Scalable Pandas Meetup No. 9: Pandas on Snowflake + BigQuery Using Ponder

Feb 16, 2023 2 min read

Scalable Pandas Meetup No. 9: Pandas on Snowflake + BigQuery Using Ponder image

Post-event Update (2/27): Watch the recording of the meetup here!


We’re really looking forward to our ninth Scalable Pandas Meetup!

  • What: Devin Petersohn (Co-Founder and CTO of Ponder, and creator of Modin) will demonstrate how you can run pandas on your data warehouse (Snowflake, BigQuery, etc.) with Ponder. He will answer questions from the audience + moderator, Peter Olson (Chief of Staff at Ponder).
  • When: Thursday, February 23rd, 10:00 – 10:45 AM PT.
  • Where: Online (Zoom).
  • How: Join the Zoom call directly here.

This meetup is the ninth in a series of conversations centered around how you can leverage pandas at scale. The Scalable Pandas Meetup is a forum dedicated to developers, data scientists, and data engineers to share their stories, practical advice, examples, and best practices around scaling pandas workflows.

For the recording of our last meetup, see here.

What is the focus of these meetups?

  • To learn about the technical challenges and existing solutions for making pandas performant with large dataframes and complex workloads.
  • To discuss and envision next-generation solutions to those problems so that more enterprise-quality, production-level work can be done with the pandas API.

Who is the intended audience of these meetups?

We welcome all pandas users, enthusiasts, gurus, masters, who are ready to take their pandas skills to the next level with a community of like-minded peers. Our content will be geared towards intermediate and advanced pandas users, especially those who find themselves:

  • Using pandas with data larger than 500 MB
  • Crafting their own custom workflows to parallelize pandas
  • Leaving the pandas ecosystem to do things that pandas should be able to do
  • Agreeing to duel (joust, etc.) ruffians who besmirch the honor of pandas!

We’re excited to see you on Thursday!

Ready to level up your Pandas game?

Try Ponder now