Looping through or lapply on list of dataframes in R

Question

I do have some grasp on how to use lapply to, say, change the names of variables in several dataframes in a list. However, I am looking to carry out a slightly (but only slightly) more complicated operation.

More specifically, I am looking to calculate the mean growth rates for several entities. The growth rate have already been calculated, so I just need to perfor the following operations on all dataframes

for (i in 1:13) {
  growth.type[,i] <- tapply(growth[,8+i] , growth$type, mean, na.rm = TRUE) 
}

This creates a new dataframe ( growth.type ) that includes the mean of all several hundred growth rates in the original dataframe ( growth ), by type .

Now, I would like to do this to several dataframes (like growth ) and put them into new dataframes (like growth.type ).

I hope this makes sense.

Answer 1

Put all data.frames you wish to process in a list

xy <- list(growth1, growth2, growth3, ...)

and then apply a custom function to this xy object.

customFunction <- function(.data) {
  for (i in 1:13) {
    growth.type[,i] <- tapply(.data[,8+i] , .data$type, mean, na.rm = TRUE) 
  }
  growth.type # this is the object which will be returned when function finishes
}

then just do

out <- lapply(xy, FUN = customFunction)

If you want to combine the result of lapply , you can use do.call , eg do.call("rbind", out) .