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mondial_geo

Which Asian country gave its agricultural sector the largest share of its gross domestic product?

Gross domestic product = GDP; Largest share of GDP in agricultural sector was mentioned in economy.Agriculture

SELECT T2.Country FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T2.Country = T3.Code INNER JOIN economy AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Asia' ORDER BY T4.Agriculture DESC LIMIT 1

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

What form of governance does the least prosperous nation in the world have?

Nation and country are synonyms; Form of governance was mentioned in politics.Government; Least prosperous means lowest GDP

SELECT T3.Government FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country INNER JOIN politics AS T3 ON T3.Country = T2.Country WHERE T2.GDP IS NOT NULL ORDER BY T2.GDP ASC LIMIT 1

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

What year saw the greatest number of organizations created on the European continent?

SELECT STRFTIME('%Y', T4.Established) FROM continent AS T1 INNER JOIN encompasses AS T2 ON T1.Name = T2.Continent INNER JOIN country AS T3 ON T2.Country = T3.Code INNER JOIN organization AS T4 ON T4.Country = T3.Code WHERE T1.Name = 'Europe' GROUP BY STRFTIME('%Y', T4.Established) ORDER BY COUNT(T4.Name) DESC LIMIT 1

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

What other country does the most populated nation in the world share a border with and how long is the border between the two nations?

Nation and country are synonyms

SELECT T2.Country2, T2.Length FROM country AS T1 INNER JOIN borders AS T2 ON T1.Code = T2.Country1 INNER JOIN country AS T3 ON T3.Code = T2.Country2 WHERE T1.Name = ( SELECT Name FROM country ORDER BY Population DESC LIMIT 1 )

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

What is the population density of the nation whose capital city is in the Distrito Federal province, and what portion of its gross domestic product is devoted to its industries?

ation and country are synonyms; Gross domestic product = GDP; Portion of GDP devoted to industries appears in economy.Industry; Population Density = Population / Area

SELECT T1.Population / T1.Area, T2.Industry FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Province = 'Distrito Federal'

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

Lists all governments with a parliamentary democracy that achieved their independence between 01/01/1950 and 12/31/1999.

Inhabitants, synonymous with population

SELECT * FROM politics WHERE STRFTIME('%Y', Independence) BETWEEN '1950' AND '1999' AND Government = 'parliamentary democracy'

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

What percentage of countries became independent during the year 1960?

Percentage = count(countries independent 1960) / total num of countries

SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Independence) = '1960' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(Country) FROM politics

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

List all deserts that are not between latitudes 30 and 40.

SELECT Name FROM desert WHERE Latitude < 30 OR Latitude > 40

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

Indicate the coordinates of all the deserts whose area is in more than one country.

coordinates consists of Latitude, Longitude

SELECT T1.Latitude, T1.Longitude FROM desert AS T1 INNER JOIN geo_desert AS T2 ON T1.Name = T2.Desert GROUP BY T1.Name, T1.Latitude, T1.Longitude HAVING COUNT(T1.Name) > 1

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

mondial_geo

What is the provincial capital of the province with a population of less than 80,000 that has the highest average population per area?

Average population per area = population / area

SELECT CapProv FROM province WHERE Population < 80000 ORDER BY Population / Area DESC LIMIT 1

