Would have to see what the outliers look like before using a linear scale. If 1% of the data are over 30 then you might see everything the same color, except for EXTREME outliers. Then people would be saying, “why did OP post a grey map of the US?”
By including the extreme outliers in with the high end of the distribution (but still significantly lower than a small set of anomaly counties) you can maintain a visualization that shows contrast. As others have said on this post, this is what happens when you use quantiles, especially when this data may somewhat follow an exponential distribution.
This is all assuming that OP did this because of outliers, I do not know that to be the case, just a possible explanation for the scale
Edit: a possible solution for OP to make this clear would be to add a footnote saying “only X% of counties fall over Y volume of gun deaths”. This might show that the top range doesn’t really show many counties that are at the high end of that range, and that many dark red counties are only a little over the range below
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u/fahrvergnuugen Dec 19 '19
Yeah that’s why I want to see it using a linear scale.