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Course

Foundations of Functional Programming with purrr

IntermediateSkill Level

4.7+

Updated 01/2026

Learn to easily summarize and manipulate lists using the purrr package.

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RProgramming4 hr13 videos44 Exercises3,750 XP11,228Statement of Accomplishment

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Course Description

Lists can be difficult to both understand and manipulate, but they can pack a ton of information and are very powerful. In this course, you will learn to easily extract, summarize, and manipulate lists and how to export the data to your desired object, be it another list, a vector, or even something else! Throughout the course, you will work with the purrr package and a variety of datasets from the repurrrsive package, including data from Star Wars and Wes Anderson films and data collected about GitHub users and GitHub repos. Following this course, your list skills will be purrrfect!

Prerequisites

Introduction to the Tidyverse Intermediate R

1

Simplifying Iteration and Lists With purrr

Iteration is a powerful way to make the computer do the work for you. It can also be an area of coding where it is easy to make lots of typos and simple mistakes. The purrr package helps simplify iteration so you can focus on the next step, instead of finding typos.

The power of iteration

Introduction to iteration

Iteration with purrr

More iteration with for loops

More iteration with purrr

Subsetting lists

List structure

Subsetting list elements

The many flavors of map()

map() argument alternatives

2

More complex iterations

purrr is much more than a for loop; it works well with pipes, we can use it to run models and simulate data, and make nested loops!

Working with unnamed lists

Names & pipe refresher

Setting names

Pipes in map()

Simulating Data with Purrr

Run a linear model

map_dbl() and map_int()

map2() and pmap()

Simulating data with multiple inputs using map2()

Simulating data 3+ inputs with pmap()

3

Troubleshooting lists with purrr

Like anything in R, understanding how to troubleshoot issues is an important skill set. This can be particularly important with lists, where finding the problem can be tricky.

How to purrr safely()

safely() replace with NA

Convert data to numeric with purrr

Finding the problem areas

Another way to possibly() purrr

Replace safely() with possibly()

Convert values with possibly()

purrr is a walk() in the park

Comparing walk() vs. no walk() outputs

walk() for printing cleaner list outputs

4

Problem solving with purrr

Now that you have the building blocks, we will start tackling some more complex data problems with purrr.

Using purrr in your workflow

Name review

Setting names

Asking questions from a list

Even more complex problems

Questions about gh_repos

Graphs in purrr

ggplot() refresher

purrr and scatterplots

purrr and histograms

Foundations of Functional Programming with purrr

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FAQs

What does the purrr package do that basic R loops cannot?

The purrr package simplifies iteration with cleaner syntax, reduces common typos, works naturally with pipes, and provides consistent tools for extracting and transforming list data.

What datasets are used in this course?

You work with datasets from the repurrrsive package, including Star Wars character data, Wes Anderson film palettes, and data about GitHub users and repositories.

Do I need experience with lists in R before starting?

Basic familiarity with R lists helps, but the course is beginner level. You need intermediate R skills and tidyverse knowledge to get the most from the material.

Does the course cover troubleshooting and debugging list operations?

Yes. Chapter 3 is entirely dedicated to troubleshooting list issues with purrr, teaching you to identify and fix problems that commonly arise when working with complex list structures.

Will I learn to use purrr for running models and simulating data?

Yes. Chapter 2 shows how purrr goes beyond simple loops by demonstrating its use for running models, simulating data, and creating nested iteration patterns.

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