At J.P. Morgan, traders, researchers, and engineers use Jupyterlab and Perspective, a high-performance streaming data visualization library, for analytics across large, real-time datasets. Junyuan Tan demonstrates how Perspective and Apache Arrow can be used to accumulate, dissect, and visualize streaming data—all within a Jupyter Notebook.
Many data visualization libraries are built with static data in mind, where everything is known before the visualization is created. Analyzing data streams in real-time, however, is a crucial part of many industries. Combining JupyterLab’s ease-of-use and flexibility with Perspective, a high-performance streaming data visualization library, users can rapidly prototype, analyze, and visualize results from a multitude of data sources both live and static.
Using real-time stock quotes from the IEX Cloud API, Junyuan Tan demonstrates how Perspective can be used to visualize streaming data, combine real-time information with analysis and data points from various sources, and export data snapshots using Apache Arrow, without leaving the Jupyter Notebook.
Attendees will learn:
A working knowledge of Python is recommended but not required.
Notebooks/Presentation Materials: https://github.com/sc1f/streaming-perspective-jupytercon-2020
Apache Arrow: https://arrow.apache.org/