df.to_dict make duplicated index (pandas) as primary key in a nested dict

I have this data frame which I’d like to convert to a dict in python, I have many other categories, but showed just two for simplicity

Category   Name                     Description             Price       
Diesel     Land Rover               No Description found    £ x
Electric   Tesla Model X            No Description found    £ x

I want the output to be like this

dict = {"Category": {"Diesel" : {
                                "Name": "Land Rover", 
                                "Description":"No Description Found", 
                                "Price": "£ x" },
                                           
                    "Electric" : {"Name": "Tesla Model X", 
                                  "Description":"No Description Found", 
                                  "Price": "£ x" }
                    }               
        }

Answer

You can do this without assigning an additional column or aggregating using list:

def collect(category):
  return category[['Name', 'Description', 'Price']].to_dict('records')

data = {'Category': df.groupby('Category').apply(collect).to_dict()}

I created a separate function for readability – you could, of course, pass it as a lambda too:

{
  'Category': df.groupby('Category').apply(
    lambda x: x[['Name', 'Description', 'Price']].to_dict('records')).to_dict()
}