database name:db_id mondial_geo borders table borders Cols: Country1 dtype text, Country2 dtype text, Length dtype real, city table city Cols: Name dtype text, Country dtype text, Province dtype text, Population dtype integer, Longitude dtype real, Latitude dtype real, continent table continent Cols: Name dtype text, Area dtype real, country table country Cols: Name dtype text, Code dtype text, Capital dtype text, Province dtype text, Area dtype real, Population dtype integer, desert table desert Cols: Name dtype text, Area dtype real, Longitude dtype real, Latitude dtype real, economy table economy Cols: Country dtype text, gross domestic product dtype real, Agriculture dtype real, Service dtype real, Industry dtype real, Inflation dtype real, encompasses table encompasses Cols: Country dtype text, Continent dtype text, Percentage dtype real, ethnicGroup table ethnicGroup Cols: Country dtype text, Name dtype text, Percentage dtype real, geo_desert table geo_desert Cols: Desert dtype text, Country dtype text, Province dtype text, geo_estuary table geo_estuary Cols: River dtype text, Country dtype text, Province dtype text, geo_island table geo_island Cols: Island dtype text, Country dtype text, Province dtype text, geo_lake table geo_lake Cols: Lake dtype text, Country dtype text, Province dtype text, geo_mountain table geo_mountain Cols: Mountain dtype text, Country dtype text, Province dtype text, geo_river table geo_river Cols: River dtype text, Country dtype text, Province dtype text, geo_sea table geo_sea Cols: Sea dtype text, Country dtype text, Province dtype text, geo_source table geo_source Cols: River dtype text, Country dtype text, Province dtype text, island table island Cols: Name dtype text, Islands dtype text, Area dtype real, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, islandIn table islandIn Cols: Island dtype text, Sea dtype text, Lake dtype text, River dtype text, isMember table isMember Cols: Country dtype text, Organization dtype text, Type dtype text, lake table lake Cols: Name dtype text, Area dtype real, Depth dtype real, Altitude dtype real, Type dtype text, River dtype text, Longitude dtype real, Latitude dtype real, language table language Cols: Country dtype text, Name dtype text, Percentage dtype real, located table located Cols: City dtype text, Province dtype text, Country dtype text, River dtype text, Lake dtype text, Sea dtype text, locatedOn table locatedOn Cols: City dtype text, Province dtype text, Country dtype text, Island dtype text, mergeswith table mergeswith Cols: Sea1 dtype text, Sea2 dtype text, mountain table mountain Cols: Name dtype text, Mountains dtype text, Height dtype real, Type dtype text, Longitude dtype real, Latitude dtype real, mountainonisland table mountainonisland Cols: Mountain dtype text, Island dtype text, organization table organization Cols: Abbreviation dtype text, Name dtype text, City dtype text, Country dtype text, Province dtype text, Established dtype date, politics table politics Cols: Country dtype text, Independence dtype date, Dependent dtype text, Government dtype text, population table population Cols: Country dtype text, population growth dtype real, infant mortality dtype real, province table province Cols: Name dtype text, Country dtype text, Population dtype integer, Area dtype real, Capital dtype text, capital province dtype text, religion table religion Cols: Country dtype text, Name dtype text, Percentage dtype real, river table river Cols: Name dtype text, River dtype text, Lake dtype text, Sea dtype text, Length dtype real, SourceLongitude dtype real, SourceLatitude dtype real, Mountains dtype text, SourceAltitude dtype real, EstuaryLongitude dtype real, EstuaryLatitude dtype real, sea table sea Cols: Name dtype text, Depth dtype real, target table target Cols: Country dtype text, Target dtype text,

software_company

How many customers have never married?

MARITAL_STATUS = 'Never-married';

SELECT COUNT(ID) FROM Customers WHERE MARITAL_STATUS = 'Never-married'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among all the customers, how many of them are teenagers?

teenager is a person aged between 13 and 19 years;

SELECT COUNT(ID) FROM Customers WHERE age >= 13 AND age <= 19

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Please list the occupations of the customers with an education level of 11.

education level of 11 refers to EDUCATIONNUM = 11;

SELECT DISTINCT OCCUPATION FROM Customers WHERE EDUCATIONNUM = 11

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Of the first 60,000 customers' responses to the incentive mailing sent by the marketing department, how many of them are considered a true response?

RESPONSE = 'true';

SELECT COUNT(REFID) custmoer_number FROM Mailings1_2 WHERE RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the customers over 30, how many of them are Machine-op-inspcts?

over 30 refers to age > 30; OCCUPATION = 'Machine-op-inspct';

SELECT COUNT(ID) FROM Customers WHERE OCCUPATION = 'Machine-op-inspct' AND age > 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

How many female customers have an education level of over 11?

education level of 11 refers to EDUCATIONNUM = 11; SEX = 'Female';

SELECT COUNT(ID) FROM Customers WHERE EDUCATIONNUM > 11 AND SEX = 'Female'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are female?

RESPONSE = 'true'; SEX = 'Female';

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.SEX = 'Female' AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Please list the occupations of the customers over 40 and have sent a true response to the incentive mailing sent by the marketing department.

over 40 refers to age > 40; RESPONSE = 'true';

SELECT DISTINCT T1.OCCUPATION FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.age > 40 AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the male customers, how many of them come from a place with over 30,000 inhabitants?

SEX = 'Male', over 30,000 inhabitants refer to NHABITANTS_K > 30; place refers to GEOID;

SELECT COUNT(T1.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Male' AND T2.INHABITANTS_K > 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

How many customers are from the place with the highest average income per month?

place with the highest average income per month refers to GEOID where MAX(INCOME_K);

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INCOME_K DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the customers from a place with more than 20,000 and less than 30,000 inhabitants, how many of them are Machine-op-inspcts?

place with more than 20,000 and less than 30,000 inhabitants refers to GEOID where INHABITANTS_K BETWEEN 20 AND 30; OCCUPATION = 'Machine-op-inspct';

SELECT COUNT(T1.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Machine-op-inspct' AND T2.INHABITANTS_K > 20 AND T2.INHABITANTS_K < 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Which customer come from a place with more inhabitants, customer no.0 or customer no.1?

place with more inhabitants refers to GEOID where ID = 0 OR ID = 1 and MAX(NHABITANTS_K);

SELECT T1.ID FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.ID = 0 OR T1.ID = 1 ORDER BY INHABITANTS_K DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are from a place with more than 30,000 inhabitants?

