Introduction

The afp–Applied Functional Programming–package provides functionals to simplify iterative processes in R. The Base R *apply() family, purrr1 library, and Julia programming language2 are the principal influences. The former two contain tools essential for functional programming that minimize the need to incorporate loops and increase code brevity; however, there is inelegance with respect to specific situations.

For example, to map a function and consequently bind rows or columns, purrr splits the decision into two functions rather than within one: map_dfr() and map_dfc()3, both of which only output to data frames (the former behaves the same as map_df()4)–while this feature is as intended, they nonetheless omit the possibility of a matrix when such a data type is preferred. Additionally, to reduce the results of a mapping, one must encase Map()/lapply() in Reduce(), while Julia blends the routine into mapreduce()5.

As such, afp exists to supplement the functionals in Base R, purrr, and others to support efficient and concise programming.

This handbook shows how to install afp, followed by descriptions of each function in the package before concluding.

  1. https://purrr.tidyverse.org/↩︎

  2. https://julialang.org/↩︎

  3. https://purrr.tidyverse.org/reference/map.html↩︎

  4. Type purrr::map_df in the console and compare with purrr::map_dfr.↩︎

  5. https://docs.julialang.org/en/v0.6.1/stdlib/collections/#Base.mapreduce-NTuple%7B4,Any%7D↩︎