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forcats

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Overview

R uses factors to handle categorical variables, variables that have a fixed and known set of possible values. Factors are also helpful for reordering character vectors to improve display. The goal of the forcats package is to provide a suite of tools that solve common problems with factors, including changing the order of levels or the values. Some examples include:

You can learn more about each of these in vignette("forcats"). If you’re new to factors, the best place to start is the chapter on factors in R for Data Science.

Installation

# The easiest way to get forcats is to install the whole tidyverse:
install.packages("tidyverse")

# Alternatively, install just forcats:
install.packages("forcats")

# Or the the development version from GitHub:
# install.packages("devtools")
devtools::install_github("tidyverse/forcats")

Cheatsheet

Getting started

forcats is part of the core tidyverse, so you can load it with library(tidyverse) or library(forcats).

library(forcats)
library(dplyr)
library(ggplot2)
starwars %>% 
  filter(!is.na(species)) %>%
  count(species, sort = TRUE)
#> # A tibble: 37 × 2
#>    species      n
#>    <chr>    <int>
#>  1 Human       35
#>  2 Droid        6
#>  3 Gungan       3
#>  4 Kaminoan     2
#>  5 Mirialan     2
#>  6 Twi'lek      2
#>  7 Wookiee      2
#>  8 Zabrak       2
#>  9 Aleena       1
#> 10 Besalisk     1
#> # … with 27 more rows
starwars %>%
  filter(!is.na(species)) %>%
  mutate(species = fct_lump(species, n = 3)) %>%
  count(species)
#> # A tibble: 4 × 2
#>   species     n
#>   <fct>   <int>
#> 1 Droid       6
#> 2 Gungan      3
#> 3 Human      35
#> 4 Other      39
ggplot(starwars, aes(x = eye_color)) + 
  geom_bar() + 
  coord_flip()

starwars %>%
  mutate(eye_color = fct_infreq(eye_color)) %>%
  ggplot(aes(x = eye_color)) + 
  geom_bar() + 
  coord_flip()

More resources

For a history of factors, I recommend stringsAsFactors: An unauthorized biography by Roger Peng and stringsAsFactors = <sigh> by Thomas Lumley. If you want to learn more about other approaches to working with factors and categorical data, I recommend Wrangling categorical data in R, by Amelia McNamara and Nicholas Horton.

Getting help

If you encounter a clear bug, please file a minimal reproducible example on Github. For questions and other discussion, please use community.rstudio.com.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.