Bind the term frequency and inverse document frequency of a tidy text dataset to the dataset
Calculate and bind the term frequency and inverse document frequency of a tidy text dataset, along with the product, tf-idf, to the dataset. Each of these values are added as columns. This function supports non-standard evaluation through the tidyeval framework.
bind_tf_idf(tbl, term, document, n)
tbl |
A tidy text dataset with one-row-per-term-per-document |
term |
Column containing terms as string or symbol |
document |
Column containing document IDs as string or symbol |
n |
Column containing document-term counts as string or symbol |
The arguments term, document, and n
are passed by expression and support quasiquotation;
you can unquote strings and symbols.
If the dataset is grouped, the groups are ignored but are retained.
The dataset must have exactly one row per document-term combination for this to work.
library(dplyr) library(janeaustenr) book_words <- austen_books() %>% unnest_tokens(word, text) %>% count(book, word, sort = TRUE) book_words # find the words most distinctive to each document book_words %>% bind_tf_idf(word, book, n) %>% arrange(desc(tf_idf))
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