pandas 无法使用系列内置函数对时间戳应用方法
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/26089670/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Unable to apply methods on timestamps using Series built-ins
提问by Amelio Vazquez-Reina
On the following series:
在以下系列中：
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
This command (convert to timestamp, localize and convert to EST) works:
此命令（转换为时间戳、本地化并转换为 EST）有效：
pd.to_datetime(my_series, unit='ms').apply(lambda x: x.tz_localize('UTC').tz_convert('US/Eastern'))
but this onefails:
但是这个失败了：
pd.to_datetime(my_series, unit='ms').tz_localize('UTC').tz_convert('US/Eastern')
with:
和：
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
and so does this one:
所以做这个：
my_series.tz_localize('UTC').tz_convert('US/Eastern')
with:
和：
---------------------------------------------------------------------------
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
As far as I understand, the second approach above (the first one that fails) should work. Why does it fail?
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？
采纳答案by Jeff
tz_localize/tz_convertact 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()
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()
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
回答by John Zwinck
As Jeff's answer mentions, tz_localize()and tz_convert()act on the index, not the data. This was a huge surprise to me too.
杰夫的回答中提到，tz_localize()和tz_convert()对指数，而不是数据的行为。这对我来说也是一个巨大的惊喜。
Since Jeff's answer was written, Pandas 0.15 added a new Series.dtaccessor that helps your use case. You can now do this:
由于 Jeff 的答案已写好，Pandas 0.15 添加了一个新的Series.dt访问器来帮助您的用例。你现在可以这样做：
pd.to_datetime(my_series, unit='ms').dt.tz_localize('UTC').dt.tz_convert('US/Eastern')
回答by mocobk
this work fine
这工作很好
pd.to_datetime(my_series,unit='ms', utc=True).dt.tz_convert('US/Eastern')
