List the most (or least) frequently occurring features in a dfm, either as a whole or separated by document.
topfeatures(
x,
n = 10,
decreasing = TRUE,
scheme = c("count", "docfreq"),
groups = NULL
)the object whose features will be returned
how many top features should be returned
If TRUE, return the n most frequent features;
otherwise return the n least frequent features
one of count for total feature frequency (within
group if applicable), or docfreq for the document frequencies
of features
grouping variable for sampling, equal in length to the number
of documents. This will be evaluated in the docvars data.frame, so that
docvars may be referred to by name without quoting. This also changes
previous behaviours for groups. See news(Version >= "3.0", package = "quanteda") for details.
A named numeric vector of feature counts, where the names are the
feature labels, or a list of these if groups is given.
dfmat1 <- corpus_subset(data_corpus_inaugural, Year > 1980) |>
tokens(remove_punct = TRUE) |>
dfm()
dfmat2 <- dfm_remove(dfmat1, stopwords("en"))
# most frequent features
topfeatures(dfmat1)
#> the and of to we our a in is that
#> 1201 1023 838 649 627 608 472 379 329 317
topfeatures(dfmat2)
#> us america must people new world nation can time one
#> 192 116 109 99 96 95 91 88 77 76
# least frequent features
topfeatures(dfmat2, decreasing = FALSE)
#> hatfield mondale baker moomaw momentous occurrence
#> 1 1 1 1 1 1
#> routinely unique really every-4-year
#> 1 1 1 1
# top features of individual documents
topfeatures(dfmat2, n = 5, groups = docnames(dfmat2))
#> Error in eval(groupsub): object 'dfmat2' not found
# grouping by president last name
topfeatures(dfmat2, n = 5, groups = President)
#> $Biden
#> us america can one nation
#> 27 18 16 15 12
#>
#> $Bush
#> freedom us nation america can
#> 36 27 27 27 24
#>
#> $Clinton
#> us new world must america
#> 40 38 28 28 26
#>
#> $Obama
#> us must can nation people
#> 44 25 20 18 18
#>
#> $Reagan
#> us government people world one
#> 52 29 25 23 22
#>
#> $Trump
#> america american people country one
#> 18 11 10 9 8
#>
# features by document frequencies
tail(topfeatures(dfmat1, scheme = "docfreq", n = 200))
#> unity like cannot even challenges schools
#> 8 8 8 8 8 8