This is a classic example of a simple problem meeting a formula that is almost, but not quite, right. WinterStormBorn has 32,000 rows of solar data logged in 15-minute intervals and needs to sum them into daily totals. The instinct is correct, automate the aggregation. The approach, however, reveals a fundamental mismatch between how the spreadsheet interprets the formula and how the user intends it to work.
The core issue lies in the use of `ROWS(E8)`. This function returns the total number of rows in the reference, which is always 1. Multiplying that by 96 and subtracting 1 gives the formula a constant starting point. When dragging the formula down, the reference `E8` updates to `E9`, `E10`, and so on, but the `ROWS` function still evaluates to 1 for each new cell. The offset never jumps by 96 rows; it creeps down one row at a time. WinterStormBorn is watching the function shift by a single cell while expecting it to leap by 96, and the spreadsheet is following the logic it was given, not the logic that was intended.
There is a better way, and it does not require wrestling with `OFFSET` at all. The `INDEX` function combined with `SEQUENCE` provides a cleaner, more predictable method. A formula like `=SUM(INDEX(E:E, (ROW(A1)-1)*96+8):INDEX(E:E, (ROW(A1)-1)*96+103))` explicitly defines the start and end rows of each 96-cell block. As the formula is dragged down, `ROW(A1)` increments to 2, 3, and so on, which shifts the block by exactly 96 rows each time. This removes the guesswork and the fragility of `OFFSET`, which recalculates on every cell change.
This situation highlights a broader truth about working with large datasets in traditional spreadsheets. The tools are powerful, but they were designed for manual, cell-by-cell manipulation. When you have 32,000 rows of time-series data, the manual approach is not just tedious, it is a barrier to insight. The user should not have to become a spreadsheet engineer just to get a daily sum. The solution exists, but it requires knowing the right formula pattern. For anyone facing similar repetitive aggregation tasks, the real win is not just fixing this one formula. It is recognizing that the spreadsheet itself is the wrong tool for this job. A modern, AI-native approach would let you describe the task in plain language: "Sum the 15-minute solar data by day." The system would understand the structure of your data and execute the aggregation without requiring you to debug row counts. Until then, use `INDEX` and `SEQUENCE`, and save yourself the headache of 32,000 manual sums.