title: Upsampling (disaggregating) summed quarterly data to monthly data
body: <p>I am trying to upsample data from aggregated quarterly up to monthly, but the numbers that below code produces are not what I need. I would need these data points to be disaggregated into monthly numbers (that add back up to the immediately following quarter). So each new value would need to be about a third of the following quarter.</p>
  
  <pre><code>i = ['2000-01-01','2000-04-01','2000-07-01','2000-10-01','2001-01-01','2001-04-01','2001-07-01','2001-10-01']
  d = [0,54957.84767,0,0,0,56285.54879,0,0]
  
  df = pd.DataFrame(index=i, data=d)
  df.index = pd.to_datetime(df.index,infer_datetime_format=True)
  df.index = df.index.to_period('Q')
  
  df.resample('M').first().interpolate(method='cubic')
  </code></pre>
  
  <p>UPDATE: Let's say a toy series is [0,0,9]. So January, February, March. The value at the end of March is 9. I would like the interpolated result to be [3,3,3]. So every month has the value of 3, and when you aggregate them back into quarters it results in a 9 again.</p>