我可以将pandas DataFrame导出到Excel中以剥离tzinfo吗? [英] Can I export pandas DataFrame to Excel stripping tzinfo?

问题描述

我在pandas 0.10.1中有一个了解时区的TimeSeries.我想导出到Excel，但是时区阻止该日期被识别为Excel中的日期.

I have a timezone aware TimeSeries in pandas 0.10.1. I want to export to Excel, but the timezone prevents the date from being recognized as a date in Excel.

In [40]: resultado
Out[40]: 
fecha_hora
2013-04-11 13:00:00+02:00    31475.568
2013-04-11 14:00:00+02:00    37263.072
2013-04-11 15:00:00+02:00    35979.434
2013-04-11 16:00:00+02:00    35132.890
2013-04-11 17:00:00+02:00    36356.584

如果我使用 .tz_convert(None)删除tzinfo，则日期将转换为UTC:

If I strip the tzinfo with .tz_convert(None), the date gets converted to UTC:

In [41]: resultado.tz_convert(None)
Out[41]: 
fecha_hora
2013-04-11 11:00:00    31475.568
2013-04-11 12:00:00    37263.072
2013-04-11 13:00:00    35979.434
2013-04-11 14:00:00    35132.890
2013-04-11 15:00:00    36356.584

是否有TimeSeries方法将 .replace(tzinfo = None)应用于索引中的每个日期?

Is there a TimeSeries method to apply .replace(tzinfo=None) to each date in the index?

或者，有没有一种方法可以将对时间敏感的TimeSeries正确导出到Excel?

Alternativelly, is there a way to properly export time-aware TimeSeries to Excel?

推荐答案

您可以简单地创建一个没有时区的副本.

You can simply create a copy without timezone.

import pandas as pa

time = pa.Timestamp('2013-04-16 10:08', tz='Europe/Berlin')
time_wo_tz = pa.datetime(year=time.year, month=time.month, day=time.day, 
                         hour=time.hour, minute=time.minute, second=time.second,
                         microsecond=time.microsecond)

要转换时间序列的整个索引时，请使用列表推导.

When you want to convert the whole index of the timeseries, use a list comprehension.

ts.index = [pa.datetime(year=x.year, month=x.month, day=x.day, 
                        hour=x.hour, minute=x.minute, second=x.second, 
                        microsecond=x.microsecond) 
            for x in ts.index]

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