Switch to the store?

Python Data Visualization Cookbook - Second Edition

More Information
Learn
  • Introduce yourself to the essential tooling to set up your working environment
  • Explore your data using the capabilities of standard Python Data Library and Panda Library
  • Draw your first chart and customize it
  • Use the most popular data visualization Python libraries
  • Make 3D visualizations mainly using mplot3d
  • Create charts with images and maps
  • Understand the most appropriate charts to describe your data
  • Know the matplotlib hidden gems
  • Use plot.ly to share your visualization online
About

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 will 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 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. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python.

Features
  • Learn how to set up an optimal Python environment for data visualization
  • Understand how to import, clean and organize your data
  • Determine different approaches to data visualization and how to choose the most appropriate for your needs
Page Count 302
Course Length 9 hours 3 minutes
ISBN9781784396695
Date Of Publication 30 Nov 2015

Authors

Igor Milovanović

Igor Milovanović is an experienced developer, with strong background in Linux system knowledge and software engineering education. He is skilled in building scalable data-driven distributed software rich systems.

An evangelist for high-quality systems design, he has a strong interest in software architecture and development methodologies. Igor is always committed to advocating methodologies that promote high-quality software, such as test-driven development, one-step builds, and continuous integration.

He also possesses solid knowledge of product development. With field experience and official training, he is capable of transferring knowledge and communication flow from business to developers and vice versa.

Igor is most grateful to his girlfriend for letting him spend hours on work instead with her and being an avid listener to his endless book monologues. He thanks his brother for being the strongest supporter. He is also thankful to his parents for letting him develop in various ways to become a person he is today.

Giuseppe Vettigli

Giuseppe Vettigli is a data scientist who has worked in the research industry and academia for many years. His work is focused on the development of machine learning models and applications to use information from structured and unstructured data. He also writes about scientific computing and data visualisation in Python on his blog at http://glowingpython.blogspot.com.

Dimitry Foures

Dimitry is a data scientist with a background in applied mathematics and theoretical physics. After completing his physics undergraduate studies in ENS Lyon (France), he studied fluid mechanics at École Polytechnique in Paris where he obtained first Class class Master’s degree. He holds a PhD in applied mathematics from the University of Cambridge. He currently works as a data-scientist for a smart-energy start-up in Cambridge, in close collaboration with the university.