3 It’s all about the data

 

This chapter covers

  • Where and how to acquire data
  • Understanding data at a fundamental level
  • Describing data values (discrete vs. continuous, sequential vs. categorical)
  • Storing data in rows and columns
  • Nesting data in key-value pairs

In chapter 2, we learned all about some basic design principles and concepts we’ll be using throughout this book, but this chapter is all about the data. To ensure everyone has the same basic understanding of data fundamentals, we’ll first touch on where you might find data out in the wild. Next, we’ll answer the question “What is data?” and talk about several basic data types. After that, we’ll learn how to describe the values of data and whether they are discrete or continuous and sequential or categorical. Finally, we’ll cover the two main types of data structures you’ll encounter in your visualization journey: tables and nested data.

3.1 Where you get data

Somehow, you’ve got some free time outside of work, where you don’t typically have access to data managed by IT and then handed to you on a platter. With that time, you want to make a visualization, and I say, good for you, my fellow nerd! Now what?

The initial step when making a visualization could go one of two ways:

  1. You have an awesome idea, a story you want to tell, but you need some data.
  2. You have some awesome data, but you’ll need to dig around to find a story.

3.1.1 Find some open data

3.1.2 Buy it

3.1.3 Gather it yourself

3.2 Dimensions and measures

3.3 A primer of data types

3.3.1 Strings

3.3.2 Numbers

3.3.3 Dates

3.3.4 Booleans

3.4 Describing data values

3.4.1 Discrete vs. continuous