R is the conditional amount in the data frame depending on the word in the column

Question

I have a data frame containing words and numerical entries. I want to summarize all entries for which the string entry in the word is now identical.

District name Population Child birth rate A 30,000 .7 A 20,000 .5 B 10,000 .09 B 15,000 .6 C 80,000 .007 

I want to summarize the demographic and child birth rates at the district level. I tried using lapply and sum, but I can't figure it out.

Result for dput (head (mydata):

 structure(list(District = structure(c(5L, 5L, 5L, 5L, 5L, 5L), .Label = c("Charlottenburg-Wilmersdorf", "Friedrichshain-Kreuzberg", "Lichtenberg", "Marzahn-Hellersdorf", "Mitte", "Neukoelln", "Pankow", "Reinickendorf", "Spandau", "Steglitz-Zehlendorf", "Tempelhof-Schoeneberg", "Treptow-Koepenick"), class = "factor"), Population = c(81205L, 70911L, 5629L, 12328L, 78290L, 84789L ), Overall.crime = c(27864L, 13181L, 943L, 4515L, 15673L, 16350L), Robbery = c(315L, 195L, 20L, 79L, 232L, 261L), Mugging = c(183L, 81L, 9L, 54L, 111L, 118L), Assault = c(2016L, 1046L, 51L, 468L, 1679L, 1718L), Molestation.Stalking = c(480L, 429L, 16L, 114L, 567L, 601L), Theft = c(13587L, 4961L, 396L, 2019L, 6725L, 6954L), Car.Theft = c(185L, 149L, 10L, 28L, 159L, 159L), Bycicle.Theft = c(1444L, 561L, 95L, 123L, 588L, 595L ), Burglary = c(557L, 297L, 37L, 87L, 397L, 528L), Arson = c(36L, 51L, 7L, 15L, 28L, 56L), Property.Damage = c(2113L, 871L, 64L, 260L, 1257L, 1172L), Drug.Offenses = c(781L, 538L, 24L, 87L, 604L, 492L)), .Names = c("District", "Population", "Overall.crime", "Robbery", "Mugging", "Assault", "Molestation.Stalking", "Theft", "Car.Theft", "Bycicle.Theft", "Burglary", "Arson", "Property.Damage", "Drug.Offenses"), row.names = c(NA, 6L), class = "data.frame") 

I spared you all these German names before, but I think it was stupid, because the problem is in the data ...

Using ddply gives me the following error:

 Error in df$Population : object of type 'closure' is not subsettable 

Thanks for any help!

Answer 1

Using the data that you originally posted, did you want to do this?

 df <- read.table( text = "District_name Population Child_birth_rate A 30000 .7 A 20000 .5 B 10000 .09 B 15000 .6 C 80000 .007" , h = TRUE ) aggregate( cbind( Population , Child_birth_rate ) ~ District_name , data = df , sum ) # District_name Population Child_birth_rate #1 A 50000 1.200 #2 B 25000 0.690 #3 C 80000 0.007 

Is it good to summarize the birth rate?

Using your actual data, it would be more convenient to use ddply from plyr for plyr -style aggregation (but you want to use sum and mean for two different columns):

 require( plyr ) ddply( mydata , "District" , function(df) c( "Pop" = sum( df$Population), "Robbery" = mean( df$Robbery ) ) ) # District Pop Crime #1 Mitte 333152 183.6667