Practical Python Data Wrangling and Data Quality

Chapter 11. Beyond Python

Python is an exceptionally powerful and versatile tool for working with data, and if you’ve followed along with the exercises in this book, you are hopefully starting to feel confident about using it to move your own data wrangling projects forward. Thanks to the vibrant Python community and the constantly evolving suite of helpful libraries that its members create and maintain, the work you’ve put into learning the fundamentals in this book will still be valuable whether your next data wrangling project comes along tomorrow or next year. Also, while Python as a programming language is unique in many ways, the programming skills and vocabulary that you’ve acquired here will give you a head start with other programming languages, especially ones relatively object-oriented ones like JavaScript.

Still, one thing I’ve tried to clarify throughout this book is that there are times when the “programmatic” solution to a problem is not really the most efficient one. Our work with Excel and XML files in Chapter 4, for example, highlighted that sometimes trying to do things programmatically just doesn’t make sense. For example, while in Example 4-12 we could have written a Python script to traverse our entire XML document in order to discover its structure, it was undoubtedly faster and easier to simply look at our data, identify the elements that interested us, and write our Python program to target them directly. Likewise, there are times when writing a Python ...