将可变 Pandas DataFrame 的所有日期时间列转换为不同的时区

Question

I have to deal with a Pandas DataFrame that can be composed by different datetime columns (they can vary, I can have 0..N datetime cols). I know that each datetime column timezone is UTC and I need to convert their data to another timezone. If I do as follows:

df['a_datetime_column'].dt.tz_localize('UTC').dt.tz_convert('my_timezone') 

it works but I need to know in advance the datetime column names (ok, I could get them in some way).

Is there a specific way to do this conversion on all the DataFrame at once independently from the composition of its columns?

Answer 1

查看select_dtypes ，您可以使用它仅选择datetime64[ns]列并将您的tz_convert应用于这些列：

df.select_dtypes(inlcude=["datetime64[ns]"]).dt.tz_localize('UTC').dt.tz_convert('my_timezone') 

Answer 2

You can loop over the columns which have datetime type:

for col,dtyp in df.dtypes.iteritems():
    if dtyp == 'datetime64[ns]':
        df[col] = df[col].dt.tz_localize('UTC').dt.tz_convert('my_timezone')