expand_grid() is heavily motivated by expand.grid().
Compared to expand.grid(), it:
Produces sorted output by varying the first column the slowest by default.
Returns a tibble, not a data frame.
Never converts strings to factors.
Does not add any additional attributes.
Can expand any generalised vector, including data frames.
Arguments
- ...
Name-value pairs. The name will become the column name in the output.
- .name_repair
One of
"check_unique","unique","universal","minimal","unique_quiet", or"universal_quiet". Seevec_as_names()for the meaning of these options.- .vary
One of:
"slowest"to vary the first column slowest. This produces sorted output and is generally the most useful."fastest"to vary the first column fastest. This matches the behavior ofexpand.grid().
Value
A tibble with one column for each input in .... The output will
have one row for each combination of the inputs, i.e. the size will be
equal to the product of the sizes of the inputs. This implies that if any
input has length 0, the output will have zero rows. The ordering of the
output depends on the .vary argument.
Examples
# Default behavior varies the first column "slowest"
expand_grid(x = 1:3, y = 1:2)
#> # A tibble: 6 × 2
#> x y
#> <int> <int>
#> 1 1 1
#> 2 1 2
#> 3 2 1
#> 4 2 2
#> 5 3 1
#> 6 3 2
# Vary the first column "fastest", like `expand.grid()`
expand_grid(x = 1:3, y = 1:2, .vary = "fastest")
#> # A tibble: 6 × 2
#> x y
#> <int> <int>
#> 1 1 1
#> 2 2 1
#> 3 3 1
#> 4 1 2
#> 5 2 2
#> 6 3 2
# Can also expand data frames
expand_grid(df = tibble(x = 1:2, y = c(2, 1)), z = 1:3)
#> # A tibble: 6 × 2
#> df$x $y z
#> <int> <dbl> <int>
#> 1 1 2 1
#> 2 1 2 2
#> 3 1 2 3
#> 4 2 1 1
#> 5 2 1 2
#> 6 2 1 3
# And matrices
expand_grid(x1 = matrix(1:4, nrow = 2), x2 = matrix(5:8, nrow = 2))
#> # A tibble: 4 × 2
#> x1[,1] [,2] x2[,1] [,2]
#> <int> <int> <int> <int>
#> 1 1 3 5 7
#> 2 1 3 6 8
#> 3 2 4 5 7
#> 4 2 4 6 8