MyData['sort_id'] = MyData['salary'].groupby(MyData['dep_id']).rank()

import pandas as pd
data_dict = {"name": 
       ["Rose", "Jack", "Tom", "Kyle", "Jery", "Adam", "Bill", "David", "Denny", "Evan"],
      "class": [1, 2, 3, 1, 2, 3, 1, 2, 3, 1],
      "score": [88, 92, 38, 98, 22, 65, 45, 53, 97, 100]}
df = pd.DataFrame(data=data_dict)
df

df = df.groupby('class', sort=False)\

    .apply(lambda x:x.sort_values("score", ascending=False))\

    .reset_index(drop=True)
df

df["rank"] = None
# 标识班级
flag = df.loc[0].values[1]
rank = 0
for i in range(len(df)):
  temp = df.loc[i].values[1]
  if (temp == flag).all():
    # 同一班级
    rank += 1
  else:
    # 不同班级，重新计算排名
    flag = temp
    rank = 1
  df.loc[i, "rank"] = rank
df