How to use json_normalize to create subcolumns in csv file

I need some help on using json_normalizer to create multiple subcolumns from main columns ? The below code is able to generate an output file but its puts everything in one column however i need something seperate columns with heading like moniker.config, moniker.type, moniker.key, moniker.keyparts for each row

from pandas.io.json import json_normalize
import os
import pandas as pd

def json_normalize_recursive(base_column, data, df=pd.DataFrame()):
    if df.empty:
        df = json_normalize(data, record_prefix=base_column+'.')
    nested = df.select_dtypes(include='object')

    for col in nested.columns:
        try:
            nested_df = json_normalize(nested[col].tolist())
            nested_df.columns = [base_column+'.'+str(col)+'.'+str(c) for c in nested_df.columns]
            df = pd.concat([df.drop(col, axis=1), nested_df], axis=1)
        except ValueError:
            pass
    return df

data = {
   "errors":[
   ],
   "data":[
      {
         "moniker":{
            "config":"fx.ipv.london.eod",
            "type":"fx.spot",
            "key":"EUR/CZK",
            "keyParts":[
               "EUR",
               "CZK"
            ],
            "configType":"fx.ipv.london.eod/fx.spot",
            "live":True
         },
         "queryMoniker":{
            "config":"fx.ipv.london.eod",
            "type":"EUR/CZK",
            "key":"EUR/CZK",
            "tag":{
               "owner":"official",
               "type":"fx.spot",
               "key":"EUR/CZK",
               "tag":{
                  "owner":"official",
                  "date":13434324400999,
                  "cutoff":"London",
                  "name":"ipv",
                  "live":True
               },
               "keyParts":[
                  "EUR",
                  "CZK"
               ],
               "configType":"fx.ipv.london.eod/fx.spot",
               "live":False
            },
            "instance":{
               "data":"<FxSpot Currency1=\"EUR\"Currency2=\"CZK\" bid=\"24.14\" ask=\"24.147\"/>",
               "unmarshalled":True,
               "marshalled":True,
               "format":"fx/xml/1",
               "valid":True,
               "sequence":1643434234234,
               "instanceMoniker":{
                  "source":"viper.tagcopy",
                  "config":"fx.london.official.copy",
                  "keyParts":[
                     "EUR",
                     "CZK"
                  ]
               }
            }
         }
      }
   ]
}

df = json_normalize_recursive('', data)
print(df)

cwd = os.getcwd()


filepath = os.path.join(cwd, 'Desktop', 'output.csv')

df.to_csv(filepath, index=False)

Desired output:

Solution

try using df = pd.json_normalize(data,'data'['monier','queryMonier']