Categorical data cleaning

- [Instructor] In this final lesson … of the EDA and data cleaning chapter, … we'll take what we learned through our EDA … on categorical variables, … and we'll apply it to clean up our dataset. … Part of this is going to be repeating … what we did in the last lesson, … but we'll remove all of the exploratory work … so you can see a clear, … direct way of how this data should be cleaned. … So start by importing the packages that we need, … reading in our data, and then we're going to drop the name … and the ticket features. … We already talked through why we're dropping name. … We're going to drop ticket as well, … since it's essentially a randomly assigned number. … We already captured ticket class with the P class feature. … So in order to drop those two features, … we'll just call this .drop method, pass in a list … of those two features, tell it we want to drop the columns, … and we want to alter titanic in place. … So go ahead and run that. … In the last section, … we learned that missing values for Cabin weren't missing …