Improving Your Data Visualization Flow with Altair and Vega-Lite
Improving Your Data Visualization Flow with Altair and Vega-Lite

Abstract: 

Your boss just asked you to ""whip up"" a chart for a stakeholder review in an hour. You know you made that really slick visual a couple months ago, it would be a perfect fit for your current dataset. However, you can only find the final PNG, not the original notebook with your carefully crafted matplotlib magic. After a quarter hour's search, you give up and start pummeling Stack Overflow, hoping to find that thread that had all the answers last time...

Sound familiar? If you're a Pythonista whose data visualization process could use a makeover, then this talk is for you. We'll identify the elements of an effective data visualization flow and explore how the Altair and Vega-Lite stack can improve your own data visualization practice.

The visualization demonstration will feature data sourced from S&P Global's curated content sets, now available through the Snowflake Cloud Data Platform.

Bio: 

Rachel House is a Senior Data Scientist on S&P Global's Artificial Intelligence Engineering team. Prior to her tenure at S&P, Rachel served as a software developer in the ad tech industry and as a proposal writer in defense contracting. She has leveraged her dual background in technology and communication to build a portfolio of experience in the design and development of robust, elegant systems as well as the ability to pitch those creations to varied audiences.

Open Data Science

Open Data Science
Innovation Center
101 Main St
Cambridge, MA 02142
info@odsc.com

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