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I know dual-axes time series plots can be misleading. They're difficult to make in ggplot because Hadley Wickham believes they are fundamentally flawed. Others have concluded that they are ok sometimes, when axes are chosen so that the lines look as though they had been converted to indices first (even if they are given in their actual units). I'm wondering if this example is one in which dual-axes are justifiable.

This online tool is an example similar to what I want to create: https://carve.ornl.gov/visualize/ Measurements taken at the same point in time, from the same flight, are plotted over time. The user can select any two measurements to overlay, and the time matches up with a map showing flight coordinates. I think this is an elegant way for users to interact with the data, and I can't really imagine an alternative that would convey the same information.

That being said, I am interested to hear other opinions. Will this type of plot draw vitriol from other data scientists?! Do you have other ideas? And, if you have recommendations for what R tools I should turn to (since ggplot might be off the table...), I would love to hear them (I will be using Shiny). Thanks!

Zoey RW
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The debate on multiple axis on a same cartesian plane is indeed a hot one. It reminds me of the endless debates around social science´s approaches. If you follow the orthodoxy of the Grammar of GraphicsG Gospel, then the graph you linked is flawed. To come back into the herd, you could simply map either the CO2 or the Altitude to a different plotted symbology, like the size of the dots or color. Or simply plot two different panels, aligned by the X scale. Now, the Grammar of Graphic people have much fewer problems with multiple scales on the plotted scales than on the cartesian scales. Yet, I think that methodological opportunism is preferable to methodological orthodoxy. Do whatever is easier for you to communicate the idea to the public.

Nicolás Velasquez
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