- Get Interactive Plots Directly With Pandas - Jun 14, 2021.
Telling a story with data is a core function for any Data Scientist, and creating data visualizations that are simultaneously illuminating and appealing can be challenging. This tutorial reviews how to create Plotly and Bokeh plots directly through Pandas plotting syntax, which will help you convert static visualizations into interactive counterparts -- and take your analysis to the next level.
- Top 20 Python Libraries for Data Science in 2018 - Jun 27, 2018.
Our selection actually contains more than 20 libraries, as some of them are alternatives to each other and solve the same problem. Therefore we have grouped them as it's difficult to distinguish one particular leader at the moment.
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- Beautiful Python Visualizations: An Interview with Bryan Van de Ven, Bokeh Core Developer - Aug 1, 2017.
Read this insightful interview with Bokeh's core developer, Bryan Van de Ven, and gain an understanding of what Bokeh is, when and why you should use it, and what makes Bryan a great fit for helming this project.
- KDnuggets™ News 17:n09, Mar 8: 7 More Steps to Mastering Machine Learning w. Python; Every Intro to Data Science Course, Ranked - Mar 8, 2017.
Also The Data Science Project Playbook; Hadoop Is Falling - Why? Bokeh Cheat Sheet: Data Visualization in Python
- Bokeh Cheat Sheet: Data Visualization in Python - Mar 3, 2017.
Bokeh is the Python data visualization library that enables high-performance visual presentation of large datasets in modern web browsers. The package is flexible and offers lots of possibilities to visualize your data in a compelling way, but can be overwhelming.
- 10 Useful Python Data Visualization Libraries for Any Discipline - Jun 14, 2016.
A great overview of 10 useful Python data visualization tools. It covers some of the big ones, like matplotlib and Seaborn, but also explores some more obscure libraries, like Gleam, Leather, and missingno.
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- Make Beautiful Interactive Data Visualizations Easily, Dec 15 Webinar - Dec 7, 2015.