以不同的印度语言以编程方式从Asp.net发送短信[关闭](Sending SMS programatically from Asp.net in different Indian languages [closed])

 那是你要的吗？ 
 
cols = df.columns.drop('name').tolist()
 
 或者按照@jezrael的建议： 
 
cols = df.columns.difference(['name']) 
 
 接着： 
 
s = df.groupby('name')[cols].apply(lambda x: x.to_dict('r')).to_json()
 
 让我们打印得很好： 
 
In [45]: print(json.dumps(json.loads(s), indent=2))
{
  "bill": [
    {
      "credits": 3.0,
      "email": "something_else@a.com"
    },
    {
      "credits": 4.0,
      "email": "something@a.com"
    }
  ],
  "bob": [
    {
      "credits": null,
      "email": "test1@foo.com"
    },
    {
      "credits": 6.0,
      "email": "test@foo.com"
    }
  ],
  "tammy": [
    {
      "credits": 5.0,
      "email": "hello@gmail.org"
    }
  ]
}

Is that what you want?
 
cols = df.columns.drop('name').tolist()
 
or as recommended by @jezrael:
 
cols = df.columns.difference(['name']) 
 
and then:
 
s = df.groupby('name')[cols].apply(lambda x: x.to_dict('r')).to_json()
 
let's print it nicely:
 
In [45]: print(json.dumps(json.loads(s), indent=2))
{
  "bill": [
    {
      "credits": 3.0,
      "email": "something_else@a.com"
    },
    {
      "credits": 4.0,
      "email": "something@a.com"
    }
  ],
  "bob": [
    {
      "credits": null,
      "email": "test1@foo.com"
    },
    {
      "credits": 6.0,
      "email": "test@foo.com"
    }
  ],
  "tammy": [
    {
      "credits": 5.0,
      "email": "hello@gmail.org"
    }
  ]
}