rename first colnames in list of dataframes to match the name of the dataframe-CodePudding

I have a list of dataframes. each dataframe has 1 column named "a" I want to rename column "a" of each dataframe pasting the name of the dataframe after the column name "a". Here is the example.

green <- data.frame(a=c(1,2,3,4,5))

yellow <- data.frame(a=c(6,7,8,9,10))

black <- data.frame(a=c(11,12,13,14,15))

my_list <- list(green=green,
                yellow=yellow,
                black=black)

names(my_list)
[1] "green"  "yellow" "black"

My desired results sould be something like:

> yellow
   a_yellow
1  6
2  7
3  8
4  9
5 10

and so on...

I was trying to do this with lapply but is there is something wrong I don't get...

my_list <- lapply(my_list, function(x)
  colnames(x)=paste(colnames(x), names(x), sep = "_"))

CodePudding user response：

Here are couple of options -

Using tidyverse -

library(dplyr)
library(purrr)

imap(my_list, ~.x %>% rename_with(function(x) paste(x, .y, sep = '_'), 1))

#$green
#  a_green
#1       1
#2       2
#3       3
#4       4
#5       5

#$yellow
#  a_yellow
#1        6
#2        7
#3        8
#4        9
#5       10

#$black
#  a_black
#1      11
#2      12
#3      13
#4      14
#5      15

Or in base R -

Map(function(x, y) {
    names(x)[1] <- paste(names(x)[1], y, sep = '_')
    x
}, my_list, names(my_list))

You can simplify the process if you have only 1 column in each dataframe like in the example.

Map(setNames, my_list, paste('a', names(my_list), sep = '_'))

CodePudding user response：

You can use purrr::imap

library(tidyverse)
black <- tibble(a = 1:10)
yellow <- tibble(a = 11:21)

list("black" = black, "yellow" = yellow) %>%
  imap(\(x, y){
    x %>%
      set_names(glue::glue("a_{y}"))
  })
#> $black
#> # A tibble: 10 x 1
#>    a_black
#>      <int>
#>  1       1
#>  2       2
#>  3       3
#>  4       4
#>  5       5
#>  6       6
#>  7       7
#>  8       8
#>  9       9
#> 10      10
#> 
#> $yellow
#> # A tibble: 11 x 1
#>    a_yellow
#>       <int>
#>  1       11
#>  2       12
#>  3       13
#>  4       14
#>  5       15
#>  6       16
#>  7       17
#>  8       18
#>  9       19
#> 10       20
#> 11       21