asset_correlation_norm_prices.py

def normalise_price(df):
    df = df.assign(norm_close=0)
    for symbol in df["symbol"].unique():
        symbol_df = df[df["symbol"] == symbol]
        min_date = symbol_df["date"].min()
        ref_val = symbol_df[symbol_df["date"] == min_date]["close"].values[0]
        df.loc[df["symbol"] == symbol, "norm_close"] = df.loc[df["symbol"] == symbol, "close"] / ref_val
    return df