vec_interleave() combines multiple vectors together, much like vec_c(), but does so in such a way that the elements of each vector are interleaved together.

It is a more efficient equivalent to the following usage of vec_c():

vec_interleave(x, y) == vec_c(x[1], y[1], x[2], y[2], ..., x[n], y[n])

## Usage

vec_interleave(
...,
.ptype = NULL,
.name_spec = NULL,
.name_repair = c("minimal", "unique", "check_unique", "universal", "unique_quiet",
"universal_quiet")
)

## Arguments

...

Vectors to interleave. These will be recycled to a common size.

.ptype

If NULL, the default, the output type is determined by computing the common type across all elements of ....

Alternatively, you can supply .ptype to give the output known type. If getOption("vctrs.no_guessing") is TRUE you must supply this value: this is a convenient way to make production code demand fixed types.

.name_spec

A name specification for combining inner and outer names. This is relevant for inputs passed with a name, when these inputs are themselves named, like outer = c(inner = 1), or when they have length greater than 1: outer = 1:2. By default, these cases trigger an error. You can resolve the error by providing a specification that describes how to combine the names or the indices of the inner vector with the name of the input. This specification can be:

• A function of two arguments. The outer name is passed as a string to the first argument, and the inner names or positions are passed as second argument.

• An anonymous function as a purrr-style formula.

• A glue specification of the form "{outer}_{inner}".

• An rlang::zap() object, in which case both outer and inner names are ignored and the result is unnamed.

See the name specification topic.

.name_repair

How to repair names, see repair options in vec_as_names().

## Dependencies

### vctrs dependencies

• list_unchop()

## Examples

# The most common case is to interleave two vectors
vec_interleave(1:3, 4:6)
#> [1] 1 4 2 5 3 6

# But you aren't restricted to just two
vec_interleave(1:3, 4:6, 7:9, 10:12)
#>  [1]  1  4  7 10  2  5  8 11  3  6  9 12

# You can also interleave data frames
x <- data_frame(x = 1:2, y = c("a", "b"))
y <- data_frame(x = 3:4, y = c("c", "d"))

vec_interleave(x, y)
#> # A tibble: 4 × 2
#>       x y
#>   <int> <chr>
#> 1     1 a
#> 2     3 c
#> 3     2 b
#> 4     4 d