extracting days from a numpy.timedelta64 value

Suppose you have a timedelta series:

import pandas as pd
from datetime import datetime
z = pd.DataFrame({'a':[datetime.strptime('20150101', '%Y%m%d')],'b':[datetime.strptime('20140601', '%Y%m%d')]})

td_series = (z['a'] - z['b'])

One way to convert this timedelta column or series is to cast it to a Timedelta object (pandas 0.15.0+) and then extract the days from the object:

td_series.astype(pd.Timedelta).apply(lambda l: l.days)

Another way is to cast the series as a timedelta64 in days, and then cast it as an int:

td_series.astype('timedelta64[D]').astype(int)

Use dt.days to obtain the days attribute as integers.

For eg:

In [14]: s = pd.Series(pd.timedelta_range(start='1 days', end='12 days', freq='3000T'))

In [15]: s
Out[15]: 
0    1 days 00:00:00
1    3 days 02:00:00
2    5 days 04:00:00
3    7 days 06:00:00
4    9 days 08:00:00
5   11 days 10:00:00
dtype: timedelta64[ns]

In [16]: s.dt.days
Out[16]: 
0     1
1     3
2     5
3     7
4     9
5    11
dtype: int64

More generally - You can use the .components property to access a reduced form of timedelta.

In [17]: s.dt.components
Out[17]: 
   days  hours  minutes  seconds  milliseconds  microseconds  nanoseconds
0     1      0        0        0             0             0            0
1     3      2        0        0             0             0            0
2     5      4        0        0             0             0            0
3     7      6        0        0             0             0            0
4     9      8        0        0             0             0            0
5    11     10        0        0             0             0            0

Now, to get the hours attribute:

In [23]: s.dt.components.hours
Out[23]: 
0     0
1     2
2     4
3     6
4     8
5    10
Name: hours, dtype: int64

You can convert it to a timedelta with a day precision. To extract the integer value of days you divide it with a timedelta of one day.

>>> x = np.timedelta64(2069211000000000, 'ns')
>>> days = x.astype('timedelta64[D]')
>>> days / np.timedelta64(1, 'D')
23

Or, as @PhillipCloud suggested, just days.astype(int) since the timedelta is just a 64bit integer that is interpreted in various ways depending on the second parameter you passed in ('D', 'ns', ...).

You can find more about it here.