Equal interval classification
A way to group data into classes for a map by splitting the range of values into steps of the same size, whatever the number of features in each.
Equal interval classification takes the range of values, from the lowest to the highest, and cuts it into steps of the same width. With values from 0 to 100 and five classes, the breaks fall at 20, 40, 60 and 80. Each class covers the same span of values, however many features end up in it.
That makes the classes easy to read. A legend that says 40 to 60 means the same thing on every map that uses it, so equal intervals suit values with a familiar range, such as percentages, shares or temperatures.
| Class | Range | Districts | Values |
|---|---|---|---|
| 1 | 0 to 20 % | 1 | 18 |
| 2 | 20 to 40 % | 1 | 34 |
| 3 | 40 to 60 % | 4 | 41, 47, 52, 58 |
| 4 | 60 to 80 % | 4 | 63, 66, 71, 79 |
| 5 | 80 to 100 % | 2 | 85, 92 |
Here the classes are uneven in size, and that is the information: most districts sit in the middle, and the two weakest stand out.
The method fails when a few values are far from the rest. One very high value stretches the range, and most features fall into the lowest class while the upper classes stay nearly empty. The quantile classification page shows this with the same ten values in both methods. For data like that, quantile or heads and tails classification usually gives a more useful map. In GOAT, equal interval is one of six methods in attribute-based styling, with seven classes by default.