corpus

I have the following code: # returns string w/o leading or trailing whitespace trim <- function (x) gsub("^\\s+|\\s+$", "", x) news_corpus <- Corpus(VectorSource(news_raw$text)) # a column of strings. corpus_clean <- tm_map(news_corpus, tolower) corpus_clean <- tm_map(corpus_clean, removeNumbers) corpus_clean <- tm_map(corpus_clean, removeWords, stopwords('english')) corpus_clean <- tm_map(corpus_clean, removePunctuation) corpus_clean <- tm_map(corpus_clean, stripWhitespace) corpus_clean <- tm_map(corpus_clean, trim) news_dtm <- DocumentTermMatrix(corpus_clean) # errors here When I run the

I am using the tm package to clean up some data using the following code: mycorpus <- Corpus(VectorSource(x)) mycorpus <- tm_map(mycorpus, removePunctuation) I then want to convert the corpus back into a data frame in order to export a text file that contains the data in the original format of a data frame. I have tried the following: dataframe <- as.data.frame(mycorpus) But this returns an error: "Error in as.data.frame.default.(mycorpus) : cannot coerce class "c(vcorpus, > corpus")" to a data.frame How can I convert a corpus into a data frame? MrFlick Your corpus is really just a character

I use following code and I get it form Classification using movie review corpus in NLTK/Python import string from itertools import chain from nltk.corpus import movie_reviews as mr from nltk.corpus import stopwords from nltk.probability import FreqDist from nltk.classify import NaiveBayesClassifier as nbc import nltk stop = stopwords.words('english') documents = [([w for w in mr.words(i) if w.lower() not in stop and w.lower() not in string.punctuation], i.split('/')[0]) for i in mr.fileids()] word_features = FreqDist(chain(*[i for i,j in documents])) word_features = word_features.keys()[:100]