Preface

Data visualization is intended to provide information clearly and help the viewer understand them qualitatively. The well-known expression that a picture is worth a thousand words may be rephrased as "a picture tells a story as well as a large collection of words". Visualization is, therefore, a very precious tool that helps the viewer understand a concept quickly. However, data visualization is more of an art than a skill because if you try to overdo it, it could have a reverse effect.

We are currently faced with a plethora of data containing many insights that hold the key to success in the modern day. It is important to find the data, clean it, and use the right tool to visualize it. This book explains several different ways to visualize data using Python packages, along with very useful examples in many different areas such as numerical computing, financial models, statistical and machine learning, and genetics and networks.

This book presents an example code developed on Mac OS X 10.10.5 using Python 2.7, IPython 0.13.2, matplotlib 1.4.3, NumPy 1.9.2, SciPy 0.16.0, and conda build version 1.14.1.