Data Visualization with Python and JavaScript

Chapter 15. Building a Visualization

In Chapter 14 we used the results of our Pandas exploration of the Nobel Prize dataset (see Chapter 11) to imagine a visualization. Figure 15-1 shows the visualization we imagined, and in this chapter we’ll see how to go about building it, leveraging the power of JavaScript and D3.

Figure 15-1. Our target, a Nobel Prize visualization

I’ll show how the visual elements we conceived combine to transform our freshly cleaned and processed Nobel dataset into an interactive web visualization, deployable to billions of devices at the flick of a switch. But before going into the details, let’s have a look at the core components of a modern web visualization.

Preliminaries

Before beginning to build the Nobel visualization, let’s consider the core components that will be used and how we will organize our files.

Core Components

As we saw in “A Basic Page with Placeholders”, building a modern web visualization requires four key components:

• An HTML skeleton upon which to hang our JavaScripted creation

• One or more CSS stylesheets to govern the look and feel of the dataviz

• The JavaScript files themselves, including any third-party libraries you might need (D3 being our biggest dependency)

• And last but not least, the data to be transformed, ideally in the JSON or CSV (if wholly static data) format

Before we start looking at our dataviz components, ...