Towards Data Science is a community-powered publication that showcases work in data science, machine learning and artificial intelligence. Every day newcomers, seasoned researchers and industry practitioners publish tutorials, research notes and real-world case studies that help the field move forward.

Towards Data Science

A beginner-friendly introduction to PySpark covering three core concepts: clusters (driver/executor architecture), Spark DataFrames, and lazy vs eager evaluation. Includes a practical setup guide using Conda and WSL2, plus hands-on code examples for creating a local Spark session, building DataFrames from inline data and CSV files, and performing column transformations. The lazy execution model is explained with a concrete 10-million-record scenario showing how Spark's predicate pushdown optimization avoids unnecessary computation.

PySpark for Beginners: Mastering the Basics