Portable Scalable Data Visualization Techniques for Apache Spark and Python Notebook-based Analytics

Python Notebooks are great for communicating data analysis & research but how do you port these data visualizations between the many available platforms (Jupyter, Databricks, Zeppelin, Colab,…). Also learn about how to scale up your visualizations using Spark. This talk will address:

-6-8 strategies to render Matplotlib that generalize well
-Reviewing the landscape of Python visualization packages and calling out gotchas
-Headless rendering and how to scale your visualization from one to 10,000
-How to create a cool animation
-Connecting your big data via Spark to these visualizations