You Should Be Using purrr for More than Just Iteration

You Should Be Using purrr for More than Just Iteration

3 functions from the Tidyverse package that improve working with lists in R. If you can store things in a dataframe instead, and use dplyr rather than purrr for your purposes, then you should! But for the times when you're working with lists, purrr is a great and often underutilized tool.

The purrr package is one of the mainstays of the Tidyverse, right up there with dplyr and the pipe operator in terms of usefulness and universality. One of its main purposes is to align the intent of a loop with its syntax. Instead of involving a bunch of tedious boilerplate when writing a for-loop — which tells the reader little about what the loop does — a purrr map can be read almost like plain English, and fits neatly into groups of piped-together operations.

But this is not all purrr has to offer. For the longest time, I only used mapwalk, and their variants. Since then, I’ve discovered the package’s other utilities that make working with lists a breeze.

Because these functions were not hiding at all, sitting in plain sight within documentation pages, I felt a little silly for not using them earlier. But it’s all too easy for programmers to get locked into the same routines, unconsciously following a “if it ain’t broke” mindset. So in the interest of whetting your appetite for the lesser-known tools purrr has on offer, I’ve selected a few of my favorites to share. I hope that doing so will improve your workflows and make you more curious about what else this R package can provide.

coding data-science programming functional-programming r

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