python - 对多个列进行分组并在组内排名

Question

嗨，

我正在寻找组内的设定排名，但不知道该怎么做。

Below is the test data, 
df = pd.DataFrame()

names = ['California','New York','California','New York', 'California','New York', 'California', 'California', 'California', 'California']
types = ['Student','Student','Student','Student','Student', 'Pleasure', 'Pleasure', 'Pleasure','Business', 'Business']

df['names'] = names
df['type'] = types

df.groupby(['names', 'type']).size().reset_index(name='counts')

Below is the output
    names       type        counts
0   California  Business    2
1   California  Pleasure    2
2   California  Student     3
3   New York    Pleasure    1
4   New York    Student     2

我想得到以下输出，排名基于列名称和计数(desc)。在加利福尼亚州，“商务与休闲”具有相同的计数，对我来说，结果排名是 2,3 还是 2,2 并不重要。

        names   type      counts Rank
0   California  Business  2      2      
1   California  Pleasure  2      2
2   California  Student   3      1
3   New York    Pleasure  1      2
4   New York    Student   2      1

任何想法/解决方案

谢谢

Answer 1

使用GroupBy.rank通过 Series.astype 将 float 转换为整数:

df['Rank'] = df.groupby('names')['counts'].rank(ascending=False, method='dense').astype(int)
print(df)
        names      type  counts  Rank
0  California  Business       2     2
1  California  Pleasure       2     2
2  California   Student       3     1
3    New York  Pleasure       1     2
4    New York   Student       2     1