May-20-2018, 06:30 AM
Hi All,
I have following json data-
I have tried with following in Python3.6 -
Can anyone please try with above json data and share me the required dataframe?
I have following json data-
{ 'SuccessResponse': { 'Head': { 'RequestAction': 'GetCategoryTree', 'RequestId': '', 'ResponseType': 'Categories', 'Timestamp': '2018-05-19T00:30:55+08:00' }, 'Body': [ { 'categoryId': 1902, 'children': [ { 'categoryId': 10001930, 'children': [ { 'categoryId': 10001958, 'children': [ ], 'leaf': True, 'name': 'Accessories', 'var': False }, { 'categoryId': 10001957, 'children': [ ], 'leaf': True, 'name': 'Backpacks', 'var': False }, { 'categoryId': 10001956, 'children': [ ], 'leaf': True, 'name': 'Backpacks Trolley', 'var': False }, { 'categoryId': 10001955, 'children': [ ], 'leaf': True, 'name': 'Bags', 'var': False } ], 'leaf': False, 'name': 'Kids Bags', 'var': False }, { 'categoryId': 10001928, 'children': [ { 'categoryId': 10001947, 'children': [ { 'categoryId': 10001990, 'children': [ ], 'leaf': True, 'name': 'Fashion backpacks', 'var': True } ], 'leaf': False, 'name': 'Backpacks', 'var': False }, { 'categoryId': 10001946, 'children': [ ], 'leaf': True, 'name': 'Business Bags', 'var': True }, { 'categoryId': 10001948, 'children': [ ], 'leaf': True, 'name': 'Crossbody Bags', 'var': True }, { 'categoryId': 10001945, 'children': [ ], 'leaf': True, 'name': 'Messenger Bags', 'var': True }, { 'categoryId': 10001949, 'children': [ ], 'leaf': True, 'name': 'Tote Bags', 'var': True }, { 'categoryId': 10001950, 'children': [ { 'categoryId': 10001993, 'children': [ ], 'leaf': True, 'name': 'Card Holders', 'var': True }, { 'categoryId': 10001992, 'children': [ ], 'leaf': True, 'name': 'Coin Holders & Pouches', 'var': True }, { 'categoryId': 10001994, 'children': [ ], 'leaf': True, 'name': 'Key Holders', 'var': True }, { 'categoryId': 10001995, 'children': [ ], 'leaf': True, 'name': 'Money Clips', 'var': True }, { 'categoryId': 10001991, 'children': [ { 'categoryId': 10002040, 'children': [ ], 'leaf': True, 'name': 'Fashion Wallets', 'var': True } ], 'leaf': False, 'name': 'Wallets', 'var': False } ], 'leaf': False, 'name': 'Wallets & Accessories', 'var': False } ], 'leaf': False, 'name': 'Men Bags', 'var': False }, { 'categoryId': 10001931, 'children': [ { 'categoryId': 10001961, 'children': [ { 'categoryId': 10002017, 'children': [ ], 'leaf': True, 'name': 'Briefcases', 'var': False }, { 'categoryId': 10002020, 'children': [ ], 'leaf': True, 'name': 'Laptop Backpacks', 'var': False }, { 'categoryId': 10002019, 'children': [ ], 'leaf': True, 'name': 'Laptop cases', 'var': False }, { 'categoryId': 10002018, 'children': [ ], 'leaf': True, 'name': 'Messenger Bags', 'var': False } ], 'leaf': False, 'name': 'Laptop Bags', 'var': False }, { 'categoryId': 10001959, 'children': [ { 'categoryId': 10001998, 'children': [ ], 'leaf': True, 'name': 'Kids Luggage', 'var': False }, { 'categoryId': 10001997, 'children': [ ], 'leaf': True, 'name': 'Luggage Sets', 'var': False }, { 'categoryId': 10001996, 'children': [ ], 'leaf': True, 'name': 'Suitcases', 'var': False } ], 'leaf': False, 'name': 'Luggage', 'var': False }, { 'categoryId': 10001960, 'children': [ { 'categoryId': 10002015, 'children': [ ], 'leaf': True, 'name': 'Compression Bags', 'var': False }, { 'categoryId': 10002013, 'children': [ ], 'leaf': True, 'name': 'Garment Bags', 'var': False }, { 'categoryId': 10001999, 'children': [ ], 'leaf': True, 'name': 'Luggage Carts', 'var': False }, { 'categoryId': 10002000, 'children': [ ], 'leaf': True, 'name': 'Luggage Locks', 'var': False }, { 'categoryId': 10002001, 'children': [ ], 'leaf': True, 'name': 'Luggage Scales', 'var': False }, { 'categoryId': 10002005, 'children': [ { 'categoryId': 10002041, 'children': [ ], 'leaf': True, 'name': 'Luggage Straps', 'var': False }, { 'categoryId': 10002042, 'children': [ ], 'leaf': True, 'name': 'Luggage Tags', 'var': False } ], 'leaf': False, 'name': 'Luggage Straps & Tags', 'var': False }, { 'categoryId': 10002004, 'children': [ ], 'leaf': True, 'name': 'Luggage protectors & covers', 'var': False }, { 'categoryId': 10002010, 'children': [ ], 'leaf': True, 'name': 'Organizer