title: Association rules with pandas dataframe
body: <p>I have a dataframe like this</p>
  
  <pre><code>df = pd.DataFrame(data=[980,169,104,74], columns=['Count'], index=['X,Y,Z', 'X,Z','X','Y,Z'])
  
             Count
  X, Y, Z      980
  X,Z          169
  X            104
  Y,Z           74
  </code></pre>
  
  <p>I want to be able to extract association rules from this. I've seen that the <strong>Apriori algorithm</strong> is the reference. And also found the <em>Orange library</em> for data mining is well-known in this field.</p>
  
  <p>But the problem is, in order to use the <a href="http://orange.biolab.si/docs/latest/reference/rst/Orange.associate.html" rel="nofollow">AssociationRulesInducer</a> I need to create first a file containing all the transactions. Since my dataset is really huge (20 columns and 5 million rows) it will be too expensive to write all this data in a file and read it again with Orange.</p>
  
  <p>Do you have any idea how can I take advantage of my current dataframe structure in order to find association rules ?</p>