Bokeh tracking and usage
Websites using Bokeh over time
1,088websites on 11 Nov 2026
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We track 1,088 websites using Bokeh, along with their country, traffic, industry and platforms. There are 12 websites using Bokeh in United States.
About Bokeh
Bokeh is an open-source visualization library that developers and scientists use to build interactive plots, dashboards, and data applications, including in Jupyter notebooks.
Websites using Bokeh by countrymarket share
1.1%
🇺🇸US8%
🇩🇪DE2.6%
🇬🇧GB2.4%
🇳🇱NL2.3%
🇮🇩ID2.3%
🇫🇷FR1.9%
🇮🇹IT1.6%
🇵🇱PLWebsites using Bokeh by industrymarket share · top 6 industries
Photography
Software Development
Movies & TV
Technology & Computing
Entertainment
Design & Creative
0%10%20%30%40%
Websites using Bokeh
showing 25 of 1,088| Website | Country | Traffic | Industry |
|---|---|---|---|
| - | Top 50K | Software Development | |
| 🇺🇸US | Top 500K | Technology & Computing | |
| - | Top 1M | Entertainment | |
| 🇫🇮FI | Top 5M | Photography | |
| 🇩🇰DK | Top 5M | Music | |
| 🇫🇷FR | - | - | |
| 🇬🇧GB | - | Software Development | |
| 🇺🇸US | - | Software Development | |
| 🇸🇦SA | - | Business & Finance | |
| 🇬🇧GB | - | Design & Creative | |
| 🇪🇸ES | - | Environment & Sustainability | |
| - | - | Society | |
| 🇸🇪SE | - | Photography | |
| 🇨🇱CL | - | Architecture & Engineering | |
| 🇳🇿NZ | - | Photography | |
| 🇮🇹IT | - | - | |
| 🇩🇪DE | - | - | |
| 🇺🇸US | - | Shopping | |
| 🇪🇸ES | - | Software Development | |
| 🇬🇧GB | - | Insurance | |
| 🇩🇪DE | - | Music | |
| - | - | Business & Finance | |
| 🇺🇸US | - | Society | |
| 🇬🇧GB | - | Software Development | |
| 🇺🇸US | - | Design & Creative |
Showing 25 of 1,088 websitesView detailed list →
Frequently asked
What is Bokeh in data visualization?›
Bokeh is an interactive data visualization library in Python that provides versatile, elegant, and high-performance graphics tools. It enables users to create web-based plots with simple or complex interactions and dashboards by generating HTML, CSS, and JavaScript output. Bokeh is suitable for constructing aesthetic visualizations to display large datasets efficiently.
Can Bokeh be integrated with other Python libraries?›
Yes, Bokeh can be integrated with multiple popular Python libraries, including NumPy, Pandas, Datashader, HoloViews, and others. This integration allows users to create more sophisticated visualizations and take full advantage of the Python data science ecosystem.
How does Bokeh compare to other visualization libraries like Matplotlib and Plotly?›
Bokeh differs from other visualization libraries, such as Matplotlib and Plotly, in its focus on providing robust and high-performance interactive plots in a web browser. While Matplotlib excels in creating static images, and Plotly specializes in online interactive visualizations, Bokeh balances these aspects by offering versatile visualization options with interactive features.
Is it possible to create a stand-alone HTML file with my Bokeh visualization?›
Yes, Bokeh allows users to create stand-alone HTML files containing their visualizations. By using the output_file() function along with the save() or show() function, the plots can be either saved to an HTML file or displayed in a new browser window as a self-contained file. This feature enables easy sharing and embedding of Bokeh plots.
Can I customize the appearance and style of my Bokeh plots?›
Absolutely! Bokeh provides abundant options for users to customize their visualizations, including modifying the plot title, axes labels, color palettes, background color, and gridlines. Additionally, the library supports the integration of custom CSS styling, allowing even more control over the appearance of the plots.
