如何将pd.Series转换为日期时间？

Question

我的env: python3.6_x64，熊猫0.17.0，numpy 1.12.0

代码：

>>> import pandas as pd
>>> import numpy as np
>>> df_date = pd.Series(['2017-3-1','2017-3-2'])
>>> df_date
0    2017-3-1
1    2017-3-2
>>> pd.to_datetime(df_date)

错误：

ValueError: Error parsing datetime string "2017-3-1" at position 5
...
SystemError: <class 'str'> returned a result with an error set

Answer 1

这在pandas中看起来很像pandas，当使用Python 3.6时，它在0.19.2中被标记为固定。

In [12]: pd.Timestamp('invalid')
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
ValueError: Error parsing datetime string "invalid" at position 0 

The above exception was the direct cause of the following exception:

SystemError                               Traceback (most recent call last)
<ipython-input-12-91abde127db1> in <module>()
----> 1 pd.Timestamp('invalid')
pandas/tslib.pyx in pandas.tslib.Timestamp.__new__ (pandas/tslib.c:9932)()
pandas/tslib.pyx in pandas.tslib.convert_to_tsobject (pandas/tslib.c:25231)()
pandas/tslib.pyx in pandas.tslib.convert_str_to_tsobject (pandas/tslib.c:26851)()
pandas/src/datetime.pxd in datetime._string_to_dts (pandas/tslib.c:87106)()
SystemError: <class 'str'> returned a result with an error set

Answer 2

如果仍然需要日期时间列，请考虑将熊猫系列对象转换为简单的DataFrame对象，然后将该列转换为日期时间。

Answer 3

我的env:熊猫(0.18.1)，numpy (1.12.1)，Python 3.6.1 (缺省值，2017年4月18日，01:19:53)

我使用相同的代码，但没有错误。我的输出如下：

>>> import pandas as pd
>>> import numpy as np
>>> df_date = pd.Series(['2017-3-1','2017-3-2'])
>>> pd.to_datetime(df_date)
0   2017-03-01
1   2017-03-02
dtype: datetime64[ns]