Returns document subsets of a dfm that meet certain conditions,
including direct logical operations on docvars (document-level variables).
dfm_subset functions identically to subset.data.frame(),
using non-standard evaluation to evaluate conditions based on the
docvars in the dfm.
dfm_subset(
x,
subset,
min_ntoken = NULL,
max_ntoken = NULL,
drop_docid = TRUE,
...
)dfm object to be subsetted.
logical expression indicating the documents to keep: missing values are taken as false.
minimum and maximum lengths of the documents to extract.
if TRUE, docid for documents are removed as the result
of subsetting.
not used
dfm object, with a subset of documents (and docvars) selected according to arguments
To select or subset features, see dfm_select() instead.
When select is a dfm, then the returned dfm will be equal in
document dimension and order to the dfm used for selection. This is the
document-level version of using dfm_select() where
pattern is a dfm: that function matches features, while
dfm_subset will match documents.
corp <- corpus(c(d1 = "a b c d", d2 = "a a b e",
d3 = "b b c e", d4 = "e e f a b"),
docvars = data.frame(grp = c(1, 1, 2, 3)))
dfmat <- dfm(tokens(corp))
# selecting on a docvars condition
dfm_subset(dfmat, grp > 1)
#> Document-feature matrix of: 2 documents, 6 features (41.67% sparse) and 1 docvar.
#> features
#> docs a b c d e f
#> d3 0 2 1 0 1 0
#> d4 1 1 0 0 2 1
# selecting on a supplied vector
dfm_subset(dfmat, c(TRUE, FALSE, TRUE, FALSE))
#> Document-feature matrix of: 2 documents, 6 features (41.67% sparse) and 1 docvar.
#> features
#> docs a b c d e f
#> d1 1 1 1 1 0 0
#> d3 0 2 1 0 1 0