我有一組日期時間，我需要將其轉換為日期時間串列。我的陣列如下所示：
import numpy as np
my_array = np.array(['2017-06-28T22:47:51.213500000', '2017-06-28T22:48:37.570900000',
'2017-06-28T22:49:46.736800000', '2017-06-28T22:50:41.866800000',
'2017-06-28T22:51:17.024100000', '2017-06-28T22:51:24.038300000'], dtype='datetime64[ns]')
my_list = my_array.tolist()
我需要一個日期時間值串列，但是當我這樣做時my_array.tolist()，我會得到一個數字時間戳串列：
[1498690071213500000,
1498690117570900000,
1498690186736800000,
1498690241866800000,
1498690277024100000,
1498690284038300000]
我的問題是從陣列到串列時如何保留日期時間格式，或者如何將時間戳串列轉換為日期時間值串列？
uj5u.com熱心網友回復：
NumPy 無法將 的實體轉換'datetime64[ns]'為 Pythondatetime.datetime實體，因為datetime實體不支持納秒級解析度。
如果您將陣列轉換為'datetime64[us]'，因此時間戳只有微秒解析度，那么該.tolist()方法將為您提供datetime.datetime實體：
In [25]: my_array
Out[25]:
array(['2017-06-28T22:47:51.213500000', '2017-06-28T22:48:37.570900000',
'2017-06-28T22:49:46.736800000', '2017-06-28T22:50:41.866800000',
'2017-06-28T22:51:17.024100000', '2017-06-28T22:51:24.038300000'],
dtype='datetime64[ns]')
In [26]: my_array.astype('datetime64[us]').tolist()
Out[26]:
[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)]
uj5u.com熱心網友回復：
將顯式轉換numpy.ndarray為原生 Pythonlist會將內容保留為numpy.datetime64物件：
>>> 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，如果您想從整數時間戳回傳到numpy.datetime64物件，此處numpy.ndarray.tolist給出的數字以納秒格式給出，因此您也可以使用如下串列推導：
>>> [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')]
如果您希望最終結果是 Pythondatetime.datetime物件而不是numpy.datetime64物件，您可以使用這樣的方法（根據本地需要進行調整）：
>>> 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)]
編輯： Warren Weckesser 的回答提供了一種比這里描述的更直接的方法來從numpy.datetime64[ns]陣列到 Python 物件串列。datetime.datetime
uj5u.com熱心網友回復：
嘗試
# convert to string type first
my_list = my_array.astype(str).tolist()
my_list
# ['2017-06-28T22:47:51.213500000', '2017-06-28T22:48:37.570900000', '2017-06-28T22:49:46.736800000', '2017-06-28T22:50:41.866800000', '2017-06-28T22:51:17.024100000', '2017-06-28T22:51:24.038300000']
其他答案提供了更直接的方法，但為了完整起見，您可以datetime.datetime.fromtimestamp回圈呼叫
from datetime import datetime
[datetime.fromtimestamp(x) for x in my_array.astype(object)/1e9]
#[datetime.datetime(2017, 6, 28, 15, 47, 51, 213500),
# datetime.datetime(2017, 6, 28, 15, 48, 37, 570900),
# datetime.datetime(2017, 6, 28, 15, 49, 46, 736800),
# datetime.datetime(2017, 6, 28, 15, 50, 41, 866800),
# datetime.datetime(2017, 6, 28, 15, 51, 17, 24100),
# datetime.datetime(2017, 6, 28, 15, 51, 24, 38300)]
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