Converting factors to numeric values in R

Question

I have factors in R that are salary ranges of the form $100,001 - $150,000, over $150,000, $25,000, etc. and would like to convert these to numeric values (e.g. converting the factor $100,001 - $150,000 to the integer 125000).

Similarly I have educational categories such as High School Diploma, Current Undergraduate, PhD, etc. that I would like to assign numbers to (e.g., giving PhD a higher value than High School Diploma).

How do I do this, given the dataframe containing these values?

Answer 1

For converting the currency

# data
df <- data.frame(sal = c("$100,001 - $150,000" , "over $150,000" , 
    "$25,000"), educ = c("High School Diploma", "Current Undergraduate",
   "PhD"),stringsAsFactors=FALSE)

 # Remove comma and dollar sign
temp <- gsub("[,$]","", df$sal)

# remove text
temp <- gsub("[[:alpha:]]","", temp)

# get average over range
df$ave.sal <- sapply(strsplit(temp , "-") , function(i) mean(as.numeric(i)))

For your education levels - if you want it numeric

df$educ.f <- as.numeric(factor(df$educ , levels=c("High School Diploma" ,
          "Current Undergraduate", "PhD")))


df
#                  sal                  educ  ave.sal educ.f
# 1 $100,001 - $150,000   High School Diploma 125000.5      1
# 2       over $150,000 Current Undergraduate 150000.0      2
# 3             $25,000                   PhD  25000.0      3

EDIT

Having missing / NA values should not matter

# Data that includes missing values

df <- data.frame(sal = c("$100,001 - $150,000" , "over $150,000" , 
                 "$25,000" , NA), educ = c(NA, "High School Diploma", 
"Current Undergraduate", "PhD"),stringsAsFactors=FALSE)

Rerun the above commands to get

df
 #                 sal                  educ  ave.sal educ.f
# 1 $100,001 - $150,000                  <NA> 125000.5     NA
# 2       over $150,000   High School Diploma 150000.0      1
# 3             $25,000 Current Undergraduate  25000.0      2
# 4                <NA>                   PhD       NA      3

Answer 2

You could use the recode function in the car package.

For example:

library(car)
df$salary <- recode(df$salary, 
    "'$100,001 - $150,000'=125000;'$150,000'=150000")

For more information on how to use this function see the help file.

Answer 3

I'd just make a vector of values that map to the levels of your factor and map them in. The code below is a much less elegant solution than I'd have liked because I can't figure out how to do the indexing with a vector, but nonetheless this will do the job if your data's not overwhelmingly large. Say we want to map the factor elements of fact to the numbers in vals:

fact<-as.factor(c("a","b","c"))
vals<-c(1,2,3)

#for example:
vals[levels(fact)=="b"]
# gives: [1] 2

#now make an example data frame:
sample(1:3,10,replace=T)
data<-data.frame(fact[sample(1:3,10,replace=T)])
names(data)<-c("myvar")

#our vlookup function:
vlookup<-function(fact,vals,x) {
    #probably should do an error checking to make sure fact 
    #   and vals are the same length

    out<-rep(vals[1],length(x)) 
    for (i in 1:length(x)) {
        out[i]<-vals[levels(fact)==x[i]]
    }
    return(out)
}

#test it:
data$myvarNumeric<-vlookup(fact,vals,data$myvar)

This should work for what you're describing.