Combine many data frames into one data frame

This pair of functions binds together data frames (and vectors), either row-wise or column-wise. Row-binding creates a data frame with common type across all arguments. Column-binding creates a data frame with common length across all arguments.

vec_rbind(..., .ptype = NULL)

vec_cbind(..., .ptype = NULL, .size = NULL)

Arguments

...	Data frames or vectors. vec_rbind() ignores names. vec_cbind() preserves outer names, combining with inner names if also present. NULL inputs are silently ignored. Empty (e.g. zero row) inputs will not appear in the output, but will affect the derived .ptype.
.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.
.size	If, NULL, the default, will determing the number of rows in vec_cbind() output by using the standard recycling rules. Alternatively, specify the desired number of rows, and any inputs of length 1 will be recycled appropriately.

Value

A data frame, or subclass of data frame.

If ... is a mix of different data frame subclases, vec_type2() will be used to determine the output type. For vec_rbind(), this will determine the type of the container and the type of each column; for vec_cbind() it only determines the type of the output container. If there are no non-NULL inputs, the result will be data.frame().

Invariants

• vec_size(vec_rbind(x, y)) == vec_size(x) + vec_size(y)

• vec_type(vec_rbind(x, y)) = vec_type_common(x, y)

• vec_size(vec_cbind(x, y)) == vec_size_common(x, y)

• vec_type(vec_cbind(x, y)) == vec_cbind(vec_type(x), vec_type(x))

See also

vec_c() for combining 1d vectors.

Examples

# row binding -----------------------------------------

# common columns are coerced to common class
vec_rbind(
  data.frame(x = 1),
  data.frame(x = FALSE)
)
#>   x
#> 1 1
#> 2 0

# unique columns are filled with NAs
vec_rbind(
  data.frame(x = 1),
  data.frame(y = "x")
)
#>    x    y
#> 1  1 <NA>
#> 2 NA    x

# null inputs are ignored
vec_rbind(
  data.frame(x = 1),
  NULL,
  data.frame(x = 2)
)
#>   x
#> 1 1
#> 2 2

# bare vectors are treated as rows
vec_rbind(
  c(x = 1, y = 2),
  c(x = 3)
)
#>   x  y
#> 1 1  2
#> 2 3 NA

# default names will be supplied if arguments are not named
vec_rbind(
  1:2,
  1:3,
  1:4
)
#> New names:
#>  -> ..1
#>  -> ..2
#> New names:
#>  -> ..1
#>  -> ..2
#>  -> ..3
#> New names:
#>  -> ..1
#>  -> ..2
#>  -> ..3
#>  -> ..4
#>   ..1 ..2 ..3 ..4
#> 1   1   2  NA  NA
#> 2   1   2   3  NA
#> 3   1   2   3   4

# column binding --------------------------------------

# each input is recycled to have common length
vec_cbind(
  data.frame(x = 1),
  data.frame(y = 1:3)
)
#>   x y
#> 1 1 1
#> 2 1 2
#> 3 1 3

# bare vectors are treated as columns
vec_cbind(
  data.frame(x = 1),
  y = letters[1:3]
)
#>   x y
#> 1 1 a
#> 2 1 b
#> 3 1 c

# outer names are combined with inner names
vec_cbind(
  x = data.frame(a = 1, b = 2),
  y = 1
)
#>   x..a x..b y
#> 1    1    2 1

# duplicate names are flagged
vec_cbind(x = 1, x = 2)
#> New names:
#> x -> x..1
#> x -> x..2
#>   x..1 x..2
#> 1    1    2