RESPONSE = 'true'; place with more than 30,000 inhabitants refers to GEOID where INHABITANTS_K > 30;

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T3.INHABITANTS_K > 30 AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are divorced males?

RESPONSE = 'true'; SEX = 'Male'; MARITAL_STATUS = 'Divorced';

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.SEX = 'Male' AND T1.MARITAL_STATUS = 'Divorced' AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

How many of the first 60,000 customers from the place with the highest average income per month have sent a true response to the incentive mailing sent by the marketing department?

place with the highest average income per month refers to GEOID where MAX(INCOME_K); RESPONSE = 'true';

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T2.RESPONSE = 'true' ORDER BY T3.INCOME_K DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the number of inhabitants of the place the most customers are from?

the most customers are from refers to GEOID where MAX(COUNT(ID)); number of inhabitants refers to INHABITANTS_K;

SELECT DISTINCT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INHABITANTS_K DESC

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the customers who come from the place with 25746 inhabitants, how many of them are male?

place with 44114 inhabitants refers to GEOID where INHABITANTS_K = 44.114; SEX = 'Male';

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INHABITANTS_K = 25.746 AND T1.SEX = 'Male'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Of the first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department, how many of them are teenagers?

RESPONSE = 'true'; teenagers are people aged between 13 and 19 years;

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.age >= 13 AND T1.age <= 19 AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the average education level of customers from the place with the highest average income per month?

place with the highest average income per month refers to GEOID where MAX(INCOME_K); average education level refers to AVG(EDUCATIONNUM);

SELECT AVG(T1.EDUCATIONNUM) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T2.INCOME_K DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the average age of first 60,000 customers who sent a true response to the incentive mailing sent by the marketing department?

RESPONSE = 'true'; AVG(age);

SELECT AVG(T1.age) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

How many of the customers are male?

SEX = 'Male';

SELECT COUNT(ID) FROM Customers WHERE SEX = 'Male'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List down the customer's geographic identifier who are handlers or cleaners.

geographic identifier refers to GEOID; OCCUPATION = 'Handlers-cleaners';

SELECT GEOID FROM Customers WHERE OCCUPATION = 'Handlers-cleaners'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the total number of customers with an age below 30?

age below 30 refers to age < 30;

SELECT COUNT(ID) FROM Customers WHERE age < 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List down the geographic identifier with an income that ranges from 2100 to 2500.

geographic identifier with an income that ranges from 2100 to 2500 refers to GEOID where INCOME_K BETWEEN 2100 AND 2500;

SELECT GEOID FROM Demog WHERE INCOME_K >= 2100 AND INCOME_K <= 2500

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In geographic identifier from 20 to 50, how many of them has a number of inhabitants below 20?

geographic identifier from 20 to 50 refers to GEOID BETWEEN 20 AND 50; number of inhabitants below 20 refers to INHABITANTS_K < 20;

SELECT COUNT(GEOID) FROM Demog WHERE INHABITANTS_K < 20 AND GEOID >= 20 AND GEOID <= 50

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the number of inhabitants and income of geographic identifier 239?

geographic identifier 239 refers to GEOID = 239; number of inhabitants refers to INHABITANTS_K; income refers to INCOME_K;

SELECT INHABITANTS_K FROM Demog WHERE GEOID = 239

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Give the level of education and occupation of customers ages from 20 to 35 with an income K of 2000 and below.

customers ages from 20 to 35 refer to ID where age BETWEEN 20 AND 35; income K of 2000 and below refers to INCOME_K < 2000; level of education refers to EDUCATIONNUM;

SELECT T1.EDUCATIONNUM, T1.OCCUPATION FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INCOME_K < 2000 AND T1.age >= 20 AND T1.age <= 35

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List down the number of inhabitants of customers with a divorced marital status and older than 50 years old.

number of inhabitants refers to INHABITANTS_K; older than 50 years old refers to age < 50; MARITAL_STATUS = 'Divorced;

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.MARITAL_STATUS = 'Divorced' AND T1.age < 50

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the geographic identifier and income of the oldest customer?

the oldest customer refers to MAX(age); geographic identifier refers to GEOID; income refers to INCOME_K;

SELECT T1.GEOID, T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID ORDER BY T1.age DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the male customers with an level of education of 4 and below, list their income K.

male customers with an level of education of 4 and below refer to SEX = 'Male' where EDUCATIONNUM < 4;

SELECT INCOME_K FROM Demog WHERE GEOID IN ( SELECT GEOID FROM Customers WHERE EDUCATIONNUM < 4 AND SEX = 'Male' )

