Renaming data frame column variables without using column name

Question

I want to create a function which renames specific values in a column to something else, which is specified by the function, something like this (although in reality there would be much more to rename):

func <- function(x) x %>%
                    mutate(col_name = ifelse(col_name =="something","something else", 
                                      ifelse(col_name == "something2","something_else2")))

Note that it isn't the column names that I want to change, it is the values themselves in the column. However, I would like this to work regardless of which column the values are in (e.g. the function works all over the data frame). Also, this only works if the values named in the function is present, and I would like it to ignore the ones that aren't present in the columns. here is a small reproducible example: (column values are arbitrary)

col1 <- c("a","b","c","d","e")
col2 <- c("b","f","d","c","g")

df <- data.frame(col1, col2)

col3 <- c("a","h","i","b","c")
col4 <- c("c","d","j","a","g")

df2 <- data.frame(col3, col4)

Which looks like this:

df1:
  col1 col2
1    a    b
2    b    f
3    c    d
4    d    c
5    e    g

df2:
  col3 col4
1    a    c
2    h    d
3    i    j
4    b    a
5    c    g

Say that i want to rename like this:

df1:

   col1 col2
1  can  chi
2  chi  pig
3  equ  she
4  she  equ
5  fox  bov

df2:

   col3 col4
1  can  equ
2  avi  she
3  tyr  asp
4  chi  can
5  equ  bov

So what I was hoping to get was a function that changes the names of multiple values in data frame columns regardless of its position in the data frame, and that it ignores the values not found in the data frame by the function.

Answer 1

Recode all columns

library(dplyr)
func = function(x, originals = letters[1:10], 
                rename_tos = c("can", "chi", "equ", "she", "fox", "pig", "bov", "avi", "tyr", "asp")){
  names(rename_tos) = originals
  x %>%
    mutate_if(is.factor, as.character) %>%
    lapply(function(y){
      y = rename_tos[y]
    }) %>%
    data.frame(row.names = NULL) 
}

Results:

> func(df)
  col1 col2
1  can  chi
2  chi  pig
3  equ  she
4  she  equ
5  fox  bov

> func(df2)
  col3 col4
1  can  equ
2  avi  she
3  tyr  asp
4  chi  can
5  equ  bov

Notes:

The method I used is basically to create a lookup table (named vector) for the renames and index the rename_tos vector with column values. Here, I've set the originals and renames as the default of the function, but you can also supply your own.

User-supplied column names

If you want to be able to rename columns specified and leave the other columns the same, you can do something like the following:

library(dplyr)
library(rlang)

func = function(x, ..., originals = letters[1:10], 
                rename_tos = c("can", "chi", "equ", "she", "fox", "pig", "bov", "avi", "tyr", "asp")){
  names(rename_tos) = originals
  dots = quos(...)
  x %>%
    mutate_at(vars(!!! dots), as.character) %>%
    mutate_at(vars(!!! dots), funs(rename_tos[.])) %>%
    data.frame(row.names = NULL) 
}

Result:

> func(df, col2)
  col1 col2
1    a  chi
2    b  pig
3    c  she
4    d  equ
5    e  bov

> func(df2, col3, col4)
  col3 col4
1  can  equ
2  avi  she
3  tyr  asp
4  chi  can
5  equ  bov

> func(df2, c(col3, col4))
  col3 col4
1  can  equ
2  avi  she
3  tyr  asp
4  chi  can
5  equ  bov

Notes:

Here, I added the ... argument to allow the user to input their own column names. I used quos from rlang to quote the ... arguments and later unquoted them inside vars to mutate_at using !!!. For example, if the user supplied func(df, col2), the first argument of mutate_at evaluates to vars(col2). This works with multiple arguments as well as a vector of arguments as one can see in the results.