Book Image

Python Data Visualization Cookbook

By : Igor Milovanovic
Book Image

Python Data Visualization Cookbook

By: Igor Milovanovic

Overview of this book

Today, data visualization is a hot topic as a direct result of the vast amount of data created every second. Transforming that data into information is a complex task for data visualization professionals, who, at the same time, try to understand the data and objectively transfer that understanding to others. This book is a set of practical recipes that strive to help the reader get a firm grasp of the area of data visualization using Python and its popular visualization and data libraries. Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing you how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. During the book, we go from simple plots and charts to more advanced ones, thoroughly explaining why we used them and how not to use them. As we go through the book, we will also discuss 3D diagrams. We will peep into animations just to show you what it takes to go into that area. Maps are irreplaceable for displaying geo-spatial data, so we also show you how to build them. In the last chapter, we show you how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python. This book will help those who already know how to program in Python to explore a new field – one of data visualization. As this book is all about recipes that explain how to do something, code samples are abundant, and they are followed by visual diagrams and charts to help you understand the logic and compare your own results with what is explained in the book.
Table of Contents (15 chapters)
Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

About the Reviewers

Tarek Amr achieved his postgraduate degree in Data Mining and Information Retrieval from the University of East Anglia. He has about 10 years' experience in Software Development. He has been volunteering in Global Voices Online (GVO) since 2007, and currently he is the local ambassador of the Open Knowledge Foundation (OKFN) in Egypt. Words such as Open Data, Government 2.0, Data Visualisation, Data Journalism, Machine Learning, and Natural Language Processing are like music to his ears.

Tarek's Twitter handle is @gr33ndata and his homepage is http://tarekamr.appspot.com/.

Jayesh K. Gupta is the Lead Developer of Matlab Toolbox for Biclustering Analysis (MTBA). He is currently an undergraduate student and researcher at IIT Kanpur. His interests lie in the field of pattern recognition. His interests also lie in basic sciences, recognizing them as the means of analyzing patterns in nature. Coming to IIT, he realized how this analysis is being augmented by Machine Learning algorithms with various diverse applications. He believes that augmenting human thought with machine intelligence is one of the best ways to advance human knowledge. He is a long time technophile and a free-software Evangelist. He usually goes by the handle, rejuvyesh online. He is also an avid reader and his books can be checked out at Goodreads. Checkout his projects at Bitbucket and GitHub. For all links visit http://home.iitk.ac.in/~jayeshkg/. He can be contacted at .

Kostiantyn Kucher was born in Odessa, Ukraine. He received his Master's degree in Computer Science from Odessa National Polytechnic University in 2012. He used Python as well as Matplotlib and PIL for Machine Learning and Image Recognition purposes.

Currently, Kostiantyn is a PhD student in Computer Science specializing in Information Visualization. He conducts his research under the supervision of Prof. Dr. Andreas Kerren with the ISOVIS group at the Computer Science Department of Linnaeus University (Växjö, Sweden).

Kenneth Emeka Odoh performs research on state of the art Data Visualization techniques. His research interest includes exploratory search where the users are guided to their search results using visual clues.

Kenneth is proficient in Python programming. He has presented a Python conference talk at Pycon, Finland in 2012 where he spoke about Data Visualization in Django to a packed audience.

He currently works as a Graduate Researcher at the University of Regina, Canada. He is a polyglot with experience in developing applications in C, C++, Python, and Java programming languages.

When Kenneth is not writing source codes, you can find him singing at the Campion College chant choir.