Yep, it's a cold weekend here in Pittsburgh (as is typical for this time of year). But at first glance, that's not the story my brain receives from WTAE's wind chill trend display.
Typically, when I look at a column chart like this, I associate greater values with longer column lengths, and smaller values with shorter column lengths. My mind thinks that the longest column length corresponds with the greatest negative temperature. But that's not what I'm seeing here - I'm seeing the coldest wind chill temperatures associated with the shortest columns.
I do see the logic that is used here. The chart is in fact showing a "drop in wind chill temperatures". But I'd argue that the drop would be better displayed in reverse.
When we talk about wind chills, it's usually in the context of "degrees below zero". So why not use the "below zero" context to orient the display as below...
In my makeover, I've changed a couple things. First, I use a zero baseline and I extend my negative values downward. Now I can associate a greater negative value with a longer column length (and I can visually process this more efficiently). I'm also using a sequential color palette to associate colder wind chills with darker blue colors. Finally, I've omitted the value labels and instead use an x-axis and very light colored grid lines to tie the columns to their values.
The takeaway here is to use the context of your story to your advantage. When we're presenting negative values, they should usually be displayed below your zero baseline. And that is especially true when we're talking about wind chill temperatures that are "below zero".
