![]() ![]() The designer has to make choices about scales and this can have a big impact on the viewer.Here’s my attempt at a paraphrase of the case against dual axis charts: Hadley Wickham is famously opposed to dual axes and has made it difficult to use them in ggplot2 (I have to say, in the case of this example I agree with Professor Wickham’s comment “MY EYES. There are a lot of shorter pieces such as this one pouring scorn on the technique too. A nice piece by Keran Healy looks at a particular example and concludes that the dual axes encourage sloppy thinking with regard to time series causality. Stephen Few looks at the issue of dual axes plots in a well reasoned piece and concludes cautiously that they are never justified. colour code the axes to match the data series, using colours with equal chroma and luminance so they are perceptually equal.choose vertical scales that make the two series as comparable as possible, equivalent graphically to how they would be drawn it they were indexed rather than original values.For the record, my improvement steps were: ![]() The data come from the Reserve Bank of New Zealand, and my chart below is essentially a version of their graphic that I’ve enhanced to meet my own style requirements. But I’ve come to the surprising conclusion (surprising for me) that the arguments against them don’t stack up - at least not to the stage of justifying a blanket ban.īefore I go further, here’s my best example of one of these charts with real data, as a talking point. Looking down on dual axis time series charts is one of the things that mark one as a member of a serious data visualiser - after shaking our heads at pie charts, and cringing in horror at three-dimensional chart junk. I’ve been mulling over time series charts with two different y axes, which are widely deprecated in the world of people who see ourselves as professional data workers. ![]()
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