如何将多个功能应用于groupby对象 [英] How to apply multiple functions to a groupby object

问题描述

例如，我有两个lambda函数可应用于分组的数据帧:

For example, I have two lambda functions to apply to a grouped data frame:

df.groupby(['A', 'B']).apply(lambda g: ...)
df.groupby(['A', 'B']).apply(lambda g: ...)

这两种方法都可以，但结合使用则不能:

Both would work, but not when combined:

df.groupby(['A', 'B']).apply([lambda g: ..., lambda g: ...])

那是为什么?如何将不同的功能应用于已分组的对象，并将每个结果按列连接在一起?

Why is that? How can I apply different functions to a grouped object and get each result concatenated column wise together?

有没有一种方法可以不为函数指定某些列?您建议的所有内容似乎仅适用于某些列.

Is there a way not to specify some column to a function? All you have suggested seemed to only work with certain columns.

推荐答案

这是一个很好的机会来突出显示熊猫0.20的变化之一

This is a good opportunity to highlight one of the changes in pandas 0.20

这是什么意思?
考虑数据帧df

What does this mean?
Consider the dataframe df

df = pd.DataFrame(dict(
        A=np.tile([1, 2], 2).repeat(2),
        B=np.repeat([1, 2], 2).repeat(2),
        C=np.arange(8)
    ))
df

   A  B  C
0  1  1  0
1  1  1  1
2  2  1  2
3  2  1  3
4  1  2  4
5  1  2  5
6  2  2  6
7  2  2  7

我们以前可以做

df.groupby(['A', 'B']).C.agg(dict(f1=lambda x: x.size, f2=lambda x: x.max()))

     f1  f2
A B        
1 1   2   1
  2   2   5
2 1   2   3
  2   2   7

我们的名字'f1'和'f2'被放置为列标题.但是，使用熊猫0.20可以得到这个

And our names 'f1' and 'f2' were placed as column headers. However, with pandas 0.20 I get this

//anaconda/envs/3.6/lib/python3.6/site-packages/ipykernel/__main__.py:1: FutureWarning: using a dict on a Series for aggregation
is deprecated and will be removed in a future version
  if __name__ == '__main__':

那是什么意思?如果我做两个lambdas没有命名字典怎么办?

So what does that mean? What if I do two lambdas without the naming dictionary?

df.groupby(['A', 'B']).C.agg([lambda x: x.size, lambda x: x.max()])

---------------------------------------------------------------------------
SpecificationError                        Traceback (most recent call last)
<ipython-input-398-fc26cf466812> in <module>()
----> 1 print(df.groupby(['A', 'B']).C.agg([lambda x: x.size, lambda x: x.max()]))

//anaconda/envs/3.6/lib/python3.6/site-packages/pandas/core/groupby.py in aggregate(self, func_or_funcs, *args, **kwargs)
   2798         if hasattr(func_or_funcs, '__iter__'):
   2799             ret = self._aggregate_multiple_funcs(func_or_funcs,
-> 2800                                                  (_level or 0) + 1)
   2801         else:
   2802             cyfunc = self._is_cython_func(func_or_funcs)

//anaconda/envs/3.6/lib/python3.6/site-packages/pandas/core/groupby.py in _aggregate_multiple_funcs(self, arg, _level)
   2863             if name in results:
   2864                 raise SpecificationError('Function names must be unique, '
-> 2865                                          'found multiple named %s' % name)
   2866 
   2867             # reset the cache so that we

SpecificationError: Function names must be unique, found multiple named <lambda>

在名为'<lambda>'

pandas错误

解决方案:为您的函数命名

Solution: Name your functions

def f1(x):
    return x.size

def f2(x):
    return x.max()

df.groupby(['A', 'B']).C.agg([f1, f2])

     f1  f2
A B        
1 1   2   1
  2   2   5
2 1   2   3
  2   2   7

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