如何使用“命名聚合" [英] How to use "Named aggregation"

问题描述

我想在 Pandas DataFrameGroupBy 的同一列上应用两个不同的聚合，并命名新列.

我已经尝试使用文档中显示的内容.https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#named-aggregation

<块引用>

在[82]中:animals.groupby("kind").agg(....: min_height=('height', 'min'),....: max_height=('height', 'max'),....: average_weight=('weight', np.mean),....:)....:出[82]:min_height max_height average_weight种类猫 9.1 9.5 8.90狗 6.0 34.0 102.75

我想做的事情是:

df = pd.DataFrame({"year": [2001, 2001, 2001, 2005, 2005],"值": [1, 2, 5, 3, 1]})df = df.groupby("year").agg(sum=('value', 'sum'),计数=('值'，'大小'))

然而，这给出了以下内容:

TypeError:aggregate() 缺少 1 个必需的位置参数:'arg'

解决方案

由于您需要为一列使用两个 aggfunction ，因此您可能需要传递给列表，就像您未将 pandas 更新为 0.25 一样.0

df = df.groupby("year").value.agg(['sum','count'])df总和数年2001 8 32005 4 2

在pandas 0.25.0

pd.__version__'0.25.0'df = df.groupby("year").agg(sum=('value', 'sum'),计数=('值'，'计数'))df总和数年2001 8 32005 4 2

I want to apply two different aggregates on the same column in a pandas DataFrameGroupBy and have the new columns be named.

I've tried using what is shown here in the documentation. https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#named-aggregation

In [82]: animals.groupby("kind").agg(
   ....:     min_height=('height', 'min'),
   ....:     max_height=('height', 'max'),
   ....:     average_weight=('weight', np.mean),
   ....: )
   ....: 
Out[82]: 
      min_height  max_height  average_weight
kind                                        
cat          9.1         9.5            8.90
dog          6.0        34.0          102.75

Something like what I'm trying to do is:

df = pd.DataFrame({"year": [2001, 2001, 2001, 2005, 2005],
                   "value": [1, 2, 5, 3, 1]})

df = df.groupby("year").agg(sum=('value', 'sum'),
                            count=('value', 'size'))

However, this gives the following:

TypeError: aggregate() missing 1 required positional argument: 'arg'

解决方案

Since you need two aggfunction for one columns , you may need to pass to list like when you are not update your pandas to 0.25.0

df = df.groupby("year").value.agg(['sum','count'])
df
      sum  count
year            
2001    8      3
2005    4      2 

In pandas 0.25.0

pd.__version__
'0.25.0'
df = df.groupby("year").agg(sum=('value', 'sum'),
                            count=('value', 'count'))
df
      sum  count
year            
2001    8      3
2005    4      2

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