In Step 2, we created a QuantFig object by passing a DataFrame containing the input data, as well as some arguments for the title and legend's position. We could have created a simple candlestick chart by running the iplot method of QuantFig immediately afterward.

However, in Step 3, we also added two moving average lines by using the add_sma/add_ema methods. We decided to consider 20 periods (days, in this case). By default, the averages are calculated using the close column, however, we can change this by providing the column argument.

The difference between the two moving averages is that the exponential one puts more weight on recent prices. By doing so, it is more responsive to new information and reacts faster to any changes in the general trend.