Python numpy.array.tolist() 将 numpy.datetime64 转换为 int

将numpy.ndarray显式转换为本机Python list将把内容保留为numpy.datetime64个对象:

>>> list(my_array)
[numpy.datetime64('2017-06-28T22:47:51.213500000'),
 numpy.datetime64('2017-06-28T22:48:37.570900000'),
 numpy.datetime64('2017-06-28T22:49:46.736800000'),
 numpy.datetime64('2017-06-28T22:50:41.866800000'),
 numpy.datetime64('2017-06-28T22:51:17.024100000'),
 numpy.datetime64('2017-06-28T22:51:24.038300000')]

但是，如果您想从整数时间戳返回到numpy.datetime64对象，这里numpy.ndarray.tolist给出的数字是纳秒格式的，因此您也可以使用如下列表理解:

>>> [np.datetime64(x, "ns") for x in my_list]
[numpy.datetime64('2017-06-28T22:47:51.213500000'),
 numpy.datetime64('2017-06-28T22:48:37.570900000'),
 numpy.datetime64('2017-06-28T22:49:46.736800000'),
 numpy.datetime64('2017-06-28T22:50:41.866800000'),
 numpy.datetime64('2017-06-28T22:51:17.024100000'),
 numpy.datetime64('2017-06-28T22:51:24.038300000')]

如果希望最终结果是Python datetime.datetime对象，而不是numpy.datetime64对象，you can use a method like this(根据位置需要进行调整):

>>> from datetime import datetime
>>> list(map(datetime.utcfromtimestamp, my_array.astype(np.uint64) / 1e9))
[datetime.datetime(2017, 6, 28, 22, 47, 51, 213500),
 datetime.datetime(2017, 6, 28, 22, 48, 37, 570900),
 datetime.datetime(2017, 6, 28, 22, 49, 46, 736800),
 datetime.datetime(2017, 6, 28, 22, 50, 41, 866800),
 datetime.datetime(2017, 6, 28, 22, 51, 17, 24100),
 datetime.datetime(2017, 6, 28, 22, 51, 24, 38300)]

Edit: Warren Weckesser's answer提供了一种从numpy.datetime64[ns]数组到Python datetime.datetime对象列表的更直接的方法，这比这里描述的更简单.