本文介紹了無法使用 Series 內置函數對時間戳應用方法的處理方法,對大家解決問題具有一定的參考價值,需要的朋友們下面隨著小編來一起學習吧!
問題描述
關于以下系列:
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(轉換為時間戳、本地化并轉換為 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'))
但是這個失敗了:
pd.to_datetime(my_series, unit='ms').tz_localize('UTC').tz_convert('US/Eastern')
與:
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
這個也是如此:
my_series.tz_localize('UTC').tz_convert('US/Eastern')
與:
---------------------------------------------------------------------------
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
據我了解,上面的第二種方法(第一種失敗的方法)應該有效.為什么會失敗?
As far as I understand, the second approach above (the first one that fails) should work. Why does it fail?
推薦答案
tz_localize/tz_convert
作用于對象的 INDEX,而不是值.最簡單的方法是將其轉換為索引,然后進行本地化和轉換.如果你想要一個系列回來,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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