Applying dplyr's rename to all columns while using pipe operator

Question

I\'m working with an imported data set that corresponds to the extract below:

set.seed(1)
dta <- data.frame(\"This is Column One\" = runif(n = 10),
               


        

Answer 1

You can also try this

set.seed(1)
dta <- data.frame("This is Column One" = runif(n = 10),
                 "Another amazing Column name" = runif(n = 10),
                 "!## This Columns is so special€€€" = runif(n = 10),
                check.names = FALSE)

dta <- dta  %>% 
  setNames(gsub("[^[:alnum:] ]", perl = TRUE,
            "",
            names(.))) %>% 
  setNames(gsub("(\\w)(\\w*)",
            "\\U\\1\\L\\2",
            perl = TRUE,
            names(.)))

names(dta)
[1] "This Is Column One"          "Another Amazing Column Name" " This Columns Is So Special"

Answer 2

mtcars %>% 
  data.table::setnames(
    old = mtcars %>% names(),
    new = mtcars %>% names() %>% paste0("_new_name")
  )

The function setnames in data.table package is to rename the column names in data frame. old and new are two arguments in this function we need.

mtcars %>% names() outputs the column names of data frame mtcars in pipeline %>% way, so you can also use names(mtcars). They are same thing.

In this minimal example, I rename the column names in pipeline %>% and add all old column names with a postfix using paste0 function. You can add prefix, postfix or other rules.

Answer 3

I know this is an old question, and I'm sure you found the solution by now, but I stumbled here searching for the same question, and ultimately found a few new ways to do this.

Dplyr

Using dplyr 0.6.0 and above, there is now a rename_all function:

  dta %>% 
    rename_all(funs(gsub("[[:punct:]]", "", make.names(names(dta)))))

Which works, but it's a little messy to me. If you want more flexibility with dplyr, you can also call on:

• rename_at
• rename_if

Janitor

This is a pretty nice package (with plenty of additional utility) that can easily clean up column names:

library(janitor)

dta %>% 
  clean_names()

Which will rename and clean all column names to the following:

[1] "this_is_column_one"  "another_amazing_column_name"  "x_this_columns_is_so_special"

Everything becomes snake_case rather than CamelCase, but overall clean_names is very flexible in the column names it handles. If that IS a deal breaker, you can use yet another package snakecase for its function to_big_camel_case() within the rename_all function...although that is starting to get a little too esoteric

Answer 4

Using Stringr and Dplyr, and the dot operator:

dta %>%
   dplyr::rename_all(funs(
                     stringr::str_replace_all( ., "[[:punct:]]", "_" )
   ))

Answer 5

Set column names with the pipe like so:

iris %>% `colnames<-`(c("newcol1", "newcol2", "newcol3", "newcol4", "newcol5"))

Which returns

    newcol1 newcol2 newcol3 newcol4    newcol5
1       5.1     3.5     1.4     0.2     setosa
2       4.9     3.0     1.4     0.2     setosa
3       4.7     3.2     1.3     0.2     setosa