dplyr mutate a variable by comparing a variable and vectors of different sizes

Question

I have the dataframe of the following type

df <- tibble::tribble(~x,
                      c("A", "B"),
                      c("A", "B", "C"),
                      c("A", "B", "C", "D"),
                      c("A", "B"))

and vectors like these

vec1 <- c("A", "B")
vec2 <- c("A", "B", "C")
vec3 <- c("A", "B", "C", "D")

I want to mutate a variable y that shows which row has which vector. I tried the following, but getting the empty y variable with the warning: "longer object length is not a multiple of shorter object length"

df_new <- df %>%
  mutate(y = case_when(x == vec1 ~ "vec1",
                       x == vec2 ~ "vec2",
                       x == vec2 ~ "vec3"))

The desired output is

df_new <- tibble::tribble(~x,                      ~y,
                          c("A", "B"),             "vec1",
                          c("A", "B", "C"),        "vec2",
                          c("A", "B", "C", "D"),   "vec3",
                          c("A", "B"),             "vec1")

Answer 1

A solution using map2_lgl and identical to assess if the vectors are the same.

library(tidyverse)

df_new <- df %>%
  mutate(y = case_when(
    map2_lgl(x, list(vec1), ~identical(.x, .y))  ~"vec1",
    map2_lgl(x, list(vec2), ~identical(.x, .y))  ~"vec2",
    map2_lgl(x, list(vec3), ~identical(.x, .y))  ~"vec3"
  ))
df_new
# # A tibble: 4 x 2
#   x         y    
#   <list>    <chr>
# 1 <chr [2]> vec1 
# 2 <chr [3]> vec2 
# 3 <chr [4]> vec3 
# 4 <chr [2]> vec1 

Answer 2

Here's an alternative that's more programmatic - you don't need to specify each vector explicitly

Data

df <- tibble::tribble(~x,
                      c("A", "B"),
                      c("A", "B", "C"),
                      c("A", "B", "C", "D"),
                      c("A", "B"))

vec1 <- c("A", "B")
vec2 <- c("A", "B", "C")
vec3 <- c("A", "B", "C", "D")

Solution - takes advantage of ls(...) to return relevant vector names using a pattern

vecs <- ls(pattern="vec")
L <- lapply(vecs, get)
names(L) <- vecs
df %>%
  mutate(y = names(L)[match(x, L)])

# A tibble: 4 x 2
  # x         y    
  # <list>    <chr>
# 1 <chr [2]> vec1 
# 2 <chr [3]> vec2 
# 3 <chr [4]> vec3 
# 4 <chr [2]> vec1