How do I remove words from a wordcloud?

问题:

I'm creating a wordcloud using the wordcloud package in R, and the help of "Word Cloud in R".

I can do this easily enough, but I want to remove words from this wordcloud. I have words in a file (actually an excel file, but I could change that), and I want to exclude all these words, of which there are a couple hundred. Any suggestions?

require(XML)
require(tm)
require(wordcloud)
require(RColorBrewer)
ap.corpus=Corpus(DataframeSource(data.frame(as.character(data.merged2[,6]))))
ap.corpus=tm_map(ap.corpus, removePunctuation)
ap.corpus=tm_map(ap.corpus, tolower)
ap.corpus=tm_map(ap.corpus, function(x) removeWords(x, stopwords("english")))
ap.tdm=TermDocumentMatrix(ap.corpus)
ap.m=as.matrix(ap.tdm)
ap.v=sort(rowSums(ap.m),decreasing=TRUE)
ap.d=data.frame(word = names(ap.v),freq=ap.v)
table(ap.d$freq)

回答1:

@Tyler Rinker has given the answer, just add another line of removeWords(), but here's a bit more detail.

Let's say your excel file is called nuts.xls and has a single column of words like this

stopwords
peanut
cashew
walnut
almond
macadamia

In R you might proceed like this

     library(gdata) # package with xls import function
     library(tm)
     # now load the excel file with the custom stoplist, note a few of the arguments here 
     # to clean the data by removing spaces that excel seems to insert and prevent it from 
     # importing the characters as factors. You can use any args from read.table(), which is
     # handy
     nuts<-read.xls("nuts.xls", header=TRUE, stringsAsFactor=FALSE, strip.white=TRUE)

     # now make some words to build a corpus to test for a two-step stopword removal process...
     words1<- c("peanut, cashew, walnut, macadamia, apple, pear, orange, lime, mandarin, and, or, but")
     words2<- c("peanut, cashew, walnut, almond, apple, pear, orange, lime, mandarin, if, then, on")
     words3<- c("peanut, walnut, almond, macadamia, apple, pear, orange, lime, mandarin, it, as, an")
     words.all<-data.frame(rbind(words1,words2,words3))
     words.corpus<-Corpus(DataframeSource((words.all)))

     # now remove the standard list of stopwords, like you've already worked out
     words.corpus.nostopwords <- tm_map(words.corpus, removeWords, stopwords("english"))
     # now remove the second set of stopwords, this time your custom set from the excel file, 
     # note that it has to be a reference to a character vector containing the custom stopwords
     words.corpus.nostopwords <- tm_map(words.corpus.nostopwords, removeWords, nuts$stopwords)

     # have a look to see if it worked
     inspect(words.corpus.nostopwords)
     A corpus with 3 text documents

     The metadata consists of 2 tag-value pairs and a data frame
     Available tags are:
          create_date creator 
     Available variables in the data frame are:
          MetaID 

     $words1
        , , , , apple, pear, orange, lime, mandarin, , , 

     $words2
        , , , , apple, pear, orange, lime, mandarin, , , 

     $words3
        , , , , apple, pear, orange, lime, mandarin, , , 

Success! the standard stopwords are gone, as are the words in the custom list from the excel file. Undoubtedly there are other ways to do it.

回答2:

Convert the data you want to make a datacloud into a data frame. Create a CSV file with the words you want to be eliminated and read it as a data frame. You can then make an anti_join:

allWords = as.data.frame(table(bigWords$Words))

wordsToAvoid = read.csv("wordsToDrop.csv")

finalWords = anti_join(allWords, wordsToAvoid, by = "Words")