Accessing `.days` for a pandas Series of timedeltas

Question

A pandas TimedeltaIndex has an attribute days that can be used for operations with other normal dtypes (float64, etc):

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')

But when tds is converted to a Series (explicitly, or as a DataFrame column), it loses this attribute.

print(pd.Series(tds).days)
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-115-cb20b4d368f4> in <module>()
----> 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]
-> 3081             return object.__getattribute__(self, name)
   3082 
   3083     def __setattr__(self, name, value):

AttributeError: 'Series' object has no attribute 'days'

And accessing .days requires converting back over to an Index:

print(pd.Index(pd.Series(tds)).days)
Int64Index([30, 29, 28, 27, 26, 25, 24, 23, 22, 21], dtype='int64')

Is there a more straightforward way to access this attribute than with the conversion above?

Answer 1

Use .dt accessor:

print(pd.Series(tds).dt.days)

Output:

0    30
1    29
2    28
3    27
4    26
5    25
6    24
7    23
8    22
9    21
dtype: int64