Accessing `.days` for pandas timedeltas series
A pandas TimedeltaIndex
has an attribute days
that can be used to operate on 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
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 to Index
:
print(pd.Index(pd.Series(tds)).days)
Int64Index([30, 29, 28, 27, 26, 25, 24, 23, 22, 21], dtype='int64')
Is there an easier way to access this attribute than with the transformation above?
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