Produces counts and document frequencies summaries of the features in a dfm, optionally grouped by a docvars variable or other supplied grouping variable.

textstat_frequency(x, n = NULL, groups = NULL)

## Arguments

x a dfm object (optional) integer specifying the top n features to be returned, within group if groups is specified either: a character vector containing the names of document variables to be used for grouping; or a factor or object that can be coerced into a factor equal in length or rows to the number of documents. See groups for details.

## Value

a data.frame containing the following variables:

feature

(character) the feature

frequency

count of the feature

rank

rank of the feature, where 1 indicates the greatest frequency

docfreq

document frequency of the feature, as a count (the number of documents in which this feature occurred at least once)

docfreq

document frequency of the feature, as a count

group

(only if groups is specified) the label of the group. If the features have been grouped, then all counts, ranks, and document frequencies are within group. If groups is not specified, the group column is omitted from the returned data.frame.

textstat_frequency returns a data.frame of features and their term and document frequencies within groups.

## Examples

dfm1 <- dfm(c("a a b b c d", "a d d d", "a a a"))
textstat_frequency(dfm1)#>   feature frequency rank docfreq group
#> 1       a         6    1       3   all
#> 2       d         4    2       2   all
#> 3       b         2    3       1   all
#> 4       c         1    4       1   alltextstat_frequency(dfm1, groups = c("one", "two", "one"))#>   feature frequency rank docfreq group
#> 1       a         5    1       2   one
#> 2       b         2    2       1   one
#> 3       c         1    3       1   one
#> 4       d         1    4       1   one
#> 5       d         3    1       1   two
#> 6       a         1    2       1   two
corpus_subset(data_corpus_inaugural, President == "Obama") %>%
dfm(remove_punct = TRUE, remove = stopwords("english"))
head(freq, 10)#>    feature frequency rank docfreq group
#> 1       us        44    1       2   all
#> 2     must        25    2       2   all
#> 3      can        20    3       2   all
#> 4   nation        18    4       2   all
#> 5   people        18    5       2   all
#> 6      new        17    6       2   all
#> 7     time        16    7       2   all
#> 8    every        15    8       2   all
#> 9  america        14    9       2   all
#> 10     now        11   10       2   all
# plot 20 most frequent words
library("ggplot2")
ggplot(freq[1:20, ], aes(x = reorder(feature, frequency), y = frequency)) +
geom_point() +
coord_flip() +
labs(x = NULL, y = "Frequency")
# plot relative frequencies by group
dfm_weight_pres <- data_corpus_inaugural %>%
corpus_subset(Year > 2000) %>%
dfm(remove = stopwords("english"), remove_punct = TRUE) %>%
dfm_weight(scheme = "prop")

# calculate relative frequency by president
freq_weight <- textstat_frequency(dfm_weight_pres, n = 10,
groups = "President")

# plot frequencies
ggplot(data = freq_weight, aes(x = nrow(freq_weight):1, y = frequency)) +
geom_point() +
facet_wrap(~ group, scales = "free") +
coord_flip() +
scale_x_continuous(breaks = nrow(freq_weight):1,
labels = freq_weight\$feature) +
labs(x = NULL, y = "Relative frequency")