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Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization
About This Book- 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
If you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you.
What You Will 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
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.
Style and approachA step-by-step recipe based approach to data visualization. The topics are explained sequentially as cookbook recipes consisting of a code snippet and the resulting visualization.
- Sales Rank: #449816 in Books
- Published on: 2015-11-30
- Released on: 2015-11-30
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .69" w x 7.50" l, 1.15 pounds
- Binding: Paperback
- 302 pages
About the Author
Igor Milovanovic
Igor Milovanovic 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. Evangelist for high-quality systems design who holds strong interests in software architecture and development methodologies, Igor is always persistent on advocating methodologies which promote high-quality software, such as test-driven development, one-step builds and continuous integration. He also possesses solid knowledge of product development. Having 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 spent hours on the work instead with her and being avid listener to his endless book monologues. He thanks his brother for being the strongest supporter. He is thankful to his parents to let him develop in various ways and become a person he is today.
Dimitry Foures
Dimitry Foures is a data scientist with a background in applied mathematics and theoretical physics. After completing his undergraduate studies in physics at ENS Lyon (France), he studied fluid mechanics at Ecole Polytechnique in Paris where he obtained a first class master's. He holds a PhD in applied mathematics from the University of Cambridge. He currently works as a data scientist for a smart-energy startup in Cambridge, in close collaboration with the university.
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 visualization in Python on his blog at http://glowingpython.blogspot.com.
Most helpful customer reviews
2 of 2 people found the following review helpful.
A good guide to get the basics right in visualisation in Python
By Tarik
What I liked about this book was that it gives clear and short examples of various visualization techniques in Python. It dives right in without much fluff, while it is still easy to follow.
A strong point is the second chapter which shows how to import and prepare various types of input data.
The book focusses mostly on statistical type visuals such as bars and histograms. I expected the book to cover a larger number of visuals and go beyond the basic statistical visuals. For example, I hoped it would also discuss heatmaps, network graphs, treemaps and starplots.
The book discusses a number of Python frameworks, but could have included some more for example Bokeh or Python-Igraph.
What it discusses, it discusses well. Therefore I give it four stars.
1 of 1 people found the following review helpful.
This is a great book!
By Amazon Customer
I received a free copy of this book in exchange for my review. I think this is a great book. The examples for the different plotting methods and customizations all worked. The first chapter describe set-up and code samples for using data in different formats. I remember when I was first given the task to add a chart to a report to represent data and how it took me a minute to ensure I was doing things correctly. This book would helped me a great deal at that time. Many questions I had previously about plotting and correctly coding solutions for charts I haven't been asked to make yet, were answered. I have been creating reports and charts for a University Research team and this book has been a godsend. I think this book would have helped me when I was working using java for reports and charts. I just this is a great book.
1 of 1 people found the following review helpful.
Python Data Visualization and More ...
By Oleg Okun
The title of this book includes the word "cookbook" and as a cookbook the book contains a plenty of practical recipes of data visualization in Python. It presents not a mere description of Python packages and commands related to visualization, but embeds these tools into real-world scenarios. Not only visualization itself but also data manipulation enabling insightful visualization are discussed in detail. Needless to say, the discussion of every topic is accompanied by ready-to-use Python code.
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