title: Backfilling a pandas dataframe missed the first month
body: <p>I have a pandas df or irrigation demand data that has daily values from 1900 to 2099.  I resampled the df to get the monthly average and then resampled and backfilled the monthly averages on a daily frequency, so that the average daily value for each month, was input as the daily value for every day of that month.</p>
  
  <p>My problem is that the first month was not backfilled and there is only a value for the last day of that month (1900-01-31).</p>
  
  <p>Here is my code, any suggestions on what I am doing wrong?</p>
  
  <pre><code>I2 = pd.DataFrame(IrrigDemand, columns = ['Year', 'Month', 'Day', 'IrrigArea_1', 'IrrigArea_2','IrrigArea_3','IrrigArea_4','IrrigArea_5'],dtype=float)  
  
  # set dates as index 
  I2.set_index('Year')   
  
  # make a column of dates in datetime format
  dates = pd.to_datetime(I2[['Year', 'Month', 'Day']])       
  
  # add the column of dates to df
  I2['dates'] = pd.Series(dates, index=I2.index) 
  
  # set dates as index of df
  I2.set_index('dates')                                                    
  
  # delete the three string columns replaced with datetime values
  I2.drop(['Year', 'Month', 'Day'],inplace=True,axis=1)    
  
  # calculate the average daily value for each month 
  I2_monthly_average = I2.reset_index().set_index('dates').resample('m').mean()                           
  I2_daily_average = I2_monthly_average.resample('d').bfill()  
  </code></pre>