title: Dates fill in for date range and fillna
body: <p>I am querying my database to show records from the past week. I am then aggregating the data and transposing it in python and pandas into a DataFrame.
  In this table I am attempting to show what occurred on each day in the past 7 week, however, on some days no events occur. In these cases, the date is missing altogether. I am looking for an approach to append the dates that are not present (but are part of the date range specified in the query) so that I can then fillna with any value I wish for the other missing columns.</p>
  
  <p>In some trials I have the data set into a pandas Dataframe where the dates are the index and in others the dates are a column. I am preferably looking to have the dates as the top index - so group by name, stack purchase and send_back and dates are the 'columns'.</p>
  
  <p>Here is an example of how the dataframe looks now and what I am looking for:</p>
  
  <p>Dates set in query for - 01.08.2016 - 08.08.2016. The dataframe looks liks so:</p>
  
  <pre><code>       |  dates       | name     | purchase | send_back
     0  01.08.2016    Michael     120          0
     1  02.08.2016    Sarah       100         40
     2  04.08.2016    Sarah       55           0
     3  05.08.2016    Michael     80          20
     4  07.08.2016    Sarah       130          0
  </code></pre>
  
  <p>After:</p>
  
  <pre><code>     | dates       | name     | purchase | send_back
     0 01.08.2016    Michael      120          0
     1 02.08.2016    Sarah        100          40
     2 03.08.2016    -            0            0
     3 04.08.2016    Sarah        55           0
     4 05.08.2016    Michael      80           20
     5 06.08.2016    -            0            0
     6 07.08.2016    Sarah        130          0
     7 08.08.2016    Sarah        0            35
     8 08.08.2016    Michael      20           0 
  </code></pre>
  
  <p>Printing the following:</p>
  
  <pre><code> df.index
  </code></pre>
  
  <p>gives:</p>
  
  <pre><code> 'Index([   u'dates',u'name',u'purchase',u'send_back'],
        dtype='object')
  
  RangeIndex(start=0, stop=1, step=1)'
  </code></pre>
  
  <p>I appreciate any guidance.</p>