Preface

Preface

Data visualisation is a branch of descriptive statistics that can be considered both an art and a science. It allows information to be communicated with clarity and efficiency, ultimately aiding the viewer in their analysis by making the data digestible. Each visualisation has its own strengths and weaknesses depending on the encoding (e.g. markers, lines, or bars) and arrangement. They can be used to compare values, observe frequencies, understand relationships, expose clusters, and reveal more about the data than what was previously understood.

Although the primary goal of data visualisation is to communicate information, it doesn't mean that they can't be aesthetically pleasing, or beautiful. In fact, we can almost always consider the secondary goal of data visualisation to be how engaging a visualisation is for the viewer. A carefully crafted data visualisation can both turn heads and paint the bigger picture.

In [9]:
# Visualising the confirmed cases of COVID-19 in England (21 March 2020)

An inevitable extension to data visualisation was taking the graphical representation from something that was static to something that was interactive. Whilst static data visualisation (raster or vector) can help us better understand data, interactive data visualisation allows us to also explore and obtain even deeper insight.

Throughout this book, we will journey through many different types of data and view them through the lens of many different types of data visualisation. We will progress through the "good enough" representations of the data, all the way to the elegant and beautiful. We will cover static and interactive visualisations, and usually, visualisations that can be interactive whilst degrading gracefully for print.

We won't restrict ourselves to one technology but as a starting point, we will be working with Python and its various plotting packages. There may be visualisations that require looking into JavaScript libraries, or powerful engines such as Unity3D for the more demanding visualisations and generative art.

Note

I aim to generate everything in this book through code. This means you will see the code for all my figures and tables, including things like flowcharts.

This book is currently available in early access form. It is being actively worked on and updated.

Every section is intended to be independent, so you will find some repetition as you progress from one section to another.

Support this work

You can access this notebook and more by getting the e-book, Data is Beautiful.