• 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)

vec_rep_each(x, 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.

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