title: How do I print lda topic model and the word cloud of each of the topics
body: <pre><code>from nltk.tokenize import RegexpTokenizer
  from stop_words import get_stop_words
  from gensim import corpora, models
  import gensim
  import os
  from os import path
  from time import sleep
  import matplotlib.pyplot as plt
  import random
  from wordcloud import WordCloud, STOPWORDS
  tokenizer = RegexpTokenizer(r'\w+')
  en_stop = set(get_stop_words('en'))
  with open(os.path.join('c:\users\kaila\jobdescription.txt')) as f:
      Reader = f.read()
  
  Reader = Reader.replace("will", " ")
  Reader = Reader.replace("please", " ")
  
  
  texts = unicode(Reader, errors='replace')
  tdm = []
  
  raw = texts.lower()
  tokens = tokenizer.tokenize(raw)
  stopped_tokens = [i for i in tokens if not i in en_stop]
  tdm.append(stopped_tokens)
  
  dictionary = corpora.Dictionary(tdm)
  corpus = [dictionary.doc2bow(i) for i in tdm]
  sleep(3)
  ldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=8, id2word = dictionary)
  topics = ldamodel.print_topics(num_topics=8, num_words=200)
  for i in topics:
      print(i)
      wordcloud = WordCloud().generate(i)
      plt.imshow(wordcloud)
      plt.axis("off")
      plt.show()
  </code></pre>
  
  <p>The issue is with the word cloud. I cannot get the word cloud for each of the 8 topics. I would want an output which gives 8 word clouds for the 8 topics. 
  If anyone can help me regarding this issue, it will be great. </p>