Lecture 13: Lists, Iterations, and purrr

STAT 545 - Fall 2025

Learning Outcomes

  • Use the map family of functions from the purrr package to iteratively apply a function.

  • Create and operate on list columns in a tibble using nest(), unnest(), and the map_*() family of functions.

  • Define functions on-the-fly within a map function using shortcuts.

  • Create and operate on list columns in a tibble using nest(), unnest()

Written Notes

(No video lecture this week!)

Required Packages

We will require the following packages:

library(tidyverse) #purrr is automatically downloaded with tidyverse

Lists

Here is a list in R; it holds multiple items.

Vectors Lists
Access elements with square brackets [] Access elements with [[]]
Each element must be an atomic data type (i.e., a single value) Elements can be anything, even another list or another vector
Each element has to be of the same type Elements can be as different as you like

Lists

Let’s take our sample list and access some items stored in it.

To access the data within the vector, we can index it as well:

Lists

Elements within a list can also be named using names().

Once the elements are named, you can access them using the $ operator, similar to how you can grab columns from a data frame or tibble:

Tibbles, as a List?

Data frames and tibbles are actually a special type of list:

  • We can efficiently apply a function to each column of a tibble by learning how to apply a function to each entry of a list.

Iteration

Let’s write a “for loop” in R that iterates over the entries of a numeric vector x, squares each entry, and stores the result in a numeric vector output:

Iteration with purrr

Often, you can replace loops with a compact call to a function in the purrr package.

There are many map_*() functions, a few of which we will highlight here:

  • map(): applies a function to each element in a list or vector, returns a list
  • map_dbl(): applies a function to each element in a list or vector, returns a vector
  • map_dfr(): applies a function to each element in a list or vector, returns a data frame

The first argument of each function specifies the list/vector we want to iterate over, and the second argument specifies a function that we want to apply to each entry.

Iteration with purrr

Let’s use these map functions over a list containing ages of some made-up people

We will compare the outputs of these functions when applying a simple square function to their ages.

Iteration with purrr

map()

A list is returned!

Iteration with purrr

map_dbl()

A vector is returned!

Iteration with purrr

map_dfr()

A dataframe is returned!

Iteration with purrr

purrr Shortcuts

Here’s an example using purrr::map_dbl() and a custom function:

Here are two examples of “shortcuts”:

List Columns

Consider the following example: a snippet of the Game of Thrones data from An API of Ice and Fire.

## # A tibble: 6 × 3
##   name              gender titles   
##   <chr>             <chr>  <list>   
## 1 Theon Greyjoy     Male   <chr [2]>
## 2 Tyrion Lannister  Male   <chr [2]>
## 3 Victarion Greyjoy Male   <chr [2]>
## 4 Will              Male   <chr [1]>
## 5 Areo Hotah        Male   <chr [1]>
## 6 Chett             Male   <chr [1]>

  • Some characters have one title (e.g., Will); others have more than one title (e.g., Theon Greyjoy).

  • The titles column is a list column, where each entry is a list that contains as many or as few strings as we like.

List Columns

Create List Columns using nest()

  • Instead of having one row per child, perhaps we want to nest the data such that there is only one row per family.

  • We can nest the child column!

  • Aside: in general this data will not be tidy, but we’re demonstrating how to nest and un-nest data here

List Columns

Create List Columns using nest()

We first need to group by family_id to gather children from each family, and then create a nested column called “children”:

Now we have a list column that contains vectors of varying lengths with the children’s names within each family.

List Columns

Remove List Columns using unnest()

We can revert back to the original tibble using unnest().

Worksheet B3

You’ll dive deeper into these topics in Worksheet B3

Take the rest of today’s class and Thursday’s class to work through the worksheet and ask for help if needed.