title: pandas- changing the start and end date of resampled timeseries
body: <p>I've a time series that i resampled into this dataframe <code>df</code> ,</p>
  
  <p>My data is from 6th june to 28 june. it want to extend the data from 1st june to 30th june. count column will have 0 value in only extended period and my real values from 6th to 28th.</p>
  
  <pre><code>Out[123]: 
                           count
  Timestamp                    
  2009-06-07 02:00:00         1
  2009-06-07 03:00:00         0
  2009-06-07 04:00:00         0
  2009-06-07 05:00:00         0
  2009-06-07 06:00:00         0
  </code></pre>
  
  <p>i need to the make the </p>
  
  <p>start date:<code>2009-06-01 00:00:00</code></p>
  
  <p>end date:<code>2009-06-30 23:00:00</code></p>
  
  <p>so the data would look something like this:</p>
  
  <pre><code>                         count
  Timestamp                    
  2009-06-01 01:00:00         0
  2009-06-01 02:00:00         0
  2009-06-01 03:00:00         0
  </code></pre>
  
  <p>is there an effective way to perform this. the only way i can think of is not that effective.i am trying this since yesterday. please help</p>
  
  <pre><code>  index = pd.date_range('2009-06-01 00:00:00','2009-06-30 23:00:00', freq='H')
      df = pandas.DataFrame(numpy.zeros(len(index),1), index=index)
      df.columns=['zeros']
      result= pd.concat([df2,df])
      result1= pd.concat([df,result])
      result1.fillna(0)
      del result1['zero']
  </code></pre>