PySpark vs Pandas: Choosing the Right Tool for Your Data Workflow
“The big-data world rewards the right abstraction at the right scale.” After more than a decade of wrestling with datasets that range from a few megabytes to multiple terabytes, I’m often asked “Should I use Pandas or PySpark?” Both libraries live in the Python ecosystem, both expose a DataFrame API, and—on the surface—they feel remarkably similar. Yet they’re built for very different contexts. This post breaks down the key differences so you can pick the right hammer for the job. ...