Median imputation using sapply

Question

I want to replace missing values in columns of a dataframe. I have written the following code

MedianImpute <- function(data=data)
     {
      for(i in 1:ncol(data))
        {        
        if(class(data[,i]) %in% c("numeric","integer"))
          {
          if(sum(is.na(data[,i])))
            {
            data[is.na(data[,i]),i] <- 
                          median(data[,i],na.rm = TRUE)
            }
          }
        }
      return(data)
      }

This returns the dataframe with the NAs replaced by the column median. I do no want to use for loop, how can I get the same result using any of the apply functions in R?

Answer 1

You could use apply to apply a function across all columns

dat<-data.frame(c1=c(1,2,3,NA),c2=c(10, NA, 20, 30))
apply(dat, 2, function(x) ifelse(is.na(x), median(x, na.rm=T), x))

slightly faster

imputeMedianv3<-function(x) apply(x, 2, function(x){x[is.na(x)]<-median(x, na.rm=T); x})

I'm sure if what you're looking for is performance, someone will provide a data table solution (unfortunately I am not familiar with that package so can't do myself).