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the occupation and income of male customers with an level of education of 4 to 6.

male customers with an level of education of 4 to 6 refer to SEX = 'Male' where EDUCATIONNUM BETWEEN 4 AND 6; income refers to INCOME_K;

SELECT T1.OCCUPATION, T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.EDUCATIONNUM >= 4 AND T1.EDUCATIONNUM <= 6 AND T1.SEX = 'Male'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In widowed male customers ages from 40 to 60, how many of them has an income ranges from 3000 and above?

widowed male customers ages from 40 to 60 refer to SEX = 'Male' where age BETWEEN 40 AND 60 and MARITAL_STATUS = 'Widowed'; income ranges from 3000 and above refers to INCOME_K BETWEEN 2000 AND 3000;

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.age >= 40 AND T1.age <= 60 AND T1.MARITAL_STATUS = 'Widowed' AND T1.SEX = 'Male' AND T2.INCOME_K >= 2000 AND T2.INCOME_K <= 3000

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the occupation of customers within number of inhabitants ranges of 30 to 40?

number of inhabitants ranges of 30 to 40 refers to INHABITANTS_K BETWEEN 30 AND 40;

SELECT DISTINCT T1.OCCUPATION FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INHABITANTS_K >= 30 AND T2.INHABITANTS_K <= 40

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the widowed female customers, give the income of those who has an level of education of 5 and below.

widowed female customers refer to SEX = 'Female' where MARITAL_STATUS = 'Widowed'; level of education of 5 and below refers to EDUCATIONNUM ≤ 5;

SELECT INCOME_K FROM Demog WHERE GEOID IN ( SELECT GEOID FROM Customers WHERE EDUCATIONNUM < 5 AND SEX = 'Female' AND MARITAL_STATUS = 'Widowed' )

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the marital status of customers within the age of 40 to 60 that has the highest income among the group.

age of 40 to 60 refers to age BETWEEN 40 AND 60; the highest income refers to MAX(INCOME_K);

SELECT T1.MARITAL_STATUS FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.age >= 40 AND T1.age <= 60 ORDER BY T2.INCOME_K DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the number of inhabitants of male customers ages from 20 to 30 years old who are farming or fishing?

male customers ages from 20 to 30 years old refer to SEX = 'Male' where age BETWEEN 20 AND 30; farming or fishing refers to OCCUPATION; number of inhabitants refers to INHABITANTS_K;

SELECT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Farming-fishing' AND T1.SEX = 'Male' AND T1.age >= 20 AND T1.age <= 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the customers with a marital status of married-civ-spouse, list the number of inhabitants and age of those who are machine-op-inspct.

OCCUPATION = 'Machine-op-inspct'; number of inhabitants refers to INHABITANTS_K;

SELECT T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Farming-fishing' AND T1.SEX = 'Male' AND T1.age >= 20 AND T1.age <= 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In female customers ages from 50 to 60, how many of them has an number of inhabitants ranges from 19 to 24?

female customers ages from 50 to 60 refer to SEX = 'Female' where age BETWEEN 50 AND 60; number of inhabitants ranges from 19 to 24 refers to INHABITANTS_K BETWEEN 19 AND 24;

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.age >= 50 AND T1.age <= 60 AND T2.INHABITANTS_K >= 19 AND T2.INHABITANTS_K <= 24

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the income and number of inhabitants of customers with an age greater than the 80% of average age of all customers?

age greater than the 80% of average age refers to age > (AVG(age) * 0.8); income refers to INCOME_K; number of inhabitants refers to INHABITANTS_K;

SELECT T2.INCOME_K, T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID GROUP BY T2.INCOME_K, T2.INHABITANTS_K HAVING T1.age > 0.8 * AVG(T1.age)

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In customers with marital status of never married, what is the percentage of customers with income of 2500 and above?

DIVIDE(COUNT(INCOME_K ≥ 2500 where MARITAL_STATUS = 'Never-married'), COUNT(INCOME_K where MARITAL_STATUS = 'Never-married')) as percentage;

SELECT CAST(SUM(CASE WHEN T2.INCOME_K > 2500 THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.MARITAL_STATUS = 'Never-married'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Find and list the id and geographic ID of the elderly customers with an education level below 3.

elderly customers with an education level below 3 refer to age > 65 where EDUCATIONNUM < 3; geographic ID refers to GEOID;

SELECT ID, GEOID FROM Customers WHERE EDUCATIONNUM < 3 AND age > 65

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the geographic id of places where the income is above average.

geographic ID refers to GEOID; income is above average refers to INCOME_K > DIVIDE(SUM(INCOME_K), COUNT(GEOID));

SELECT AVG(INCOME_K) FROM Demog

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Calculate the number of customers who did not respond in February of 2007.

