如何创建熊猫中按索引分组的记录列表?

我有一个CSV记录:

name,credits,email
bob,,test1@foo.com
bob,6.0,test@foo.com
bill,3.0,something_else@a.com
bill,4.0,something@a.com
tammy,5.0,hello@gmail.org

name

{
  "bob": [
      { "credits": null, "email": "test1@foo.com"},
      { "credits": 6.0, "email": "test@foo.com" }
  ], 
  // ...
}

我目前的解决方案有点笨拙,因为它似乎只将pandas用作读取CSV的工具,但它生成了我预期的JSONish输出:

#!/usr/bin/env python3

import io
import pandas as pd
from pprint import pprint
from collections import defaultdict

def read_data():
    s = """name,credits,email
bob,,test1@foo.com
bob,6.0,test@foo.com
bill,3.0,something_else@a.com
bill,4.0,something@a.com
tammy,5.0,hello@gmail.org
"""

    data = io.StringIO(s)
    return pd.read_csv(data)

if __name__ == "__main__":
    df = read_data()
    columns = df.columns
    index_name = "name"
    print(df.head())

    records = defaultdict(list)

    name_index = list(columns.values).index(index_name)
    columns_without_index = [column for i, column in enumerate(columns) if i != name_index]

    for record in df.values:
        name = record[name_index]
        record_without_index = [field for i, field in enumerate(record) if i != name_index]
        remaining_record = {k: v for k, v in zip(columns_without_index, record_without_index)}
        records[name].append(remaining_record)
    pprint(dict(records))

有没有办法在当地的熊猫(和numpy)身上做同样的事情?