Aligning Grouped Rolling Counts with Stock Data

Summary

The post asks how to calculate, for each instrument, the rolling five-day count of sessions when a stock value exceeds an index value, then assign those counts back to the original dataframe. The author reports that the grouped calculation produces the expected values when printed, but assigning the result after resetting its index gives mismatched values. The example highlights that grouped results can have an index structure or row order that does not match the source dataframe, so removing index labels does not necessarily preserve the intended instrument-to-row alignment.

The document provides no accepted fix or comparison of alternative approaches. It is a narrow data-handling question rather than a tested trading method, and it omits the displayed data needed to diagnose the exact alignment. Its practical lesson is to check both row order and index structure when attaching grouped rolling calculations to multi-instrument market data.

Key ideas

• The example computes a rolling five-session count of stock values greater than index values within each instrument.
• The author reports that the grouped calculation looks correct before assignment to the original dataframe.
• Resetting the result index may leave values misaligned with source rows when group order differs.
• The post gives no final solution, so the exact correction cannot be established from the available text.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.