SOORAJ TS
Sooraj is a Product Engineer at Strollby Inc, where he focuses on building scalable backend architectures and driving performance-focused optimizations.
He is an open-source contributor to frameworks like Agno AGI and Google ADK, and an active speaker at community events — including PyData Global 2025 and the Trivandrum Python Community — where he shares insights on backend architecture, AI systems, and developer productivity tools.
He was also a finalist in the Python Code Jam 2025, recognized for his out of the box solutions
Session
Pandas is one of the most widely used tools in Python, yet many developers unintentionally write slow or memory heavy DataFrame code. This talk covers practical performance techniques that can significantly speed up Pandas workflows: vectorization, avoiding apply, optimizing data types, reducing memory usage, minimizing DataFrame copies, improving joins and groupbys, and using chunked loading for large files. We also look at when to extend Pandas with Polars, Apache Arrow, or DuckDB for faster execution. If you work with data at any scale, this session gives you simple, actionable tricks to make your Pandas pipelines faster and more production ready.