Get year month or day from numpy datetime64

Question

I have an array of datetime64 type   dates   np datetime64   2010-10-17    2011-05-13    2012-01-15      Is there a better way than looping through each element just to get np array of years   years   f dates   output  array  2010  2011  2012   dtype int8   or dtype   string   I m using stable numpy version 1 6 2

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If you upgrade to numpy 1 7  where datetime is still labeled as experimental  the following should work   dates np timedelta64 1  Y

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Anon s answer works great for me  but I just need to modify the statement for days  from   days   dates - dates astype  datetime64 M      1  to   days   dates astype  datetime64 D    - dates astype  datetime64 M      1

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This is how I do it   import numpy as np  def dt2cal dt               Convert array of datetime64 to a calendar array of year  month  day  hour      minute  seconds  microsecond with these quantites indexed on the last axis       Parameters     ----------     dt   datetime64 array               numpy ndarray of datetimes of arbitrary shape      Returns     -------     cal   uint32 array       7          calendar array with last axis representing year  month  day  hour          minute  second  microsecond                allocate output      out   np empty dt shape    7    dtype  u4         decompose calendar floors     Y  M  D  h  m  s    dt astype f M8  x     for x in  YMDhms       out      0    Y   1970   Gregorian Year     out      1     M - Y    1   month     out      2     D - M    1   dat     out      3     dt - D  astype  m8 h      hour     out      4     dt - h  astype  m8 m      minute     out      5     dt - m  astype  m8 s      second     out      6     dt - s  astype  m8 us      microsecond     return out   It s vectorized across arbitrary input dimensions  it s fast  its intuitive  it works on numpy v1 15 4  it doesn t use pandas    I really wish numpy supported this functionality  it s required all the time in application development  I always get super nervous when I have to roll my own stuff like this  I always feel like I m missing an edge case

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There s no direct way to do it yet  unfortunately  but there are a couple indirect ways    dt year for dt in dates astype object     or   datetime datetime strptime repr d     Y- m- d  H  M  S   year for d in dates    both inspired by the examples here   Both of these work for me on Numpy 1 6 1  You may need to be a bit more careful with the second one  since the repr   for the datetime64 might have a fraction part after a decimal point

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Use dates tolist   to convert to native datetime objects  then simply access year  Example    gt  gt  gt  dates   np array   2010-10-17    2011-05-13    2012-01-15    dtype  datetime64    gt  gt  gt   x year for x in dates tolist     2010  2011  2012    This is basically the same idea exposed in https   stackoverflow com a 35281829 2192272  but using simpler syntax   Tested with python 3 6   numpy 1 18

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There should be an easier way to do this  but  depending on what you re trying to do  the best route might be to convert to a regular Python datetime object   datetime64Obj   np datetime64  2002-07-04T02 55 41-0700   print datetime64Obj astype object  year   2002 print datetime64Obj astype object  day   4   Based on comments below  this seems to only work in Python 2 7 x and Python 3 6

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As datetime is not stable in numpy I would use pandas for this   In  52   import pandas as pd  In  53   dates   pd DatetimeIndex   2010-10-17    2011-05-13    2012-01-15     In  54   dates year Out 54   array  2010  2011  2012   dtype int32    Pandas uses numpy datetime internally  but seems to avoid the shortages  that numpy has up to now

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I find the following tricks give between 2x and 4x speed increase versus the pandas method described above  i e  pd DatetimeIndex dates  year etc    The speed of  dt year for dt in dates astype object   I find to be similar to the pandas method  Also these tricks can be applied directly to ndarrays of any shape  2D  3D etc    dates   np arange np datetime64  2000-01-01    np datetime64  2010-01-01    years   dates astype  datetime64 Y    astype int    1970 months   dates astype  datetime64 M    astype int    12   1 days   dates - dates astype  datetime64 M      1

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Using numpy version 1 10 4 and pandas version 0 17 1   dates   np array   2010-10-17    2011-05-13    2012-01-15    dtype np datetime64  pd to datetime dates  year   I get what you re looking for   array  2010  2011  2012   dtype int32

User · Answer

Another possibility is   np datetime64 dates  Y   - returns - numpy datetime64  2010     or  np datetime64 dates  Y   astype int  1970 - returns - 2010   but works only on scalar values  won t take array

[python] Get year, month or day from numpy datetime64

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