What are accepted ways for visualizing this example dataset for a journal or other "professional" endpoint?
The graph I have in mind looks like this
, roughly speaking:
• I have two datasets that I am comparing with two separate y-axes. For the purposes of illustration, higher values of variables 1 and 2 are "bad", lower values are "good".
• The first dataset (green) is showing data results for variables 1 and 2 across all categories (x-axis, A to N).
• The second dataset (red) is showing data results for variables 1 and 2 across a subset of categories (A to K).
• The categories are continuous and equally distanced values, which is why lines are used instead of discrete points.
What I would like to do:
I want to show that the second dataset (red) not only performs worse than the first dataset (green) after the first category, but that it cuts out entirely past category K.
What I am doing now:
That red ball is supposed to be a visual indicator that would be explained in the figure legend. The ball could be replaced with a box or cross.
What are other ways in which this kind of data comparison can be visualized, which follow accepted conventions for data visualization in modern scientific journals?
I would like to avoid the "cheat" of using the red ball, since I would have to explain this in writing in the figure legend, and I don't want to confuse the inferences that the audience should derive from the figure.
If there is something I can put in which other authors use as a matter of course, I would like to use that for less confusion. For example, should I draw a vertical line at category K, to highlight that cutoff point?
I am thumbing through Tufte's books for inspiration, so there's no need to point me there unless there's a specific book and page number that you think meets the criteria for a demonstrative example.
: I would greatly prefer specifics and pointers to figures in journal articles or textbooks, etc. as examples, as opposed to generalities. (I am not
looking for philosophical approaches to visualization, so much as concrete examples of this problem being solved elsewhere.)
In particular, if you have examples which communicate the same dimensions of data results which are not line graphs, but are a different design that is clearer, more efficient and more elegant, I would be grateful for that kind of inspiration.