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Thursday, June 23 • 11:00am - 11:50am
raku::Dan - Re-Inventing the DataFrame

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Elevator Pitch:
The explosion in Data Analytics and Data Science applications has been driven by Python and its library modules such as Pandas and Polars. This talk is about re-inventing DataFrames using a raku-centric approach to fundamentally improve architecture, code concision and manipulexity.

As raku matures, we need useful basic eco-system modules to bring the unique strengths and cultural style of raku to real-world use-cases.
raku::Dan (Data ANalytics) is a new raku module family (also Dan::Pandas and Dan::Polars) that offers top level Raku-oriented data structures for Series and DataFrames. The thinking is:
  1. we need a Raku-esque way to do the analytics basics - Series and DataFrames
  2. much has been inspired by Python Pandas (not least for good interworking)
  3. we can draw from many Raku native capabilities (accessors, types, hypers, laziness, pipes, sort, grep, splice, etc.)
  4. Pandas suffers from featuritis (Pandas has 422 object methods, plus 50 or so module methods and raku offers a fresh start
This talk will describe the raku::Dan family - design considerations, focus & roadmap and unique differentiators - with hands on examples of Data Munging in Raku and interworking with Python Pandas via raku Inline::Python.

avatar for p6steve


Principal, Henley Cloud Consulting

Thursday June 23, 2022 11:00am - 11:50am CDT
Raku Track 12426 Greenspoint Dr, Houston, TX 77060

Attendees (6)