Go to your Jupyter Notebook and filter the stock data data frame to display all observations with null values in the price target feature.

The way we do that is by creating a Boolean mask using the pandas is null function. That is null function is going to then look at this feature that we pass it, which here we're indicating we want to look at the feature price target and is null looks at that and it returns a series of true and false values. It looks at each observation and determines is this null true or is it not false? And that gives us a Boolean mask that we can then pass to our stock data dataframe. And when I execute that, it will give me these seven observations with null values. And when I look at these observations, I can see that they're ETFs, so it makes sense that those values would be null. Now I can make a decision about whether or not I want to include them in my dataset.