title: How to select specific quarter in Pandas timeseries
body: <p>What's the best way to select specific individual rows from a timeseries?</p>
  
  <p>I've got some data:</p>
  
  <pre><code>indexed = df.set_index("Month").resample("Q-MAR", how="sum")['count']
  indexed
  
  Month
  2010-12-31     6942
  2011-03-31    23677
  2011-06-30    24131
  2011-09-30    23144
  2011-12-31    22249
  2012-03-31    24216
  2012-06-30    22938
  2012-09-30    25468
  2012-12-31    21733
  2013-03-31    21385
  2013-06-30    23093
  2013-09-30    26206
  2013-12-31    22248
  2014-03-31    20737
  2014-06-30    23384
  2014-09-30    25285
  2014-12-31    22210
  2015-03-31    22627
  2015-06-30    25185
  2015-09-30    27038
  2015-12-31    25352
  2016-03-31    16694
  Freq: Q-MAR, Name: count, dtype: int64
  </code></pre>
  
  <p>I can slice out individual entries, like this:</p>
  
  <pre><code>indexed.ix["2012-09-30"]
  25468
  
  indexed.ix["2015-09-30"]
  27038
  </code></pre>
  
  <p>But how do I select both?</p>
  
  <p>I tried:</p>
  
  <pre><code>indexed.ix[["2012-09-30", "2015-09-30"],:]
  </code></pre>
  
  <p>Which returns a too many indexers error...</p>
  
  <p>While </p>
  
  <pre><code>indexed.ix[["2012-09-30", "2015-09-30"]]
  </code></pre>
  
  <p>brings back </p>
  
  <pre><code>Month
  2012-09-30   NaN
  2015-09-30   NaN
  </code></pre>
  
  <p>And I don't understand why</p>
  
  <pre><code>indexed.ix["2012-09-30", "2015-09-30"]
  </code></pre>
  
  <p>returns</p>
  
  <pre><code>25468
  </code></pre>
  
  <p>Could someone please explain it to me, please?</p>