Creating Dataframe From Nested Dictionary

I am calling an API that returns a batch request of multiple stock tickers in JSON format. It is a nested dictionary, with 2 levels of keys and then a list of dictionaries. Here is

Solution 1:

This will do the job, not sure if it's the cleanest way:

import json 
import requests 
import pandas as pd

r = requests.get('https://api.iextrading.com/1.0/stock/market/batch?symbols=aapl,wpx,mnro,twnk,labl,plnt,fsct,qyls,vrns,tree&types=chart&range=3m')

x = r.json()

output = pd.DataFrame()

for ticker, chart in x.items():   
    for  k, v in chart.items():
        for dictionary in v:
            data = dictionary
            data['ticker'] = ticker
            output = output.append(data, ignore_index=True)

This will have the output:

    change  changeOverTime  changePercent   close   date    high    label   low     open    ticker  unadjustedVolume    volume  vwap
0   0.129548    0.000000    0.060   217.6107    2018-09-19  218.8564    Sep 19, 18  214.5514    217.7403    AAPL    27123833.0  27123833.0  216.6509
1   1.654200    0.007602    0.760   219.2650    2018-09-20  221.5071    Sep 20, 18  218.3880    219.4742    AAPL    26608794.0  26608794.0  219.9999
2   -2.361800   -0.003251   -1.077  216.9032    2018-09-21  220.5903    Sep 21, 18  216.5345    220.0123    AAPL    96246748.0  96246748.0  217.7347
3   3.119100    0.011082    1.438   220.0223    2018-09-24  220.4907    Sep 24, 18  215.8768    216.0661    AAPL    27693358.0  27693358.0  218.6857