In R, how do I add a string of text to column names?-CodePudding

I want to add a string of text at the end of the column names in my data frame. How do I do this?

Example data (where I want to change column names A, B, C, D, E to Atext, Btext, Ctext, Dtext, Etext):

df <- structure(list(User_ID = 1:4, A = c(0.815353067, 0.698314902, 0.774619233, 0.949620322),
                      B = c(0.684046246, 0.427028078, 0.579449798, 0.977426626),
                      C = c(0.101562005, 0.943064479, 0.19946195, 0.70068721),
                      D = c(0.525384365, 0.638082727, 0.651924335, 0.112375646), 
                      E = c(0.415664129, 0.006406548, 0.85036104, 0.510504667)),
                class = "data.frame", row.names = c(NA, -4L))

CodePudding user response：

Use grep to find the letter name columns, along with paste to concatenate the string text to the end:

names.change <- grep("^[A-Z] $", names(df))
names(df)[names.change] <- paste0(names(df)[names.change], "text")
df

  User_ID     Atext     Btext     Ctext     Dtext       Etext
1       1 0.8153531 0.6840462 0.1015620 0.5253844 0.415664129
2       2 0.6983149 0.4270281 0.9430645 0.6380827 0.006406548
3       3 0.7746192 0.5794498 0.1994619 0.6519243 0.850361040
4       4 0.9496203 0.9774266 0.7006872 0.1123756 0.510504667

CodePudding user response：

I'd prefer it in a one-liner with dplyr::rename_with:

library(dplyr)

df %>% rename_with(~paste0(., "Text"), grep("^[A-Z]$", names(.)))

Output:

  User_ID     AText     BText     CText     DText       EText
1       1 0.8153531 0.6840462 0.1015620 0.5253844 0.415664129
2       2 0.6983149 0.4270281 0.9430645 0.6380827 0.006406548
3       3 0.7746192 0.5794498 0.1994619 0.6519243 0.850361040
4       4 0.9496203 0.9774266 0.7006872 0.1123756 0.510504667

CodePudding user response：

Here is a base R solution without grepl:

colnames(df)[-1] <- paste0(colnames(df)[-1], "text")

output:

  User_ID     Atext     Btext     Ctext     Dtext       Etext
1       1 0.8153531 0.6840462 0.1015620 0.5253844 0.415664129
2       2 0.6983149 0.4270281 0.9430645 0.6380827 0.006406548
3       3 0.7746192 0.5794498 0.1994619 0.6519243 0.850361040
4       4 0.9496203 0.9774266 0.7006872 0.1123756 0.510504667

CodePudding user response：

I would also use rename_with. But i think we can use the .cols argument, so we can include a selection helper before the call to rename_with, obviating the need for grep.

df %>% rename_with(.cols=matches('[A-E]'), ~paste0(.x, 'text'))

If the selected columns are consistently A-Z, the selection can be even simpler:

df %>% rename_with(~paste0(.x, 'text'), A:E)

output

  User_ID     Atext     Btext     Ctext     Dtext       Etext
1       1 0.8153531 0.6840462 0.1015620 0.5253844 0.415664129
2       2 0.6983149 0.4270281 0.9430645 0.6380827 0.006406548
3       3 0.7746192 0.5794498 0.1994619 0.6519243 0.850361040
4       4 0.9496203 0.9774266 0.7006872 0.1123756 0.510504667