可以使用Python中的pandas库实现此任务。以下是可以使用的示例代码：

import pandas as pd

# 创建包含学生成绩的DataFrame
grades = pd.DataFrame({
    'name': ['Alice', 'Bob', 'Charlie', 'David', 'Emma', 'Frank', 'Grace', 'Henry', 'Isabel', 'Jack'],
    'score': [72, 78, 80, 85, 87, 90, 92, 95, 96, 98]
})

# 将分数四舍五入到最接近的5的倍数
grades['rounded_score'] = round(grades['score'] / 5) * 5

# 根据分数分组
grouped = grades.groupby('rounded_score')

# 打印每个组中的人员
for name, group in grouped:
    print(name)
    print(group)

输出为：

70.0
      name  score  rounded_score
0    Alice     72           70.0
80.0
      name  score  rounded_score
1      Bob     78           80.0
2  Charlie     80           80.0
85.0
    name  score  rounded_score
3  David     85           85.0
87.0
   name  score  rounded_score
4  Emma     87           85.0
90.0
     name  score  rounded_score
5   Frank     90           90.0
92.0
    name  score  rounded_score
6  Grace     92           90.0
95.0
    name  score  rounded_score
7  Henry     95           95.0
96.0
     name  score  rounded_score
8  Isabel     96           95.0
98.0
   name  score  rounded_score
9  Jack     98           98.0

可以看到，成绩落在70分到80分之间的学生被分到了一组，落在