did not respond refers to RESPONSE = 'false'; February of 2007 refers to REF_DATE BETWEEN '2007-02-01 12:00:00.0'AND '2007-02-28 12:00:00.0';

SELECT COUNT(REFID) custmoer_number FROM Mailings1_2 WHERE RESPONSE = 'false' AND REF_DATE BETWEEN '2007-02-01' AND '2007-02-28'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

How many teenagers are working as Machine-op-inspct?

teenager is a person aged between 13 and 19 years; OCCUPATION = 'Machine-op-inspct';

SELECT COUNT(ID) teenager_number FROM Customers WHERE OCCUPATION = 'Machine-op-inspct' AND age >= 13 AND age <= 19

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Of customers who provide other services, how many are from places where inhabitants are more than 20000?

OCCUPATION = 'Other-service'; inhabitants are more than 20000 refer to INHABITANTS_K > 20;

SELECT COUNT(T2.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.OCCUPATION = 'Other-service' AND T2.INHABITANTS_K > 20

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the male customer in their twenties, how many are from places where the average income is more than 3000?

male customer in their twenties refer to SEX = 'Male' where age BETWEEN 20 AND 29; average income is more than 3000 refers to INCOME_K > 3000;

SELECT COUNT(T2.GEOID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Male' AND T2.INCOME_K > 3000 AND T1.age >= 20 AND T1.age <= 29

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What percentage of elderly customers who are never married in the place with geographic ID 24?

elderly customers refer to age > 65; DIVIDE(COUNT(ID where age > 65, MARITAL_STATUS = 'never married' and GEOID = 24), COUNT(ID where GEOID = 24)) as percentage;

SELECT CAST(SUM(CASE WHEN T1.MARITAL_STATUS = 'never married' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.GEOID = 24

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the customers with an average income per inhabitant above 3000, what percentage are in their eighties?

average income per inhabitant above 3000 refers to INCOME_K > 3000; eighties refer to age BETWEEN 80 AND 89; DIVIDE(COUNT(INCOME_K > 3000 and age BETWEEN 80 AND 89), COUNT(INCOME_K > 3000 )) as percentage;

SELECT CAST(SUM(CASE WHEN T1.age BETWEEN 80 AND 89 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INCOME_K > 3000

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

How many of the customer's reference ID that has a TRUE response?

reference ID refers to REFID;

SELECT COUNT(REFID) FROM Mailings1_2 WHERE RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List down the customer's reference ID with true response.

reference ID refers to REFID;

SELECT REFID FROM Mailings1_2 WHERE RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the total number of widowed customers with an age below 50?

widowed customers with an age below 50 refer to MARITAL_STATUS = 'Widowed' where age < 50;

SELECT COUNT(ID) FROM Customers WHERE MARITAL_STATUS = 'Widowed' AND age < 50

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List down the geographic identifier with an number of inhabitants less than 30.

geographic identifier with an number of inhabitants less than 30 refers to GEOID where INHABITANTS_K < 30;

SELECT GEOID FROM Demog WHERE INHABITANTS_K < 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In geographic identifier from 10 to 30, how many of them has an income below 2000?

GEOID BETWEEN 10 AND 30; INCOME_K < 2000;

SELECT COUNT(GEOID) FROM Demog WHERE INCOME_K < 2000 AND GEOID >= 10 AND GEOID <= 30

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the marital status of the customer ages 62 with an level of education of 7?

customer ages 62 with an level of education of 7 refer age = 62 where EDUCATIONNUM = 7;

SELECT DISTINCT MARITAL_STATUS FROM Customers WHERE EDUCATIONNUM = 7 AND age = 62

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List down the number of inhabitants of customers with a widowed marital status and false response .

number of inhabitants refers to INHABITANTS_K; RESPONSE = 'false';

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.MARITAL_STATUS = 'Widowed' AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the response and number of inhabitants of the oldest female customer?

number of inhabitants refers to INHABITANTS_K; oldest female customer refers to SEX = 'Female' where MAX(age);

SELECT T2.RESPONSE, T3.INHABITANTS_K FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.SEX = 'Female' ORDER BY T1.age DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the female customers with an level of education of 3 and below, list their income.

female customers with level of education of 3 and below refer to SEX = 'Female' where EDUCATIONNUM ≤ 3; income refers to INCOME_K;

SELECT INCOME_K FROM Demog WHERE GEOID IN ( SELECT GEOID FROM Customers WHERE EDUCATIONNUM < 3 AND SEX = 'Female' )

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the level of education and income of customers ages from 30 to 55 with a true response.

ages from 30 to 55 refer to age BETWEEN 30 AND 55; RESPONSE = 'true'; income refers to INCOME_K; education level refers to EDUCATIONNUM;

