зеркало из https://github.com/microsoft/wpa.git
57 строки
1.6 KiB
R
57 строки
1.6 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/tm_wordcloud.R
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\name{tm_wordcloud}
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\alias{tm_wordcloud}
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\title{Generate a wordcloud}
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\usage{
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tm_wordcloud(
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data,
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stopwords = NULL,
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seed = 100,
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keep = 100,
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return = "plot",
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...
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)
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}
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\arguments{
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\item{data}{A Meeting Query dataset in the form of a data frame.}
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\item{stopwords}{A single-column data frame labelled 'word' containing custom stopwords to remove.}
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\item{seed}{A numeric vector to set seed for random generation.}
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\item{keep}{A numeric vector specifying maximum number of words to keep.}
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\item{return}{Character vector specifying what to return, defaults to "plot".
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Valid inputs are "plot" and "table". A "table" returns the data used to generate the wordcloud.}
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\item{...}{Additional parameters to be passed to \code{ggwordcloud::geom_text_wordcloud()}#'}
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}
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\description{
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Generate a wordcloud with the meeting query.
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This is a sub-function that feeds into \code{meeting_tm_report()}.
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}
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\details{
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Uses the {ggwordcloud} package for the underlying implementation, thus
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returning a ggplot. Additional layers can be added onto the plot using
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a ggplot \code{+} syntax.
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The recommendation is not to return over 100 words in a word cloud.
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This function uses \code{tm_clean()} as the underlying data wrangling function.
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There is an option to remove stopwords by passing a data frame into the \code{stopwords}
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argument.
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}
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\examples{
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tm_wordcloud(mt_data, keep = 30)
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}
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\seealso{
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Other Text-mining:
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\code{\link{meeting_tm_report}()},
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\code{\link{subject_validate_report}()},
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\code{\link{tm_clean}()},
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\code{\link{tm_cooc}()},
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\code{\link{tm_freq}()}
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}
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\concept{Text-mining}
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