SQL_QUERY>SELECT district_name FROM district ORDER BY city_population DESC LIMIT 1</SQL_QUERY> | store_product | SELECT district_name FROM district ORDER BY city_population DESC LIMIT 1 | What is the name of the district with the most residents? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which district has the least area?</question>
[SQL]:
| <SQL_QUERY>SELECT district_name FROM district ORDER BY city_area ASC LIMIT 1</SQL_QUERY> | store_product | SELECT district_name FROM district ORDER BY city_area ASC LIMIT 1 | Which district has the least area? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the district with the smallest area?</question>
[SQL]:
| <SQL_QUERY>SELECT district_name FROM district ORDER BY city_area ASC LIMIT 1</SQL_QUERY> | store_product | SELECT district_name FROM district ORDER BY city_area ASC LIMIT 1 | What is the name of the district with the smallest area? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total population of the top 3 districts with the largest area.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(city_population) FROM district ORDER BY city_area DESC LIMIT 3</SQL_QUERY> | store_product | SELECT sum(city_population) FROM district ORDER BY city_area DESC LIMIT 3 | Find the total population of the top 3 districts with the largest area. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total number of residents for the districts with the 3 largest areas?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(city_population) FROM district ORDER BY city_area DESC LIMIT 3</SQL_QUERY> | store_product | SELECT sum(city_population) FROM district ORDER BY city_area DESC LIMIT 3 | What is the total number of residents for the districts with the 3 largest areas? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all types of store and number of them.</question>
[SQL]:
| <SQL_QUERY>SELECT TYPE , count(*) FROM store GROUP BY TYPE</SQL_QUERY> | store_product | SELECT TYPE , count(*) FROM store GROUP BY TYPE | Find all types of store and number of them. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each type of store, how many of them are there?</question>
[SQL]:
| <SQL_QUERY>SELECT TYPE , count(*) FROM store GROUP BY TYPE</SQL_QUERY> | store_product | SELECT TYPE , count(*) FROM store GROUP BY TYPE | For each type of store, how many of them are there? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of all stores in Khanewal District.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t3.district_name = "Khanewal District"</SQL_QUERY> | store_product | SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t3.district_name = "Khanewal District" | Find the names of all stores in Khanewal District. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all the stores located in Khanewal District?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t3.district_name = "Khanewal District"</SQL_QUERY> | store_product | SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t3.district_name = "Khanewal District" | What are the names of all the stores located in Khanewal District? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the stores in the district with the most population.</question>
[SQL]:
| <SQL_QUERY>SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id WHERE district_id = (SELECT district_id FROM district ORDER BY city_population DESC LIMIT 1)</SQL_QUERY> | store_product | SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id WHERE district_id = (SELECT district_id FROM district ORDER BY city_population DESC LIMIT 1) | Find all the stores in the district with the most population. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all the stores in the largest district by population?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id WHERE district_id = (SELECT district_id FROM district ORDER BY city_population DESC LIMIT 1)</SQL_QUERY> | store_product | SELECT t1.store_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id WHERE district_id = (SELECT district_id FROM district ORDER BY city_population DESC LIMIT 1) | What are the names of all the stores in the largest district by population? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which city is the headquarter of the store named "Blackville" in?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.store_name = "Blackville"</SQL_QUERY> | store_product | SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.store_name = "Blackville" | Which city is the headquarter of the store named "Blackville" in? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What city is the headquarter of the store Blackville?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.store_name = "Blackville"</SQL_QUERY> | store_product | SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.store_name = "Blackville" | What city is the headquarter of the store Blackville? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of stores in each city.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.headquartered_city , count(*) FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city</SQL_QUERY> | store_product | SELECT t3.headquartered_city , count(*) FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city | Find the number of stores in each city. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many stores are headquarted in each city?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.headquartered_city , count(*) FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city</SQL_QUERY> | store_product | SELECT t3.headquartered_city , count(*) FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city | How many stores are headquarted in each city? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the city with the most number of stores.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | store_product | SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city ORDER BY count(*) DESC LIMIT 1 | Find the city with the most number of stores. