22. Stock Option Range

Question:

In the next lesson, we’ll talk about feature scaling. It’s a type of feature preprocessing that you should perform before some classification and regression tasks. Here’s a sneak preview that should call your attention to the general outline of what feature scaling does.

What are the maximum and minimum values taken by the “exercised_stock_options” feature used in this example?

(NB: if you look at finance_features, there are some "NaN" values that have been cleaned away and replaced with zeroes--so while those might look like the minima, it's a bit deceptive because they're more like points for which we don't have information, and just have to put in a number. So for this question, go back to data_dict and look for the maximum and minimum numbers that show up there, ignoring all the "NaN" entries.)