title: Python ,faster computation
body: <p>i am trying to read a dataset and apply some information retrieval code. 
  this code is supposed to read a list of strings calculate and present the 10 most frequently used words, along with their frequencies. The code seems to be working but since the dataset is very large, it takes forever to compute the results(particularly for line 15). any suggestions on how to make it perform faster? Thanks</p>
  
  <pre><code>Summaries_file = 'data/aspirin__Summaries.pkl.bz2'
  Summaries = pickle.load( bz2.BZ2File( Summaries_file, 'rb' ) )
  paper = namedtuple( 'paper', ['title', 'authors', 'year', 'doi'] )
  for (id, paper_info) in Summaries.items():
      Summaries[id] = paper( *paper_info )
  from collections import OrderedDict
  the_list = []
  a=[]
  v=''
  for p in Summaries: 
      my_list = (Summaries[p].title)
      the_list.append(my_list)
  a = " ".join(the_list).split()
  wordfreq = []
  for w in a:
      wordfreq.append(a.count(w))
  
  final = (sorted([i for i in zip(a, wordfreq)],reverse=True,key=lambda x:x[1]))
  
  s = []
  for i in final:
     if i not in s:
        s.append(i)
  print(s[0:10])
  </code></pre>