Pandas 按列分組並獲得頻率為 0

Question

我有一個 dataframe，我想按 Col1 Col2 Col3 分組並獲得 Value 列的 0 頻率：df =

Col1 Col2 Col3 Value
Val1 Val2  A    0
Val1 Val2  A    1
Val1 Val2  A    2
Val1 Val2  A    0
Val1 Val2  A    1

Val1 Val2  B    0
Val1 Val2  B    0
Val1 Val2  B    0
Val1 Val2  B    0
Val1 Val2  B    1
...

如何應用 groupby 來實現

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

謝謝！

Answer 1

一個簡單的lambda function 為您完成。 生成一個列表，其中Value==0 ，獲取此列表的 len 和組中的項目 len。 你有百分比

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)})

output

                Value
Col1 Col2 Col3       
Val1 Val2 A       0.4
          B       0.8

Answer 2

在 dataframe 上使用 groupby，然后對生成的 dataframe 應用 size() 方法。 例如，假設您創建了一個名為 df 的 dataframe 包含這些值

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]}) 

然后可以使用找到單個元素的頻率計數

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

Answer 3

這是不使用 lambda 的另一種方法，這對我來說似乎更容易理解：

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

Answer 4

為Value等於 0 創建 boolean 列，並在Col列上進行 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