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Python scientific visualization is important. It consists of countless tools, ranging from the most general and widely used to the more specialized and confidential. Some of these tools are community-based, while others are developed by companies. Some are made specifically for web pages, some are for desktop only, some deal with 3D and big data, and others are for perfect 2D rendering. In this regard, Matplotlib has a very special place. It is a versatile and powerful library that allows you to design very high-quality drawings, suitable for scientific publishing. It also provides a simple and intuitive interface, and an object-oriented architecture that allows you to adjust anything in the graph. Finally, it can be used as a general graphics library to design non-scientific graphics.
https://github.com/rougier/scientific-visualization-book
This book is divided into four parts . The first part considers the basic principles of the Matplotlib library. This includes reviewing the different parts that make up a figure, the different coordinate systems, the scales and projections available, and we'll also introduce some concepts about typography and color. The second part is the actual design of a graphic. After introducing some simple rules for producing better graphs, we'll move on to explaining the Matplotlib defaults and style system before diving into graph layout organization. Then, we'll explore the different types of plots available, and see how to decorate a figure with different elements. The third part focuses on more advanced concepts, namely 3D characters, optimization and animation. The fourth and final part is the collection of showcases.
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