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the city with the most number of flagship stores?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | store_product | SELECT t3.headquartered_city FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id GROUP BY t3.headquartered_city ORDER BY count(*) DESC LIMIT 1 | What is the city with the most number of flagship stores? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average pages per minute color?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(pages_per_minute_color) FROM product</SQL_QUERY> | store_product | SELECT avg(pages_per_minute_color) FROM product | What is the average pages per minute color? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average number of pages per minute color?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(pages_per_minute_color) FROM product</SQL_QUERY> | store_product | SELECT avg(pages_per_minute_color) FROM product | What is the average number of pages per minute color? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What products are available at store named "Miramichi"?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.product FROM product AS t1 JOIN store_product AS t2 ON t1.product_id = t2.product_id JOIN store AS t3 ON t2.store_id = t3.store_id WHERE t3.store_name = "Miramichi"</SQL_QUERY> | store_product | SELECT t1.product FROM product AS t1 JOIN store_product AS t2 ON t1.product_id = t2.product_id JOIN store AS t3 ON t2.store_id = t3.store_id WHERE t3.store_name = "Miramichi" | What products are available at store named "Miramichi"? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What products are sold at the store named Miramichi?</question>
[SQL]:
| <SQL_QUERY>SELECT t1.product FROM product AS t1 JOIN store_product AS t2 ON t1.product_id = t2.product_id JOIN store AS t3 ON t2.store_id = t3.store_id WHERE t3.store_name = "Miramichi"</SQL_QUERY> | store_product | SELECT t1.product FROM product AS t1 JOIN store_product AS t2 ON t1.product_id = t2.product_id JOIN store AS t3 ON t2.store_id = t3.store_id WHERE t3.store_name = "Miramichi" | What products are sold at the store named Miramichi? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find products with max page size as "A4" and pages per minute color smaller than 5.</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE max_page_size = "A4" AND pages_per_minute_color < 5</SQL_QUERY> | store_product | SELECT product FROM product WHERE max_page_size = "A4" AND pages_per_minute_color < 5 | Find products with max page size as "A4" and pages per minute color smaller than 5. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the products with the maximum page size A4 that also have a pages per minute color smaller than 5?</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE max_page_size = "A4" AND pages_per_minute_color < 5</SQL_QUERY> | store_product | SELECT product FROM product WHERE max_page_size = "A4" AND pages_per_minute_color < 5 | What are the products with the maximum page size A4 that also have a pages per minute color smaller than 5? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find products with max page size as "A4" or pages per minute color smaller than 5.</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE max_page_size = "A4" OR pages_per_minute_color < 5</SQL_QUERY> | store_product | SELECT product FROM product WHERE max_page_size = "A4" OR pages_per_minute_color < 5 | Find products with max page size as "A4" or pages per minute color smaller than 5. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the products with the maximum page size eqal to A4 or a pages per minute color less than 5?</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE max_page_size = "A4" OR pages_per_minute_color < 5</SQL_QUERY> | store_product | SELECT product FROM product WHERE max_page_size = "A4" OR pages_per_minute_color < 5 | What are the products with the maximum page size eqal to A4 or a pages per minute color less than 5? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the product whose name contains the word "Scanner".</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE product LIKE "%Scanner%"</SQL_QUERY> | store_product | SELECT product FROM product WHERE product LIKE "%Scanner%" | Find all the product whose name contains the word "Scanner". | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all of the products whose name includes the substring "Scanner"?</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE product LIKE "%Scanner%"</SQL_QUERY> | store_product | SELECT product FROM product WHERE product LIKE "%Scanner%" | What are all of the products whose name includes the substring "Scanner"? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the most prominent max page size among all the products.</question>
[SQL]:
| <SQL_QUERY>SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | store_product | SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1 | Find the most prominent max page size among all the products. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the most common maximum page size?</question>
[SQL]:
| <SQL_QUERY>SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | store_product | SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1 | What is the most common maximum page size? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of the products that are not using the most frequently-used max page size.</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE product != (SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1)</SQL_QUERY> | store_product | SELECT product FROM product WHERE product != (SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1) | Find the name of the products that are not using the most frequently-used max page size. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all products that are not the most frequently-used maximum page size?</question>
[SQL]:
