We have a straightforward opinion on this scatter plot mystery: the problem is almost certainly an Excel default that quietly overrides user intent, and the fix is simpler than most people expect. The user here defined Series X values from column Z and Series Y values from column X, yet the resulting chart plotted Portfolio ID from column A on the x-axis instead. That is not a bug; it is Excel's stubborn assumption that the first column of a data range should serve as the category label, even when the user has explicitly pointed elsewhere. This happens because Excel often interprets the leftmost column as a row-identifier, especially when the data is arranged in a table or when the chart source includes multiple columns. The software guesses that the user wants that column to define the horizontal axis, regardless of what the Series X field says.
For anyone who has fought with a chart that refuses to show what you told it to show, this is the moment to recognize the pattern. The practical fix is to check the "Select Data" dialog closely: click the scatter plot, right-click, choose "Select Data," and then edit the horizontal axis labels. If Excel has inserted a reference to column A, delete it and manually set the axis to column X. Alternatively, restructure the source data so that the x-axis values are in the leftmost column, which often prevents the override from happening in the first place. This is not a workaround; it is a direct acknowledgment of how the tool behaves under the hood. The user's blue dots were not lost, they were just misaligned because Excel assumed a relationship that did not exist.
We think this episode reveals something larger about spreadsheet tools in general. They are powerful, but they are also full of silent assumptions that can derail a simple task. The user did everything right: they specified the columns, they checked the formulas, and they still got the wrong result. That is not a reflection on their skill; it is a reflection on software that prioritizes convenience over clarity. The takeaway is that when a chart does not match your data, do not assume you made an error, assume the tool made a guess. Then override it. That is the difference between frustration and control.