unnest_ngrams {tidytext}

Wrapper around unnest_tokens for n-grams

Description

These functions are wrappers around unnest_tokens( token = "ngrams" ) and unnest_tokens( token = "skip_ngrams" ) .

Usage

unnest_ngrams(
  tbl,
  output,
  input,
  n = 3L,
  n_min = n,
  ngram_delim = " ",
  format = c("text", "man", "latex", "html", "xml"),
  to_lower = TRUE,
  drop = TRUE,
  collapse = NULL,
  ...
)

unnest_skip_ngrams(
  tbl,
  output,
  input,
  n_min = 1,
  n = 3,
  k = 1,
  format = c("text", "man", "latex", "html", "xml"),
  to_lower = TRUE,
  drop = TRUE,
  collapse = NULL,
  ...
)

Arguments

tbl

A data frame

output

Output column to be created as string or symbol.

input

Input column that gets split as string or symbol.

The output/input arguments are passed by expression and support quasiquotation; you can unquote strings and symbols.

n

The number of words in the n-gram. This must be an integer greater than or equal to 1.

n_min

The minimum number of words in the n-gram. This must be an integer greater than or equal to 1, and less than or equal to n.

ngram_delim

The separator between words in an n-gram.

format

Either "text", "man", "latex", "html", or "xml". When the format is "text", this function uses the tokenizers package. If not "text", this uses the hunspell tokenizer, and can tokenize only by "word".

to_lower

Whether to convert tokens to lowercase.

drop

Whether original input column should get dropped. Ignored if the original input and new output column have the same name.

collapse

A character vector of variables to collapse text across, or NULL.

For tokens like n-grams or sentences, text can be collapsed across rows within variables specified by collapse before tokenization. At tidytext 0.2.7, the default behavior for collapse = NULL changed to be more consistent. The new behavior is that text is not collapsed for NULL.

Grouping data specifies variables to collapse across in the same way as collapse but you cannot use both the collapse argument and grouped data. Collapsing applies mostly to token options of "ngrams", "skip_ngrams", "sentences", "lines", "paragraphs", or "regex".

...

Extra arguments passed on to tokenizers

k

For the skip n-gram tokenizer, the maximum skip distance between words. The function will compute all skip n-grams between 0 and k.

See Also

• unnest_tokens()

Examples

library(dplyr)
library(janeaustenr)

d <- tibble(txt = prideprejudice)

d %>%
  unnest_ngrams(word, txt, n = 2)

d %>%
  unnest_skip_ngrams(word, txt, n = 3, k = 1)