CODEWITHSUNDEEP
pythonpandas
Alex
Alex

Reputation: 237

convert dataframe to nested json

I am using 

pd.read_sql_query()

to get data from database and then use 

to_json(orient='records')

this is the dataframe:

(1)
  price_formula_id  premium  product_id  exchange  product_name  product_code   weight  
0            30064      0.0        c001       CME          2018            CL      0.3
1            30064      0.0        c002       CME          2018            CL      0.7

(2)
price_formula_id  premium  product_id  exchange  product_name  product_code   weight  
0            30064      NONE        c001       CME          2018            CL      0.3
1            30064      NONE        c002       CME          2018            CL      0.7

to convert to this formation.

[{
    "price_formula_id": "30064",
    "premium": "0.0",
    "product_id": "c001",
    "exchange": "CME",
    "product_name": "2018",
    "product_code": "CL",
    "weight": "0.3"
},
{
    "price_formula_id": "30064",
    "premium": "0.0",
    "product_id": "c002",
    "exchange": "CME",
    "product_name": "2018",
    "product_code": "CL",
    "weight": "0.7"
}]

but what I really want should be like this :

 { 
   "price_formula_id": "30064",
   "premium": "0.0",
   "basket": 
    [
     {"product_id": "c001",
      "exchange": "CME",
      "product_name": "2018",
      "product_code": "CL",
      "weight": "0.3"
     },
     {
      "product_id": "c002",
      "exchange": "CME",
      "product_name": "2018",
      "product_code": "CL",
      "weight": "0.7"
     }
    ]
 }

I need to group the same info and set a new index 'basket' for the rest. how could I make it? Thanks very much.

Upvotes: 4

Views: 3901

Answers (1)

jezrael
jezrael

Reputation: 862671

Use groupby with custom function with to_dict for all columns filtered by difference, reset_index and last convert it to_json:

cols = df.columns.difference(['price_formula_id','premium'])
j = (df.groupby(['price_formula_id','premium'])[cols]
       .apply(lambda x: x.to_dict('r'))
       .reset_index(name='basket')
       .to_json(orient='records'))
print (j)

[{
    "price_formula_id": 30064,
    "premium": 0.0,
    "basket": [{
            "exchange": "CME",
            "product_code": "CL",
            "product_id": "c001",
            "product_name": 2018,
            "weight": 0.3
        },
        {
            "exchange": "CME",
            "product_code": "CL",
            "product_id": "c002",
            "product_name": 2018,
            "weight": 0.7
        }
    ]
}]

Upvotes: 6

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