output: github_document

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

# remotes::install_github("GuangchuangYu/badger")
library(badger)
library(incase)

parties <- sample(
  c("D", "R", "G", "L", "I", NA),
  20,
  replace = TRUE,
  c(0.25, 0.25, 0.075, 0.075, 0.25, 0.1)
)

incase

r badge_cran_release(color = "brightgreen") r badge_runiverse() r badge_lifecycle("stable") r badge_license(color = "blueviolet") r badge_github_actions(action = "R-CMD-check") r badge_codecov(branch = "main")

incase provides a more pipe-friendly alternative to dplyr's case_when() and if_else().

Installation

You can install the released version of incase from CRAN with:

install.packages("incase")

or the development version from GitHub with:

# install.packages("pak")
pak::pkg_install("rossellhayes/incase")

Usage

Pipe-friendly conditionals

incase's in_case() and if_case() accept a vector as their first input, allowing you to take full advantage of magrittr's .

1:20 %>%
  in_case(
    . %% 15 == 0 ~ "fizz buzz",
    . %%  3 == 0 ~ "fizz",
    . %%  5 == 0 ~ "buzz",
    TRUE         ~ .
  )

1:20 %>% if_case(. %% 3 == 0, "fizz", .)

Automatic type conversion

incase functions automatically coerce types. This is especially useful when dealing with integers or NAs.

x <- -1:5

# Replace -1 with NA
dplyr::case_when(x == -1 ~ NA, TRUE ~ x)
dplyr::case_when(x == -1 ~ NA_integer_, TRUE ~ x)
in_case(x == -1 ~ NA, TRUE ~ x)

# Replace -1 with 0
dplyr::case_when(x == -1 ~ 0, TRUE ~ x)
dplyr::case_when(x == -1 ~ 0L, TRUE ~ x)
in_case(x == -1 ~ 0, TRUE ~ x)

With incase, you no longer have to worry about specifying the type of your NAs or adding L to your integers.

Easy default values

in_case() adds preserve and default arguments as a more intuitive alternative to TRUE ~ ....*

1:20 %>%
  in_case(
    . %% 15 == 0 ~ "fizz buzz",
    . %%  3 == 0 ~ "fizz",
    . %%  5 == 0 ~ "buzz"
  )

1:20 %>%
  in_case(
    . %% 15 == 0 ~ "fizz buzz",
    . %%  3 == 0 ~ "fizz",
    . %%  5 == 0 ~ "buzz",
    preserve     = TRUE
  )

1:20 %>%
  in_case(
    . %% 15 == 0 ~ "fizz buzz",
    . %%  3 == 0 ~ "fizz",
    . %%  5 == 0 ~ "buzz",
    default      = "pass"
  )

Simplified interface for recoding

switch_case() works as a convenient shorthand for in_case() when recoding discrete values.

parties

parties %>%
  switch_case(
    "D"         ~ "Democrat",
    "R"         ~ "Republican",
    c("G", "L") ~ "Other",
    c("I", NA)  ~ "Independent"
  )

grep_case() allows you to recode values with pattern matching.

countries <- c(
  "France", "Ostdeutschland", "Westdeutschland", "Nederland",
  "België (Vlaanderen)", "Belgique (Wallonie)", "Luxembourg", "Italia"
)

grep_case(
  countries,
  "Deutschland" ~ "Germany",
  "Belg"        ~ "Belgium",
  "Nederland"   ~ "Netherlands",
  "Italia"      ~ "Italy",
  preserve      = TRUE,
  ignore.case   = TRUE
)

Easily recode to (ordered) factor

When you need an ordered factor, the *_fct() family of functions lets you save a step by using the order of your cases as the order of your factor levels. Use ordered = TRUE to create an ordered factor and ordered = FALSE to make a regular-old factor.

data <- runif(10, 0, 10)
data

data %>% 
  in_case_fct(
    . < 3   ~ "Low",
    . < 7   ~ "Medium",
    default = "High",
    ordered = TRUE
  )

parties %>%
  switch_case_fct(
    "D"         ~ "Democrat",
    "R"         ~ "Republican",
    c("G", "L") ~ "Other",
    c("I", NA)  ~ "Independent"
  )