This is a straightforward problem with a straightforward fix, and it's one that trips up more people than it should. The user who posted this has done the hard work, cleaned the data in Power Query, reduced it to just a header and two rows, only to have their accounting software insist there are phantom values lurking in rows 4 through 7. The frustration is real, and the temptation to blame the software or start hunting for hidden formatting is strong. But the culprit is almost certainly something Power Query itself left behind: a table that still contains empty rows or a connection that preserves the original sheet's range.
What the upload software sees is not the visible data alone. It sees the entire worksheet range that Excel or Power Query defined when the file was created. If the original file had data in those lower rows, even if you deleted it visually, the table structure may still reference them. Power Query's output is a new table, but it inherits the source file's used range unless you explicitly tell it to stop. The fix is not complicated. In Power Query, before loading the result, add a step to remove blank rows. Use the "Remove Rows" dropdown and choose "Remove Blank Rows." That single action tells the query to trim the table to only the rows that actually contain data. Alternatively, you can filter each column for non-null values, which achieves the same result and gives you more control over edge cases.
The deeper lesson here is about how data tools interpret "empty." To a human, a blank row is nothing. To an accounting system, it is a row with missing values, and missing values can cause failed uploads, misaligned ledgers, or silent errors that surface weeks later. The user is right to trust their data prep instincts. Power Query is capable of handling this, but it requires thinking like the software that will consume the output. That means being explicit about what constitutes a valid row and what should be discarded.
Our opinion is plain: do not accept a file that your own tool thinks is clean when it is not. Add the blank-row removal step into every Power Query workflow that feeds an accounting system. Test the output by opening the file and scrolling to the last row. If you see nothing, the upload will see nothing. If you see a blank cell that your eye skips, your software will not. That is the difference between a file that works and one that wastes an afternoon.