text_unnest_remove_stem_words: Pre-clean consultation responses
In DataS-DHSC/consultations: Re-usable functions for describing the responses to a public consultation or call for evidence
Description
Usage
Arguments
Details
Value
Examples
View source: R/text_unnest_remove_stem_words.R
Description
Takes a dataframe with a free-text column as input. Unnests words from the free text, removes stopwords, profanity, and number-only words,
removes an optional custom list of words, and stems words (using hunspell) so they can be grouped better.
Usage
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text_unnest_remove_stem_words(
data,
text_col,
token = "words",
custom_words = c(""),
...
)
Arguments
data
dataframe of responses
text_col
name of column containing free text to be analysed
token
what text entity to be analysed? by default word-by-word, but other options are defined in tidytext::unnest_tokens
Details
Note that, although you may choose a token other than "words" (like "sentences"), the word removal and stemming expects word tokens only.
Value
dataframe with stemmed, unnested words with removed words
Examples
1
text_unnest_remove_stem_words(dummy_response, colnames(dummy_response)[7], "words")
DataS-DHSC/consultations documentation built on Jan. 28, 2022, 1:56 a.m.
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Description Usage Arguments Details Value Examples
View source: R/text_unnest_remove_stem_words.R
Description
Takes a dataframe with a free-text column as input. Unnests words from the free text, removes stopwords, profanity, and number-only words, removes an optional custom list of words, and stems words (using hunspell) so they can be grouped better.
Usage
1 2 3 4 5 6 7 | text_unnest_remove_stem_words(
data,
text_col,
token = "words",
custom_words = c(""),
...
)
|
Arguments
data |
dataframe of responses |
text_col |
name of column containing free text to be analysed |
token |
what text entity to be analysed? by default word-by-word, but other options are defined in tidytext::unnest_tokens |
Details
Note that, although you may choose a token other than "words" (like "sentences"), the word removal and stemming expects word tokens only.
Value
dataframe with stemmed, unnested words with removed words
Examples
1 | text_unnest_remove_stem_words(dummy_response, colnames(dummy_response)[7], "words")
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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