richardr1126/spider-context-instruct huggingface dataset:
### Instruction:

Convert text to sql: What document types have more than 2 corresponding documents? | roles : role_code , role_description | users : user_id , role_code , user_name , user_login , password | document_structures : document_structure_code , parent_document_structure_code , document_structure_description | functional_areas : functional_area_code , parent_functional_area_code , functional_area_description | images : image_id , image_alt_text , image_name , image_url | documents : document_code , document_structure_code , document_type_code , access_count , document_name | document_functional_areas : document_code , functional_area_code | document_sections : section_id , document_code , section_sequence , section_code , section_title | document_sections_images : section_id , image_id | users.role_code = roles.role_code | documents.document_structure_code = document_structures.document_structure_code | document_functional_areas.functional_area_code = functional_areas.functional_area_code | document_functional_areas.document_code = documents.document_code | document_sections.document_code = documents.document_code | document_sections_images.image_id = images.image_id | document_sections_images.section_id = document_sections.section_id | 

### Response:

select document_type_code from documents group by document_type_code having count ( * ) > 2

### Instruction:

Convert text to sql: Give the codes of document types that have more than 2 corresponding documents. | roles : role_code , role_description | users : user_id , role_code , user_name , user_login , password | document_structures : document_structure_code , parent_document_structure_code , document_structure_description | functional_areas : functional_area_code , parent_functional_area_code , functional_area_description | images : image_id , image_alt_text , image_name , image_url | documents : document_code , document_structure_code , document_type_code , access_count , document_name | document_functional_areas : document_code , functional_area_code | document_sections : section_id , document_code , section_sequence , section_code , section_title | document_sections_images : section_id , image_id | users.role_code = roles.role_code | documents.document_structure_code = document_structures.document_structure_code | document_functional_areas.functional_area_code = functional_areas.functional_area_code | document_functional_areas.document_code = documents.document_code | document_sections.document_code = documents.document_code | document_sections_images.image_id = images.image_id | document_sections_images.section_id = document_sections.section_id | 

### Response:

select document_type_code from documents group by document_type_code having count ( * ) > 2
### Instruction:

Convert text to sql: How many companies are there? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select count ( * ) from companies

### Instruction:

Convert text to sql: Count the number of companies. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select count ( * ) from companies

### Instruction:

Convert text to sql: List the names of companies in descending order of market value. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from companies order by market_value_billion desc

### Instruction:

Convert text to sql: Sort the company names in descending order of the company's market value. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from companies order by market_value_billion desc

### Instruction:

Convert text to sql: What are the names of companies whose headquarters are not "USA"? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from companies where headquarters != 'USA'

### Instruction:

Convert text to sql: Find the names of the companies whose headquarters are not located in "USA". | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from companies where headquarters != 'USA'
### Instruction:

Convert text to sql: What are the name and assets of each company, sorted in ascending order of company name? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name , assets_billion from companies order by name asc

### Instruction:

Convert text to sql: List the name and assets of each company in ascending order of company name. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name , assets_billion from companies order by name asc

### Instruction:

Convert text to sql: What are the average profits of companies? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select avg ( profits_billion ) from companies

### Instruction:

Convert text to sql: Compute the average profits companies make. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select avg ( profits_billion ) from companies

### Instruction:

Convert text to sql: What are the maximum and minimum sales of the companies whose industries are not "Banking". | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select max ( sales_billion ) , min ( sales_billion ) from companies where industry != 'Banking'
### Instruction:

Convert text to sql: Find the maximum and minimum sales of the companies that are not in the "Banking" industry. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select max ( sales_billion ) , min ( sales_billion ) from companies where industry != 'Banking'

### Instruction:

Convert text to sql: How many different industries are the companies in? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select count ( distinct industry ) from companies

### Instruction:

Convert text to sql: Count the number of distinct company industries. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select count ( distinct industry ) from companies

### Instruction:

Convert text to sql: List the names of buildings in descending order of building height. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from buildings order by height desc

### Instruction:

Convert text to sql: What are the names of buildings sorted in descending order of building height? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from buildings order by height desc

### Instruction:

Convert text to sql: Find the stories of the building with the largest height. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select stories from buildings order by height desc limit 1
### Instruction:

Convert text to sql: What is the stories of highest building? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select stories from buildings order by height desc limit 1

### Instruction:

Convert text to sql: List the name of a building along with the name of a company whose office is in the building. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select companies.name , buildings.name from office_locations join buildings on office_locations.building_id = buildings.id join companies on office_locations.company_id = companies.id

### Instruction:

Convert text to sql: For each company, return the company name and the name of the building its office is located in. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select companies.name , buildings.name from office_locations join buildings on office_locations.building_id = buildings.id join companies on office_locations.company_id = companies.id

### Instruction:

Convert text to sql: Show the names of the buildings that have more than one company offices. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select buildings.name from office_locations join buildings on office_locations.building_id = buildings.id join companies on office_locations.company_id = companies.id group by office_locations.building_id having count ( * ) > 1
### Instruction:

Convert text to sql: Which buildings have more than one company offices? Give me the building names. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select buildings.name from office_locations join buildings on office_locations.building_id = buildings.id join companies on office_locations.company_id = companies.id group by office_locations.building_id having count ( * ) > 1

### Instruction:

Convert text to sql: Show the name of the building that has the most company offices. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select buildings.name from office_locations join buildings on office_locations.building_id = buildings.id join companies on office_locations.company_id = companies.id group by office_locations.building_id order by count ( * ) desc limit 1

### Instruction:

Convert text to sql: Which building has the largest number of company offices? Give me the building name. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select buildings.name from office_locations join buildings on office_locations.building_id = buildings.id join companies on office_locations.company_id = companies.id group by office_locations.building_id order by count ( * ) desc limit 1

### Instruction:

Convert text to sql: Please show the names of the buildings whose status is "on-hold", in ascending order of stories. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from buildings where status = 'on-hold' order by stories asc
### Instruction:

Convert text to sql: Find the names of the buildings in "on-hold" status, and sort them in ascending order of building stories. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from buildings where status = 'on-hold' order by stories asc

### Instruction:

Convert text to sql: Please show each industry and the corresponding number of companies in that industry. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry , count ( * ) from companies group by industry

### Instruction:

Convert text to sql: Whah are the name of each industry and the number of companies in that industry? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry , count ( * ) from companies group by industry

### Instruction:

Convert text to sql: Please show the industries of companies in descending order of the number of companies. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry from companies group by industry order by count ( * ) desc

### Instruction:

Convert text to sql: Sort all the industries in descending order of the count of companies in each industry | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry from companies group by industry order by count ( * ) desc
### Instruction:

Convert text to sql: List the industry shared by the most companies. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry from companies group by industry order by count ( * ) desc limit 1

### Instruction:

Convert text to sql: Which industry has the most companies? | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry from companies group by industry order by count ( * ) desc limit 1

### Instruction:

Convert text to sql: List the names of buildings that have no company office. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from buildings where id not in ( select building_id from office_locations )

### Instruction:

Convert text to sql: Which buildings do not have any company office? Give me the building names. | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select name from buildings where id not in ( select building_id from office_locations )

### Instruction:

Convert text to sql: Show the industries shared by companies whose headquarters are "USA" and companies whose headquarters are "China". | buildings : id , name , city , height , stories , status | companies : id , name , headquarters , industry , sales_billion , profits_billion , assets_billion , market_value_billion | office_locations : building_id , company_id , move_in_year | office_locations.company_id = companies.id | office_locations.building_id = buildings.id | 

### Response:

select industry from companies where headquarters = 'USA' intersect select industry from companies where headquarters = 'China'