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April Meeting: Scaling Up Your Pandas Workflows With Modin

April Meeting: Scaling Up Your Pandas Workflows With Modin

Details

This month, we'll have a lightning talk about testing by Glen Jarvis and a full talk about Modin by its creator, Devin Petersohn. Come join us!

Lightning Talk: 'Mock()'ing an old dog to 'return_value' new tricks
Speaker: Glen Jarvis

Main Talk: Scaling Up Your Pandas Workflows With Modin

Pandas is one of the most commonly used data science libraries in Python, with a convenient set of APIs to help data scientists prepare, analyze, and explore their data. However, despite its widespread adoption, pandas suffers from severe memory and performance issues on moderately large datasets. We present Modin (https://github.com/modin-project/modin), a fast, scalable drop-in replacement for pandas. By changing just a single line of code, Modin seamlessly speeds up pandas workflow on a laptop or in a cluster. Modin has over 6.6k GitHub stars, 2.8 million downloads, and is deployed at many data-centric organizations to accelerate dataframe workflows.

Speaker Bio: Devin Petersohn
Devin Petersohn is the lead developer of Modin and the co-founder and CTO of Ponder. Devin recently completed his Ph.D. from UC Berkeley RISE Lab, where he did research on distributed systems for data science. As a part of this work, he created Modin, a system for enabling scalable interactive data science.

Code of Conduct

https://baypiggies.net/pages/code_of_conduct.html
Interactions online have less nuance than in-person interactions. Please be Open, Considerate and Respectful. Also, please refrain from discussing topics unrelated to the Python community or the technical content of the meeting.

RSVP

We will conduct the meeting via Zoom meeting. When you RSVP "Yes" to this event, the link to the Zoom meeting will become visible in MeetUp.

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