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UID:pretalx-pyconde-pydata-2026-7PNT37@pretalx.com
DTSTART;TZID=CET:20260415T173500
DTEND;TZID=CET:20260415T180500
DESCRIPTION:Do you find yourself weighing up the pros and cons of using nes
 ted types in the Polars library - pondering whether you should encode your
  variables in structures using lists\, arrays or opt for a flat format wit
 hout complex hierarchy? This talk focuses on the crucial design choices av
 ailable\, the performance implications\, and how this impacts the logic of
  your queries\, as well as code readability\, when deciding how to impleme
 nt your big data pipeline in Polars. The methods available for nested type
 s in Polars have seen some significant additions over the last year\, with
  powerful functionality\, such as filtering and aggregation\, released in 
 the latest versions of the library. These provide much-needed shortcuts fo
 r queries interrogating complex nested structures that previously required
  sophisticated user-defined functions. It makes the use of nested types mu
 ch easier and intuitive\, but does this mean you should nest your data? Th
 rough practical examples you’ll learn some guidelines to help you decide
 .
DTSTAMP:20260523T180014Z
LOCATION:Helium [3rd Floor]
SUMMARY:To nest\, or not to nest? Nested data types in Polars with big data
  - Daniel Finnan
URL:https://pretalx.com/pyconde-pydata-2026/talk/7PNT37/
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