How to convert numpy datetime64 into datetime [duplicate]

Question

I basically face the same problem posted here:Converting between datetime, Timestamp and datetime64

but I couldn't find satisfying answer from it, my question how to extract datetime from numpy.datetime64 type:

if I try:

np.datetime64('2012-06-18T02:00:05.453000000-0400').astype(datetime.datetime)

it gave me: 1339999205453000000L

my current solution is convert datetime64 into a string and then turn to datetime again. but it seems quite a silly method.

I found from the test file, that dtype 'M8[ms]' readily converts to datetime. — hpaulj
– hpaulj, Commented Apr 20, 2015 at 21:19
have your read my answer to the end? Have you noticed that different numpy versions behave differently here? The answer contains code for different numpy versions (the versions are explicitly specified). There is even code example that produces long number and then later is shown how to get datetime in this case. — jfs
– jfs, Commented Apr 20, 2015 at 23:08
I'm sorry but both the original answer and this one are confusing. There seem to be a lot of different ways of doing it and I'm still not any clearer on the question of how to convert a numpy datetime to a pandas date time. For example, I am not clear if the solution below is saying that: pdDateTime = datetime.datetime.utcfromtimestamp(x.tolist()/1e9) ?? — Reddspark
– Reddspark, Commented Jun 27, 2017 at 14:24

constantstranger · Accepted Answer · 2022-05-15 11:38:24Z

47

Borrowing from Converting between datetime, Timestamp and datetime64

In [220]: x
Out[220]: numpy.datetime64('2012-06-17T23:00:05.453000000-0700')

In [221]: datetime.datetime.utcfromtimestamp(x.tolist()/1e9)
Out[221]: datetime.datetime(2012, 6, 18, 6, 0, 5, 452999)

Accounting for timezones I think that's right. Looks rather clunky though.

Using int() is more explicit (I think) than tolist()):

In [294]: datetime.datetime.utcfromtimestamp(int(x)/1e9)
Out[294]: datetime.datetime(2012, 6, 18, 6, 0, 5, 452999)

or to get datetime in local:

In [295]: datetime.datetime.fromtimestamp(x.astype('O')/1e9)

But in the test_datetime.py file https://github.com/numpy/numpy/blob/master/numpy/core/tests/test_datetime.py

I find some other options - first convert the general datetime64 to one of the format that specifies units:

In [296]: x.astype('M8[D]').astype('O')
Out[296]: datetime.date(2012, 6, 18)

In [297]: x.astype('M8[ms]').astype('O')
Out[297]: datetime.datetime(2012, 6, 18, 6, 0, 5, 453000)

This works for arrays:

In [303]: np.array([[x,x],[x,x]],dtype='M8[ms]').astype('O')[0,1]
Out[303]: datetime.datetime(2012, 6, 18, 6, 0, 5, 453000)

edited May 15, 2022 at 11:38

constantstranger

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answered Apr 20, 2015 at 17:01

hpaulj

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3 Comments

jfs Over a year ago

See my comment to @eumiro's answer (that you've borrowed from).

hpaulj Over a year ago

So the long is the result of the units being [ns]

Andras Deak -- Слава Україні Over a year ago

At first glance I thought that x.tolist()/1e9 was a mistake, because I didn't notice that x was a scalar in your case. I strongly suggest replacing it with x.item() to clarify.

Jeff · Accepted Answer · 2015-04-20 18:30:19Z

22

Note that Timestamp IS a sub-class of datetime.datetime so the [4] will generally work

In [4]: pd.Timestamp(np.datetime64('2012-06-18T02:00:05.453000000-0400'))
Out[4]: Timestamp('2012-06-18 06:00:05.453000')

In [5]: pd.Timestamp(np.datetime64('2012-06-18T02:00:05.453000000-0400')).to_pydatetime()
Out[5]: datetime.datetime(2012, 6, 18, 6, 0, 5, 453000)