Bokeh
Bokeh is a Python-based visualization library, capable of building plots from simple charts to interactive dashboards.
Bokeh is an interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics, and to extend this capability with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.
90000
3000 / day
150000
5000 / day
00:03:45
2.5 page per visit
40%
-
Domain Rating
-
Domain Authority
-
Citation Level
2013
English, etc
Key Features of the Site
Interactive Plots
Create highly interactive plots that can be zoomed, panned, updated, and more.
Streaming Data
Efficiently visualize streaming and large datasets with Bokeh's ability to handle real-time data.
Customizable Themes
Easily customize the look and feel of your visualizations with built-in themes or create your own.
Server Deployment
Deploy your Bokeh applications on a server to share with others, with support for user authentication and permissions.
Wide Range of Plot Types
From simple line plots to complex statistical charts, Bokeh supports a wide variety of plot types.
Integration with Jupyter Notebooks
Seamlessly integrate Bokeh plots into Jupyter notebooks for interactive data analysis.
Python and JavaScript APIs
Bokeh provides both Python and JavaScript APIs, making it versatile for both backend and frontend development.
Export to Web Formats
Export your visualizations to standalone HTML files or embed them in web applications.
High-Level and Low-Level Interfaces
Bokeh offers both high-level interfaces for quick plotting and low-level interfaces for detailed customization.
Active Community
Bokeh has an active community of developers and users, providing a wealth of resources and support.
Additional information
License
Bokeh is released under the BSD 3-Clause License, making it free for both personal and commercial use.
Development Status
Bokeh is under active development, with regular updates and new features being added.
Documentation
Comprehensive documentation is available, including tutorials, examples, and API references.
Community Support
Support is available through various channels including GitHub issues, Gitter chat, and the Bokeh mailing list.
Contributing
Bokeh welcomes contributions from the community, including code, documentation, and feedback.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for bokeh.org