rename_if() together with starts_with() to prefix certain columns [duplicate]

Question

My data looks like this:

#>           Artist          Album Year
#> 1        Beatles  Sgt. Pepper's 1967
#> 2 Rolling Stones Sticky Fingers 1971

And my question should be quite simple. I'm trying to use rename_if to prefix only the columns that start with the letter "A". So my desired output is:

#>       df1_Artist      df1_Album Year
#> 1        Beatles  Sgt. Pepper's 1967
#> 2 Rolling Stones Sticky Fingers 1971

You can see that "Year" should not be prefixed.

This is my attempt, but it's not quite working. Am I using starts_with incorrectly? Should I try break it into two lines so I can understand it more clearly? The purrr style functions I'm still learning, so it's not always intuitive to me yet.

df1 %>% rename_if(starts_with("A"), .funs = ~ paste0(df1, .))
#> Error in df1 %>% rename_if(starts_with("A"), .funs = ~paste0(df1, .)): could not find function "%>%"

Code for data input:

df1 <- data.frame(stringsAsFactors=FALSE,
      Artist = c("Beatles", "Rolling Stones"),
       Album = c("Sgt. Pepper's", "Sticky Fingers"),
        Year = c(1967, 1971)
)

Answer 1

rename_if expects a logical vector as predicate function. starts_with selects variables based on their name. Use base startsWith instead which returns a logical vector based on prefix

library(dplyr)
df1 %>% rename_if(startsWith(names(.), "A"), ~paste0("df1_", .))

#      df1_Artist      df1_Album Year
#1        Beatles  Sgt. Pepper's 1967
#2 Rolling Stones Sticky Fingers 1971

Or if you want to stay in tidyverse you can also use str_detect

df1 %>% rename_if(stringr::str_detect(names(.), "^A"), ~paste0("df1_", .))

---

To use starts_with we can use rename_at which has vars argument.

df1 %>% rename_at(vars(starts_with("A")), ~paste0("df1_", .))