Data-driven styles answer questions about your data, such as Where? What? How much? When? or a combination of those questions. A layer's style is configured with its renderer.
A renderer defines how symbols are applied to each feature. In the case of a data-driven visualization, the symbol is always determined based on data (or an attribute value) returned from one of two data sources:
- Field value (and optional normalization field) - Field values are typically referenced using a field or column name from a layer, a table, or a service.
- Arcade expression - An expression evaluating to a number or text value. Arcade expressions are typically referenced as a string in the
valueproperty of a renderer or visual variable.
The renderer will match the values returned from these sources to a predefined symbol used to represent each feature, or use the data value to override one of the symbol's properties, such as size or color.
Learn how to visualize data by categories.
Learn how to classify data by discrete numeric ranges.
Learn how to communicate potential relationships between two or more data attributes using multiple visual variables.
Learn how to visualize dates as a timeline or an age relative to another date.
Learn how to visualize two or more data attributes with the same renderer.
Learn how to visualize the predominant value among a set of competing attributes (or subcategories).
Learn how to visualize the density of subcategories of a count or population.
Learn how to visualize the potential relationship between two numeric attributes using a blend of two color ramps.
Learn how to take advantage of Smart Mapping APIs to explore unfamiliar datasets.