How to Sum Every Nth Row in Excel

Why This Task Matters in Excel

In many business and analytical scenarios, data arrives in repeating patterns. You may export weekly sales that list four lines per product (one for each region), receive sensor readings where every third row is a calibration record, or collect survey responses interleaved with metadata rows. When totals are needed only for the recurring data points—say, every fourth row—manual summing becomes tedious, error-prone, and unscalable. Being able to tell Excel, “Add up every 4th line,” saves hours and prevents mistakes, especially when the dataset extends into thousands of rows or refreshes automatically.

Finance teams routinely confront this requirement when they download bank statements that insert a blank or descriptive line after each transaction block. Manufacturing engineers often log machine metrics in cycles, with a header, then three readings, header, three readings, and so on; they normally need the sum or average of just the third reading in each set. Marketing analysts using campaign exports see totals, sub-totals, and periodic commentary lines—these reports are unreadable until repetitive non-data rows are isolated or ignored.

Excel excels (pun intended) at pattern recognition through formulas like MOD, OFFSET, INDEX, FILTER, and dynamic-array functions such as SEQUENCE. Instead of restructuring data outside Excel or writing macros, you can build a single, robust formula that updates instantly when new rows arrive. Not having this skill can lead to manual deletions, copy-pasting, and accidental omission of rows, all of which skew results and undermine decision-making. Mastering “sum every nth row” integrates naturally with other core skills—conditional aggregation, dynamic range sizing, and dashboard automation—making it a valuable technique across finance, operations, marketing, and data science workflows.

Best Excel Approach

The most universally compatible, transparent, and performant formula for summing every nth row is a SUMPRODUCT that checks the row number against the desired pattern. SUMPRODUCT works in all modern Excel versions, avoids the volatility of OFFSET, handles filters gracefully, and does not require spilling like dynamic arrays.

Syntax pattern:

=SUMPRODUCT(--(MOD(ROW(data_range)-ROW(first_cell), n)=0), data_range)

Explanation:

• data_range – contiguous range holding the values you want to add.
• first_cell – the top cell of data_range. Subtracting it normalises the row numbers so the very first row counts as zero.
• n – the interval: 2 for every second row, 3 for every third row, and so on.
• MOD(… , n)=0 – returns TRUE for rows whose position in the pattern equals zero (that is, the nth row), FALSE otherwise.
• Double unary -- converts TRUE/FALSE to 1/0 so SUMPRODUCT can multiply by the actual values and add the results.

When you only need every kth row in a column of numbers, this method is concise, readable, and immune to accidental insertion of helper columns.

Alternative approach using FILTER and SEQUENCE (dynamic arrays, Microsoft 365):

=SUM(FILTER(data_range, MOD(SEQUENCE(ROWS(data_range)), n)=0))

This variation spills the filtered values, then sums them. It is more intuitive for Office 365 users but not available in Excel 2016 or earlier.

Parameters and Inputs

• n (Interval): Positive integer indicating the row frequency. Choosing n=1 simply sums the whole range; n≥2 focuses on periodic rows.
• data_range: Must be a single column or single row range—[B2:B1000], [D5:D250]—because the ROW function returns a single row index. If you need to sum every nth row across multiple columns, treat each column separately or switch to OFFSET/INDEX 2-D patterns.
• first_cell: Only required when your data range starts beyond row 1. Using ROW(first_cell) in the MOD adjustment keeps the formula portable: copying the same formula down other columns stays correct without edits.
• Numeric Values: Blank cells or text inside data_range contribute zero to SUMPRODUCT; error values will propagate unless wrapped in IFERROR.
• Dynamic Data: If the list expands, convert it to an Excel Table. Excel automatically grows the data_range reference, e.g., Table1[Sales], preserving the nth-row logic without rewriting formulas.
• Edge Cases: n larger than the number of rows returns zero. A negative or zero n triggers #DIV/0! from MOD; include a validation IF to intercept invalid entries.

