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Bokeh vs Matplotlib: What are the differences?
Bokeh vs Matplotlib: Key Differences
Bokeh and Matplotlib are two popular visualization libraries used in Python for creating interactive and static plots respectively. While both libraries serve the purpose of data visualization, there are several key differences between Bokeh and Matplotlib.
Ease of Use: Bokeh simplifies the process of creating interactive visualizations by allowing users to create plots with only a few lines of code, while Matplotlib requires more code to achieve the same level of interactivity. Bokeh provides a higher level of abstraction, making it easier for users to build interactive plots quickly and efficiently.
Rendering: Bokeh renders plots using JavaScript, HTML, and CSS, whereas Matplotlib generates static images in various formats such as PNG, PDF, and SVG. This fundamental difference in rendering mechanisms gives Bokeh an advantage when it comes to creating interactive visualizations that can be easily embedded in web applications.
Interactivity: Bokeh focuses on providing interactivity out of the box, allowing users to easily add tools like zooming, panning, and hover tooltips to their plots. Matplotlib, on the other hand, requires users to manually add interactivity to their plots by writing custom code.
Backends: Matplotlib supports a variety of backends, including Tk, GTK, and Qt, which allow users to choose the most suitable backend for their specific needs. Bokeh, on the other hand, mainly relies on a web-based interface and is designed to work well with modern web browsers.
Integration with Web Frameworks: Bokeh seamlessly integrates with popular web frameworks like Flask and Django, allowing users to embed interactive plots directly into their web applications. Matplotlib, on the other hand, is primarily used for generating static plots and does not offer the same level of integration with web frameworks.
Performance: When it comes to performance, Matplotlib has an advantage over Bokeh, especially for generating static plots. Matplotlib is a highly optimized library with a wide range of backend options, enabling it to generate plots quickly. Bokeh, on the other hand, relies on web technologies for rendering, which can introduce some overhead and impact performance, particularly for large datasets.
In summary, Bokeh and Matplotlib differ in terms of ease of use, rendering mechanisms, interactivity support, backends, integration with web frameworks, and performance characteristics. Understanding these key differences can help users choose the most suitable library for their specific data visualization requirements.
Pros of Bokeh
- Beautiful Interactive charts in seconds12
Pros of Matplotlib
- The standard Swiss Army Knife of plotting11
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Cons of Bokeh
Cons of Matplotlib
- Lots of code5