Repeat a vector

Source: R/rep.R

  • vec_rep() repeats an entire vector a set number of times.

  • vec_rep_each() repeats each element of a vector a set number of times.

  • vec_unrep() compresses a vector with repeated values. The repeated values are returned as a key alongside the number of times each key is repeated.

vec_rep(
  x,
  times,
  ...,
  error_call = current_env(),
  x_arg = "x",
  times_arg = "times"
)

vec_rep_each(
  x,
  times,
  ...,
  error_call = current_env(),
  x_arg = "x",
  times_arg = "times"
)

vec_unrep(x)

Arguments

x

A vector.

times

For vec_rep(), a single integer for the number of times to repeat the entire vector.

For vec_rep_each(), an integer vector of the number of times to repeat each element of x. times will be recycled to the size of x.

...

These dots are for future extensions and must be empty.

error_call

The execution environment of a currently running function, e.g. caller_env(). The function will be mentioned in error messages as the source of the error. See the call argument of abort() for more information.

x_arg, times_arg

Argument names for errors.

Value

For vec_rep(), a vector the same type as x with size vec_size(x) * times.

For vec_rep_each(), a vector the same type as x with size sum(vec_recycle(times, vec_size(x))).

For vec_unrep(), a data frame with two columns, key and times. key is a vector with the same type as x, and times is an integer vector.

Details

Using vec_unrep() and vec_rep_each() together is similar to using base::rle() and base::inverse.rle(). The following invariant shows the relationship between the two functions:

compressed <- vec_unrep(x)
identical(x, vec_rep_each(compressed$key, compressed$times))

There are two main differences between vec_unrep() and base::rle():

  • vec_unrep() treats adjacent missing values as equivalent, while rle() treats them as different values.

  • vec_unrep() works along the size of x, while rle() works along its length. This means that vec_unrep() works on data frames by compressing repeated rows.

Dependencies

Examples

# Repeat the entire vector
vec_rep(1:2, 3)
#> [1] 1 2 1 2 1 2

# Repeat within each vector
vec_rep_each(1:2, 3)
#> [1] 1 1 1 2 2 2
x <- vec_rep_each(1:2, c(3, 4))
x
#> [1] 1 1 1 2 2 2 2

# After using `vec_rep_each()`, you can recover the original vector
# with `vec_unrep()`
vec_unrep(x)
#>   key times
#> 1   1     3
#> 2   2     4

df <- data.frame(x = 1:2, y = 3:4)

# `rep()` repeats columns of data frames, and returns lists
rep(df, each = 2)
#> $x
#> [1] 1 2
#> 
#> $x
#> [1] 1 2
#> 
#> $y
#> [1] 3 4
#> 
#> $y
#> [1] 3 4
#> 

# `vec_rep()` and `vec_rep_each()` repeat rows, and return data frames
vec_rep(df, 2)
#>   x y
#> 1 1 3
#> 2 2 4
#> 3 1 3
#> 4 2 4
vec_rep_each(df, 2)
#>   x y
#> 1 1 3
#> 2 1 3
#> 3 2 4
#> 4 2 4

# `rle()` treats adjacent missing values as different
y <- c(1, NA, NA, 2)
rle(y)
#> Run Length Encoding
#>   lengths: int [1:4] 1 1 1 1
#>   values : num [1:4] 1 NA NA 2

# `vec_unrep()` treats them as equivalent
vec_unrep(y)
#>   key times
#> 1   1     1
#> 2  NA     2
#> 3   2     1