Developing Advanced Plots with Matplotlib [Video]

Developing Advanced Plots with Matplotlib [Video]

Benjamin Keller

Understand and build beautiful and advanced plots with Matplotlib and Python
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Video Description

Matplotlib is a multi-platform data visualization tool built upon the Numpy and Scipy frameworks. One of Matplotlib’s most important features is its ability to work well with many operating systems and graphics backends. In this video course, you’ll get hands-on with customizing your data plots with the help of Matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more on tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this tutorial. You’ll delve into niche plots and visualizing ordinal and tabular data.

In this video, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will be also be explored. Finally you’ll learn how to create interactive plots with the help of Jupyter. By the end of this video tutorial, you’ll be able to construct advanced plots with additional customization techniques and 3D plot types.

Style and Approach

A step-by-step practical guide filled with real-world use cases and examples that will help cdevelopers and data scientists create elaborate visualizations (graphs and data plots) for their projects using the Matplotlib library.

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What You Will Learn

  • Deal with non-trivial and unusual plots
  • Customize and represent data in 3D
  • Construct Non-Cartesian and vector plots
  • Design interactive plots using Jupyter Notebook
  • Make movies for enhanced data representation

Authors

Video Details

ISBN 139781788627825
Course Length3 hours 11 minutes
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