Table of contents
Interactive Visualizations
Bokeh is designed specifically for creating interactive and highly customizable visualizations, making it suitable for engaging data exploration.
Python Integration
Bokeh integrates well with the Python ecosystem, allowing direct use of pandas, NumPy, and other Python libraries, facilitating seamless data manipulation and visualization.
Web Compatibility
Bokeh generates plots that are ready to be embedded into web applications, making it a powerful tool for creating dashboards and interactive reports.
Server Functionality
Bokeh provides a server component that allows users to build and deploy sophisticated interactive applications using just Python.
Variety of Plotting Options
Bokeh offers a wide range of plotting capabilities including charts, maps, and streamgraphs, enabling users to create complex visual stories.
Visualization: https://docs.bokeh.org/en/latest/. Source: almost 3 years ago
Now that we can get task timing information in a consistent manner, let’s do some plotting. For this, I’m going to use Bokeh which generates nice interactive plots. - Source: dev.to / about 3 years ago
Bokeh The Bokeh library is native to Python and is mainly used to create interactive, web-ready plots, which can be easily output as HTML documents, JSON objects, or interactive web applications. Like ggplot, its concepts are also based on the Grammar of Graphics. It has the added advantage of managing real-time data and streaming. This library can be used for creating common charts such as histograms, bar plots,... - Source: dev.to / over 3 years ago
It's not in the least bit "underrated" and it's documentation is extensive. Source: almost 4 years ago
Hi guys! I am currently working on a project to enrich my Master thesis with some interactive plots. I have been using the Bokeh library to make a standalone application, which I was then planning to deploy in Heroku. You can find the code in this repository. But I will also add it at the bottom of the post. Source: about 4 years ago
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