quanteda (version 1.5.2)

corpus_trim: 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_trim(
  x,
  what = c("sentences", "paragraphs", "documents"),
  min_ntoken = 1,
  max_ntoken = NULL,
  exclude_pattern = NULL
)
char_trim(
  x,
  what = c("sentences", "paragraphs", "documents"),
  min_ntoken = 1,
  max_ntoken = NULL,
  exclude_pattern = NULL
)

Arguments

x

corpus or character object whose sentences will be selected.

what

units of trimming, "sentences" or "paragraphs", or "documents"

min_ntoken, max_ntoken

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

Value

a corpus or character vector equal in length to the input. 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. This is a single sentence.  Short sentence. Three word sentence.",
         "PAGE 2. Very short! Shorter.",
         "Very long sentence, with multiple parts, separated by commas.  PAGE 3.")
corp <- corpus(txt, docvars = data.frame(serial = 1:3))
texts(corp)

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

# trimming character objects
char_trim(txt, "sentences", min_ntoken = 3)
char_trim(txt, "sentences", exclude_pattern = "sentence\\.")
# }

Run the code above in your browser using DataCamp Workspace