title: Pivoting a Pandas Dataframe containing strings - 'No numeric types to aggregate' error
body: <p>There is a good number of questions about this error, but after looking around I'm still not able to find/wrap my mind around a solution yet.
  I'm trying to pivot a data frame with strings, to get some row data to become columns, but not working out so far.</p>
  
  <p><strong>Shape of my df</strong> </p>
  
  <pre><code>&lt;class 'pandas.core.frame.DataFrame'&gt;
  Int64Index: 515932 entries, 0 to 515931
  Data columns (total 5 columns):
  id                 515932 non-null object
  cc_contact_id      515932 non-null object
  Network_Name       515932 non-null object
  question           515932 non-null object
  response_answer    515932 non-null object
  dtypes: object(5)
  memory usage: 23.6+ MB
  </code></pre>
  
  <p><strong>Sample format</strong></p>
  
  <pre><code>id  contact_id  question    response_answer
  16  137519  2206    State   Ca
  17  137520  2206    State   Ca
  18  137521  2206    State   Ca
  19  137522  2206    State   Ca
  20  137523  2208    City    Lancaster
  21  137524  2208    City    Lancaster
  22  137525  2208    City    Lancaster
  23  137526  2208    City    Lancaster
  24  137527  2208    Trip_End Location   Home
  25  137528  2208    Trip_End Location   Home
  26  137529  2208    Trip_End Location   Home
  27  137530  2208    Trip_End Location   Home
  </code></pre>
  
  <p><strong>What I would like to pivot to</strong></p>
  
  <pre><code>id  contact_id      State   City       Trip_End Location
  16  137519  2206    Ca      None       None None
  20  137523  2208    None    Lancaster  None None
  24  137527  2208    None    None       None Home
  etc. etc. 
  </code></pre>
  
  <p>Where the <em>question</em> values become the columns, with the <em>response_answer</em> being in it's corresponding column, and retaining the ids</p>
  
  <p>What I have tried</p>
  
  <pre><code>unified_df = pd.DataFrame(unified_data, columns=target_table_headers, dtype=object)
  
  pivot_table = unified_df.pivot_table('response_answer',['id','cc_contact_id'],'question')
  # OR
  pivot_table = unified_df.pivot_table('response_answer','question')
  </code></pre>
  
  <p><em>DataError: No numeric types to aggregate</em></p>
  
  <p>What is the way to pivot a data frame with string values?</p>