extracting days from a numpy timedelta64 value

Question

I am using pandas python and I have two date time series s1 and s2  that have been generated using the  to datetime  function on a field of the df containing dates times   When I subtract s1 from s2     s3   s2 - s1   I get a series  s3  of type      timedelta64 ns    0    385 days  04 10 36 1     57 days  22 54 00 2    642 days  21 15 23 3    615 days  00 55 44 4    160 days  22 13 35 5    196 days  23 06 49 6     23 days  22 57 17 7      2 days  22 17 31 8    622 days  01 29 25 9     79 days  20 15 14 10    23 days  22 46 51 11   268 days  19 23 04 12                  NaT 13                  NaT 14   583 days  03 40 39   How do I look at 1 element of the series      s3 10    I get something like this      numpy timedelta64 2069211000000000  ns     How do I extract days from s3 and maybe keep them as integers not so interested in hours mins etc     Thanks in advance for any help

User · Accepted Answer

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.

User · Answer

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

User · Answer

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

[python] extracting days from a numpy.timedelta64 value

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