Step-by-Step Examples

Example 1: Basic Scenario

Suppose you download a SKU inventory list that alternates quantity and blank separators. Column B contains the quantities in [B2:B21]:

Row | Quantity
2   | 145
3   | –
4   | 175
5   | –
…

You only need the non-blank rows, which repeat every second row. The steps:

1. Decide interval n. Because usable data appears every other row, n=2.
2. Place the formula in any empty cell:

=SUMPRODUCT(--(MOD(ROW([B2:B21])-ROW(B2),2)=0),[B2:B21])

3. Press Enter. Excel returns the total of the quantities: 2,873 (expected).

Why does this work?

• ROW([B2:B21]) produces an array [2,3,4,…,21].
• ROW(B2) subtracts 2, giving [0,1,2,…,19].
• MOD(…,2) gives 0 for even counts, 1 for odd.
• The logical test equals zero is TRUE for rows 0,2,4…—the data rows.
• The double unary converts TRUE to 1, FALSE to 0, effectively “filtering” the dataset during multiplication by the actual values.

Common variations: If the separator row contains text rather than blank, the formula still ignores those rows because the MOD filter already excludes them. Troubleshooting tip: If you see #VALUE!, confirm B-column cells contain numeric data or wrap data_range in N(B2:B21) to coerce text to zero.

Example 2: Real-World Application

A retailer tracks daily online orders in a raw dump that groups seven rows per weekday: six categories followed by an “All Channels” grand total. Management only wants the grand total figure from each block for month-to-date analysis.

Sample layout in [E2:E366] (52 weeks × 7):

• Rows 1-6: Category totals
• Row 7: All Channels grand total
• Pattern repeats.

Steps:

1. Determine interval n=7 (grand total row).
2. Convert the column to a table called Orders. This adds resilience when next month’s data is appended.
3. Enter the formula:

=SUMPRODUCT(--(MOD(ROW(Orders[Value])-ROW(Orders[Value])+1,7)=0), Orders[Value])

Notice the +1 shift. Because the grand total is the seventh item, we want MOD result zero when the position equals seven, not zero. Adding one re-aligns the pattern.

Business resolution: The finance analyst now has a single cell that reports total “All Channels” sales without manually hiding six out of every seven rows. When the portal exports week 53, the table expands and the total refreshes instantly.

Performance considerations: SUMPRODUCT with a 52-week dataset (364 rows) is instantaneous. Even at 100,000 rows, modern Excel completes it under a second because MOD and multiplication are vectorised. The formula’s calculation cost is negligible compared with volatile functions like OFFSET.

Example 3: Advanced Technique

Scenario: A manufacturing plant logs machine output in [A2:C50000]. Column A is a timestamp, column B is Output-Type, column C is Units. Each monitoring cycle records five system tests followed by one operational reading (row 6). You need the sum of operational readings, but only for rows where Units greater than 100, and you want a reusable dynamic array result, not just a single total.

Steps:

1. Set interval n=6 (operational reading).
2. Build a helper dynamic array that isolates the 6th row within the pattern and meets the 100-unit criterion.

=FILTER(C2:C50000, (MOD(SEQUENCE(ROWS(C2:C50000)),6)=0)*(C2:C50000>100))

3. Wrap SUM around the FILTER spill:

=SUM(FILTER(C2:C50000, (MOD(SEQUENCE(ROWS(C2:C50000)),6)=0)*(C2:C50000>100)))

Why advanced?

• The formula stacks two filters: positional (MOD) and value-based (>100).
• Using SEQUENCE avoids referencing row numbers explicitly, making the solution robust if rows are inserted.
• FILTER returns a spill range for auditing. You see which rows matched before they are aggregated.
• Dynamic arrays can feed charts or pivoted dashboards directly.

Edge case handling: If no rows satisfy both conditions, FILTER returns #CALC!. Wrap in IFERROR(…,0) to produce zero instead. Performance: Despite 50,000 rows, calculations are instantaneous because Excel’s dynamic array engine is optimised for vector operations.

