There is a better way to work with large datasets, and this question proves it. The user who posted this is staring down 200,000 rows and ten columns, trying to find duplicate column permutations, and they are stuck in a mindset that treats this as a manual puzzle. It is not. The problem is real, and the scale is intimidating, but the solution is about reframing how you approach the data, not grinding through it row by row.
The key is to stop thinking about columns as separate entities and start thinking about them as sequences of values that can be compared directly. When you have 200,000 rows, your brain is not the tool for the job. The tool is a method that flattens each column into a single string or hash, then compares those strings across all columns. If two columns produce identical hashes, they are duplicates, regardless of how the values are arranged. This is not about cleverness; it is about delegating the heavy lifting to the software that is already in front of you.
What this means for you is simple: the answer is not in learning a new formula or memorizing a shortcut. It is in understanding that your spreadsheet is a computation engine, not a visual grid. When you treat columns as data objects rather than as visual arrangements, you unlock the ability to process 200,000 rows in seconds. The user who posted this question is already halfway there by asking the right question. The next step is to embrace the idea that the solution is structural, not manual. You do not need to eyeball anything. You need to encode the column values into a comparable form and let the machine do what it does best.
The practical takeaway here is that you should never accept the limitations of a traditional spreadsheet workflow when the data is large enough to make manual checking impossible. If you are facing a similar problem, start by writing a formula that concatenates each column into a single cell, or use a simple script to hash each column. Then compare those outputs. It is direct, it is fast, and it removes the guesswork. The moment you stop trying to mentally track 200,000 rows and instead reduce the problem to ten strings, you have already won. Do not let the scale intimidate you. Let the method do the work.