Putting it all together into high-quality code

Now that we have the fundamentals about analyzing data with descriptive statistics, we're going to improve our code's structure and flexibility by breaking it up into functions. Even though this is common knowledge among efficient programmers, it's not a common practice among data analysts. Many data analysts would simply paste the code we have developed all together, as-is, into a single file, and run it every time they wanted to perform the analysis. We won't be adding new features to the analysis. All we'll do is reorder code into functions to encapsulate their inner-workings and communicate intention with function names (this substantially reduces the need for comments).

We'll focus on producing high-quality code that is easy to read, reuse, modify, and fix (in case of bugs). The way we actually do it is a matter of style, and different ways of arranging code are fit for different contexts. The method we'll work with here is one that has...