title: Convert Python dict into a dataframe
body: <p>I have a Python dictionary like the following:</p>
  
  <pre><code>{u'2012-06-08': 388,
   u'2012-06-09': 388,
   u'2012-06-10': 388,
   u'2012-06-11': 389,
   u'2012-06-12': 389,
   u'2012-06-13': 389,
   u'2012-06-14': 389,
   u'2012-06-15': 389,
   u'2012-06-16': 389,
   u'2012-06-17': 389,
   u'2012-06-18': 390,
   u'2012-06-19': 390,
   u'2012-06-20': 390,
   u'2012-06-21': 390,
   u'2012-06-22': 390,
   u'2012-06-23': 390,
   u'2012-06-24': 390,
   u'2012-06-25': 391,
   u'2012-06-26': 391,
   u'2012-06-27': 391,
   u'2012-06-28': 391,
   u'2012-06-29': 391,
   u'2012-06-30': 391,
   u'2012-07-01': 391,
   u'2012-07-02': 392,
   u'2012-07-03': 392,
   u'2012-07-04': 392,
   u'2012-07-05': 392,
   u'2012-07-06': 392}
  </code></pre>
  
  <p>The keys are <a href="http://en.wikipedia.org/wiki/Unicode" rel="noreferrer">Unicode</a> dates and the values are integers. I would like to convert this into a pandas dataframe by having the dates and their corresponding values as two separate columns. Example: col1: Dates col2: DateValue (the dates are still Unicode and datevalues are still integers)</p>
  
  <pre><code>     Date         DateValue
  0    2012-07-01    391
  1    2012-07-02    392
  2    2012-07-03    392
  .    2012-07-04    392
  .    ...           ...
  .    ...           ...
  </code></pre>
  
  <p>Any help in this direction would be much appreciated. I am unable to find resources on the pandas docs to help me with this.</p>
  
  <p>I know one solution might be to convert each key-value pair in this dict, into a dict so the entire structure becomes a dict of dicts, and then we can add each row individually to the dataframe. But I want to know if there is an easier way and a more direct way to do this.</p>
  
  <p>So far I have tried converting the dict into a series object but this doesn't seem to maintain the relationship between the columns:</p>
  
  <pre><code>s  = Series(my_dict,index=my_dict.keys())
  </code></pre>