Data frame type

A data frame with typed columns. Each column is validated as a vector, so the usual length and constraint syntax applies to it; a column that comes back the wrong length for the number of rows is an error, as is a missing column.

Usage

frame(..., .extra = c("ignore", "forbid"))

Arguments

...

Named columns, one type each.

.extra

"ignore" (default) or "forbid", for columns that were not declared.

Value

A type.

Details

While parsing JSON, an array of objects is reshaped into a data frame – and a row that is missing a key is reported by name instead of quietly producing a list column.

See also

list_of()

Examples

roster <- frame(id = int, name = chr)
str(roster(data.frame(id = c(1, 2), name = c("Ada", "Bob"))))
#> 'data.frame':	2 obs. of  2 variables:
#>  $ id  : int  1 2
#>  $ name: chr  "Ada" "Bob"

try(roster(data.frame(id = 1)))
#> Error : 1 validation problem in frame(id, name)
#>   $name  expected chr, got <missing column>
try(frame(id = int, .extra = "forbid")(data.frame(id = 1L, junk = 2)))
#> Error : 1 validation problem in frame(id)
#>   $junk  expected <no such column>, got num[1] 2

from_json(roster, '[{"id": 1, "name": "Ada"}, {"id": 2, "name": "Bob"}]')
#>   id name
#> 1  1  Ada
#> 2  2  Bob
try(from_json(roster, '[{"id": 1}]'))
#> Error : 1 validation problem in frame(id, name)
#>   $name  expected chr, got <missing in row 1>
nrow(from_json(roster, "[]"))
#> [1] 0