Sets', 'var': False }, { 'categoryId': 10002016, 'children': [ ], 'leaf': True, 'name': 'Other Packing Organizers', 'var': False }, { 'categoryId': 10002008, 'children': [ ], 'leaf': True, 'name': 'Other Travel Accessories', 'var': False }, { 'categoryId': 10002002, 'children': [ ], 'leaf': True, 'name': 'Passport Covers', 'var': False }, { 'categoryId': 10002012, 'children': [ ], 'leaf': True, 'name': 'Shoe Bags', 'var': False }, { 'categoryId': 10002009, 'children': [ ], 'leaf': True, 'name': 'Toiletries & Cosmetics Bags', 'var': False }, { 'categoryId': 10002014, 'children': [ ], 'leaf': True, 'name': 'Travel Size Bottles & Containers', 'var': False }, { 'categoryId': 10002003, 'children': [ ], 'leaf': True, 'name': 'Travel Wallets', 'var': False }, { 'categoryId': 10002006, 'children': [ ], 'leaf': True, 'name': 'Travel adapters & Converters', 'var': False }, { 'categoryId': 10002007, 'children': [ { 'categoryId': 10002046, 'children': [ ], 'leaf': True, 'name': 'Ear plugs', 'var': False }, { 'categoryId': 10002045, 'children': [ ], 'leaf': True, 'name': 'Eye masks', 'var': False }, { 'categoryId': 10002044, 'children': [ ], 'leaf': True, 'name': 'Travel pillows', 'var': False }, { 'categoryId': 10002043, 'children': [ ], 'leaf': True, 'name': 'Travel sets', 'var': False } ], 'leaf': False, 'name': 'Travel pillows & eye masks', 'var': False }, { 'categoryId': 10002011, 'children': [ ], 'leaf': True, 'name': 'Underwear Organizers', 'var': False } ], 'leaf': False, 'name': 'Travel Accessories', 'var': False }, { 'categoryId': 10001962, 'children': [ { 'categoryId': 10002023, 'children': [ ], 'leaf': True, 'name': 'Foldable & Drawstring bags', 'var': False }, { 'categoryId': 10002022, 'children': [ ], 'leaf': True, 'name': 'Waist Packs', 'var': False }, { 'categoryId': 10002021, 'children': [ ], 'leaf': True, 'name': 'Weekender bags', 'var': False } ], 'leaf': False, 'name': 'Travel Bags', 'var': False } ], 'leaf': False, 'name': 'Travel', 'var': False }, { 'categoryId': 10001929, 'children': [ { 'categoryId': 10001951, 'children': [ ], 'leaf': True, 'name': 'Backpacks', 'var': True }, { 'categoryId': 10001953, 'children': [ ], 'leaf': True, 'name': 'Card Holders', 'var': True }, { 'categoryId': 10001952, 'children': [ ], 'leaf': True, 'name': 'Coin Purses & Pouches', 'var': True }, { 'categoryId': 10001954, 'children': [ ], 'leaf': True, 'name': 'Key Holders', 'var': True } ], 'leaf': False, 'name': 'Unisex Bags', 'var': False }, { 'categoryId': 10001927, 'children': [ { 'categoryId': 10001942, 'children': [ ], 'leaf': True, 'name': 'Backpacks', 'var': True }, { 'categoryId': 10001941, 'children': [ ], 'leaf': True, 'name': 'Clutches', 'var': True }, { 'categoryId': 10001939, 'children': [ ], 'leaf': True, 'name': 'Cross Body & Shoulder Bags', 'var': True }, { 'categoryId': 10001940, 'children': [ ], 'leaf': True, 'name': 'Top-Handle Bags', 'var': True }, { 'categoryId': 10001938, 'children': [ ], 'leaf': True, 'name': 'Tote Bags', 'var': True }, { 'categoryId': 10001944, 'children': [ { 'categoryId': 10001985, 'children': [ ], 'leaf': True, 'name': 'Bag Charms & Accessories', 'var': True }, { 'categoryId': 10001988, 'children': [ ], 'leaf': True, 'name': 'Card Holders', 'var': True }, { 'categoryId': 10001987, 'children': [ ], 'leaf': True, 'name': 'Coin Purses & Pouches', 'var': True }, { 'categoryId': 10001989, 'children': [ ], 'leaf': True, 'name': 'Key Holders', 'var': True }, { 'categoryId': 10001986, 'children': [ ], 'leaf': True, 'name': 'Wallets', 'var': True } ], 'leaf': False, 'name': 'Wallets & Accessories', 'var': False }, { 'categoryId': 10001943, 'children': [ ], 'leaf': True, 'name': 'Wristlets', 'var': True } ], 'leaf': False, 'name': 'Women Bags', 'var': False } ], 'leaf': False, 'name': 'Bags and Travel', 'var': False } ] } }Now I want to fetch 'categoryId','name' from above nested json and store them in a pandas Dataframe.
I have tried with following in Python3.6 -
dfCat = json_normalize(json_data['SuccessResponse']['Body'],'children')But couldn't get all values of required columns due to this nested json data.
Can anyone please try with above json data and share me the required dataframe?