title: Pandas: decompress date range to individual dates
body: <p><strong>Dataset:</strong> I have a 1GB dataset of stocks, which have values between date ranges. There is no overlapping in date ranges and the dataset is sorted on (ticker, start_date).</p>
  
  <pre><code>&gt;&gt;&gt; df.head()
               start_date    end_date                   val    
  ticker         
  AAPL         2014-05-01  2014-05-01         10.0000000000
  AAPL         2014-06-05  2014-06-10         20.0000000000
  GOOG         2014-06-01  2014-06-15         50.0000000000
  MSFT         2014-06-16  2014-06-16                  None
  TWTR         2014-01-17  2014-05-17         10.0000000000
  </code></pre>
  
  <p><strong>Goal:</strong> I want to decompress the dataframe so that I have individual dates instead of date ranges. For example, the AAPL rows would go from being only 2 rows to 7 rows:</p>
  
  <pre><code>&gt;&gt;&gt; AAPL_decompressed.head()
                     val
  date                       
  2014-05-01         10.0000000000
  2014-06-05         20.0000000000
  2014-06-06         20.0000000000
  2014-06-07         20.0000000000
  2014-06-08         20.0000000000
  </code></pre>
  
  <p>I'm hoping there's a nice optimized method from pandas like resample that can do this in a couple lines.</p>