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rename() changes the names of individual variables using new_name = old_name syntax; rename_with() renames columns using a function.

Usage

rename(.data, ...)

rename_with(.data, .fn, .cols = everything(), ...)

Arguments

.data

A data frame, data frame extension (e.g. a tibble), or a lazy data frame (e.g. from dbplyr or dtplyr). See Methods, below, for more details.

...

For rename(): <tidy-select> Use new_name = old_name to rename selected variables.

For rename_with(): additional arguments passed onto .fn.

.fn

A function used to transform the selected .cols. Should return a character vector the same length as the input.

.cols

<tidy-select> Columns to rename; defaults to all columns.

Value

An object of the same type as .data. The output has the following properties:

  • Rows are not affected.

  • Column names are changed; column order is preserved.

  • Data frame attributes are preserved.

  • Groups are updated to reflect new names.

Methods

This function is a generic, which means that packages can provide implementations (methods) for other classes. See the documentation of individual methods for extra arguments and differences in behaviour.

The following methods are currently available in loaded packages: dbplyr (tbl_lazy), dplyr (data.frame) .

See also

Other single table verbs: arrange(), filter(), mutate(), reframe(), select(), slice(), summarise()

Examples

iris <- as_tibble(iris) # so it prints a little nicer
rename(iris, petal_length = Petal.Length)
#> # A tibble: 150 × 5
#>    Sepal.Length Sepal.Width petal_length Petal.Width 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 
#> # ℹ 140 more rows

# Rename using a named vector and `all_of()`
lookup <- c(pl = "Petal.Length", sl = "Sepal.Length")
rename(iris, all_of(lookup))
#> # A tibble: 150 × 5
#>       sl Sepal.Width    pl Petal.Width 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 
#> # ℹ 140 more rows

# If your named vector might contain names that don't exist in the data,
# use `any_of()` instead
lookup <- c(lookup, new = "unknown")
try(rename(iris, all_of(lookup)))
#> Error in all_of(lookup) : Can't rename columns that don't exist.
#>  Column `unknown` doesn't exist.
rename(iris, any_of(lookup))
#> # A tibble: 150 × 5
#>       sl Sepal.Width    pl Petal.Width 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 
#> # ℹ 140 more rows

rename_with(iris, toupper)
#> # A tibble: 150 × 5
#>    SEPAL.LENGTH SEPAL.WIDTH PETAL.LENGTH PETAL.WIDTH 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 
#> # ℹ 140 more rows
rename_with(iris, toupper, starts_with("Petal"))
#> # A tibble: 150 × 5
#>    Sepal.Length Sepal.Width PETAL.LENGTH PETAL.WIDTH 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 
#> # ℹ 140 more rows
rename_with(iris, ~ tolower(gsub(".", "_", .x, fixed = TRUE)))
#> # A tibble: 150 × 5
#>    sepal_length sepal_width petal_length petal_width 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 
#> # ℹ 140 more rows

# If your renaming function uses `paste0()`, make sure to set
# `recycle0 = TRUE` to ensure that empty selections are recycled correctly
try(rename_with(
  iris,
  ~ paste0("prefix_", .x),
  starts_with("nonexistent")
))
#> Error in rename_with(iris, ~paste0("prefix_", .x), starts_with("nonexistent")) : 
#>   `.fn` must return a vector of length 0, not 1.

rename_with(
  iris,
  ~ paste0("prefix_", .x, recycle0 = TRUE),
  starts_with("nonexistent")
)
#> # A tibble: 150 × 5
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width 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 
#> # ℹ 140 more rows