Difference between revisions of "R: tidytext RPJP BAPPENAS"

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Line 1: Line 1:
 +
install.packages("xlsx")
 +
install.packages("tm")
 +
install.packages("wordcloud")
 +
install.packages("ggplot2")
 +
 +
library(xlsx)
 +
library(tm)
 +
library(wordcloud)
 +
library(ggplot2)
  
 
  library(tidyverse)
 
  library(tidyverse)

Revision as of 12:49, 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 = stopwords("english"), 
    stemming = TRUE))
dtm_bigram <- DocumentTermMatrix(docs, control = list(tokenize = BigramTokenizer,
    removePunctuation = TRUE,
    stopwords = stopwords("english"),
    stemming = TRUE))
inspect(dtm_unigram)
inspect(dtm_bigram)


converted %>%
  tidy() %>%
  filter(!grepl("[0-9]+", term))
# converted adalah DocumentTermMatrix



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