1sf/bird-sql-train-with-schema huggingface dataset:
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Which nation, with a population ranging from 60,000,000 to 99,000,000, has the greatest gross domestic product?
Evidence: GDP refers to gross domestic product; Nation and country are synonyms
SQL: SELECT T1.Name, T2.GDP FROM country AS T1 INNER JOIN economy AS T2 ON T1.Code = T2.Country WHERE T1.Population BETWEEN 60000000 AND 90000000 ORDER BY T2.GDP DESC LIMIT 1
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Which Asian country gave its agricultural sector the largest share of its gross domestic product?
Evidence: Gross domestic product = GDP; Largest share of GDP in agricultural sector was mentioned in economy.Agriculture
SQL: 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: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What form of governance does the least prosperous nation in the world have?
Evidence: Nation and country are synonyms; Form of governance was mentioned in politics.Government; Least prosperous means lowest GDP
SQL: 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: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What year saw the greatest number of organizations created on the European continent?
SQL: 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: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: 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?
Evidence: Nation and country are synonyms
SQL: 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: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: 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?
Evidence: ation and country are synonyms; Gross domestic product = GDP; Portion of GDP devoted to industries appears in economy.Industry; Population Density = Population / Area
SQL: 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: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: Lists all governments with a parliamentary democracy that achieved their independence between 01/01/1950 and 12/31/1999.
Evidence: Inhabitants, synonymous with population
SQL: SELECT * FROM politics WHERE STRFTIME('%Y', Independence) BETWEEN '1950' AND '1999' AND Government = 'parliamentary democracy'
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: What percentage of countries became independent during the year 1960?
Evidence: Percentage = count(countries independent 1960) / total num of countries
SQL: SELECT CAST(SUM(CASE WHEN STRFTIME('%Y', Independence) = '1960' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(Country) FROM politics
Database: mondial_geo
Tables: borders, city, continent, country, desert, economy, encompasses, ethnicGroup, geo_desert, geo_estuary, geo_island, geo_lake, geo_mountain, geo_river, geo_sea, geo_source, island, islandIn, isMember, lake, language, located, locatedOn, mergesWith, mountain, mountainOnIsland, organization, politics, population, province, religion, river, sea, target
Columns (table index, column name): -1, *, 0, Country1, 0, Country2, 0, Length, 1, Name, 1, Country, 1, Province, 1, Population, 1, Longitude, 1, Latitude, 2, Name, 2, Area, 3, Name, 3, Code, 3, Capital, 3, Province, 3, Area, 3, Population, 4, Name, 4, Area, 4, Longitude, 4, Latitude, 5, Country, 5, GDP, 5, Agriculture, 5, Service, 5, Industry, 5, Inflation, 6, Country, 6, Continent, 6, Percentage, 7, Country, 7, Name, 7, Percentage, 8, Desert, 8, Country, 8, Province, 9, River, 9, Country, 9, Province, 10, Island, 10, Country, 10, Province, 11, Lake, 11, Country, 11, Province, 12, Mountain, 12, Country, 12, Province, 13, River, 13, Country, 13, Province, 14, Sea, 14, Country, 14, Province, 15, River, 15, Country, 15, Province, 16, Name, 16, Islands, 16, Area, 16, Height, 16, Type, 16, Longitude, 16, Latitude, 17, Island, 17, Sea, 17, Lake, 17, River, 18, Country, 18, Organization, 18, Type, 19, Name, 19, Area, 19, Depth, 19, Altitude, 19, Type, 19, River, 19, Longitude, 19, Latitude, 20, Country, 20, Name, 20, Percentage, 21, City, 21, Province, 21, Country, 21, River, 21, Lake, 21, Sea, 22, City, 22, Province, 22, Country, 22, Island, 23, Sea1, 23, Sea2, 24, Name, 24, Mountains, 24, Height, 24, Type, 24, Longitude, 24, Latitude, 25, Mountain, 25, Island, 26, Abbreviation, 26, Name, 26, City, 26, Country, 26, Province, 26, Established, 27, Country, 27, Independence, 27, Dependent, 27, Government, 28, Country, 28, Population_Growth, 28, Infant_Mortality, 29, Name, 29, Country, 29, Population, 29, Area, 29, Capital, 29, CapProv, 30, Country, 30, Name, 30, Percentage, 31, Name, 31, River, 31, Lake, 31, Sea, 31, Length, 31, SourceLongitude, 31, SourceLatitude, 31, Mountains, 31, SourceAltitude, 31, EstuaryLongitude, 31, EstuaryLatitude, 32, Name, 32, Depth, 33, Country, 33, Target
Question: List all deserts that are not between latitudes 30 and 40.
SQL: SELECT Name FROM desert WHERE Latitude < 30 OR Latitude > 40