| <SQL_QUERY>SELECT product FROM product WHERE product != (SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1)</SQL_QUERY> | store_product | SELECT product FROM product WHERE product != (SELECT max_page_size FROM product GROUP BY max_page_size ORDER BY count(*) DESC LIMIT 1) | What are the names of all products that are not the most frequently-used maximum page size? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the total population of the districts where the area is bigger than the average city area.</question>
[SQL]:
| <SQL_QUERY>SELECT sum(city_population) FROM district WHERE city_area > (SELECT avg(city_area) FROM district)</SQL_QUERY> | store_product | SELECT sum(city_population) FROM district WHERE city_area > (SELECT avg(city_area) FROM district) | Find the total population of the districts where the area is bigger than the average city area. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total population for all the districts that have an area larger tahn the average city area?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(city_population) FROM district WHERE city_area > (SELECT avg(city_area) FROM district)</SQL_QUERY> | store_product | SELECT sum(city_population) FROM district WHERE city_area > (SELECT avg(city_area) FROM district) | What is the total population for all the districts that have an area larger tahn the average city area? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the names of districts where have both city mall and village store type stores.</question>
[SQL]:
| <SQL_QUERY>SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "City Mall" INTERSECT SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "Village Store"</SQL_QUERY> | store_product | SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "City Mall" INTERSECT SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "Village Store" | Find the names of districts where have both city mall and village store type stores. | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number);</schema>"
<primary_keys>[Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id</primary_keys>"
<foreign_keys>[Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the districts that have both mall and village store style shops?</question>
[SQL]:
| <SQL_QUERY>SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "City Mall" INTERSECT SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "Village Store"</SQL_QUERY> | store_product | SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "City Mall" INTERSECT SELECT t3.District_name FROM store AS t1 JOIN store_district AS t2 ON t1.store_id = t2.store_id JOIN district AS t3 ON t2.district_id = t3.district_id WHERE t1.Type = "Village Store" | What are the names of the districts that have both mall and village store style shops? | [Schema (values) (types)]: | store_product | product : product_id (text) , product (number) , dimensions (text) , dpi (text) , pages_per_minute_color (number) , max_page_size (number) , interface (text) | store : store_id (text) , store_name (number) , type (text) , area_size (text) , number_of_product_category (number) , ranking (number) | district : district_id (text) , district_name (number) , headquartered_city (text) , city_population (text) , city_area (number) | store_product : store_id (text) , product_id (number) | store_district : store_id (text) , district_id (number); | [Primary Keys]: product : product_id, store : store_id, district : district_id, store_product : store_id, store_district : store_id | [Foreign Keys]: store_product : store_id = store : store_id | store_district : district_id = district : district_id | store_district : store_id = store : store_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)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total enrollment number of all colleges?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(enr) FROM College</SQL_QUERY> | soccer_2 | SELECT sum(enr) FROM College | What is the total enrollment number of all colleges? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students are enrolled in college?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(enr) FROM College</SQL_QUERY> | soccer_2 | SELECT sum(enr) FROM College | How many students are enrolled in college? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average enrollment number?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(enr) FROM College</SQL_QUERY> | soccer_2 | SELECT avg(enr) FROM College | What is the average enrollment number? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students, on average, does each college have enrolled?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(enr) FROM College</SQL_QUERY> | soccer_2 | SELECT avg(enr) FROM College | How many students, on average, does each college have enrolled? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many colleges in total?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM College</SQL_QUERY> | soccer_2 | SELECT count(*) FROM College | How many colleges in total? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different colleges are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM College</SQL_QUERY> | soccer_2 | SELECT count(*) FROM College | How many different colleges are there? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many players have more than 1000 hours of training?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Player WHERE HS > 1000</SQL_QUERY> | soccer_2 | SELECT count(*) FROM Player WHERE HS > 1000 | How many players have more than 1000 hours of training? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different players trained for more than 1000 hours?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM Player WHERE HS > 1000</SQL_QUERY> | soccer_2 | SELECT count(*) FROM Player WHERE HS > 1000 | How many different players trained for more than 1000 hours? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many colleges has more than 15000 students?