Stok daily return

def daily_return_estimator(df):
    df_daily_return = df.copy()

# Loop through each stock (column of the dataframe except Date collumn)
    for i in df.columns[1:]:

        # Loop through each row/price belonging to the stock
        for j in range(1, len(df)):

            # Calculate the percentage of change from the previous day's close price.
            # Simple equation of percentage change.
            df_daily_return[i][j] = ((df[i][j]- df[i][j-1])/df[i][j-1]) * 100

         # set the value of first row to zero (previous value is not available)
        df_daily_return.loc[0, i] = 0

    return df_daily_return