Tips and Best Practices

1. Convert your dataset to an Excel Table. Structured references like Table1[Total] automatically resize and make formulas self-documenting.
2. Always normalise row numbers with ROW(first_cell). This keeps the formula correct when the data range starts at any row and when the sheet contains header rows.
3. Use named ranges such as nInterval or SalesData to avoid hard-coding 6, 7, 10 in multiple formulas. Changing the interval later becomes a single-cell edit.
4. Combine logical conditions in SUMPRODUCT by multiplying them: (MOD(...)=0)*(criteria). It avoids nested IFs and remains readable.
5. When performance matters, prefer SUMPRODUCT over OFFSET. OFFSET is volatile and recalculates every time anything changes, whereas SUMPRODUCT triggers only when precedent cells update.
6. Document the pattern in an adjacent comment or cell (e.g., “Every 5th row = machine reading”) so future team members understand the logic.

Common Mistakes to Avoid

1. Forgetting to subtract ROW(first_cell). This mis-aligns the MOD pattern and yields inaccurate totals. Fix: always anchor the offset to the first row of your data_range.
2. Using n set to zero or negative. MOD with zero divisor returns #DIV/0!, crashing the formula. Validate n with an IF(n less than 1, …).
3. Applying the formula to a multi-column range. ROW returns the row number of the first column only; unexpected shifts occur. Target a single column or wrap the formula per column.
4. Placing the formula inside the data_range in an Excel Table. Tables may replicate the formula down every row, causing exponential calculation. Keep the summary formula outside.
5. Overlooking text or error cells inside data_range. Even though SUMPRODUCT treats text as zero, a stray #N/A propagates an error. Solution: wrap data_range in IFERROR or use N() to coerce non-numbers.

Alternative Methods

Choose SUMPRODUCT when you need simple, immediate results and maximum compatibility. Pick FILTER for dynamic-array workflows. Resort to Power Query when the data cleaning already occurs there or you need automation beyond formulas.

FAQ

When should I use this approach?

Use these formulas whenever your dataset contains repeating groups and only certain positional rows matter—financial statement exports, periodic sensor logs, or any report with sub-totals that should be excluded.

Can this work across multiple sheets?

Yes. Qualify the ranges with the sheet name: Sheet2!B2:B500. You can also wrap each sheet’s SUMPRODUCT in SUM to build a workbook-level total: `=SUM(`SheetA_Total,SheetB_Total).

What are the limitations?

The technique assumes a fixed pattern. If the interval changes mid-dataset, you must segment the data or use more complex logic. Also, SUMPRODUCT in very old Excel versions (pre-2007) has row limits; upgrade if your range exceeds 65,536 rows.

How do I handle errors?

Wrap the summing range in IFERROR to convert errors to zero: `=SUMPRODUCT(`--(MOD(...)=0), IFERROR(range,0)). For FILTER, nest IFERROR around the entire formula.

Does this work in older Excel versions?

SUMPRODUCT works back to Excel 2000. Dynamic-array functions (FILTER, SEQUENCE) require Microsoft 365 or Excel 2021. OFFSET and helper-column methods are compatible with all versions but may be slower.

What about performance with large datasets?

SUMPRODUCT scales well to hundreds of thousands of rows because it leverages Excel’s native array engine. Avoid volatile OFFSET in large files, and disable manual calculation if you cascade many SUMPRODUCTs across sheets.

Conclusion

Being able to sum every nth row transforms messy, pattern-laden exports into clean, actionable summaries. Whether you prefer the timeless SUMPRODUCT method or modern dynamic arrays, mastering this skill streamlines financial reconciliations, engineering logs, marketing analytics, and more. Practice the examples above on your own data, experiment with different intervals, and integrate these formulas into tables and dashboards. Your spreadsheets will be leaner, faster, and far less error-prone—an essential step on your journey to Excel mastery.