Functional Programming with purrr

purrr is the tidyverse's functional-programming toolkit: it lets you apply a function to every element of a list or vector with map() , replacing hand-written loops with short, type-safe, composable pipelines.

Learn Functional Programming with purrr in our free R course — a beginner-friendly interactive lesson with worked examples, a practice exercise and a quick…

Part of the free R course at LearnCodingFast — hands-on lessons with examples you run in your browser, plus practice exercises and a quick quiz.

In this lesson you'll learn map() and its typed variants, the ~ .x formula shorthand, parallel iteration with map2() / pmap() , folding with reduce() , and filtering with keep() / discard() — and how they compare to the base apply family.

What You'll Learn in This Lesson

1️⃣ map() and the Typed Variants

The core verb is map() : give it a list or vector and a function, and it runs the function on each element, returning a list of the same length. You can pass a function by name, write one inline, or use the formula shorthand.

A plain map() always returns a list, which is awkward if you wanted a numeric vector. The typed variants return an atomic vector of exactly that type — and error loudly if a result doesn't fit, catching bugs early.

2️⃣ The ~ .x Shorthand & Parallel Maps

For short transformations, the ~ formula is the idiomatic purrr style: .x stands for the current element. It's just a compact way to write an anonymous function.

When you need to walk two or more vectors in lockstep, reach for map2() (exactly two, with .x and .y ) or pmap() (any number, passed as a list).

3️⃣ reduce(), keep() & discard()

Not every job is one-to-one. reduce() folds a whole list into a single value, and keep() / discard() filter a list by a predicate. Together with map() , they let you express most iteration as one readable pipe.

Notice the final pipe: keep then map_dbl then reduce . Each verb does one thing, and the data flows left to right — far easier to read and modify than a nested for loop.

Your turn. Fill in the # TODO blank and run it.

Mini-Challenge: Per-Group Means

This is the everyday purrr task: summarising a list of vectors without a single loop. Combine map_dbl() , map_int() , keep() , and reduce() .

Common Errors (and the fix)

• ❌ map_dbl() errors with "must be a single double" — ✅ your function returned the wrong type or length; use plain map() , or fix the function to return one number.
• ❌ Using .x outside a ~ formula — ✅ .x only exists inside purrr's formula shorthand; in a normal function(x) use x .
• ❌ map2() length mismatch — ✅ the two inputs must be the same length (or one of length 1); check with length() .
• ❌ Forgetting to library(purrr) — ✅ load the package (or library(tidyverse) ) before using map() .

Pro Tips

• 💡 Extract by name or position: map_chr(records, "name") pulls the name element from each list — a shortcut for ~ .x$name .
• 💡 Build data frames: map_dfr() row-binds each result into one tibble — ideal for reading many files.
• 💡 Side effects only: use walk() instead of map() when you just want to print or save and don't need the return value.

📋 Quick Reference — purrr

Task

R Syntax

Map → list

map(x, f)

Map → numeric

map_dbl(x, ~ .x * 2)

Two inputs

map2_dbl(x, y, ~ .x + .y)

Many inputs

pmap_dbl(list(a, b), f)

Fold to one value

reduce(x, )

Filter a list

keep(x, ~ .x > 0)

Frequently Asked Questions

🎉 Lesson Complete!

• ✅ map() applies a function to each element and returns a list
• ✅ Typed variants ( map_dbl , map_chr , …) return a safe atomic vector
• ✅ ~ .x is shorthand for an anonymous function
• ✅ map2() / pmap() iterate over several inputs at once
• ✅ reduce() folds to one value; keep() / discard() filter
• ✅ Next lesson: Dates with lubridate

Practice quiz

Continue this course

• Previous: Reshaping: pivot_longer & pivot_wider
• Next: Dates with lubridate