Matplotlib for Python Developers - Second Edition

Leverage the power of Matplotlib to visualize and understand your data more effectively
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Matplotlib for Python Developers - Second Edition

Aldrin Yim, Claire Chung, Allen Yu
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Leverage the power of Matplotlib to visualize and understand your data more effectively
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Book Details

ISBN 139781788625173
Paperback300 pages

Book Description

Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library.

Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples

By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations.

Table of Contents

Chapter 1: Introduction to Matplotlib
What is Matplotlib?
Setting up Matplotlib
Summary
Chapter 2: Getting Started with Matplotlib
Loading data
Our first plots with Matplotlib
Adjusting axes, grids, labels, titles, and legends
A complete example
Saving plots to a file
Configuring Matplotlib
Summary
Chapter 3: Decorating Graphs with Plot Styles and Types
Controlling the colors
Line and marker styles
More native Matplotlib plot types
Text and annotations
Using style sheets
Aesthetics and readability considerations in styling
Summary
Chapter 4: Advanced Matplotlib
Drawing Subplots
Adjusting axes and ticks
More on Pandas-Matplotlib integration
Expanding plot types with Seaborn 
Image plotting
Financial plotting
3D plots with Axes3D
Geographical plotting
Summary
Chapter 5: Embedding Matplotlib in GTK+3
Installing and setting up GTK+3
Summary
Chapter 6: Embedding Matplotlib in Qt 5
A brief introduction to Qt 5 and PyQt 5
Differences between Qt 4 and PyQt 4
Summary
Chapter 7: Embedding Matplotlib in wxWidgets Using wxPython
A brief introduction to wxWidgets and wxPython
Summary
Chapter 8: Integrating Matplotlib with Web Applications
Installing Docker
More about Django
Showing Bitcoin prices using Django and Matplotlib
Summary
Chapter 9: Matplotlib in the Real World
Typical API data formats
Importing and visualizing data from a JSON API
Scraping information from websites
Matplotlib graphical backends
Creating animated plot
Summary
Chapter 10: Integrating Data Visualization into the Workflow
Getting started
Visualizing sample images from the dataset
Exploring the data nature by the t-SNE method
Creating a CNN to recognize digits
Evaluating prediction results with visualizations
Summary

What You Will Learn

  • Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots
  • Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib
  • Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn
  • Create interactive plots with real-time updates
  • Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django
  • Write data visualization code that is readily expandable on the cloud platform

Authors

Table of Contents

Chapter 1: Introduction to Matplotlib
What is Matplotlib?
Setting up Matplotlib
Summary
Chapter 2: Getting Started with Matplotlib
Loading data
Our first plots with Matplotlib
Adjusting axes, grids, labels, titles, and legends
A complete example
Saving plots to a file
Configuring Matplotlib
Summary
Chapter 3: Decorating Graphs with Plot Styles and Types
Controlling the colors
Line and marker styles
More native Matplotlib plot types
Text and annotations
Using style sheets
Aesthetics and readability considerations in styling
Summary
Chapter 4: Advanced Matplotlib
Drawing Subplots
Adjusting axes and ticks
More on Pandas-Matplotlib integration
Expanding plot types with Seaborn 
Image plotting
Financial plotting
3D plots with Axes3D
Geographical plotting
Summary
Chapter 5: Embedding Matplotlib in GTK+3
Installing and setting up GTK+3
Summary
Chapter 6: Embedding Matplotlib in Qt 5
A brief introduction to Qt 5 and PyQt 5
Differences between Qt 4 and PyQt 4
Summary
Chapter 7: Embedding Matplotlib in wxWidgets Using wxPython
A brief introduction to wxWidgets and wxPython
Summary
Chapter 8: Integrating Matplotlib with Web Applications
Installing Docker
More about Django
Showing Bitcoin prices using Django and Matplotlib
Summary
Chapter 9: Matplotlib in the Real World
Typical API data formats
Importing and visualizing data from a JSON API
Scraping information from websites
Matplotlib graphical backends
Creating animated plot
Summary
Chapter 10: Integrating Data Visualization into the Workflow
Getting started
Visualizing sample images from the dataset
Exploring the data nature by the t-SNE method
Creating a CNN to recognize digits
Evaluating prediction results with visualizations
Summary

Book Details

ISBN 139781788625173
Paperback300 pages
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