python - Numpy 操作对 groupby 无效。使用 .groupby(...).mean() 代替，这就是我所做的

Question

我想获得以下数据帧的前两列中每一列的平均值 people_preferences根据他们的分割Segment .

      Fun|Not-Fun              Pro-garden|Pro-home      Segment
0                          NaN                NaN       cats
1                          NaN                NaN       cats
2                         -1.0                NaN       cats

...                        ...                ...        ...
4570                      -1.0               -1.0       dogs
4571                      -1.0                1.0       dogs
4572                      -1.0                1.0       dogs

所以我尝试了 people_preferences.groupby('Segment', as_index=False).mean( skipna = True)但它返回: UnsupportedFunctionCall: numpy operations are not valid with groupby. Use .groupby(...).mean() instead
这是完整的错误消息:

---------------------------------------------------------------------------
UnsupportedFunctionCall                   Traceback (most recent call last)
<ipython-input-489-f8da6e73c33c> in <module>
     48 pairs = list(itertools.combinations(df_features.columns, 2))
     49 
---> 50 [plot_mean(pair[0],pair[1]) for pair in pairs]
     51 
     52 fig = px.scatter(df_features, x=columns_x, y=columns_y)

<ipython-input-489-f8da6e73c33c> in <listcomp>(.0)
     48 pairs = list(itertools.combinations(df_features.columns, 2))
     49 
---> 50 [plot_mean(pair[0],pair[1]) for pair in pairs]
     51 
     52 fig = px.scatter(df_features, x=columns_x, y=columns_y)

<ipython-input-489-f8da6e73c33c> in plot_mean(column_x, column_y)
     23         people_preferences = df_features[[column_x,column_y,'Segment']]
     24         print(people_preferences)
---> 25         print(people_preferences.groupby('Segment', as_index=False).mean( skipna = True))
     26         # parties.append('PEOPLE')
     27         dataframe = pd.DataFrame(dict(x=parties_x, y=parties_y, parties = parties))

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\groupby\groupby.py in mean(self, *args, **kwargs)
   1200         Name: B, dtype: float64
   1201         """
-> 1202         nv.validate_groupby_func("mean", args, kwargs, ["numeric_only"])
   1203         try:
   1204             return self._cython_agg_general(

C:\ProgramData\Anaconda3\lib\site-packages\pandas\compat\numpy\function.py in validate_groupby_func(name, args, kwargs, allowed)
    375                 "numpy operations are not valid "
    376                 "with groupby. Use .groupby(...)."
--> 377                 "{func}() instead".format(func=name)
    378             )
    379         )

Answer 1

这是 Pandas 中的一个错误。见 mean with skipna either True or False on groupby gives error
解决方法

使用 pandas.aggregate相反

# define helper function
def custom_mean(df):
    return df.mean(skipna=True)

# instead of 
df.mean(skipna=True)

# use 
df.agg(custom_mean)

(注意:可能是 skipna=True 是 pandas.mean() 的默认值，尽管出于某种原因 docs 显示了 skipna=None 的默认值)