Difference between revisions of "R: tidytext RPJP BAPPENAS"

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Line 23: Line 23:
 
  dtm_unigram <- DocumentTermMatrix(docs, control = list(tokenize="words",  
 
  dtm_unigram <- DocumentTermMatrix(docs, control = list(tokenize="words",  
 
     removePunctuation = TRUE,  
 
     removePunctuation = TRUE,  
     stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel"),
+
     stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel","pada","dan"),
 
     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 = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel"),
+
     stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel","pada","dan"),
 
     stemming = TRUE))
 
     stemming = TRUE))
  

Revision as of 16:24, 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","pada","dan"),
    stemming = TRUE))
dtm_bigram <- DocumentTermMatrix(docs, control = list(tokenize = BigramTokenizer,
    removePunctuation = TRUE,
    stopwords = c(stopwords::stopwords("id", source = "stopwords-iso"),"tabel","pada","dan"),
    stemming = TRUE))
inspect(dtm_unigram)
inspect(dtm_bigram)


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



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