Build out n-grams for multiple text inputs and keep the n most frequent combinations.
ngrams(text, ngram = c(2, 3), top = 10, stop_words = NULL, ...)Character vector
Integer vector. Number of continuous n items in text.
Integer. Keep n most frequent ngrams only.
Character vector. Words to exclude from text. Example: if you want to exclude "a", whenever that word appears it will be excluded, but when the letter "a" appears in a word, it will remain.
Additional parameters passed to remove_stopwords.
data.frame with ngrams and counters, sorted by frequency.
Other Text Mining:
cleanNames(),
cleanText(),
remove_stopwords(),
replaceall(),
sentimentBreakdown(),
textCloud(),
textFeats(),
textTokenizer(),
topics_rake()
# NOT RUN {
# You must have \code{tidytext} library to use this auxiliary function:
# }
# NOT RUN {
women <- read.csv("https://bit.ly/3mXJOOi")
x <- women$description
ngrams(x, ngram = c(2,3), top = 3)
ngrams(x, ngram = 2, top = 6, stop_words = c("a","is","of","the"))
# }
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