Diverse Plotting Types: Bokeh supports a wide range of plotting types, including scatter plots, line plots, bar plots, histograms, heatmaps, and more.It supports rendering visualizations as HTML documents, standalone web applications, or embedded components within other Python frameworks like Flask and Django. Multiple Rendering Options: Bokeh offers multiple rendering options, making it flexible for various use cases.This interactivity enhances data exploration and enables users to gain deeper insights by dynamically manipulating visual elements. Interactive Visualizations: Bokeh allows users to create interactive plots that respond to user input, such as mouse movements, clicks, or selections.In this guide, you will find links to both those resources. Bokeh automates the generation of JavaScript and HTML code and supports the loading of supplementary JavaScript from Bokeh’s CDN for enhanced functionality.īokeh’s documentation consists of several elements, including the user guide with detailed explanations and examples and the reference guide that systematically describes every element of Bokeh. Bokeh integrates a Python library responsible for defining visualization content and interactivity with BokehJS, a JavaScript library that handles the display in web browsers. Its workflow involves two stages selecting visual building blocks and customizing them. With just a few lines of Python code, Bokeh enables you to create interactive, JavaScript-powered visualizations displayable in a web browser. Whether you’re a data scientist, web developer, or data enthusiast, Bokeh provides a comprehensive set of tools to help you bring your data to life. It enables you to generate rich, interactive plots, charts, and dashboards that can be easily shared and deployed across different platforms. Among them, Bokeh stands out as a powerful and user-friendly library that allows you to build interactive visualizations with ease.īokeh is an open-source Python library specifically designed for creating interactive visualizations for modern web browsers. Python, being a versatile programming language, offers numerous libraries for creating visualizations. Data visualization plays a crucial role in understanding and communicating insights from data.
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