Rolling mean?

Understanding rolling-window calculations in pandas

This is an easy foundational question that tests familiarity with the pandas API for time-series and sliding-window operations. Quant firms expect candidates to work with rolling aggregates quickly—they appear constantly in feature engineering, signal smoothing, and real-time data pipelines.

The question probes whether you know the correct method call and parameter syntax to compute a moving average over a fixed-size window. While the computation itself is conceptually simple, using the right pandas function efficiently separates candidates who have hands-on experience from those learning on the fly.

• Window size and offset semantics in time-series analysis
• Method chaining in pandas
• Aggregation functions on rolling objects