How to Unique With Non Adjacent Columns in Excel

Why This Task Matters in Excel

In every data-driven department—finance, sales, marketing, operations—teams constantly face lists with repeating information spread across several columns. Sometimes those columns sit side-by-side, but more often the columns you care about are separated by fields you do not need. Imagine a customer table where [A] holds Customer ID, [B] holds Product Code, [C] holds Purchase Date, and [D] holds Sales Region. Suppose management asks for a distinct list of Customer ID and Sales Region combinations. The two fields are non-contiguous—separated by two other columns—yet need to be treated as one composite key.

Not knowing how to extract unique pairs (or triples) from non-adjacent columns leads to time-consuming manual copy-and-paste, hidden helper columns, or messy pivot tables that break each time the dataset grows. In business environments, such delays translate to missed deadlines, reporting errors, and decisions made on incomplete information.

Mastering unique + non-adjacent logic tightens workflows in several scenarios:

• CRM de-duplication—quickly find unique combinations of customer and campaign without dragging every column.
• Inventory management—distinct lists of SKU and warehouse when the SKU, quantity, and reorder point sit between the two needed fields.
• Financial consolidations—unique client-currency pairs for FX translation while dimensions such as department and cost center sit in the middle.

Modern Excel offers dynamic array functions—UNIQUE, CHOOSECOLS, HSTACK, LET—that make the task practically effortless. Older releases (Excel 2016 and earlier) require array‐enabled INDEX + MATCH + COUNTIF or Advanced Filter, but the principle is identical: select only the columns you want, then strip duplicates. Knowing both modern and legacy approaches ensures compatibility across teams and versions, and connects directly to other skills such as dynamic dashboards, Power Query transformations, and robust error handling.

Best Excel Approach

For Microsoft 365 or Excel 2021, the most efficient pattern pairs CHOOSECOLS with UNIQUE. CHOOSECOLS lets you pick specific columns from a larger table without moving data. UNIQUE immediately returns a distinct list of rows from that virtual subset. Because the two functions spill results dynamically, they update automatically as new records appear—eliminating refresh steps.

Core syntax:

=UNIQUE(CHOOSECOLS(DataRange, ColNum1, ColNum2, …))

Where:

• DataRange – the entire rectangular dataset (e.g., [A2:D5000])
• ColNum1, ColNum2 – index numbers of the columns you want, based on DataRange counting from the leftmost column as 1

Why it is best:

1. Zero helper columns—reduces workbook clutter.
2. Fully dynamic—you can wrap the result in SORT or SORTBY for presentation.
3. Scales to any size—UNIQUE and CHOOSECOLS work on ranges in the tens of thousands without noticeable lag on modern hardware.
4. Keeps formula readable—any analyst can glance at the function and understand which columns feed the result.

Alternative for Microsoft 365: combine HSTACK with UNIQUE if the source columns reside in completely separate ranges. For legacy Excel, Advanced Filter (manual or VBA) and a classic array formula using INDEX + MATCH + COUNTIF provide similar outcomes, although with more maintenance overhead.

=UNIQUE(HSTACK(Column1Range, Column2Range))

Parameters and Inputs

• DataRange: a continuous range containing the dataset, e.g., [A2:E10000]. Tables (ListObjects) are ideal; refer to them as SalesData.
• Column Index Numbers: integers such as 1 and 4 when you want the first and fourth columns inside DataRange. Negative integers are invalid.
• Column Ranges (HSTACK variant): independent vertical ranges of equal height; if heights differ, HSTACK pads with #N/A, so use TAKE or FILTER to equalize lengths.
• Optional UNIQUE parameters: by_col (true/false) and exactly_once (true/false). For row-wise de-duplication, keep by_col at default (false). Use exactly_once when you need values that occur only one time in the dataset.
• Data Types: ensure the selected fields share the expected type—don’t mix numbers stored as text and pure numbers in the same column, or duplicates may slip through.
• Preparation: remove leading/trailing spaces with TRIM, standardize case with UPPER/LOWER if duplicates vary by capitalization.
• Edge cases: blanks. UNIQUE treats a fully blank row as one unique row; filter blanks out beforehand if necessary (FILTER(range, range<>"")).

Step-by-Step Examples

Example 1: Basic Scenario

You have a small staff roster in [A2:D14]:

• Column A: Employee ID
• Column B: First Name
• Column C: Role
• Column D: Location

Task: produce a list of distinct pairs of Employee ID and Location.

