Python 按列分组，并获得0的频率

我有一个数据帧，我想按Col1 Col2 Col3分组，并获得值列的0频率： df=

我如何应用groupby来实现

Col1 Col2 Col3 Fercentage_of_0
Val1 Val2  A       0.2
Val1 Val2  B       0.8
...

---

谢谢大家!

一个简单的

lambda

函数可以为您完成此任务。生成一个列表，其中

Value==0

，获取此列表的len和组中项目的len。你有百分比吗

df = pd.DataFrame({"Col1":["Val1","Val1","Val1","Val1","Val1","Val1","Val1","Val1","Val1","Val1"],"Col2":["Val2","Val2","Val2","Val2","Val2","Val2","Val2","Val2","Val2","Val2"],"Col3":["A","A","A","A","A","B","B","B","B","B"],"Value":[0,1,2,0,1,0,0,0,0,1]})

df.groupby(["Col1","Col2","Col3"]).\
    agg({"Value":lambda x: len([v for v in x if v==0])/len(x)})

输出

                Value
Col1 Col2 Col3       
Val1 Val2 A       0.4
          B       0.8

---

对数据帧使用groupby，然后对生成的数据帧应用size（）方法。 例如，假设您有一个名为df的createda数据帧，其中包含这些值

df = pd.DataFrame({'Col1': ['Val1','Val1','Val1','Val1','Val1','Val1','Val1','Val1'], 
               'Col2': ['Val2','Val2','Val2','Val2','Val2','Val2','Val2','Val2'],
               'Col3': ['A','A','A','A','B','B','B','B'],
               'Value':[0,1,2,0,0,0,0,1]}) 

然后，可以使用

df.groupby(['Col1','Col2','Col3','Value']).size()
Col1  Col2  Col3  Value
Val1  Val2  A     0        2
                  1        1
                  2        1
            B     0        3
                  1        1
dtype: int64

---

这里有另一种不使用lambda的方法，这对我来说似乎更容易理解：

df['is_zero'] = df['Value'] == 0
df.groupby(['Col1', 'Col2', 'Col3'])['is_zero'].mean()

---

为

Value

创建一个等于0的布尔列，并在

Col

列上创建groupby

(
    df.assign(Percentage_Of_0=lambda x: x.Value.eq(0))
    .groupby(["Col1", "Col2", "Col3"], as_index=False)
    .Percentage_Of_0.mean()
)

    Col1    Col2    Col3    Percentage_Of_0
0   Val1    Val2    A       0.4
1   Val1    Val2    B       0.8

---

df['Value'].eq（0）.groupby（[df['Col1']，df['Col2']，df['Col3']]）。mean（）

？@QuangHoang谢谢！你从哪里学来的？

(
    df.assign(Percentage_Of_0=lambda x: x.Value.eq(0))
    .groupby(["Col1", "Col2", "Col3"], as_index=False)
    .Percentage_Of_0.mean()
)

    Col1    Col2    Col3    Percentage_Of_0
0   Val1    Val2    A       0.4
1   Val1    Val2    B       0.8