These functions are wrappers around unnest_tokens( token = "sentences" )
unnest_tokens( token = "lines" )
and unnest_tokens( token = "paragraphs" )
.
unnest_sentences(
tbl,
output,
input,
strip_punct = FALSE,
format = c("text", "man", "latex", "html", "xml"),
to_lower = TRUE,
drop = TRUE,
collapse = NULL,
...
)unnest_lines(
tbl,
output,
input,
format = c("text", "man", "latex", "html", "xml"),
to_lower = TRUE,
drop = TRUE,
collapse = NULL,
...
)
unnest_paragraphs(
tbl,
output,
input,
paragraph_break = "\n\n",
format = c("text", "man", "latex", "html", "xml"),
to_lower = TRUE,
drop = TRUE,
collapse = NULL,
...
)
A data frame
Output column to be created as string or symbol.
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.
Should punctuation be stripped?
Either "text", "man", "latex", "html", or "xml". If not text, this uses the hunspell tokenizer, and can tokenize only by "word"
Whether to convert tokens to lowercase. If tokens include
URLS (such as with token = "tweets"
), such converted URLs may no
longer be correct.
Whether original input column should get dropped. Ignored if the original input and new output column have the same name.
Whether to combine text with newlines first in case tokens (such as sentences or paragraphs) span multiple lines. If NULL, collapses when token method is "ngrams", "skip_ngrams", "sentences", "lines", "paragraphs", or "regex".
Extra arguments passed on to tokenizers
A string identifying the boundary between two paragraphs.
# NOT RUN {
library(dplyr)
library(janeaustenr)
d <- tibble(txt = prideprejudice)
d %>%
unnest_sentences(word, txt)
# }
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