Crunch Big Data on Your Laptop With Polars Streaming
Polars streaming avoids out-of-memory errors in large cross joins via processing data in chunks. Learn how to run 27M row workloads on a single machine.
Polars Boosted My Algorithm's Speed by 25x
Refactoring an RCE machine learning algorithm from Pandas lambda functions to the Polars expression API reduced execution time from six minutes to fourteen seconds. Polars cross joins, columnar operations, and Apache Arrow drive a 25x speedup.
Quick and Easy Capacity Planning with Pandas
Build a lightweight capacity planning model in Python Pandas using flow diagrams, throughput estimates, and GROUP BY operations to estimate CPU requirements and infrastructure cost. Apply Operations Research concepts to size a simple web...
Use Python Pandas to Invest in Sealed Super Mario Bros. 3
Identify investment grade copies of sealed Super Mario Bros. 3 variants through Python Pandas, Seaborn, and auction sales data. Normalize prices across market cycles and compare box grade, seal grade, release variant, and sale date to rank...
Data Exploration with Data Viz Cheat Sheet
Witness practical Pandas, Seaborn, and Matplotlib techniques for exploring machine learning datasets using the UCI Abalone database. Includes histograms, KDE plots, boxplots, correlation heatmaps, PCA, regression plots, and multidimensional...