Why does numpy.datetime64 give an error with an array of years?

Question

I am working with some data that has the date in the format 2017.08333. In the process of converting this to datetime objects I got an error when trying to convert the integer years to datetime.

np.datetime64(['2017','2018'])

The above fails with the error:Could not convert object to NumPy datetime

I was under the impression numpy functions were vectorized. Can someone explain why this doesn't work and how I can solve this? I have 3,000 dates to convert so something that doesn't involve a loop is ideal.

Dani Mesejo · Accepted Answer · 2018-12-19 01:52:02Z

7

To create an array of dates, you could do:

import numpy as np

print(np.array(['2018', '2017'], dtype=np.datetime64))

Output

['2018' '2017']

A more detailed explanation can be found here

answered Dec 19, 2018 at 1:52

Dani Mesejo

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2 Comments

Gabe Over a year ago

Thanks, so much. I spent so much time trying to figure this out.

ZisIsNotZis Over a year ago

btw, use dtype='M8[something_like_Y_or_D_or_s]' if numpy cannot recognize the unit

Redoubts · Accepted Answer · 2018-12-19 01:52:28Z

2

Some of them are. I'm not sure what your input looks like (list or np.array), but you could do something like

np.array(['2017', '2018'], dtype=np.datetime64)

or

my_np_array.astype(np.datetime64)

answered Dec 19, 2018 at 1:52

Redoubts

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Gabe Over a year ago

Wow, thanks. I have been grinding my gears for a while. I feel a little dumb for how easy this was.

U13-Forward · Accepted Answer · 2018-12-19 02:18:58Z

0

You can use map as additional too:

>>> import numpy as np
>>> np.array(list(map(np.datetime64,['2017', '2018'])))
array(['2017', '2018'], dtype='datetime64[Y]')

answered Dec 19, 2018 at 2:18

U13-Forward

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