word-cloud

I am trying to make a word cloud of publications keywords. for example: Educational data mining; collaborative learning; computer science...etc My current code is as the following: KeywordsCorpus <- Corpus(VectorSource(subset(Words$Author.Keywords, Words$Year==2012))) KeywordsCorpus <- tm_map(KeywordsCorpus, removePunctuation) KeywordsCorpus <- tm_map(KeywordsCorpus, removeNumbers) # added tolower KeywordsCorpus <- tm_map(KeywordsCorpus, tolower) KeywordsCorpus <- tm_map(KeywordsCorpus, removeWords, stopwords("english")) # moved stripWhitespace KeywordsCorpus <- tm_map(KeywordsCorpus,

I've created a simple wordcloud: require(wordcloud) words <- c('affectionate', 'ambitious', 'anxious', 'articulate', 'artistic', 'caring', 'contented', 'creative', 'cynical', 'daring', 'dependable', 'easygoing', 'energetic', 'funny', 'generous', 'genuine', 'goodlistener', 'goodtalker', 'happy', 'hardworking', 'humerous', 'impulsive', 'intelligent', 'kind', 'loyal', 'modest', 'optimistic', 'outgoing', 'outrageous', 'passionate', 'perceptive', 'physicallyfit', 'quiet', 'rational', 'respectful', 'romantic', 'shy', 'spiritual', 'spontaneous', 'sweet', 'thoughtful', 'warm') freqs <- c(134, 53, 0, 5

i have a dataframe as bellow Int64Index: 14830 entries, 25791 to 10668 Data columns (total 2 columns): word 14830 non-null object coef 14830 non-null float64 dtypes: float64(1), object(1) i try to make word cloud with coef as a frequency instead count for ample text = df['word'] WordCloud.generate_from_text(text) TypeError: generate_from_text() missing 1 required positional argument: 'text' or text = np.array(df['word']) WordCloud.generate_from_text(text) TypeError: generate_from_text() missing 1 required positional argument: 'text' How can i improve this code & made word cloud like this from

I am modifying this code: https://github.com/jasondavies/d3-cloud <script> d3.layout.cloud().size([300, 300]) .words([ "Hello", "world", "normally", "you", "want", "more", "words", "than", "this"].map(function(d) { return {text: d, size: 10 + Math.random() * 90}; })) .rotate(function() { return ~~(Math.random() * 2) * 90; }) .fontSize(function(d) { return d.size; }) .on("end", draw) .start(); function draw(words) { d3.select("body").append("svg") .attr("width", 300) .attr("height", 300) .append("g") .attr("transform", "translate(150,150)") .selectAll("text") .data(words) .enter().append("text"

I deal a bit with textual data across various grouping variables. I'm thinking of creating a method to make faceted wordcloud plots using Ian Fellows' wordcloud package. I like the way ggplot2 facets social variables. I'm deciding how to approach this problem (faceted wordcloud plot). Is it possible to use Fellows' work as a geom (I've never made a geom but may learn if this is doable) or will ggplot not play nicely because one is grid and one is base (and wordcloud also uses some C coding) or some other problem? How difficult is this (I know this is dependent on my abilities but would like

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,