asset_correlation_few_stocks_a.py

    # ========== Get token ==========
    with open("../../tokens/iex_token.txt", "r") as f:
        iex_tkn = f.read().strip()

    # ========== Get symbols to use ==========
    symbol_list = ["MSFT", "AAPL", "NVDA", "JNJ", "KHC", "ALL"]

    # ========== Get symbols to use ==========
    date_range = '3m'
    symbol_dict = dict()
    for symbol in symbol_list:
        outpath = f"data/{symbol}_{date_range}.json"
        if not os.path.exists(outpath):  # Check that the file isn't already there
            resp = get_prices(symbol, iex_tkn, date_param=date_range)
            if resp is not None:
                prices_obj = parse_resp(resp)
                with open(outpath, "w") as f:
                    json.dump(prices_obj, f)
                symbol_dict[symbol] = prices_obj
        else:
            logger.info(f"Data exists for {outpath}, skipping")
            with open(outpath, "r") as f:
                data_obj = json.load(f)
            symbol_dict[symbol] = data_obj

    df = utils.symbol_dict_to_df(symbol_dict)
    fig = px.line(df, x="date", y="close",
                  color="symbol", facet_col="symbol", facet_col_wrap=4,
                  category_orders={"symbol": list(np.sort(df["symbol"].unique()))},
                  template="plotly_white")
    fig.show()