A truly remarkable example of misleading data visualization from the Georgia department of public health.
In our book we suggest that one never assume malice when incompetence is a sufficient explanation, and one never assume incompetence when an understandable mistake could be the cause.
Can we apply that here?
Can we apply that here?
I bet we can.
A lot of cartographic software will choose bins automatically based on ranges. For example, these might be the 0-20%, 20-40%, 40-60%, 60-80%, and 80-100% bins.
As the upper bound changes over time, the scale slides much as we see here.
A lot of cartographic software will choose bins automatically based on ranges. For example, these might be the 0-20%, 20-40%, 40-60%, 60-80%, and 80-100% bins.
As the upper bound changes over time, the scale slides much as we see here.
To be clear, it's still bullshit no matter which way you slice it!
Assuming this is not deliberate, it seems to me that the real problem is that the data have temporal structure, but the data design does not take this structure into account.
