Pandas and Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars
Offered By: PyCon US via YouTube
Course Description
Overview
Explore the latest advancements in Dask DataFrame 2.0 and its integration with pandas in this 30-minute PyCon US talk. Discover how recent improvements address historical performance issues, making Dask a more robust and user-friendly option for big data processing. Learn about the new shuffle algorithm, logical query planning layer, and reduced memory footprint resulting from pandas 2.0. Compare Dask's capabilities to other popular big data tools like Spark, Polars, and DuckDB using TPC-H benchmarks. Gain insights into the future developments of pandas and Dask, including potential extensions of the logical query planning layer to frameworks such as Dask Array and XArray.
Syllabus
Talks - Patrick Hoefler: Pandas + Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars
Taught by
PyCon US
Related Courses
Web Intelligence and Big DataIndian Institute of Technology Delhi via Coursera Big Data for Better Performance
Open2Study Big Data and Education
Columbia University via edX Big Data Analytics in Healthcare
Georgia Institute of Technology via Udacity Data Mining with Weka
University of Waikato via Independent