There's a moment in every spreadsheet user's life when the data stops being a tool and becomes a burden. That moment is captured perfectly. The user isn't asking for a miracle or a magic button; they're asking for a practical path forward after Power Query let them down. And that's exactly the right instinct. The problem isn't the volume of files, though 132 workbooks is no small pile. The real issue is that the tools most people are told to use, like Power Query, assume a level of consistency that real-world data rarely has. When five of your files have mixed-up rows, the tool doesn't fail because it's weak. It fails because it's strict, and strictness doesn't survive contact with messy reality.
What this user needs isn't a workaround for Power Query. They need a different mental model entirely. Instead of trying to force every file into the same rigid template, think of the merge as a matching exercise. The five files with jumbled rows aren't broken. They're just out of order. If every file shares a common identifier, like a name, a date, or an ID column, then the order becomes irrelevant. You're not stacking rows blindly. You're aligning them by meaning. That shift, from "combine everything in sequence" to "match and then merge," turns a frustrating chore into a manageable task. It also opens the door to tools that handle this kind of fuzzy matching with less fuss, whether that's a more forgiving script, a dedicated data prep tool, or even a few well-placed formulas.
The user's instinct to avoid manual copying is spot on. That's not laziness; that's efficiency. But the answer isn't to find a single perfect tutorial that does exactly this, because that tutorial doesn't exist. The answer is to break the problem into steps: first, clean and standardize the five outliers so every file has the same column order. Then, use a simple script or a tool like Python's pandas library to loop through all files, read each one, and append them row by row. The user doesn't need to be a programmer to do this. They need a starting point, and there are plenty of copy-paste-ready scripts online that handle exactly this kind of batch merge. The key is to stop treating this as an Excel problem and start treating it as a data problem. Excel is just the container.
The practical takeaway here is simple: don't let Power Query's failure define your options. Test one file first. Open it, check the columns, confirm the data type, and run a small merge on two files before touching all 132. That single test saves hours of debugging later. And if the mixed-up rows keep causing trouble, sort every file by that common identifier before merging. That one step alone will neutralize the disorder. The user is closer to the finish line than they think. They just need to stop searching for a single magic video and start assembling their own sequence of small, deliberate moves. That's not a compromise. That's how real work gets done.