Matplotlib 2.x By Example

Unlock deeper insights into visualization in form of 2D and 3D graphs using Matplotlib 2.x
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Matplotlib 2.x By Example

Allen Yu, Claire Chung, Aldrin Yim

1 customer reviews
Unlock deeper insights into visualization in form of 2D and 3D graphs using Matplotlib 2.x

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Book Details

ISBN 139781788295260
Paperback334 pages

Book Description

Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. Matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization.

Matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples.

It begins by giving readers the basic know-how on how to create and customize plots by Matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize geographical data on maps and implement interactive charts.

By the end of this book, you will become well versed with Matplotlib in your day-to-day work to perform advanced data visualization. This book will guide you to prepare high quality figures for manuscripts and presentations. You will learn to create intuitive info-graphics and reshaping your message crisply understandable.

Table of Contents

Chapter 1: Hello Plotting World!
Hello Matplotlib!
Setting up the plotting environment
Plotting our first graph
Summary
Chapter 2: Figure Aesthetics
Basic structure of a Matplotlib figure
Setting colors in Matplotlib
Adjusting text formats
Customizing lines and markers
Customizing grids, ticks, and axes
Using style sheets
Title and legend
Test your skills
Summary
Chapter 3: Figure Layout and Annotations
Adjusting the layout
Annotations
Summary
Chapter 4: Visualizing Online Data
Typical API data formats
Introducing pandas
Visualizing the trend of data
Introducing Seaborn
Visualizing univariate distribution
Visualizing a bivariate distribution
Visualizing categorical data
Controlling Seaborn figure aesthetics
Summary
Chapter 5: Visualizing Multivariate Data
Getting End-of-Day (EOD) stock data from Quandl
Two-dimensional faceted plots
Other two-dimensional multivariate plots
Three-dimensional (3D) plots
Summary
Chapter 6: Adding Interactivity and Animating Plots
Scraping information from websites
Non-interactive backends
Interactive backends
Creating animated plots
Summary
Chapter 7: A Practical Guide to Scientific Plotting
General rules of effective visualization
Visualizing statistical data more intuitively
Summary
Chapter 8: Exploratory Data Analytics and Infographics
Visualizing population health information
Survival data analysis on cancer
Summary

What You Will Learn

  • Familiarize with the latest features in Matplotlib 2.x
  • Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more.
  • Make clear and appealing figures for scientific publications.
  • Create interactive charts and animation.
  • Extend the functionalities of Matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn.
  • Design intuitive infographics for effective storytelling.

Authors

Table of Contents

Chapter 1: Hello Plotting World!
Hello Matplotlib!
Setting up the plotting environment
Plotting our first graph
Summary
Chapter 2: Figure Aesthetics
Basic structure of a Matplotlib figure
Setting colors in Matplotlib
Adjusting text formats
Customizing lines and markers
Customizing grids, ticks, and axes
Using style sheets
Title and legend
Test your skills
Summary
Chapter 3: Figure Layout and Annotations
Adjusting the layout
Annotations
Summary
Chapter 4: Visualizing Online Data
Typical API data formats
Introducing pandas
Visualizing the trend of data
Introducing Seaborn
Visualizing univariate distribution
Visualizing a bivariate distribution
Visualizing categorical data
Controlling Seaborn figure aesthetics
Summary
Chapter 5: Visualizing Multivariate Data
Getting End-of-Day (EOD) stock data from Quandl
Two-dimensional faceted plots
Other two-dimensional multivariate plots
Three-dimensional (3D) plots
Summary
Chapter 6: Adding Interactivity and Animating Plots
Scraping information from websites
Non-interactive backends
Interactive backends
Creating animated plots
Summary
Chapter 7: A Practical Guide to Scientific Plotting
General rules of effective visualization
Visualizing statistical data more intuitively
Summary
Chapter 8: Exploratory Data Analytics and Infographics
Visualizing population health information
Survival data analysis on cancer
Summary

Book Details

ISBN 139781788295260
Paperback334 pages
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