README

install.packages("incase")

# 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] "1"         "2"         "fizz"      "4"         "buzz"      "fizz"     
#>  [7] "7"         "8"         "fizz"      "buzz"      "11"        "fizz"     
#> [13] "13"        "14"        "fizz buzz" "16"        "17"        "fizz"     
#> [19] "19"        "buzz"

1:20 %>% if_case(. %% 3 == 0, "fizz", .)
#>  [1] "1"    "2"    "fizz" "4"    "5"    "fizz" "7"    "8"    "fizz" "10"  
#> [11] "11"   "fizz" "13"   "14"   "fizz" "16"   "17"   "fizz" "19"   "20"

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)
#> [1] NA  0  1  2  3  4  5
dplyr::case_when(x == -1 ~ NA_integer_, TRUE ~ x)
#> [1] NA  0  1  2  3  4  5
in_case(x == -1 ~ NA, TRUE ~ x)
#> [1] NA  0  1  2  3  4  5

# Replace -1 with 0
dplyr::case_when(x == -1 ~ 0, TRUE ~ x)
#> [1] 0 0 1 2 3 4 5
dplyr::case_when(x == -1 ~ 0L, TRUE ~ x)
#> [1] 0 0 1 2 3 4 5
in_case(x == -1 ~ 0, TRUE ~ x)
#> [1] 0 0 1 2 3 4 5

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] NA          NA          "fizz"      NA          "buzz"      "fizz"     
#>  [7] NA          NA          "fizz"      "buzz"      NA          "fizz"     
#> [13] NA          NA          "fizz buzz" NA          NA          "fizz"     
#> [19] NA          "buzz"

1:20 %>%
  in_case(
    . %% 15 == 0 ~ "fizz buzz",
    . %%  3 == 0 ~ "fizz",
    . %%  5 == 0 ~ "buzz",
    preserve     = TRUE
  )
#>  [1] "1"         "2"         "fizz"      "4"         "buzz"      "fizz"     
#>  [7] "7"         "8"         "fizz"      "buzz"      "11"        "fizz"     
#> [13] "13"        "14"        "fizz buzz" "16"        "17"        "fizz"     
#> [19] "19"        "buzz"

1:20 %>%
  in_case(
    . %% 15 == 0 ~ "fizz buzz",
    . %%  3 == 0 ~ "fizz",
    . %%  5 == 0 ~ "buzz",
    default      = "pass"
  )
#>  [1] "pass"      "pass"      "fizz"      "pass"      "buzz"      "fizz"     
#>  [7] "pass"      "pass"      "fizz"      "buzz"      "pass"      "fizz"     
#> [13] "pass"      "pass"      "fizz buzz" "pass"      "pass"      "fizz"     
#> [19] "pass"      "buzz"

Simplified interface for recoding

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

parties
#>  [1] "G" "I" "D" "I" "R" "D" "L" "D" NA  "L" NA  "G" "R" NA  "G" NA  "L" "D" "D"
#> [20] "I"

parties %>%
  switch_case(
    "D"         ~ "Democrat",
    "R"         ~ "Republican",
    c("G", "L") ~ "Other",
    c("I", NA)  ~ "Independent"
  )
#>  [1] "Other"       "Independent" "Democrat"    "Independent" "Republican" 
#>  [6] "Democrat"    "Other"       "Democrat"    "Independent" "Other"      
#> [11] "Independent" "Other"       "Republican"  "Independent" "Other"      
#> [16] "Independent" "Other"       "Democrat"    "Democrat"    "Independent"

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
)
#> [1] "France"      "Germany"     "Germany"     "Netherlands" "Belgium"    
#> [6] "Belgium"     "Luxembourg"  "Italy"

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
#>  [1] 3.9075340 7.4098608 2.1540250 8.4599089 3.0487929 8.9268192 9.9001603
#>  [8] 9.2022173 0.3128016 5.2452107

data %>% 
  in_case_fct(
    . < 3   ~ "Low",
    . < 7   ~ "Medium",
    default = "High",
    ordered = TRUE
  )
#>  [1] Medium High   Low    High   Medium High   High   High   Low    Medium
#> Levels: Low < Medium < High

parties %>%
  switch_case_fct(
    "D"         ~ "Democrat",
    "R"         ~ "Republican",
    c("G", "L") ~ "Other",
    c("I", NA)  ~ "Independent"
  )
#>  [1] Other       Independent Democrat    Independent Republican  Democrat   
#>  [7] Other       Democrat    Independent Other       Independent Other      
#> [13] Republican  Independent Other       Independent Other       Democrat   
#> [19] Democrat    Independent
#> Levels: Democrat Republican Other Independent

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