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‎07-21-2025 01:18 PM

HP Recommended

Hi all,

I'm working with a large dataset (around 20M rows) containing event logs with timestamps, and I need to analyze hourly activity trends — e.g., peak usage hours, hourly averages, and patterns over weekdays vs weekends.

I’m currently using Pandas for grouping and visualization, but it’s starting to feel sluggish. Are there better tools or techniques for handling this at scale (maybe Dask, DuckDB, or something else)? I’m on an HP ZBook with 64GB RAM and an NVIDIA GPU if that helps.

Any suggestions for improving speed or best practices for hour-based grouping/visualization would be appreciated.

Thanks!
Jhonn Mick

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