That is definitely possible in R. You can use the package plyr for this purpose.

plyr is a set of tools for a common set of problems: you need to split up a big data structure into homogeneous pieces, apply a function to each piece and then combine all the results back together. For example, you might want to:

- fit the same model each patient subsets of a data frame
- quickly calculate summary statistics for each group
- perform group-wise transformations like scaling or standardising

my_data1 <- plyr::(my_data1, c("old-column-name1"="New-column-name1",
"old-column-name2"="new-column-name2",
.........................................))

Hope this was helpful :)