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I have been reading multiple (20+) physics research articles on related topics, which use different visualizations for the same thing. I want to state that a certain visualization is used less often than others, but how do I cite this information?

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how do I cite this information?

Cite? Isn't it your own observation? If someone else has made the same observation, you can cite them in the standard way, of course. If not, just make the claim and present the evidence for it. This might take the form of citing the various papers on the topic and categorizing them according to the type of visualizations they use. To produce convincing statistics, you may want to follow strategies for systematic reviews and use well-defined inclusion criteria for the papers you consider. Note that it's certainly OK to cite 20+ papers for background, but when you get to large enough numbers (e.g. several hundreds or more) it may be more appropriate to describe in detail the database search terms instead of listing all papers explicitly.

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Create a data table from these papers and use it as supplementary material

It sounds like you are in a situation where the academic papers at issue are data-points for your own observation and analysis, rather than contextual academic literature for your work. In such a case I think it would be reasonable to proceed without citing these papers. However, you should still use good data analytics practices by keeping a clear record of your data and analysis, and including this as supplementary material for your paper.

One way you could go about this is to create a detailed data table containing all the visualisations for each paper with a set of variables that give extensive information on the visualisations in the papers. There should be enough reference information in the table to clearly identify the papers at issue, so you should have one or more variables that give the authors, paper name, journal, etc. (ideally, this would effectively amount to full reference information). You would also have variables giving information about the visualisations that are present in the paper, in whatever you think is the most helpful form. Once you have created this data table, you should then be able to make the subsequent calculations of how often each different type of visualisation appears. As good data analytics practice, there should be a reproducible analysis of this (e.g., computation script that imports the data table and then computes the output metrics) and it should also be included in your supplementary materials.

(One more tip: When creating your data table in this case, be really detailed to aid any reader that wants to check your data. The best way would be to ensure that for each visualisation you identify and classify in the paper, you give the page number where it appears in the paper. This will make it easy for anyone to check your data for errors.)

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