Rename across equivalent

[Nilafhiosagam]

Hi all

Getting to grips with the new across function and was wondering what would be the equivalent way to paste a string to the end of numerical columns only which I can achieve as follows right now

  rename_if(is.numeric, .funs = funs(paste0(.,"_total")))
      

thanks in advance

[siddharthprabhu]

The dplyr 1.0.0 equivalent is rename_with().

library(dplyr, warn.conflicts = FALSE)

iris <- as_tibble(iris) # for nicer printing

# Old way
rename_if(iris, .predicate = is.numeric, .funs = ~ paste0(., "_total"))
#> # A tibble: 150 x 5
#>    Sepal.Length_tot~ Sepal.Width_total Petal.Length_to~ Petal.Width_tot~ Species
#>                <dbl>             <dbl>            <dbl>            <dbl> <fct>  
#>  1               5.1               3.5              1.4              0.2 setosa 
#>  2               4.9               3                1.4              0.2 setosa 
#>  3               4.7               3.2              1.3              0.2 setosa 
#>  4               4.6               3.1              1.5              0.2 setosa 
#>  5               5                 3.6              1.4              0.2 setosa 
#>  6               5.4               3.9              1.7              0.4 setosa 
#>  7               4.6               3.4              1.4              0.3 setosa 
#>  8               5                 3.4              1.5              0.2 setosa 
#>  9               4.4               2.9              1.4              0.2 setosa 
#> 10               4.9               3.1              1.5              0.1 setosa 
#> # ... with 140 more rows

# New way
rename_with(iris, .fn = ~ paste0(., "_total"), .cols = where(is.numeric))
#> # A tibble: 150 x 5
#>    Sepal.Length_tot~ Sepal.Width_total Petal.Length_to~ Petal.Width_tot~ Species
#>                <dbl>             <dbl>            <dbl>            <dbl> <fct>  
#>  1               5.1               3.5              1.4              0.2 setosa 
#>  2               4.9               3                1.4              0.2 setosa 
#>  3               4.7               3.2              1.3              0.2 setosa 
#>  4               4.6               3.1              1.5              0.2 setosa 
#>  5               5                 3.6              1.4              0.2 setosa 
#>  6               5.4               3.9              1.7              0.4 setosa 
#>  7               4.6               3.4              1.4              0.3 setosa 
#>  8               5                 3.4              1.5              0.2 setosa 
#>  9               4.4               2.9              1.4              0.2 setosa 
#> 10               4.9               3.1              1.5              0.1 setosa 
#> # ... with 140 more rows

^{Created on 2020-07-23 by the reprex package (v0.3.0)}

Also, funs() has been deprecated for quite some time so you should use list() instead. However, if you're only applying one transformation, you don't need to wrap it in list().

[Nilafhiosagam]

Perfect, thanks so much for your help

[siddharthprabhu]

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