python - 如何将 numpy datetime64 [ns] 转换为 python 日期时间？

Question

我需要在单独的函数中从 pandas 帧值转换日期:

 def myfunc(lat, lon, when):
        ts = (when - np.datetime64('1970-01-01T00:00:00Z','s')) / np.timedelta64(1, 's')
        date = datetime.datetime.utcfromtimestamp(ts)
        print("Numpy date= ", when, " Python date= ", date)
        return float(90) - next_func(lat, lon, date)

调用此函数:

new_df['new_column'] =  np.vectorize(my_func)(lat, lon, new_df['datetime(LT)'])  

但它会引发错误:

ufunc subtract cannot use operands with types dtype('int64') and dtype('<M8[s]')

如何将 numpy datetime64 [ns] 转换为 python 日期时间？

Answer 1

我想知道您是否需要所有这些转换工作。使用正确的时间单位，datetime64 可以直接生成 datetime 对象。

我不确定您的 when 变量，但我们假设它来自 pandas，并且类似于 DatetimeIndex:

In [56]: time = pandas.date_range('6/28/2013', periods=5, freq='5D')
In [57]: time
Out[57]: 
DatetimeIndex(['2013-06-28', '2013-07-03', '2013-07-08', '2013-07-13',
               '2013-07-18'],
              dtype='datetime64[ns]', freq='5D')

等效的 numpy 数组

In [58]: time.values
Out[58]: 
array(['2013-06-28T00:00:00.000000000', '2013-07-03T00:00:00.000000000',
       '2013-07-08T00:00:00.000000000', '2013-07-13T00:00:00.000000000',
       '2013-07-18T00:00:00.000000000'], dtype='datetime64[ns]')
In [59]: time.values.tolist()
Out[59]: 
[1372377600000000000,
 1372809600000000000,
 1373241600000000000,
 1373673600000000000,
 1374105600000000000]

使用[ns]，结果是一个大整数，某种“时间戳”。但是如果我将时间单位转换为秒，甚至微秒(us):

In [60]: time.values.astype('datetime64[s]')
Out[60]: 
array(['2013-06-28T00:00:00', '2013-07-03T00:00:00',
       '2013-07-08T00:00:00', '2013-07-13T00:00:00',
       '2013-07-18T00:00:00'], dtype='datetime64[s]')
In [61]: time.values.astype('datetime64[s]').tolist()
Out[61]: 
[datetime.datetime(2013, 6, 28, 0, 0),
 datetime.datetime(2013, 7, 3, 0, 0),
 datetime.datetime(2013, 7, 8, 0, 0),
 datetime.datetime(2013, 7, 13, 0, 0),
 datetime.datetime(2013, 7, 18, 0, 0)]

结果是一个datetime对象列表。