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Create a data frame from all combinations of the inputs

Source: R/expand.R
vec_expand_grid.Rd

vec_expand_grid() creates a new data frame by creating a grid of all possible combinations of the input vectors. It is inspired by expand.grid(). Compared with expand.grid(), it:

  • Produces sorted output by default by varying the first column the slowest, rather than the fastest. Control this with .vary.

  • Never converts strings to factors.

  • Does not add additional attributes.

  • Drops NULL inputs.

  • Can expand any vector type, including data frames and records.

Usage

vec_expand_grid(
  ...,
  .vary = "slowest",
  .name_repair = "check_unique",
  .error_call = current_env()
)

Arguments

...

Name-value pairs. The name will become the column name in the resulting data frame.

.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 of expand.grid().

.name_repair

One of "check_unique", "unique", "universal", "minimal", "unique_quiet", or "universal_quiet". See vec_as_names() for the meaning of these options.

.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.

Value

A data frame with as many columns as there are inputs in ... and as many rows as the prod() of the sizes of the inputs.

Details

If any input is empty (i.e. size 0), then the result will have 0 rows.

If no inputs are provided, the result is a 1 row data frame with 0 columns. This is consistent with the fact that prod() with no inputs returns 1.

Examples

vec_expand_grid(x = 1:2, y = 1:3)
#>   x y
#> 1 1 1
#> 2 1 2
#> 3 1 3
#> 4 2 1
#> 5 2 2
#> 6 2 3

# Use `.vary` to match `expand.grid()`:
vec_expand_grid(x = 1:2, y = 1:3, .vary = "fastest")
#>   x y
#> 1 1 1
#> 2 2 1
#> 3 1 2
#> 4 2 2
#> 5 1 3
#> 6 2 3

# Can also expand data frames
vec_expand_grid(
  x = data_frame(a = 1:2, b = 3:4),
  y = 1:4
)
#> Warning: corrupt data frame: columns will be truncated or padded with NAs
#>                                                                                         x
#> 1                                                 \033[38;5;246m# A tibble: 8 × 2\033[39m
#> 2                                                                                 a     b
#> 3   \033[3m\033[38;5;246m<int>\033[39m\033[23m \033[3m\033[38;5;246m<int>\033[39m\033[23m
#> 4                                                     \033[38;5;250m1\033[39m     1     3
#> 5                                                     \033[38;5;250m2\033[39m     1     3
#> 6                                                     \033[38;5;250m3\033[39m     1     3
#> 7                                                     \033[38;5;250m4\033[39m     1     3
#> 8                                                     \033[38;5;250m5\033[39m     2     4
#>   y
#> 1 1
#> 2 2
#> 3 3
#> 4 4
#> 5 1
#> 6 2
#> 7 3
#> 8 4