SELECT T1.EDUCATIONNUM, T3.INCOME_K FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.age >= 30 AND T1.age <= 55 AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In male customers ages from 30 to 50, how many of them has an income ranges from 2000 to 2300?

male customers ages from 30 to 50 refer to SEX = 'Male' where age BETWEEN 30 AND 50; income ranges from 2000 to 2300 refers to INCOME_K BETWEEN 2000 AND 3000;

SELECT COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Male' AND T1.age >= 30 AND T1.age <= 50 AND T2.INCOME_K >= 2000 AND T2.INCOME_K <= 2300

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the educationnum and response of customers within the age of 20 to 30 that has the highest number of inhabitants among the group.

age of 20 to 30 refers to age BETWEEN 20 AND 30; the highest number of inhabitants refers to MAX(INHABITANTS_K);

SELECT T1.EDUCATIONNUM, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.age >= 20 AND T1.age <= 30 ORDER BY T3.INHABITANTS_K DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the income of female customers ages from 30 to 55 years old and has an occupation of machine-op-inspct?

female customers ages from 30 to 55 years old refer to SEX = 'Female' where age BETWEEN 30 AND 55; income refers to INCOME_K;

SELECT T2.INCOME_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.age >= 30 AND T1.age <= 55 AND T1.OCCUPATION = 'Machine-op-inspct'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the marital status and response of female customers with an level of education of 8 and above.

female customers with an level of education of 8 and above refer to SEX = 'Female' where EDUCATIONNUM ≥ 8;

SELECT DISTINCT T1.MARITAL_STATUS, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.EDUCATIONNUM > 8 AND T1.SEX = 'Female'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the age of female customers within the number of inhabitants below 30?

female customers within the number of inhabitants below 30 refer to SEX = 'Female' where INHABITANTS_K < 30;

SELECT age FROM Customers WHERE GEOID IN ( SELECT GEOID FROM Demog WHERE INHABITANTS_K < 30 ) AND SEX = 'Female'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the divorced male customers, give the income and response of those who has an level of education of 6 and above.

divorced male customers refer to SEX = 'Male' where MARITAL_STATUS = 'Divorced';

SELECT DISTINCT T3.INCOME_K, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.EDUCATIONNUM > 6 AND T1.SEX = 'Male' AND T1.MARITAL_STATUS = 'Divorced'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the occupation and response of female customers within the number of inhabitants range of 20 to 25?

female customers within the number of inhabitants range of 20 to 25 refer to SEX = 'Female' where INHABITANTS_K BETWEEN 20 AND 25;

SELECT DISTINCT T1.OCCUPATION, T2.RESPONSE FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID INNER JOIN Demog AS T3 ON T1.GEOID = T3.GEOID WHERE T1.SEX = 'Female' AND T3.INHABITANTS_K >= 20 AND T3.INHABITANTS_K <= 25

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

In male customers with an occupation handlers or cleaners, what is the percentage of customers with a true response?

DIVIDE(COUNT(OCCUPATION = 'Handlers-cleaners', SEX = 'Male' and RESPONSE = 'true'), COUNT(OCCUPATION = 'Handlers-cleaners' and SEX = 'Male')) as percentage;

SELECT CAST(SUM(CASE WHEN T2.RESPONSE = 'true' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(T2.REFID) FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T1.OCCUPATION = 'Handlers-cleaners' AND T1.SEX = 'Male'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

List the income and number of inhabitants of customers with a reference ID greater than the 50% of average of number of false response?

reference ID greater than the 50% of average of number of false response refers to REFID > DIVIDE(MULTIPLY(0.5, COUNT(RESPONSE = 'false')), COUNT(RESPONSE)); income refers to INCOME_K; number of inhabitants refer to INHABITANTS_K;

SELECT T2.INCOME_K, T2.INHABITANTS_K FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID INNER JOIN Mailings1_2 AS T3 ON T1.ID = T3.REFID WHERE T3.REFID > ( SELECT 0.5 * COUNT(CASE WHEN RESPONSE = 'false' THEN 1 ELSE NULL END) / COUNT(RESPONSE) FROM Mailings1_2 )

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the ratio of male and female among the age of teenager when the education is above 10?

ratio = DIVIDE(COUNT(SEX = 'Male' where age BETWEEN 13 AND 19 and EDUCATIONNUM > 10),COUNT(SEX = 'Female' where age BETWEEN 13 AND 19 and EDUCATIONNUM > 10));

SELECT CAST(SUM(CASE WHEN SEX = 'Male' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN SEX = 'Female' THEN 1 ELSE 0 END) FROM Customers WHERE age BETWEEN 13 AND 19 AND EDUCATIONNUM > 10

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

What is the geographic ID and total income per year when the average income is above 3300 dollar.

total income per year refers to MULTIPLY(12, INHABITANTS_K, INCOME_K) where INCOME_K > 3300; geographic ID refers to GEOID;

SELECT GEOID, INHABITANTS_K * INCOME_K * 12 FROM Demog WHERE INCOME_K > 3300

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Point out the greater one between the number of actual responding and not responding to mailing.

