How to write multi-level ifelse() in R?

multilevel_ifelse.R

# How to write multi-level ifelse()
set.seed(100)
abc <- sample(letters[1:5], 1000, replace = T)
df <- data.frame(v1=abc, v2="blank", stringsAsFactors = F)
head(df)

system.time({
  df$v2 <- ifelse(df$v1 == "a", "apple", 
                  ifelse(df$v1 == "b", "ball",
                         ifelse(df$v1 == "c", "cat",
                                ifelse(df$v1 == "d", "dog", "elephant"))))
  
})
head(df)
#   user  system elapsed 
#  0.001   0.000   0.001 

# Same logic with switch()
set.seed(100)
abc <- sample(letters[1:5], 1000, replace = T)
df <- data.frame(v1=abc, v2="blank", stringsAsFactors = F)
system.time({
  for(i in 1:nrow(df)){
    val <- df$v1[i]
    df$v2[i] <- switch(val,
                       "a"="apple",
                       "b"="banana",
                       "c"="cat",
                       "d"="dog",
                       "e"="elephant")
  }
})
#   user  system elapsed 
#  0.044   0.002   0.045
head(df)

Some more methds and an even faster one

library(microbenchmark)
library(dplyr)

set.seed(100)
abc <- sample(letters[1:5], 1000, replace = T)
df <- data.frame(v1=abc, v2="blank", stringsAsFactors = F)
head(df)

v_ifelse <- function(df) {ifelse(df$v1 == "a", "apple",
ifelse(df$v1 == "b", "ball",
ifelse(df$v1 == "c", "cat",
ifelse(df$v1 == "d", "dog", "elephant"))))}

v_if_else <- function(df) {if_else(df$v1 == "a", "apple",
if_else(df$v1 == "b", "ball",
if_else(df$v1 == "c", "cat",
if_else(df$v1 == "d", "dog", "elephant"))))}

v_loop <- function(df) {for(i in 1:nrow(df)){
val <- df$v1[i]
df$v2[i] <- switch(val,
"a"="apple",
"b"="banana",
"c"="cat",
"d"="dog",
"e"="elephant")}}

v_apply <- function(df) df$v2 <- sapply(df$v1,function(val)switch(val,
"a"="apple",
"b"="banana",
"c"="cat",
"d"="dog",
"e"="elephant"), simplify = TRUE )

v_subset <- function(df){helper <- c(a = "apple", b = "banana", c = "cat", d = "dog", e = "elephant")
df$v2 <- helper[df$v1]}

microbenchmark(
v_if_else(df),
v_ifelse(df),
v_loop(df),
v_apply(df),
v_subset(df))