1. Select an empty cell, say [F2].
2. Enter:

=UNIQUE(CHOOSECOLS(A2:D14,1,4))

3. Press Enter. Because UNIQUE is a dynamic array, the results spill downward and showcase each unique Employee ID-Location combination.

Why it works: CHOOSECOLS returns a two-column array composed of just column 1 and column 4 of [A2:D14]. UNIQUE removes duplicate rows where BOTH values match—exactly what you need.

Variations:

• Wrap with SORT to alphabetize by Location: =SORT(UNIQUE(CHOOSECOLS(A2:D14,1,4)),2,1).
• Show only combinations that occur more than once (catch duplicates for cleanup): wrap in FILTER plus COUNTIFS.

Troubleshooting:

• If you get #NAME?, you are on an Excel version without UNIQUE; jump to the Alternative Methods section.
• If blank rows appear, add FILTER(A2:D14, A2:A14<>"") inside CHOOSECOLS to exclude empty employees.

Example 2: Real-World Application

Scenario: A retail chain tracks every sale in a table named SalesData with columns:

[Date] [Store_ID] [Cashier] [ProductSKU] [Units] [Revenue]

Management wants a unique list of Store_ID and ProductSKU pairs to feed the replenishment team. The dataset contains forty thousand rows updated daily.

1. Convert data to an official Excel Table: Ctrl + T, name it SalesData.
2. In a new worksheet, cell [A2], type:

=LET(
     src, SalesData,
     result, UNIQUE(CHOOSECOLS(src, 2, 4)),
     SORT(result, 1, 1)
)

Explanation: LET assigns the SalesData table to variable src, improving readability and calculation speed (Excel only evaluates it once). CHOOSECOLS picks column 2 (Store_ID) and column 4 (ProductSKU). UNIQUE removes duplicates. SORT organizes by Store_ID ascending.

Integration points:

• Use this spilled array as the source for a Data Validation dropdown—dynamic store-product menu.
• Wrap with TOCOL to convert to a single-column feed for Power Automate triggers.

Performance notes: With forty thousand rows, the formula recalculates in a fraction of a second on typical laptops; LET avoids redundant memory reads. If performance still lags, convert SalesData into a Power Query connection and load the final unique list to the worksheet (covered in Alternative Methods).

Example 3: Advanced Technique

Challenge: Build a unique list of Customer-Currency pairs where:

1. The dataset sits across two sheets: Customers[CustomerID] on Sheet1 and Transactions[Currency] on Sheet2, both with matching order by row index.
2. You must ignore any record where a transaction is older than three years or the currency field is blank.
3. You also want to flag each pair whose total transaction amount exceeds 100 000.

Steps:

1. Ensure Customers and Transactions are Tables named Cust and Trans.
2. On a summary sheet cell [B2], enter:

=LET(
    cID,   Cust[CustomerID],
    curr,  Trans[Currency],
    amt,   Trans[Amount],
    date,  Trans[Date],
    recent, date >= EDATE(TODAY(), -36),
    validRows, FILTER(HSTACK(cID, curr, amt), (curr<>"") * recent),
    matrix, HSTACK(INDEX(validRows,,1), INDEX(validRows,,2)),
    uniq,  UNIQUE(matrix),
    overLimit, MAP(uniq, LAMBDA(r1,r2, IF(SUMIFS(INDEX(validRows,,3), INDEX(validRows,,1),r1, INDEX(validRows,,2),r2) > 100000, "⚠", ""))),
    HSTACK(uniq, overLimit)
)

What happens:

• HSTACK merges the separate column ranges into a working array after applying FILTER to remove blanks and older entries.
• UNIQUE extracts distinct CustomerID-Currency pairs.
• MAP combined with LAMBDA loops over each row of uniq to compute total amount via SUMIFS and appends a warning flag where needed.

Edge cases:

• If datasets are not perfectly aligned row-for-row, use XLOOKUP inside the construction step to ensure correct pairing.
• Large datasets (hundreds of thousands of rows) might benefit from moving the heavy aggregation into Power Query.

Tips and Best Practices

1. Wrap result inside SORTBY with a user-friendly column (e.g., location name) to keep dropdowns neat.
2. Store datasets as official Tables; CHOOSECOLS works on Table references, and the function automatically adjusts as rows are added.
3. Use LET to define intermediate variables—easier to debug complex logic and boosts performance through single evaluation.
4. Combine UNIQUE with COUNTIF or PIVOT to validate no unexpected duplicates slip through due to whitespace or case differences.
5. When creating dashboards, reference the spilled array with the hash symbol (e.g., F2#) so charts automatically resize.
6. Document column numbers with inline comments or names to avoid confusion when someone inserts a new column later.

