|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:|
|Echarts||54,537||6,554||4,083||a day ago||112||September 13, 2022||2,288||apache-2.0||TypeScript|
|Apache ECharts is a powerful, interactive charting and data visualization library for browser|
|Superset||51,096||2||2 hours ago||3||April 29, 2022||1,311||apache-2.0||TypeScript|
|Apache Superset is a Data Visualization and Data Exploration Platform|
|Metabase||31,818||2 hours ago||1||June 08, 2022||2,779||other||Clojure|
|The simplest, fastest way to get business intelligence and analytics to everyone in your company :yum:|
|Bokeh||17,386||2,936||617||2 hours ago||136||July 05, 2022||701||bsd-3-clause||Python|
|Interactive Data Visualization in the browser, from Python|
|Visx||16,875||202||65||18 hours ago||47||September 09, 2020||129||mit||TypeScript|
|🐯 visx | visualization components|
|WebGL2 powered visualization framework|
|Seaborn||10,494||6,393||3,017||3 hours ago||30||June 27, 2022||115||bsd-3-clause||Python|
|Statistical data visualization in Python|
Bokeh is aninteractive visualizationlibrary for modern web browsers. It provides elegant, conciseconstructionof versatile graphics and affords high-performance interactivity across large or streaming datasets.Bokeh can help anyone who wants to create interactive plots, dashboards, and data applications quickly and easily.
Consider making a donation if you enjoy using Bokeh and want to support its development.
To install Bokeh and its required dependencies using
pip, enter the following command at a Bash or Windows command prompt:
pip install bokeh
conda, enter the following command at a Bash or Windows command prompt:
conda install bokeh
Refer to the installation documentation for more details.
Once Bokeh is installed, check out the first steps guides.
Visit the full documentation site to view the User's Guide or launch the Bokeh tutorial to learn about Bokeh in live Jupyter Notebooks.
Community support is available on the Project Discourse.
If you would like to contribute to Bokeh, please review the Contributor Guide and request an invitation to the Bokeh Dev Slack workspace.
Note: Everyone who engages in the Bokeh project's discussion forums, codebases, and issue trackers is expected to follow the Code of Conduct.
Follow us on Twitter @bokeh
The Bokeh project is grateful for individual contributions, as well as for monetary support from the organizations and companies listed below:
If your company uses Bokeh and is able to sponsor the project, please contact [email protected]
Bokeh is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Bokeh with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit numfocus.org for more information.
Donations to Bokeh are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.
Non-monetary support can help with development, collaboration, infrastructure, security, and vulnerability management. The Bokeh project is grateful to the following companies for their donation of services: