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Matplotlib 3.0 Cookbook

You're reading from   Matplotlib 3.0 Cookbook Over 150 recipes to create highly detailed interactive visualizations using Python

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789135718
Length 676 pages
Edition 1st Edition
Languages
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Authors (2):
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Nikhil Borkar Nikhil Borkar
Author Profile Icon Nikhil Borkar
Nikhil Borkar
Srinivasa Rao Poladi Srinivasa Rao Poladi
Author Profile Icon Srinivasa Rao Poladi
Srinivasa Rao Poladi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Anatomy of Matplotlib FREE CHAPTER 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 a 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 16. Other Books You May Enjoy

Introduction

Seaborn is a powerful visualization tool built on top of Matplotlib. It makes multi-variable exploratory data analysis easier and intuitive, and it adds a few new types of plots, and its background styles and color maps are much more pleasing. It has many built-in statistical functions, making it a preferred tool for statistical data analysis. It also has quite elaborate online documentation, which you can find at https://seaborn.pydata.org/index.html.

We will use two datasets to demonstrate most of the seaborn features. One dataset, Wine Quality, is already familiar to you, and we will introduce a new dataset containing snack sales data from a fictitious snack shop. Instead of reading these files many times in each of the recipes, we will describe both of them in this section, and subsequently we will just use them for plotting the graphs. This is a slight deviation...

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