模仿SQL的row_number() over (partition by column order by column)

import pandas as pd  
  
# 创建一个示例数据框  
data = {  
    'group': ['A', 'A', 'A', 'B', 'B', 'C', 'C', 'C', 'C'],  
    'value': [3, 1, 2, 5, 4, 6, 9, 7, 8]  
}  
df = pd.DataFrame(data)  
  
# 先按group分组，再按value列升序排序  
df_sorted_asc = df.sort_values(by=['group', 'value'])  
  
# 使用groupby和cumcount为每组内按value升序分配一个序号  
df_sorted_asc['group_rank_asc'] = df_sorted_asc.groupby('group').cumcount() + 1  
  
print(df_sorted_asc)

# 先按group分组，再按value列降序排序  
df_sorted_desc = df.sort_values(by=['group', 'value'], ascending=[True, False])  
  
# 使用groupby和cumcount为每组内按value降序分配一个序号  
df_sorted_desc['group_rank_desc'] = df_sorted_desc.groupby('group').cumcount() + 1  
  
print(df_sorted_desc)