Apply series of changes to multiple similar datasets in R

Question

I have 20 csv files of data that are formatted exactly the same, about 40 columns of different numbers, but with different values in each column. I want to apply a series of changes to each data frame in order to extract specific information from every one of them.

Specifically I want to extract four columns from each data frame, find the maximum value of each column in each data frame and then add all of these maximum values together, so I get one final number for each data frame. Something like this:

str(data)    
Extract<-data[c(1,2,3,4)]
Max<-apply(Extract,2,max)
Add<-Max[1] + Max[2] + Max[3] + Max[4]

I have the code written above to do all these steps for every data frame individually, but is it possible to apply this code to all of them at once?

Answer 1

If you put all 20 filenames into a vector called files

Maxes <- numeric(length(files))
i <- 1

for (file in files) {

     data <- read.csv(file)
     str(data)    
     Extract<-data[c(1,2,3,4)]
     Max<-apply(Extract,2,max)
     Add<-Max[1] + Max[2] + Max[3] + Max[4]
     Maxes[i] <- Add
     i <- i+1

}

Though that str(data) will just cause a lot of stuff to print to the terminal 20 times. I'm not sure the value of that, but it was in your question so I included.

Answer 2

Put all your files into a common folder such as /path/temp/

csvs <- list.files("/path/temp")   # vector of csv

Use custom function for colMax

colMax <- function(data) sapply(data, max, na.rm = TRUE)

Using foreach , dplyr , and readr

library(foreach)
library(dplyr)

foreach(i=1:length(csvs), .combine="c") %do% { read_csv(csvs[i]) %>%
                                                select(1:4) %>% 
                                                colMax(.) %>% 
                                                sum(.)
                                             }  # returns a vector