Comments on: Choropleth Maps – A Guide to Data Classification

By: Roman

Roman — Tue, 23 Nov 2021 06:29:45 +0000

Good examples and explanations. Is there a way to create bins that have equal variances? I guess conceptually it would be a bit of a mashup of the quantile and standard deviation methods. Would this method be useful for certain applications?

By: Sirpa

Sirpa — Fri, 14 Dec 2018 08:37:26 +0000

A clear quide and easy to follow.
One important thing this guide leaves completely out is this: to which class the limit value belongs to?
If the classification is for example
Class 1: 4 – 8
Class 2: 8 – 12
Class 3: 12 – 16
Class 4: 16 – 20
Class 5: 20 – 24
the label claims that value 8 for example belongs both to classes 1 and 2 and missleads the map reader.

By: Sanjita Dhingra

Sanjita Dhingra — Fri, 20 Apr 2018 04:14:19 +0000

Very useful, but didn’t understand the standard deviation part. How did you get stand deviation as 3.7? Please explain.

By: Jocelino Júnior

Jocelino Júnior — Mon, 30 Oct 2017 12:23:02 +0000

Great article! Very clear and useful explanations on how to use data classification methods when making choropleths maps and other data-based works. Thank you!

By: jusTodd

jusTodd — Wed, 30 Aug 2017 13:56:26 +0000

Interesting, but the piece fails to discuss a very important point in classification schemes. From a user perspective, it is always important to remember to classify in a clearly understood format. Use of meaningless percentages have relatively little impact. 13%, 68%, 91% make no statement to the common reader. Conversely, 25%, 50%, 75% are immediately recognized by most individuals and stand out and make a statement.

By: Nick

Nick — Sun, 06 Aug 2017 06:55:08 +0000

On choropleth key, please put the highest values at the top not the bottom. Also, next to each class value put the number of items in each class (n=) so the reader can see the distribution of the data.