Visualize Skewed Geographical Data

Skewness can potentially distort everything you do with data:

• data analysis,

• data visualization, and

• modeling.

I recently wanted to visualize skewed geographical data, but visualization didn’t make any sense.

While I cannot share the data and the visualization because it is private, let me walk you through an inspiring example I found which helped me handle this problem.

But first, some context!

Log transform is commonly used to eliminate skewness in data.

For instance, applying a log transform to a right-skewed distribution creates a somewhat normal distribution.

There are some considerations though, which we covered here in this newsletter: A Misconception About Log Transform.

That said, we can leverage the same idea of log transform while visualizing data. I came across it in this blog by Databrewer: Methods to Visualize Data with Skewed Distribution.

To exemplify, consider we want to visualize the population density in Africa. With raw data, we hardly get to notice any insights here, as depicted below:

The reason is pretty obvious — the data is heavily skewed, as also visible in the color scale in the above plot.

Now consider visualizing log-transformed data, which is depicted below:

For instance, consider Egypt (top right side of Africa):

• Most of the area is greyed because the population density here is zero.

• You can also notice the Nile River in Egpyt, around which there’s a heavily dense region.

This time, it’s super clear, isn’t it?

Note that the color scale has changed in the new plot since we are visualizing log-transformed data.

I used the same method in my use case, resulting in much better visualization.

Here, I would highly recommend reading the blog by Databrewer: Methods to Visualize Data with Skewed Distribution.

While I covered only geographical data in this issue, the above blog covers more data types.

👉 Over to you: What techniques do you use to visualize skewed data?

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