Common Mistakes to Avoid

1. Hard-coding absolute column letters instead of CHOOSECOLS indexes—breaks immediately when a new column is inserted. Fix: wrap in CHOOSECOLS and reference column positions dynamically or use Table structured references.
2. Forgetting to trim or standardize text, leading to invisible duplicates like \"NY \" vs \"NY\". Use TRIM and UPPER in preprocessing.
3. Attempting UNIQUE on separated single columns with mismatched lengths, causing #N/A pads from HSTACK. Align lengths first with TAKE or FILTER.
4. Using UNIQUE with by_col set to true by accident; that de-duplicates within columns independently, not rows. Always leave the argument blank or false for multi-column distinct requests.
5. Copy-pasting the spilled array elsewhere as values, then wondering why it no longer updates. Instead, reference the original spill location or convert to a Table to preserve dynamics.

Alternative Methods

When UNIQUE or CHOOSECOLS is unavailable or unsuitable, consider these options:

| Method | Excel Version | Dynamic Update | Complexity | Pros | Cons | | (UNIQUE + CHOOSECOLS) | Microsoft 365 / 2021 | Yes | Low | Fast, readable | Requires modern Excel | | INDEX + MATCH + COUNTIF Array | 2010–2019 | Limited (array refresh) | Medium | Works in older versions | Harder to audit, volatile | | Advanced Filter | 2007+ | Manual / VBA | Low | No formulas, GUI driven | Must re-run after data change | | Power Query | 2016+ (add-in for 2010/2013) | Yes (Refresh) | Medium | Handles millions of rows, GUI | Requires Refresh, external connection | | Pivot Table Distinct Count | 2013+ | Manual Refresh | Low | Drag-and-drop ease | Adds subtotals you must hide |

INDEX + MATCH + COUNTIF pattern:

=IFERROR(INDEX($A$2:$A$5000, MATCH(0, COUNTIF($F$1:F1, $A$2:$A$5000&"|"&$D$2:$D$5000), 0)), "")

Enter with Ctrl + Shift + Enter (legacy arrays). It concatenates Employee ID and Location separated by a pipe and feeds COUNTIF to detect the next unseen pair.

Power Query approach:

1. Select any cell in your data, Data ► From Table/Range.
2. In the Power Query editor, hold Ctrl and click the column headers you need, right-click ► Remove Other Columns.
3. Home ► Remove Rows ► Remove Duplicates.
4. Close & Load To … table or connection.
   The query refreshes with a single click or via auto-refresh schedule.

FAQ

When should I use this approach?

Use UNIQUE + CHOOSECOLS when you need a live updating list of distinct combinations from columns that are not next to each other, and you are on Microsoft 365 or Excel 2021. Ideal for dashboards, validation lists, and ad-hoc analysis.

Can this work across multiple sheets?

Yes. Reference each sheet’s range or Table inside CHOOSECOLS or HSTACK. Ensure the ranges have identical row counts or normalize them with ALIGN, FILTER, or LOOKUP functions before stacking.

What are the limitations?

UNIQUE counts rows as duplicates only when every selected column matches exactly. Minor spelling or case differences create separate entries. The function does not ignore blanks by default, and heavy array formulas can still slow very large (>300 000) datasets.

How do I handle errors?

Wrap suspect inputs in IFERROR or convert #N/A pads from HSTACK into blanks using IFNA. Use ISBLANK or LEN to filter out unintended empty strings before de-duplication.

Does this work in older Excel versions?

Not the modern formula approach. For Excel 2019 and earlier, switch to Advanced Filter, Power Query, or legacy array formulas as explained under Alternative Methods.

What about performance with large datasets?

Dynamic arrays are highly optimized, but if you notice slow recalc: convert ranges to Tables (improves memory handling), avoid volatile functions inside LET, and consider moving heavy grouping into Power Query. On massive datasets (millions of rows), Power Pivot or a database tool is better.

Conclusion

Extracting a distinct list from non-adjacent columns is a staple task for analysts and managers alike. With Microsoft 365’s UNIQUE + CHOOSECOLS combo you get a clean, one-cell solution that updates automatically, integrates smoothly with dashboards, and eliminates tedious manual steps. Knowing the legacy alternatives ensures you can support any team, while familiarity with Power Query opens doors to enterprise-scale data shaping. Practice the techniques above, explore each example dataset, and you will transform how quickly and reliably you summarize information—one unique pair at a time.