Skinny Pandas Riding on a Rocket


Go to NumFOCUS academy page.

With larger datasets we need to be smarter about how we use Pandas to get results. We’ll look at strategies to shrink our data to get more into RAM, offload computation to tools like Dask or Vaex, store with Parquet or SQLite, make calculations faster and retain debuggability.


Ian Ozsvald (PyDataLondon)

Ian is a Chief Data Scientist and Coach, he helps co-organise the annual PyDataLondon conference with 700+ attendees and the associated 11,000+ member monthly meetup. He runs the established Mor Consulting Data Science consultancy in London, gives conference talks internationally often as keynote speaker and is the author of the bestselling O’Reilly book High Performance Python (2nd edition). He has 18 years of experience as a senior data science leader, trainer and team coach. For fun he’s walked by his high-energy Springer Spaniel, surfs the Cornish coast and drinks fine coffee. Past talks and articles can be found at: