One downside of not using lines, it makes it harder to tell where one plot ends and the next begins.
I mean a plot like this is just a mess. You could probably get situations where it wasn’t even clear which plot a data point belonged to.
At least with the boxes, you have a nice clear visual indicator of where the data ends. Here it’s not obvious at a glance which numbers match up with which plots, and the ticks are easy to confuse for point markers.
All right it’s a bit of a mess with the edges in too. But at least it’s crisper.
I feel like displaying a grid of plots is a different use case. And if I had my druthers here, I’d want the plot bounding lines to be around the axis numbers, not within the axis numbers. And definitely not allowing the axis numbers to overlap onto neighboring plots! Wow, ugh.
Also, when displaying multiple plots you are clearly in a danger-of-misinterpretation zone when the plots don’t share the same numeric min/max points! In this case, the solution would clearly be to normalize the data, so everything was between 0 and 1. If you wanted a comparison between clusters that non-normalized data could give you, then the clusters should be on the same plot, with differing colors & symbols.
One downside of not using lines, it makes it harder to tell where one plot ends and the next begins.
I mean a plot like this is just a mess. You could probably get situations where it wasn’t even clear which plot a data point belonged to.
At least with the boxes, you have a nice clear visual indicator of where the data ends. Here it’s not obvious at a glance which numbers match up with which plots, and the ticks are easy to confuse for point markers.
All right it’s a bit of a mess with the edges in too. But at least it’s crisper.
I feel like displaying a grid of plots is a different use case. And if I had my druthers here, I’d want the plot bounding lines to be around the axis numbers, not within the axis numbers. And definitely not allowing the axis numbers to overlap onto neighboring plots! Wow, ugh. Also, when displaying multiple plots you are clearly in a danger-of-misinterpretation zone when the plots don’t share the same numeric min/max points! In this case, the solution would clearly be to normalize the data, so everything was between 0 and 1. If you wanted a comparison between clusters that non-normalized data could give you, then the clusters should be on the same plot, with differing colors & symbols.
I think in this case just spacing them out would help more.