Unpivot Data Power Query

What this does

Power Query — shown in the ribbon as Get & Transform — is the import-and-clean layer that sits in front of the worksheet. Its defining property is that it RECORDS every step rather than performing it: removing a column, splitting one, changing a type, filtering rows and unpivoting all land as an ordered list in the Applied Steps pane. Point it at next month's file and click Refresh, and the whole sequence replays. That makes it the correct answer to any cleaning job you will do more than once, and to combining a folder of identically shaped files (Get Data ▸ From File ▸ From Folder). Two operations have no practical worksheet equivalent: Unpivot Columns, which turns a wide twelve-month-columns layout into the tall three-column shape every PivotTable wants, and Merge Queries, a join that handles many-to-many where VLOOKUP cannot. It is built into Excel for Windows from 2016 and into Excel for Mac from 2019, though the Mac version supports fewer connectors. The same idea underpins a lot of everyday Excel work, so the few minutes spent getting it right here pay back across every sheet you build afterwards. Treat it as a pattern, not a one-off, and it stops being something you look up and starts being something you reach for. For “unpivot data power query”, the reliable version is a short checking loop, not just the first command that appears to work. Run it on a deliberately small range first, watch how the affected pivot table change, and only then apply the same setup to the full sheet. When this is a ribbon command, the selection matters more than the button: confirm the range, apply the command, then spot-check the output before saving. That is what makes a data step that keeps your analysis trustworthy useful in real work: repeatable, auditable, and not dependent on memory or luck.

A worked example

Twelve monthly CSV exports in one folder, each with the same headers. Data ▸ Get Data ▸ From File ▸ From Folder ▸ pick the folder ▸ Combine & Transform. Power Query stacks all twelve, and the steps you then add — remove a blank column, set Date to date type, filter out cancelled rows — apply to every file. Next month, drop file thirteen into the folder and press Data ▸ Refresh All. Any cleaning routine you perform more than once is a query you should have built the first time — the second month costs one click instead of an afternoon. If there is any chance you will reuse this, drop it into a small template tab right now: a labelled input area on the left and the formula beside it, checked once against the tool above. Next time the same question comes up, the answer is a single paste away instead of a rebuild from memory.

In Google Sheets

Everything above works in Google Sheets too. Excel and Sheets share the formula syntax used here; only the surrounding menus are arranged differently. That portability is deliberate — learn it once and it follows you between the two tools and across Windows and Mac. Nothing on this page is behind a login: the tool runs entirely in your browser, the formula is shown in full with one-click copy, and the steps work the same on Windows and Mac. That is the whole promise here — the exact answer, a way to prove it on your own numbers, and just enough context to make it stick. The short version of “unpivot data power query”: the answer is at the top of this page, the tool proves it on your own numbers, and the sections above explain why it holds so the next variation does not stump you. Excel rewards people who reference cells instead of typing values and who keep inputs separate from formulas, because that is what makes a result you can audit months later. Build it once, deliberately, with the live tool as a check, and you convert a one-off lookup into a reusable skill — which is the whole point of learning the why and not just the what.

Common mistakes

• Editing the loaded output on the sheet — the next refresh overwrites it. All edits belong in the query.
• Skipping Change Type, so numbers arrive as text and every downstream total is wrong or zero.
• Filtering on a value list, which hard-codes today's values into the step and silently drops new ones later.
• Combining files whose headers differ slightly; the step records column names, so "Amount " with a trailing space breaks the append.
• Loading a million rows to a worksheet instead of Close & Load To ▸ Connection Only ▸ Add to Data Model.
• Building the same clean-up by hand each month when the query already exists and just needs Refresh.

Frequently asked questions