所以你的方法产生:
In [56]: start = pd.Timestamp('2016-01-02 03:04:56.789101').to_pydatetime()
In [57]: start
Out[57]: datetime.datetime(2016, 1, 2, 3, 4, 56, 789101)
In [58]: dt = np.array([ 19, 14980, 19620, 54964615, 54964655, 86433958])
In [59]: time_arr = start + dt * timedelta(milliseconds=1)
In [60]: time_arr
Out[60]:
array([datetime.datetime(2016, 1, 2, 3, 4, 56, 808101),
datetime.datetime(2016, 1, 2, 3, 5, 11, 769101),
datetime.datetime(2016, 1, 2, 3, 5, 16, 409101),
datetime.datetime(2016, 1, 2, 18, 21, 1, 404101),
datetime.datetime(2016, 1, 2, 18, 21, 1, 444101),
datetime.datetime(2016, 1, 3, 3, 5, 30, 747101)], dtype=object)
等效采用np.datetime64
类型:
In [61]: dt.astype('timedelta64[ms]')
Out[61]: array([ 19, 14980, 19620, 54964615, 54964655, 86433958], dtype='timedelta64[ms]')
In [62]: np.datetime64(start)
Out[62]: numpy.datetime64('2016-01-02T03:04:56.789101')
In [63]: np.datetime64(start) + dt.astype('timedelta64[ms]')
Out[63]:
array(['2016-01-02T03:04:56.808101', '2016-01-02T03:05:11.769101',
'2016-01-02T03:05:16.409101', '2016-01-02T18:21:01.404101',
'2016-01-02T18:21:01.444101', '2016-01-03T03:05:30.747101'], dtype='datetime64[us]')
我可以生产从time_arr
同一阵列np.array(time_arr, dtype='datetime64[us]')
。
tolist
这些datetime64
项目转换为datetime
对象:
In [97]: t1=np.datetime64(start) + dt.astype('timedelta64[ms]')
In [98]: t1.tolist()
Out[98]:
[datetime.datetime(2016, 1, 2, 3, 4, 56, 808101),
datetime.datetime(2016, 1, 2, 3, 5, 11, 769101),
datetime.datetime(2016, 1, 2, 3, 5, 16, 409101),
datetime.datetime(2016, 1, 2, 18, 21, 1, 404101),
datetime.datetime(2016, 1, 2, 18, 21, 1, 444101),
datetime.datetime(2016, 1, 3, 3, 5, 30, 747101)]
或包裹回阵列中的,让您time_arr
:
In [99]: np.array(t1.tolist())
Out[99]:
array([datetime.datetime(2016, 1, 2, 3, 4, 56, 808101),
...
datetime.datetime(2016, 1, 3, 3, 5, 30, 747101)], dtype=object)
只是为了计算datatime64
速度较快,但与转化率可能不是最快的。
https://docs.scipy.org/doc/numpy/reference/arrays.datetime.html
以'%% timeit'检查,我最初的做法,每循环21.9微秒运行时,你的第一个方法('dt.astype( 'timedelta64 [毫秒]')')运行在每14.1微秒循环和使用'dt.astype('timedelta64 [ms]')'的方法在每个循环中以12.8μs运行 – API
我将放弃转换到python列表以获得性能:) – API