COUNT(REFID where RESPONSE = 'true')>or<COUNT(REFID where RESPONSE = 'false');

SELECT RESPONSE FROM Mailings1_2 GROUP BY RESPONSE ORDER BY COUNT(RESPONSE) DESC LIMIT 1

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Find out the yearly income of geographic ID when the customer is female and occupation as sales.

yearly income of geographic ID refers to GEOID where MULTIPLY(INHABITANTS_K, INCOME_K, 12); SEX = 'Female';

SELECT T2.INHABITANTS_K * T2.INCOME_K * 12 FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.SEX = 'Female' AND T1.OCCUPATION = 'Sales'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the geographic ID which has 33.658K of inhabitants, describe the education, occupation and age of female widow.

geographic ID which has 33.658K of inhabitants refers to GEOID where INHABITANTS_K = 33.658; education refers to EDUCATIONNUM; female widow refers to SEX = 'Female' where MARITAL_STATUS = 'Widowed';

SELECT T1.EDUCATIONNUM, T1.OCCUPATION, T1.age FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INHABITANTS_K = 33.658 AND T1.SEX = 'Female' AND T1.MARITAL_STATUS = 'Widowed'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Find the response status to customer whose geographic ID of 134.

GEOID = 134;

SELECT T2.RESPONSE FROM Customers AS T1 INNER JOIN mailings3 AS T2 ON T1.ID = T2.REFID WHERE T1.GEOID = 134

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Describe the average income per month and yearly income of the geographic ID in which customer of ID "209556" and "290135".

the average income per month refers to INCOME_K; yearly income of geographic ID refers to GEOID where MULTIPLY(INHABITANTS_K, INCOME_K, 12);

SELECT T2.INCOME_K, T2.INHABITANTS_K * T2.INCOME_K * 12 FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.ID = 209556 OR T1.ID = 290135

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

software_company

Among the reference ID of under 10 who got response by marketing department, compare their education status.

reference ID of under 10 refers to REFID < 10; got response refers to RESPONSE = 'true'; education status refers to EDUCATIONNUM;

SELECT T1.EDUCATIONNUM FROM Customers AS T1 INNER JOIN Mailings1_2 AS T2 ON T1.ID = T2.REFID WHERE T2.REFID < 10 AND T2.RESPONSE = 'true'

database name:db_id software_company Demog table Demog Cols: GEOGRAPHIC ID dtype integer, INHABITANTS (THOUSANDS) dtype real, INCOME (THOUSANDS) dtype real, A_VAR1 dtype real, A_VAR2 dtype real, A_VAR3 dtype real, A_VAR4 dtype real, A_VAR5 dtype real, A_VAR6 dtype real, A_VAR7 dtype real, A_VAR8 dtype real, A_VAR9 dtype real, A_VAR10 dtype real, A_VAR11 dtype real, A_VAR12 dtype real, A_VAR13 dtype real, A_VAR14 dtype real, A_VAR15 dtype real, A_VAR16 dtype real, A_VAR17 dtype real, A_VAR18 dtype real, mailings3 table mailings3 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Customers table Customers Cols: ID dtype integer, SEX dtype text, MARITAL STATUS dtype text, GEOGRAPHIC ID dtype integer, EDUCATION NUMBER dtype integer, OCCUPATION dtype text, age dtype integer, Mailings1_2 table Mailings1_2 Cols: REFERENCE ID dtype integer, REFERENCE DATE dtype datetime, RESPONSE dtype text, Sales table Sales Cols: EVENT ID dtype integer, REFERENCE ID dtype integer, EVENT DATE dtype datetime, AMOUNT dtype real,

chicago_crime

How many community areas are there in Central Chicago?

Central Chicago refers to side = 'Central'

SELECT COUNT(*) FROM Community_Area WHERE side = 'Central'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Which district is the community area Lincoln Square grouped into?

district refers to side; community area Lincoln Square refers to community_area_name = 'Lincoln Square'

SELECT side FROM Community_Area WHERE community_area_name = 'Lincoln Square'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Which district in Chicago has the most community areas?

district refers to side; the most community areas refers to max(count(side))

SELECT side FROM Community_Area GROUP BY side ORDER BY COUNT(side) DESC LIMIT 1

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Which community area has the least population?

community area refers to community_area_name; the least population refers to min(population)

SELECT community_area_name FROM Community_Area ORDER BY population ASC LIMIT 1

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Who is the person responsible for the crime cases in Central Chicago?

