具有日期时间的numpy结构化数组

Question

I tried to build a structured array with a datetime coloumn

import numpy as np
na_trades = np.zeros(2, dtype = 'datetime64,i4')
na_trades[0] = (np.datetime64('1970-01-01 00:00:00'),0)

TypeError: Cannot cast NumPy timedelta64 scalar from metadata [s] to  according to the rule 'same_kind'

Is there a way to fix this?

Answer 1

You have to specify that the datetime64 is in seconds when you create the array because the one you parse and try to assign is a datetime64[s] :

na_trades = np.zeros(2, dtype='datetime64[s],i4')
na_trades[0] = (np.datetime64('1971-01-01 00:00:00'), 0)

The error you get means that the datetime64 object that you specified is not same_kind as the one you try to assing. You try to assign a seconds resolution one, and you created a different one when you constructed the array (by default I think it's nanoseconds).

Answer 2

Try following:

>>> na_trades = np.zeros(2, dtype=[('dt', 'datetime64[s]'), ('vol', 'i4')])
>>> na_trades
array([(datetime.datetime(1970, 1, 1, 0, 0), 0),
       (datetime.datetime(1970, 1, 1, 0, 0), 0)], 
      dtype=[('dt', ('<M8[s]', {})), ('vol', '<i4')])
>>> na_trades[0] = (np.datetime64('1970-01-02 00:00:00'),1)
>>> na_trades
array([(datetime.datetime(4707, 11, 29, 0, 0), 1),
       (datetime.datetime(1970, 1, 1, 0, 0), 0)], 
      dtype=[('dt', ('<M8[s]', {})), ('vol', '<i4')])