Matplotlib 2.0 presents new features that improve user experience, including speed, and output quality, as well as resource usage.
Improved functionality and performance
by Allen Yu, Claire Chung, Aldrin Yim
Matplotlib for Python Developers
- Title Page
- Copyright and Credits
- Dedication
- Packt Upsell
- Contributors
- Preface
- Introduction to Matplotlib
- Getting Started with Matplotlib
- Decorating Graphs with Plot Styles and Types
- Advanced Matplotlib
- Drawing Subplots
- Initiating a figure with plt.figure()
- Initiating subplots as axes with plt.subplot()
- Adding subplots with plt.figure.add_subplot()
- Initiating an array of subplots with plt.subplots()
- Setting the margin with plt.tight_layout()
- Aligning subplots of different dimensions with plt.subplot2grid()
- Drawing inset plots with fig.add_axes()
- Adjusting subplot dimensions post hoc with plt.subplots_adjust
- 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
- Drawing Subplots
- Embedding Matplotlib in GTK+3
- Embedding Matplotlib in Qt 5
- Embedding Matplotlib in wxWidgets Using wxPython
- Integrating Matplotlib with Web Applications
- Matplotlib in the Real World
- Integrating Data Visualization into the Workflow
Improved functionality and performance
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