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM College WHERE enr > 15000</SQL_QUERY> | soccer_2 | SELECT count(*) FROM College WHERE enr > 15000 | How many colleges has more than 15000 students? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the number of colleges with a student population greater than 15000?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM College WHERE enr > 15000</SQL_QUERY> | soccer_2 | SELECT count(*) FROM College WHERE enr > 15000 | What is the number of colleges with a student population greater than 15000? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average training hours of all players?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(HS) FROM Player</SQL_QUERY> | soccer_2 | SELECT avg(HS) FROM Player | What is the average training hours of all players? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many hours do the players train on average?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(HS) FROM Player</SQL_QUERY> | soccer_2 | SELECT avg(HS) FROM Player | How many hours do the players train on average? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and training hours of players whose hours are below 1500.</question>
[SQL]:
| <SQL_QUERY>SELECT pName , HS FROM Player WHERE HS < 1500</SQL_QUERY> | soccer_2 | SELECT pName , HS FROM Player WHERE HS < 1500 | Find the name and training hours of players whose hours are below 1500. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and number of hours spent training for each player who trains for less than 1500 hours?</question>
[SQL]:
| <SQL_QUERY>SELECT pName , HS FROM Player WHERE HS < 1500</SQL_QUERY> | soccer_2 | SELECT pName , HS FROM Player WHERE HS < 1500 | What are the names and number of hours spent training for each player who trains for less than 1500 hours? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different colleges do attend the tryout test?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT cName) FROM tryout</SQL_QUERY> | soccer_2 | SELECT count(DISTINCT cName) FROM tryout | How many different colleges do attend the tryout test? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different colleges were represented at tryouts?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT cName) FROM tryout</SQL_QUERY> | soccer_2 | SELECT count(DISTINCT cName) FROM tryout | How many different colleges were represented at tryouts? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the unique types of player positions in the tryout?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT pPos) FROM tryout</SQL_QUERY> | soccer_2 | SELECT count(DISTINCT pPos) FROM tryout | What are the unique types of player positions in the tryout? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different types of player positions?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT pPos) FROM tryout</SQL_QUERY> | soccer_2 | SELECT count(DISTINCT pPos) FROM tryout | What are the different types of player positions? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students got accepted after the tryout?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM tryout WHERE decision = 'yes'</SQL_QUERY> | soccer_2 | SELECT count(*) FROM tryout WHERE decision = 'yes' | How many students got accepted after the tryout? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students received a yes from tryouts?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM tryout WHERE decision = 'yes'</SQL_QUERY> | soccer_2 | SELECT count(*) FROM tryout WHERE decision = 'yes' | How many students received a yes from tryouts? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students whose are playing the role of goalie?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM tryout WHERE pPos = 'goalie'</SQL_QUERY> | soccer_2 | SELECT count(*) FROM tryout WHERE pPos = 'goalie' | How many students whose are playing the role of goalie? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the number of students playing as a goalie?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM tryout WHERE pPos = 'goalie'</SQL_QUERY> | soccer_2 | SELECT count(*) FROM tryout WHERE pPos = 'goalie' | What is the number of students playing as a goalie? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the max, average and min training hours of all players.</question>
[SQL]:
| <SQL_QUERY>SELECT avg(HS) , max(HS) , min(HS) FROM Player</SQL_QUERY> | soccer_2 | SELECT avg(HS) , max(HS) , min(HS) FROM Player | Find the max, average and min training hours of all players. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average, maximum, and minimum for the number of hours spent training?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(HS) , max(HS) , min(HS) FROM Player</SQL_QUERY> | soccer_2 | SELECT avg(HS) , max(HS) , min(HS) FROM Player | What is the average, maximum, and minimum for the number of hours spent training? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is average enrollment of colleges in the state FL?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(enr) FROM College WHERE state = 'FL'</SQL_QUERY> | soccer_2 | SELECT avg(enr) FROM College WHERE state = 'FL' | What is average enrollment of colleges in the state FL? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is average number of students enrolled in Florida colleges?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(enr) FROM College WHERE state = 'FL'</SQL_QUERY> | soccer_2 | SELECT avg(enr) FROM College WHERE state = 'FL' | What is average number of students enrolled in Florida colleges? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of players whose training hours is between 500 and 1500?</question>
[SQL]:
| <SQL_QUERY>SELECT pName FROM Player WHERE HS BETWEEN 500 AND 1500</SQL_QUERY> | soccer_2 | SELECT pName FROM Player WHERE HS BETWEEN 500 AND 1500 | What are the names of players whose training hours is between 500 and 1500? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of players who train between 500 and 1500 hours?</question>
