title: Resample/Upsample Period Index and using both extreme time "edges" of the data
body: <p>I have the following DataFrame, a weekly price data timeserie with a Period Index. Let's call it <code>df</code></p>
  
  <pre><code>                            timestamp         open        high        low        close  volume
  timestamp                       
  2009-02-01/2009-02-07   733442.166309   830.540773  832.586910  828.788627  830.706009  48401.952790
  2009-02-08/2009-02-14   733449.166309   839.945279  841.763948  837.812232  839.742489  53429.330472
  2009-02-15/2009-02-21   733456.245777   790.733108  792.399775  788.897523  790.549550  50671.887387
  2009-02-22/2009-02-28   733463.166309   760.586910  762.640558  758.234979  760.428112  60565.506438
  </code></pre>
  
  <p>If I try to resample it with <code>df.resample('30min').mean()</code> the data ends at <code>2009-02-22</code>. I would like it to end at <code>2009-02-28</code>, while still starting at <code>2009-02-01</code>. How can I do that?<br>
   I suspect it has to do with the <code>closed</code> and <code>label</code> values of the <code>resample</code> function, but those are not very well explained in the doc.</p>
  
  <p>Here a snippet to reconstruct the dataframe:</p>
  
  <pre><code>import pandas as pd
  from pandas import Period
  dikt={'volume': {Period('2009-02-01/2009-02-07', 'W-SAT'): 48401.952789699571, Period('2009-02-08/2009-02-14', 'W-SAT'): 53429.330472103007, Period('2009-02-15/2009-02-21', 'W-SAT'): 50671.887387387389, Period('2009-02-22/2009-02-28', 'W-SAT'): 60565.506437768243}, 'close': {Period('2009-02-01/2009-02-07', 'W-SAT'): 830.70600858369096, Period('2009-02-08/2009-02-14', 'W-SAT'): 839.74248927038627, Period('2009-02-15/2009-02-21', 'W-SAT'): 790.54954954954951, Period('2009-02-22/2009-02-28', 'W-SAT'): 760.42811158798281}, 'open': {Period('2009-02-01/2009-02-07', 'W-SAT'): 830.54077253218884, Period('2009-02-08/2009-02-14', 'W-SAT'): 839.94527896995703, Period('2009-02-15/2009-02-21', 'W-SAT'): 790.73310810810813, Period('2009-02-22/2009-02-28', 'W-SAT'): 760.58690987124464}, 'high': {Period('2009-02-01/2009-02-07', 'W-SAT'): 832.58690987124464, Period('2009-02-08/2009-02-14', 'W-SAT'): 841.76394849785413, Period('2009-02-15/2009-02-21', 'W-SAT'): 792.39977477477476, Period('2009-02-22/2009-02-28', 'W-SAT'): 762.64055793991417}, 'low': {Period('2009-02-01/2009-02-07', 'W-SAT'): 828.78862660944208, Period('2009-02-08/2009-02-14', 'W-SAT'): 837.8122317596567, Period('2009-02-15/2009-02-21', 'W-SAT'): 788.89752252252254, Period('2009-02-22/2009-02-28', 'W-SAT'): 758.23497854077254}, 'timestamp': {Period('2009-02-01/2009-02-07', 'W-SAT'): 733442.16630901292, Period('2009-02-08/2009-02-14', 'W-SAT'): 733449.16630901292, Period('2009-02-15/2009-02-21', 'W-SAT'): 733456.24577702698, Period('2009-02-22/2009-02-28', 'W-SAT'): 733463.16630901292}}
  pd.DataFrame(dikt, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
  </code></pre>