This post follows a few others on the same topic:
Box plot has been an effective way to give us quick insights into the distribution of data. It is done by partitioning the data by quartile. Here we apply it to the visualization of the disease rate (cases/100,000 population) in California's counties.
So in the above chart, we can see that all the counties are colored by one of the 4 quartiles. We quickly get a sense of which county belongs to which quartile.
On the left, we have a box plot which shows the scale of the rate for each county, overlaid with a box plot.
And we have 3 filters: Disease, Year and Sex. Depending on these 3 variables, the distribution can be very different.
In another post, we will explain how it is done.
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