如何从一系列数组构造 pandas 数据框 [英] How to construct pandas dataframe from series of arrays
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问题描述
我有以下numpy数组熊猫系列:
Hi I have the following pandas Series of numpy arrays:
datetime
03-Sep-15 [53.5688348969, 31.2542494769, 18.002043765]
04-Sep-15 [46.845084292, 27.0833015735, 15.5997887379]
08-Sep-15 [52.8701581666, 30.7347431703, 17.6379377917]
09-Sep-15 [47.9535624339, 27.7063099999, 15.9126963643]
10-Sep-15 [51.2900606534, 29.600945626, 16.8756260105]
您知道如何将其转换为3列的数据框吗?谢谢!
Do you know how I could convert it into a dataframe with 3 columns? Thanks!
推荐答案
它不会表现出色,但是您应该可以apply(pd.Series)
:
It won't be super-performant, but you should be able to apply(pd.Series)
:
>>> ser
03-Sep-15 [53.5688348969, 31.2542494769, 18.002043765]
04-Sep-15 [46.845084292, 27.0833015735, 15.5997887379]
08-Sep-15 [52.8701581666, 30.7347431703, 17.6379377917]
09-Sep-15 [47.9535624339, 27.7063099999, 15.9126963643]
10-Sep-15 [51.2900606534, 29.600945626, 16.8756260105]
dtype: object
>>> type(ser.values[0])
<class 'numpy.ndarray'>
>>> ser.apply(pd.Series)
0 1 2
03-Sep-15 53.568835 31.254249 18.002044
04-Sep-15 46.845084 27.083302 15.599789
08-Sep-15 52.870158 30.734743 17.637938
09-Sep-15 47.953562 27.706310 15.912696
10-Sep-15 51.290061 29.600946 16.875626
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