Chapter 6: Cleaning and Exploring Data with Series Operations

We can view the recipes in the first few chapters of this book as, essentially, diagnostic. We imported some raw data and then generated descriptive statistics about key variables. This gave us a sense of how the values for those variables were distributed and helped us identify outliers and unexpected values. We then examined the relationships between variables to look for patterns, and deviations from those patterns, including logical inconsistencies. In short, our primary goal so far has been to figure out what is going on with our data.

The recipes in this chapter demonstrate how to use pandas methods to update series values once we have figured out what needs to be done. Ideally, we need to take the time to carefully examine our data before manipulating the values of our variables. We should have measures of central tendency, indicators of distribution shape and spread, correlations, and visualizations in front of...