Bokeh is a library used in Python, R, Lua, and Julia to transform your data into a beautiful visualization, using web browsers for presentation. You can prepare the data, decide on the kind of visualization, set up figures, connect, draw, and organize your data using Bokeh. You need some basic coding knowledge to organize the data in grids, tabbed layouts, and many other options.
Bokeh is a NUMfocus project, which is a non-profit. Being an open-source tool, any developer can contribute to making it better. So, Bokeh Pricing is not based on any sort of packages that you can choose, it is available as a library in a variety of languages. Bokeh Pricing mainly applies to Data Science, Artificial Intelligence, and Machine Learning.
You can make the most effective use of the User Guide and Gallery to understand how you can use Bokeh to visualize your data. If you work on various languages like Python and Julia, you would get access to Bokeh Library using necessary commands. Thus, through a variety of platforms, you can use Bokeh to prepare catchy interactive visualizations using the latest browsers.
Some fabulous features that make a difference in visualization:
- Simple commands for statistical plots
- You need simple commands to generate statistical plots.
- Data visualization becomes well-organized and creative.
- Easy to create prototypes
- You can create prototypes quickly without using tools like wireframes.
- Get outputs in a variety of medium:
- Bokeh pricing is minimal compared to the technical capabilities it offers.
- You can get the outputs in various mediums such as HTML, notebook, and server.
- Convenient embedding with other applications:
- You can embed Bokeh visualization to other apps such as Flask and Django.
- This feature makes this tool versatile and user-friendly as well.