Classifying Data
Classify quantitative data to explore and communicate spatial patterns.
How you classify quantitative data is key to effectively identifying and communicating spatial patterns. UrbanFootprint allows you to work with standard classification methods — equal interval, logarithmic, natural breaks, and quantiles — or manually classify your data using the Classes control of the Symbology Editor.
This article covers the classification methods used, and details the steps of how to classify numeric data.

Classification Methods

You can select from the equal interval, logarithmic, natural breaks, and quantile methods. All methods can include 3 to 12 classes.
Equal Interval. Equal interval classes are of equal size, suitable for representing familiar data ranges, or data that is distributed across a linear range without many outliers.
Logarithmic. Logarithmic classes are based on orders of magnitude, suitable for representing data that skews towards large values.
Natural Breaks. Natural breaks classes minimize variance within classes, and maximize difference between classes. Natural breaks classification is best applied to understand individual datasets, and is generally not suitable for comparing data between maps.
Quantiles. Quantile classes contain the same number of features per class, suitable for representing data that is distributed across a linear range.

How to Classify Numeric Data

To classify data for a numeric column:
1. Click on the layer in the Layers list to activate it. The Layer Details pane will expand.
2. Select the column that you want to classify and symbolize by selecting it from the Column list. The column must contain data in numeric format in order to be classified.
3. Click Edit symbology. The symbology editor controls appear in the Layer Details pane. The options vary depending on feature type (point, line, or polygon) and the data type of the column you selected.
4. Select a data classification method from the list in the Classes control. Options include Default, Natural Breaks, Equal Interval, Logarithmic, and Quantiles (see the previous section for definitions). Default refers to classification schemes that have been defined by UrbanFootprint as defaults for reference data or analysis module output layers; not all layers of these types will have Default classification settings.
Numeric data classes
5. Select the number of classes you would like to use from the list to the right of the classification method list. You can include from 3 to 12 classes. The map will be updated dynamically as you adjust classes, so you can actively explore your data. Use the classification controls to try different classification methods, numbers of classes, and class colors.
Classification settings, along with all other symbology options, must be saved before you navigate away. Remember this if you are comparing mapped data across multiple scenarios or layers.
6. To edit class bounds, click the Edit icon
. The Edit class bounds window appears. You can edit the lower and/or upper bounds of a class. The bounds of adjacent classes will be adjusted automatically to eliminate gaps between classes. Editing class bounds puts you into Custom classification mode. You can add or delete classes to manually define specific class ranges.
Editing class bounds
7. To delete a class, click the trash icon
. The class will be deleted and the bounds of an adjacent class (the next higher class if there is one, or the next lowest class if you are deleting the highest class) will be adjusted automatically to eliminate gaps between classes.
Deleting a class also puts you into Custom classification mode. If you select another classification method from the menu, the classes will be reset and your manual settings will be lost.
8. To add a class, click the class number. The Add new class window will appear. You can add classes if you have previously edited class bounds or deleted a class. The bounds of existing classes will be adjusted automatically to accommodate the new class. You will receive warnings if the bounds of the new class eliminates existing classes (by completely overlapping them) or are otherwise invalid.
Adding a new class
9. To restore classes to their default values (if applicable), click Restore Defaults. Class values will be reset.
Selecting a classification method from the menu at any point automatically resets the classes and overrides manual settings.
10. Use the Render 0-value as transparent toggle to show or hide zero values.
11. To save your classes, click Save. If you navigate away from the Symbology Editor without saving, your settings will be lost.
12. Style your data as needed. You can apply color ramps to your data classes, and/or manually select colors for individual classes. See Styling Point Data, Styling Line Data, and Styling Polygon Data for guidance on setting color, stroke, and opacity.
13. To save your symbology settings for the layer, click Save. Alternatively, you can discard your edits by clicking Discard.
Remember that all symbology settings, including data classes, are linked to individual users.

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