title: Accessing `.days` for a pandas Series of timedeltas
body: <p>A pandas <code>TimedeltaIndex</code> has an attribute <code>days</code> that can be used for operations with other normal dtypes (<code>float64</code>, etc):</p>
  
  <pre><code>import pandas as pd
  from pandas.tseries import offsets
  idx1 = pd.date_range('2017-01', periods=10)
  idx2 = idx1 + offsets.MonthEnd(1)
  tds = idx2 - idx1
  
  print(tds.days - 2)
  Int64Index([28, 27, 26, 25, 24, 23, 22, 21, 20, 19], dtype='int64')
  </code></pre>
  
  <p>But when <code>tds</code> is converted to a Series (explicitly, or as a DataFrame column), it loses this attribute.</p>
  
  <pre><code>print(pd.Series(tds).days)
  ---------------------------------------------------------------------------
  AttributeError                            Traceback (most recent call last)
  &lt;ipython-input-115-cb20b4d368f4&gt; in &lt;module&gt;()
  ----&gt; 1 print(pd.Series(tds).days)
  
  C:\Users\bsolomon\Anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
     3079             if name in self._info_axis:
     3080                 return self[name]
  -&gt; 3081             return object.__getattribute__(self, name)
     3082 
     3083     def __setattr__(self, name, value):
  
  AttributeError: 'Series' object has no attribute 'days'
  </code></pre>
  
  <p>And accessing <code>.days</code> requires converting back over to an <code>Index</code>:</p>
  
  <pre><code>print(pd.Index(pd.Series(tds)).days)
  Int64Index([30, 29, 28, 27, 26, 25, 24, 23, 22, 21], dtype='int64')
  </code></pre>
  
  <p><strong>Is there a more straightforward way to access this attribute than with the conversion above?</strong></p>