quanteda (version 1.1.1)

corpus_trimsentences: Remove sentences based on their token lengths or a pattern match

Description

Removes sentences from a corpus or a character vector shorter than a specified length.

Usage

corpus_trimsentences(x, min_length = 1, max_length = 10000,
  exclude_pattern = NULL, return_tokens = FALSE)
char_trimsentences(x, min_length = 1, max_length = 10000,
  exclude_pattern = NULL)

Arguments

x

corpus or character object whose sentences will be selected.

min_length, max_length

minimum and maximum lengths in word tokens (excluding punctuation)

exclude_pattern

a stringi regular expression whose match (at the sentence level) will be used to exclude sentences

return_tokens

if TRUE, return tokens object of sentences after trimming, otherwise return the input object type with the trimmed sentences removed.

Value

a corpus or character vector equal in length to the input, or a tokenized set of sentences if . If the input was a corpus, then the all docvars and metadata are preserved. For documents whose sentences have been removed entirely, a null string ("") will be returned.

Examples

# NOT RUN {
txt <- c("PAGE 1. A single sentence.  Short sentence. Three word sentence.",
         "PAGE 2. Very short! Shorter.",
         "Very long sentence, with three parts, separated by commas.  PAGE 3.")
mycorp <- corpus(txt, docvars = data.frame(serial = 1:3))
texts(mycorp)

# exclude sentences shorter than 3 tokens
texts(corpus_trimsentences(mycorp, min_length = 3))
# exclude sentences that start with "PAGE <digit(s)>"
texts(corpus_trimsentences(mycorp, exclude_pattern = "^PAGE \\d+"))

# on a character
char_trimsentences(txt, min_length = 3)
char_trimsentences(txt, min_length = 3)
char_trimsentences(txt, exclude_pattern = "sentence\\.")
# }