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bokeh python
10 reviews
- 1 profiles
- 1 categories
Average star rating
4.2
Serving customers since
bokeh python Reviews
UO
Verified User in Oil & Energy
Good viz library
Easy to learn and use, good for basic interactive charts. Allows you to provide charts in many mediums (html, notebook and server). Good alternative to plotly and pygal.
UE
Verified User in E-Learning
Bokeh: Great interactive, simple visualizations. Nearly as good as plotly
I like that it's fairly easy to create dynamic html visualizations that look slick and feel good. Since I learned R before python for statistics and visualizations, I definitely prefer R's ggplot2 syntax (which plotly can then easily convert to an html version with plotly::ggplotly()). However, for the python work that I do (when my coworkers prefer python notebooks, etc.) the capability of bokeh is great! The api is fairly consistent across different types of plots which is great.
BB
Bisma B.
Data Science | Analytics | ProgrammingBokeh library for visualization
The library has a lot of potential to create a rainbow of visualizations. I like that the dashboards are interactive.
About
What is bokeh python?
Bokeh is an interactive visualization library in Python designed to enable the creation of sophisticated and interactive plots and dashboards. It provides an accessible way for developers to create visual presentations that can be easily embedded into web-based applications. Bokeh focuses on providing high-performance visualizations by converting data into a JavaScript format that allows for seamless interaction and dynamic updates in the browser. It supports a wide range of chart types and layouts, and it integrates well with popular data analysis tools such as Pandas and Jupyter Notebooks.
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