How do I json normalize this nested structure using Pandas? - json

Question

I have a JSON url with the following structure from THIS url and am trying to get the name, price and volume from the structure below
{'data': {'1': {'id': 1,
'name': 'Bitcoin',
'symbol': 'BTC',
'website_slug': 'bitcoin',
'rank': 1,
'circulating_supply': 17115025.0,
'total_supply': 17115025.0,
'max_supply': 21000000.0,
'quotes': {'USD': {'price': 6317.68,
'volume_24h': 5034440000.0,
'market_cap': 108127251142.0,
'percent_change_1h': 0.22,
'percent_change_24h': 5.26,
'percent_change_7d': -4.37}},
'last_updated': 1529943576},
'2': {'id': 2,
'name': 'Litecoin',
'symbol': 'LTC',
'website_slug': 'litecoin',
'rank': 6,
'circulating_supply': 57133246.0,
'total_supply': 57133246.0,
'max_supply': 84000000.0,
'quotes': {'USD': {'price': 84.4893,
'volume_24h': 512241000.0,
'market_cap': 4827147957.0,
'percent_change_1h': 1.97,
'percent_change_24h': 8.96,
'percent_change_7d': -12.54}},
'last_updated': 1529943541}},
'metadata': {'timestamp': 1529943282,
'num_cryptocurrencies': 1586,
'error': None}}
I tried several variations to get each coin in a row but have failed so far
Attempt 1
df = pd.read_json('https://api.coinmarketcap.com/v2/ticker')
Attempt 2
data = requests.get('https://api.coinmarketcap.com/v2/ticker',params).json()
df = pd.DataFrame(data['data'])
df
Attempt 3
I found this function on stackoverflow called json normalize and I tried to use it but no luck so far
df = pd.io.json.json_normalize(data['data'])
df
Any suggestions on how to turn each coin into a row are super appreciated
UPDATE 1
params = {'start': 0, 'sort': 'id', 'limit': 100}
data = requests.get('https://api.coinmarketcap.com/v2/ticker', params).json()
df = pd.DataFrame(data['data'])
df = df.transpose()
df.set_index('id')
This is pretty close to what I want, but how do I get the volume and price out of quotes

Answer 1

assuming "quotes" only have 1 row and the key is "USD", I did this
df.drop('quotes', 1).join(
pd.DataFrame(
df.quotes.apply(
lambda x: {'USD'+'_'+key: val for key, val in x['USD'].items()}
).tolist()
)
)