How to handle dataframe column with variable date time formats?-CodePudding

I am pretty new to pandas and I am struggling some dates in columns.

I have a dataframe column with dates in multiple formats, such as '2021-08-21T06:34:34.909Z' and '2021-08-21T06:34:34Z'

Is there an elegant way to remove all the milliseconds?

Thanks in advance

CodePudding user response：

You can try to convert as datetime64[s]:

>>> df['Datetime']
0    2021-08-21T06:34:34.909Z
1        2021-08-21T06:34:34Z
Name: Datetime, dtype: object


>>> df['Datetime'].astype('datetime64[s]')
0   2021-08-21 06:34:34
1   2021-08-21 06:34:34
Name: Datetime, dtype: datetime64[ns]

# OR

>>> pd.to_datetime(df['Datetime']).dt.floor(freq='S')
0   2021-08-21 06:34:34 00:00
1   2021-08-21 06:34:34 00:00
Name: Datetime, dtype: datetime64[ns, UTC]