🐈🐈🐈🐈: tools for working with categorical variables (factors)
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AmeliaMN and hadley Add group_other option to fct_collapse, to allow for optional recodin…
…g of all non-targeted levels into an "Other" category (#160)

Fixes #100
Latest commit 22ad55b Jan 19, 2019

README.md

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:

  • fct_reorder(): Reordering a factor by another variable.
  • fct_infreq(): Reordering a factor by the frequency of values.
  • fct_relevel(): Changing the order of a factor by hand.
  • fct_lump(): Collapsing the least/most frequent values of a factor into "other".

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")

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 x 2
#>    species      n
#>    <chr>    <int>
#>  1 Human       35
#>  2 Droid        5
#>  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 x 2
#>   species     n
#>   <fct>   <int>
#> 1 Droid       5
#> 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.

Code of Conduct

Please note that the 'forcats' project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.