无法使用 Series 内置函数对时间戳应用方法

问题描述

关于以下系列:

0    1411161507178
1    1411138436009
2    1411123732180
3    1411167606146
4    1411124780140
5    1411159331327
6    1411131745474
7    1411151831454
8    1411152487758
9    1411137160544
Name: my_series, dtype: int64

此命令(转换为时间戳、本地化并转换为 EST)有效:

This command (convert to timestamp, localize and convert to EST) works:

pd.to_datetime(my_series, unit='ms').apply(lambda x: x.tz_localize('UTC').tz_convert('US/Eastern'))

但是这个失败了:

pd.to_datetime(my_series, unit='ms').tz_localize('UTC').tz_convert('US/Eastern')

与:

TypeError                                 Traceback (most recent call last)
<ipython-input-3-58187a4b60f8> in <module>()
----> 1 lua = pd.to_datetime(df[column], unit='ms').tz_localize('UTC').tz_convert('US/Eastern')

/Users/josh/anaconda/envs/py34/lib/python3.4/site-packages/pandas/core/generic.py in tz_localize(self, tz, axis, copy, infer_dst)
   3492                 ax_name = self._get_axis_name(axis)
   3493                 raise TypeError('%s is not a valid DatetimeIndex or PeriodIndex' %
-> 3494                                 ax_name)
   3495             else:
   3496                 ax = DatetimeIndex([],tz=tz)

TypeError: index is not a valid DatetimeIndex or PeriodIndex

这个也是如此:

my_series.tz_localize('UTC').tz_convert('US/Eastern')

与:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-4-0a7cb1e94e1e> in <module>()
----> 1 lua = df[column].tz_localize('UTC').tz_convert('US/Eastern')

/Users/josh/anaconda/envs/py34/lib/python3.4/site-packages/pandas/core/generic.py in tz_localize(self, tz, axis, copy, infer_dst)
   3492                 ax_name = self._get_axis_name(axis)
   3493                 raise TypeError('%s is not a valid DatetimeIndex or PeriodIndex' %
-> 3494                                 ax_name)
   3495             else:
   3496                 ax = DatetimeIndex([],tz=tz)

TypeError: index is not a valid DatetimeIndex or PeriodIndex

据我了解，上面的第二种方法(第一种失败的方法)应该有效.为什么会失败?

As far as I understand, the second approach above (the first one that fails) should work. Why does it fail?

推荐答案

tz_localize/tz_convert 作用于对象的 INDEX，而不是值.最简单的方法是将其转换为索引，然后进行本地化和转换.如果你想要一个系列回来，你可以使用 to_series()

tz_localize/tz_convert act on the INDEX of the object, not on the values. Easiest to simply turn it into an index then localize and convert. If you then want a Series back you can use to_series()

In [47]: pd.DatetimeIndex(pd.to_datetime(s,unit='ms')).tz_localize('UTC').tz_convert('US/Eastern')
Out[47]: 
<class 'pandas.tseries.index.DatetimeIndex'>
[2014-09-19 17:18:27.178000-04:00, ..., 2014-09-19 10:32:40.544000-04:00]
Length: 10, Freq: None, Timezone: US/Eastern

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