[SQL]:
| <SQL_QUERY>SELECT pName FROM Player WHERE HS BETWEEN 500 AND 1500</SQL_QUERY> | soccer_2 | SELECT pName FROM Player WHERE HS BETWEEN 500 AND 1500 | What are the names of players who train between 500 and 1500 hours? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the players whose names contain letter 'a'.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT pName FROM Player WHERE pName LIKE '%a%'</SQL_QUERY> | soccer_2 | SELECT DISTINCT pName FROM Player WHERE pName LIKE '%a%' | Find the players whose names contain letter 'a'. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Who are the players that have names containing the letter a?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT pName FROM Player WHERE pName LIKE '%a%'</SQL_QUERY> | soccer_2 | SELECT DISTINCT pName FROM Player WHERE pName LIKE '%a%' | Who are the players that have names containing the letter a? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name, enrollment of the colleges whose size is bigger than 10000 and location is in state LA.</question>
[SQL]:
| <SQL_QUERY>SELECT cName , enr FROM College WHERE enr > 10000 AND state = "LA"</SQL_QUERY> | soccer_2 | SELECT cName , enr FROM College WHERE enr > 10000 AND state = "LA" | Find the name, enrollment of the colleges whose size is bigger than 10000 and location is in state LA. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and enrollment numbers for colleges that have more than 10000 enrolled and are located in Louisiana?</question>
[SQL]:
| <SQL_QUERY>SELECT cName , enr FROM College WHERE enr > 10000 AND state = "LA"</SQL_QUERY> | soccer_2 | SELECT cName , enr FROM College WHERE enr > 10000 AND state = "LA" | What are the names and enrollment numbers for colleges that have more than 10000 enrolled and are located in Louisiana? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all information about college sorted by enrollment number in the ascending order.</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM College ORDER BY enr</SQL_QUERY> | soccer_2 | SELECT * FROM College ORDER BY enr | List all information about college sorted by enrollment number in the ascending order. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What information do you have on colleges sorted by increasing enrollment numbers?</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM College ORDER BY enr</SQL_QUERY> | soccer_2 | SELECT * FROM College ORDER BY enr | What information do you have on colleges sorted by increasing enrollment numbers? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name of the colleges whose enrollment is greater 18000 sorted by the college's name.</question>
[SQL]:
| <SQL_QUERY>SELECT cName FROM College WHERE enr > 18000 ORDER BY cName</SQL_QUERY> | soccer_2 | SELECT cName FROM College WHERE enr > 18000 ORDER BY cName | List the name of the colleges whose enrollment is greater 18000 sorted by the college's name. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of every college in alphabetical order that has more than 18000 students enrolled?</question>
[SQL]:
| <SQL_QUERY>SELECT cName FROM College WHERE enr > 18000 ORDER BY cName</SQL_QUERY> | soccer_2 | SELECT cName FROM College WHERE enr > 18000 ORDER BY cName | What is the name of every college in alphabetical order that has more than 18000 students enrolled? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of players whose card is yes in the descending order of training hours.</question>
[SQL]:
| <SQL_QUERY>SELECT pName FROM Player WHERE yCard = 'yes' ORDER BY HS DESC</SQL_QUERY> | soccer_2 | SELECT pName FROM Player WHERE yCard = 'yes' ORDER BY HS DESC | Find the name of players whose card is yes in the descending order of training hours. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the name of the players who received a card in descending order of the hours of training?</question>
[SQL]:
| <SQL_QUERY>SELECT pName FROM Player WHERE yCard = 'yes' ORDER BY HS DESC</SQL_QUERY> | soccer_2 | SELECT pName FROM Player WHERE yCard = 'yes' ORDER BY HS DESC | What are the name of the players who received a card in descending order of the hours of training? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name of different colleges involved in the tryout in alphabetical order.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT cName FROM tryout ORDER BY cName</SQL_QUERY> | soccer_2 | SELECT DISTINCT cName FROM tryout ORDER BY cName | Find the name of different colleges involved in the tryout in alphabetical order. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different names of the colleges involved in the tryout in alphabetical order?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT cName FROM tryout ORDER BY cName</SQL_QUERY> | soccer_2 | SELECT DISTINCT cName FROM tryout ORDER BY cName | What are the different names of the colleges involved in the tryout in alphabetical order? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which position is most popular among players in the tryout?</question>
[SQL]:
| <SQL_QUERY>SELECT pPos FROM tryout GROUP BY pPos ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | soccer_2 | SELECT pPos FROM tryout GROUP BY pPos ORDER BY count(*) DESC LIMIT 1 | Which position is most popular among players in the tryout? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What was the most popular position at tryouts?</question>
[SQL]:
