Matplotlib 2.x Cookbook

Matplotlib 2.x Cookbook

by Srinivasa Rao Poladi


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Build attractive, insightful, and powerful visualizations to gain quality insights from your data

Key Features

  • Master Matplotlib for data visualization
  • Customize basic plots to make and deploy figures in cloud environments
  • Explore recipes to design various data visualizations from simple bar charts to advanced 3D plots

Book Description

Matplotlib provides a large library of customizable plots, along with a comprehensive set of backends. Matplotlib 3.0 Cookbook is your hands-on guide to exploring the world of Matplotlib, and covers the most effective plotting packages for Python 3.7.

With the help of this cookbook, you'll be able to tackle any problem you might come across while designing attractive, insightful data visualizations. With the help of over 150 recipes, you'll learn how to develop plots related to business intelligence, data science, and engineering disciplines with highly detailed visualizations. Once you've familiarized yourself with the fundamentals, you'll move on to developing professional dashboards with a wide variety of graphs and sophisticated grid layouts in 2D and 3D. You'll annotate and add rich text to the plots, enabling the creation of a business storyline. In addition to this, you'll learn how to save figures and animations in various formats for downstream deployment, followed by extending the functionality offered by various internal and third-party toolkits, such as axisartist, axes_grid, Cartopy, and Seaborn.

By the end of this book, you'll be able to create high-quality customized plots and deploy them on the web and on supported GUI applications such as Tkinter, Qt 5, and wxPython by implementing real-world use cases and examples.

What you will learn

  • Develop simple to advanced data visualizations in Matplotlib
  • Use the pyplot API to quickly develop and deploy different plots
  • Use object-oriented APIs for maximum flexibility with the customization of figures
  • Develop interactive plots with animation and widgets
  • Use maps for geographical plotting
  • Enrich your visualizations using embedded texts and mathematical expressions
  • Embed Matplotlib plots into other GUIs used for developing applications
  • Use toolkits such as axisartist, axes_grid1, and cartopy to extend the base functionality of Matplotlib

Who this book is for

The Matplotlib 3.0 Cookbook is for you if you are a data analyst, data scientist, or Python developer looking for quick recipes for a multitude of visualizations. This book is also for those who want to build variations of interactive visualizations.

Product Details

ISBN-13: 9781789135718
Publisher: Packt Publishing
Publication date: 10/22/2018
Pages: 676
Sales rank: 654,684
Product dimensions: 7.50(w) x 9.25(h) x 1.36(d)

About the Author

Srinivasa Rao Poladi has been in the IT services industry for over two decades, providing consulting and implementation services in data warehousing, business intelligence, and machine learning areas for global customers. He has worked with Wipro Technologies for two decades and played key leadership roles in building large technology practices and growing them to multi-million $ business. He spoke at international conferences, published many blogs and white papers in the areas of big data, business intelligence, and analytics. He is a co-founder of krtrimaIQ a consulting firm that provides cognitive solutions to create tomorrow's Intelligent Enterprises powered by automation, big data, machine learning, and deep learning.

Table of Contents

Table of Contents

  1. Anatomy of Matplotlib
  2. Getting Started with Basic Plots
  3. Plotting Multiple Charts, Subplots, and Figures
  4. Developing Visualizations for Publishing Quality
  5. Plotting with Object Oriented API
  6. Plotting with Advanced Features
  7. Embedding Text and Expressions
  8. Saving the Figure in Different formats
  9. Developing Interactive Plots
  10. Embedding Plots in Graphical User Interface
  11. Plotting 3D Graphs Using the mplot3d Toolkit
  12. Using the axisartist Toolkit
  13. Using the axes_grid1 Toolkit
  14. Plotting Geographical Maps Using Cartopy Toolkit
  15. Exploratory Data Analysis Using the Seaborn Toolkit

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