python - 获取按值分组的每行的百分比

问题描述

我有以下df：

df3 = pd.DataFrame(np.array([['Iza', 'Tuesday'],['Martin', 'Friday'],['John', 'Monday'],['Iza', 'Tuesday'],['Iza', 'Tuesday'],['Iza', 'Wednesday'],['Sara', 'Friday'], ['Sara', 'Friday'], ['Sara', 'Sunday'],['Silvia', 'Monday'],['Silvia', 'Wednesday'],['Paul', 'Monday'],['Paul', 'Tuesday'],['Paul', 'Wednesday']]),
                   columns=['Name', 'Day'])

df3:

    Name    Day
0   Iza     Tuesday
1   Martin  Friday
2   John    Monday
3   Iza     Tuesday
4   Iza     Tuesday
5   Iza     Wednesday
6   Sara    Friday
7   Sara    Friday
8   Sara    Sunday
9   Silvia  Monday
10  Silvia  Wednesday
11  Paul    Monday
12  Paul    Tuesday
13  Paul    Wednesday

我得到了每个用户的天数：

oo = df3.groupby(['Name','Day'])['Day'].size().reset_index(name='counts')

结果：

    Name    Day      counts
0   Iza    Tuesday      3
1   Iza    Wednesday    1
2   John    Monday      1
3   Martin  Friday      1
4   Paul    Monday      1
5   Paul    Tuesday     1
6   Paul    Wednesday   1
7   Sara    Friday      2
8   Sara    Sunday      1
9   Silvia  Monday      1
10  Silvia  Wednesday   1

丢弃只有一天记录的不受欢迎的用户；

uniq_us = oo[oo.duplicated(['Name'], keep=False)]

结果：

    Name    Day       counts
0   Iza     Tuesday     3
1   Iza     Wednesday   1
4   Paul    Monday      1
5   Paul    Tuesday     1
6   Paul    Wednesday   1
7   Sara    Friday      2
8   Sara    Sunday      1
9   Silvia  Monday      1
10  Silvia  Wednesday   1

现在我想按名称获取每个分组日期中的计数百分比：

uniq_us.groupby(['Name','Day'])['counts'].apply(lambda x: x.value_counts(normalize=True)) * 100

我有：

Name    Day         
Iza     Tuesday    3    100.0
        Wednesday  1    100.0
Paul    Monday     1    100.0
        Tuesday    1    100.0
        Wednesday  1    100.0
Sara    Friday     2    100.0
        Sunday     1    100.0
Silvia  Monday     1    100.0
        Wednesday  1    100.0
Name: counts, dtype: float64

我不知道如何按分组名称计算它

期望的输出：

     Name    Day         

    Iza     Tuesday    3    75.0
            Wednesday  1    25.0
    Paul    Monday     1    33.33
            Tuesday    1    33.33
            Wednesday  1    33.33
    Sara    Friday     2    66.66
            Sunday     1    33.34
    Silvia  Monday     1    50.0
            Wednesday  1    50.0
    Name: counts, dtype: float64

标签： pythonpandasdataframenumpy

(df3.groupby('Name') .Day .value_counts(normalize=True) .mul(100) .rename('Counts') .reset_index() .pipe(lambda x: x[x.duplicated(['Name'], keep=False)])) # Name Day Counts #0 Iza Tuesday 75.000000 #1 Iza Wednesday 25.000000 #4 Paul Monday 33.333333 #5 Paul Tuesday 33.333333 #6 Paul Wednesday 33.333333 #7 Sara Friday 66.666667 #8 Sara Sunday 33.333333 #9 Silvia Monday 50.000000 #10 Silvia Wednesday 50.000000

python - 获取按值分组的每行的百分比

问题描述

解决方案

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