Difference between revisions of "R: tidytext RPJP BAPPENAS"
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dtm_unigram <- DocumentTermMatrix(docs, control = list(tokenize="words", | dtm_unigram <- DocumentTermMatrix(docs, control = list(tokenize="words", | ||
removePunctuation = TRUE, | removePunctuation = TRUE, | ||
| − | stopwords = stopwords::stopwords("id", source = "stopwords-iso"), | + | stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel"), |
stemming = TRUE)) | stemming = TRUE)) | ||
dtm_bigram <- DocumentTermMatrix(docs, control = list(tokenize = BigramTokenizer, | dtm_bigram <- DocumentTermMatrix(docs, control = list(tokenize = BigramTokenizer, | ||
removePunctuation = TRUE, | removePunctuation = TRUE, | ||
| − | stopwords = stopwords::stopwords("id", source = "stopwords-iso"), | + | stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel"), |
stemming = TRUE)) | stemming = TRUE)) | ||
Revision as of 16:22, 6 November 2018
install.packages("xlsx")
install.packages("tm")
install.packages("wordcloud")
install.packages("ggplot2")
library(xlsx) library(tm) library(wordcloud) library(ggplot2)
library(tidyverse) library(tidytext) library(tm) directory <- "data-pdf" # create corpus from pdfs docs <- VCorpus(DirSource(directory), readerControl = list(reader = readPDF))
# docs <- VCorpus(DirSource("data", recursive=TRUE))
# Get the document term matrices
BigramTokenizer <- function(x) NGramTokenizer(x, Weka_control(min = 2, max = 2))
dtm_unigram <- DocumentTermMatrix(docs, control = list(tokenize="words",
removePunctuation = TRUE,
stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel"),
stemming = TRUE))
dtm_bigram <- DocumentTermMatrix(docs, control = list(tokenize = BigramTokenizer,
removePunctuation = TRUE,
stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel"),
stemming = TRUE))
inspect(dtm_unigram) inspect(dtm_bigram)
converted %>%
tidy() %>%
filter(!grepl("[0-9]+", term))
# converted adalah DocumentTermMatrix