Re: [R] Thinking about using two y-scales on your plot?

From: Tribo Laboy <>
Date: Fri, 04 Apr 2008 15:57:34 +0900


It always nice to follow these discussions. There's always so much to learn. I can't disagree with most of the article that Hadley pointed us to, but still I can see value in double y-axis plots. I even remember using one a few years ago. What was said about the temperature in Celsius and in Fahrenheit seems to hit the nail on the head. And also having the temperature expressed as a percentage doesn't make much sense as Martin pointed. Just to give you another example of the very rigorously mathematically treated and correct data that makes a point but obscures some commonly sensible information is this plot of recent currency fluctuations:

It shows exactly in percentage how much has the Euro and Japanese Yen become more expensive with regard to the USD in the past 91 days, but one is left none the wiser about the initial price, end price or some extreme prices in the middle. It really depends on what message one wants to convey with the graph or what data he is looking for. I personally would prefer the above graph in a double-y axis format to be able to see (easily) some co-movement and the actual prices. Then, again, I am no quantitative analyst and the financial professionals on this list would probably scream at my suggestion.

I think it is important to have freedom to choose the most appropriate visual presentation of the data, according to the author's purpose and I hope these discussions are more educational that having to do with actual implementation of features in R Graphics or in R Graphics packages (cough cough).



On Fri, Mar 28, 2008 at 2:31 AM, Martin Rittner <> wrote:
> Hello all,
> I know I'm not making friends with this, but: I absolutely see the point
> in dual-(or more!)-y-axis plots! I find them quite informative, and I
> see them often. In Earth-Sciences (and I very generously include
> atmospheric sciences here, as Johannes has given an example of a
> meteorological plot...) very often time-series plots of some values are
> given rather to show the temporal correlation of these, than to show the
> actual numerical values! The same applies for plots of some sample
> values over distance (eg. element concentration over a sample or
> investigation area). In this case one is more interested in whether some
> values change simultaneously, than what the actual values at every point
> are.
> In the mentioned plot (see link below), the temporal evolution of the
> mean temperature and of the precipitation over a year is the important
> information. No-one would get confused or yield wrong conclusions, if
> the curves would intersect somewhere else, only because of a shift of
> one y-axis relative to the other!? (which was proposed to be one of the
> great dangers of dual-scaled axes in the article Hadley posted)
> On the other hand, you would never express temperature in terms of a
> percentage of some arbitrary start value, if you could give it just in
> plain °C!? (as was proposed as a workaround in the article mentioned) An
> awkward scale like this makes the actual graph much harder to read, not
> easier, as proposed. Furthermore, since the observed values in Earth
> Sciences often show a cyclic behavior, the graphs would still cross each
> other over and over again, no matter what the scale was.
> So my conclusion for now: I'd answer the Question "are dual-scaled axes
> in graphs ever the best solution?" with a definitive YES. Maybe only in
> some specialized applications, but - yes. I strongly expect this
> discussion to go on (as I've read frequently here that these kind of
> graphs are considered very "inappropriate"..) and I am happy to learn to
> do better graphs, if you can show me to be wrong...
> Greetings,
> Martin
> Johannes Hüsing wrote:
> > I wonder how long it will take until metereologists will see the light.
> >
> >
> >
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> mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Fri 04 Apr 2008 - 07:02:23 GMT

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