| <SQL_QUERY>SELECT pPos FROM tryout GROUP BY pPos ORDER BY count(*) DESC LIMIT 1</SQL_QUERY> | soccer_2 | SELECT pPos FROM tryout GROUP BY pPos ORDER BY count(*) DESC LIMIT 1 | What was the most popular position at tryouts? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the number of students who participate in the tryout for each college ordered by descending count.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) , cName FROM tryout GROUP BY cName ORDER BY count(*) DESC</SQL_QUERY> | soccer_2 | SELECT count(*) , cName FROM tryout GROUP BY cName ORDER BY count(*) DESC | Find the number of students who participate in the tryout for each college ordered by descending count. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many students participated in tryouts for each college by descennding count?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) , cName FROM tryout GROUP BY cName ORDER BY count(*) DESC</SQL_QUERY> | soccer_2 | SELECT count(*) , cName FROM tryout GROUP BY cName ORDER BY count(*) DESC | How many students participated in tryouts for each college by descennding count? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is minimum hours of the students playing in different position?</question>
[SQL]:
| <SQL_QUERY>SELECT min(T2.HS) , T1.pPos FROM tryout AS T1 JOIN player AS T2 ON T1.pID = T2.pID GROUP BY T1.pPos</SQL_QUERY> | soccer_2 | SELECT min(T2.HS) , T1.pPos FROM tryout AS T1 JOIN player AS T2 ON T1.pID = T2.pID GROUP BY T1.pPos | What is minimum hours of the students playing in different position? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each position, what is the minimum time students spent practicing?</question>
[SQL]:
| <SQL_QUERY>SELECT min(T2.HS) , T1.pPos FROM tryout AS T1 JOIN player AS T2 ON T1.pID = T2.pID GROUP BY T1.pPos</SQL_QUERY> | soccer_2 | SELECT min(T2.HS) , T1.pPos FROM tryout AS T1 JOIN player AS T2 ON T1.pID = T2.pID GROUP BY T1.pPos | For each position, what is the minimum time students spent practicing? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of schools with the top 3 largest size?</question>
[SQL]:
| <SQL_QUERY>SELECT cName FROM college ORDER BY enr DESC LIMIT 3</SQL_QUERY> | soccer_2 | SELECT cName FROM college ORDER BY enr DESC LIMIT 3 | What are the names of schools with the top 3 largest size? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of the schools with the top 3 largest class sizes?</question>
[SQL]:
| <SQL_QUERY>SELECT cName FROM college ORDER BY enr DESC LIMIT 3</SQL_QUERY> | soccer_2 | SELECT cName FROM college ORDER BY enr DESC LIMIT 3 | What are the names of the schools with the top 3 largest class sizes? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of school that has the smallest enrollment in each state?</question>
[SQL]:
| <SQL_QUERY>SELECT cName , state , min(enr) FROM college GROUP BY state</SQL_QUERY> | soccer_2 | SELECT cName , state , min(enr) FROM college GROUP BY state | What is the name of school that has the smallest enrollment in each state? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of the school with smallest enrollment size per state?</question>
[SQL]:
| <SQL_QUERY>SELECT cName , state , min(enr) FROM college GROUP BY state</SQL_QUERY> | soccer_2 | SELECT cName , state , min(enr) FROM college GROUP BY state | What is the name of the school with smallest enrollment size per state? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the states where have some college students in tryout.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName</SQL_QUERY> | soccer_2 | SELECT DISTINCT state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName | Find the states where have some college students in tryout. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different states that have students trying out?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName</SQL_QUERY> | soccer_2 | SELECT DISTINCT state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName | What are the different states that have students trying out? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the states where have some college students in tryout and their decisions are yes.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.decision = 'yes'</SQL_QUERY> | soccer_2 | SELECT DISTINCT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.decision = 'yes' | Find the states where have some college students in tryout and their decisions are yes. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different states that had students successfully try out?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.decision = 'yes'</SQL_QUERY> | soccer_2 | SELECT DISTINCT T1.state FROM college AS T1 JOIN tryout AS T2 ON T1.cName = T2.cName WHERE T2.decision = 'yes' | What are the different states that had students successfully try out? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the name and college of students whose decisions are yes in the tryout.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.pName , T2.cName FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'yes'</SQL_QUERY> | soccer_2 | SELECT T1.pName , T2.cName FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'yes' | Find the name and college of students whose decisions are yes in the tryout. | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number);</schema>"
<primary_keys>[Primary Keys]: college : cname, player : pid, tryout : pid</primary_keys>"
<foreign_keys>[Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all the players who received a yes during tryouts, and also what are the names of their colleges?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.pName , T2.cName FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'yes'</SQL_QUERY> | soccer_2 | SELECT T1.pName , T2.cName FROM player AS T1 JOIN tryout AS T2 ON T1.pID = T2.pID WHERE T2.decision = 'yes' | What are the names of all the players who received a yes during tryouts, and also what are the names of their colleges? | [Schema (values) (types)]: | soccer_2 | College : cname (text) , state (text) , enr (text) | Player : pid (text) , pname (text) , ycard (text) , hs (number) | Tryout : pid (text) , cname (text) , ppos (text) , decision (number); | [Primary Keys]: college : cname, player : pid, tryout : pid | [Foreign Keys]: tryout : cname = college : cname | tryout : pid = player : pid |
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