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?
