pandas 如何将多个功能应用于数据框 [英] Pandas how to apply multiple functions to dataframe

问题描述

是否有一种方法可以像DataFrameGroupBy.agg函数那样将函数列表应用于DataFrame的每一列?我发现这样做很丑陋:

Is there a way to apply a list of functions to each column in a DataFrame like the DataFrameGroupBy.agg function does? I found an ugly way to do it like this:

df=pd.DataFrame(dict(one=np.random.uniform(0,10,100), two=np.random.uniform(0,10,100)))
df.groupby(np.ones(len(df))).agg(['mean','std'])

        one                 two
       mean       std      mean       std
1  4.802849  2.729528  5.487576  2.890371

推荐答案

对于Pandas 0.20.0或更高版本，请使用指出这一点):

For Pandas 0.20.0 or newer, use df.agg (thanks to ayhan for pointing this out):

In [11]: df.agg(['mean', 'std'])
Out[11]: 
           one       two
mean  5.147471  4.964100
std   2.971106  2.753578

对于较旧的版本，您可以使用

For older versions, you could use

In [61]: df.groupby(lambda idx: 0).agg(['mean','std'])
Out[61]: 
        one               two          
       mean       std    mean       std
0  5.147471  2.971106  4.9641  2.753578

另一种方式是:

In [68]: pd.DataFrame({col: [getattr(df[col], func)() for func in ('mean', 'std')] for col in df}, index=('mean', 'std'))
Out[68]: 
           one       two
mean  5.147471  4.964100
std   2.971106  2.753578

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