Object builders

Functions to build or re-build core objects, or to upgrade earlier versions of these objects to the current format.

Usage

build_dfm(
  x,
  features,
  docvars = data.frame(),
  meta = list(),
  class = NULL,
  ...
)

rebuild_dfm(x, attrs)

upgrade_dfm(x)

build_tokens(
  x,
  types,
  padding = TRUE,
  docvars = data.frame(),
  meta = list(),
  class = NULL,
  ...
)

rebuild_tokens(x, attrs)

upgrade_tokens(x)

build_corpus(x, docvars = data.frame(), meta = list(), class = NULL, ...)

rebuild_corpus(x, attrs)

upgrade_corpus(x)

build_dictionary2(x, meta = list(), class = "dictionary2", ...)

rebuild_dictionary2(x, attrs)

upgrade_dictionary2(x)

build_fcm(
  x,
  features1,
  features2 = features1,
  meta = list(),
  class = "fcm",
  ...
)

rebuild_fcm(x, attrs)

upgrade_fcm(x)

Arguments

x

an input corpus, tokens, dfm, fcm or dictionary object.

features

character for feature of resulting dfm.

docvars

data.frame for document level variables created by make_docvars(). Names of documents are extracted from the docname_ column.

meta

list for meta fields

class

class labels to be attached to the object.

...

values saved in the object meta fields. They overwrite values passed via meta. If not specified, default values in make_meta() will be used.

attrs

a list of attributes to be reassigned

types

character for types of resulting the tokens object.

padding

logical indicating if the tokens object contains paddings.

features1

character for row feature of resulting fcm.

features2

character for column feature of resulting fcm iff. different from feature1

Examples

quanteda:::build_tokens(
    list(c(1, 2, 3), c(4, 5, 6)),
    docvars = quanteda:::make_docvars(n = 2L),
    types = c("a", "b", "c", "d", "e", "f"),
    padding = FALSE
)
#> Tokens consisting of 2 documents.
#> text1 :
#> [1] "a" "b" "c"
#> 
#> text2 :
#> [1] "d" "e" "f"
#> 
quanteda:::build_corpus(
    c("a b c", "d e f"),
    docvars = quanteda:::make_docvars(n = 2L),
    unit = "sentence"
)
#> Corpus consisting of 2 documents.
#> text1 :
#> "a b c"
#> 
#> text2 :
#> "d e f"
#>