This user's struggle is a perfect example of how traditional spreadsheets fail when data gets real. They need a grouped box and whisker plot with a logarithmic y-axis, and Excel is making it nearly impossible. Our take is blunt: if your tool fights you on something this fundamental, it is not a tool, it is a barrier.
The core problem here is not the user's formatting skills. It is that Excel treats every chart as a static arrangement of cells, not a dynamic representation of relationships. When you insert a blank "gap" series to separate compound groups, the software scales the entire plot poorly because it has no built-in understanding of what a "group" means. The result is a cramped, unreadable chart that hides the very patterns you are trying to see. This is not a user error. It is a design limitation baked into a tool that was built for ledgers, not for exploratory data analysis.
What the user actually needs is a system that understands log scales as a first-class operation, not an afterthought buried in axis formatting menus. They need a chart engine that can group categorical variables (compounds) and sub-group numeric categories (sampling sites) without requiring manual placeholder rows. They need the plot to automatically respect the logarithmic distribution of their data so that outliers and medians remain visible, not squashed into a tiny corner of the page. These are not exotic requests. They are the minimum viable functionality for anyone doing environmental monitoring, pharmaceutical analysis, or any field where concentrations span orders of magnitude.
The practical takeaway for anyone reading this: when a visualization task makes you feel like you are fighting the software, stop fighting. The problem is not you. The problem is that legacy tools were designed for a world where data was simple, small, and static. Your data is none of those things. Do not waste hours jury-rigging gaps and blank series. Instead, ask yourself whether the tool you are using was built for the work you are actually doing. If the answer is no, then the next step is not to find a better workaround. It is to find a better tool, one that treats log scales and grouped plots as standard features, not hacks.