the person responsible for the crime cases refers to commander; Central Chicago refers to district_name = 'Central'

SELECT commander FROM District WHERE district_name = 'Central'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

What is the email address to contact the administrator of Central Chicago?

email address refers to email; Central Chicago refers to district_name = 'Central'

SELECT email FROM District WHERE district_name = 'Central'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

To which community area does the neighborhood Albany Park belong?

community area refers to community_area_name; the neighborhood Albany Park refers to neighborhood_name = 'Albany Park'

SELECT T2.community_area_name FROM Neighborhood AS T1 INNER JOIN Community_Area AS T2 ON T1.community_area_no = T2.community_area_no WHERE T1.neighborhood_name = 'Albany Park'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

How many neighborhoods are there in the community area of Lincoln Square?

the community area of Lincoln Square refers to community_area_name = 'Lincoln Square'

SELECT COUNT(T3.community_area_no) FROM ( SELECT T1.community_area_no FROM Community_Area AS T1 INNER JOIN Neighborhood AS T2 ON T1.community_area_no = T2.community_area_no WHERE community_area_name = 'Lincoln Square' GROUP BY T1.community_area_no ) T3

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Please list the names of all the neighborhoods in the community area with the most population.

name of neighborhood refers to neighborhood_name; the most population refers to max(population)

SELECT T1.neighborhood_name FROM Neighborhood AS T1 INNER JOIN Community_Area AS T2 ON T2.community_area_no = T2.community_area_no ORDER BY T2.population DESC LIMIT 1

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Please list the names of all the neighborhoods in Central Chicago.

name of neighborhood refers to neighborhood_name; Central Chicago refers to side = 'Central'

SELECT T2.neighborhood_name FROM Community_Area AS T1 INNER JOIN Neighborhood AS T2 ON T1.community_area_no = T2.community_area_no WHERE T1.side = 'Central'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Please list the precise location coordinates of all the crimes in Central Chicago.

location coordinates refers to latitude, longitude; Central Chicago refers to district_name = 'Central'

SELECT T2.latitude, T2.longitude FROM District AS T1 INNER JOIN Crime AS T2 ON T1.district_no = T2.district_no WHERE T1.district_name = 'Central'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

How many crimes had happened in Central Chicago?

Central Chicago refers to district_name = 'Central'

SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Among all the crimes that had happened in Central Chicago, how many of them were cases of domestic violence?

Central Chicago refers to district_name = 'Central'; case of domestic violence refers to domestic = 'TRUE'

SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central' AND T1.domestic = 'TRUE'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

Please list the case numbers of all the crimes with no arrest made in Central Chicago.

no arrest made refers to arrest = 'FALSE'; Central Chicago refers to district_name = 'Central'

SELECT COUNT(*) FROM Crime AS T1 INNER JOIN District AS T2 ON T1.district_no = T2.district_no WHERE T2.district_name = 'Central' AND T1.arrest = 'FALSE'

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,

chicago_crime

How many crimes had happened in the community area with the most population?

the most population refers to max(population)

SELECT COUNT(T2.report_no) FROM Community_Area AS T1 INNER JOIN Crime AS T2 ON T1.community_area_no = T2.community_area_no GROUP BY T1.community_area_name ORDER BY T1.population DESC LIMIT 1

database name:db_id chicago_crime Community_Area table Community_Area Cols: community area number dtype integer, community area name dtype text, side dtype text, population dtype text, District table District Cols: district number dtype integer, district name dtype text, address dtype text, zip code dtype integer, commander dtype text, email dtype text, phone dtype text, fax dtype text, tty dtype text, twitter dtype text, FBI_Code table FBI_Code Cols: fbi code number dtype text, title dtype text, description dtype text, crime against dtype text, IUCR table IUCR Cols: iucr number dtype text, primary description dtype text, secondary description dtype text, index code dtype text, Neighborhood table Neighborhood Cols: neighborhood name dtype text, community area number dtype integer, Ward table Ward Cols: ward_no dtype integer, alderman_first_name dtype text, alderman_last_name dtype text, alderman_name_suffix dtype text, ward_office_address dtype text, ward_office_zip dtype text, ward_email dtype text, ward_office_phone dtype text, ward_office_fax dtype text, city_hall_office_room dtype integer, city_hall_office_phone dtype text, city_hall_office_fax dtype text, Population dtype integer, Crime table Crime Cols: report number dtype integer, case number dtype text, date dtype text, block dtype text, Illinois Uniform Crime Reporting number dtype text, location description dtype text, arrest dtype text, domestic dtype text, beat dtype integer, district number dtype integer, ward number dtype integer, community area number dtype integer, fbi code number dtype text, latitude dtype text, longitude dtype text,