# Correlation heatmaps

CDP Data Visualization enables you to create *Correlation Heatmap*
visuals.

A correlation heatmap uses colored cells, typically in a monochromatic scale, to show a 2D correlation matrix (table) between two discrete dimensions or event types. The values of the first dimensions appear as rows of the table, while the values of the second dimension are represented by the columns of the table. The color value of the cells is proportional to the number of measurements that match the dimensional values. This enables you to quickly identify incidence patterns, and to recognize anomalies.

Correlation Heatmap visuals are similar to Chords because they both compare exactly two dimensions. Correlation heatmaps are ideal for comparing the measurement for each pair of dimension values.

The following steps demonstrate how to create a new correlation visual on a dataset
`SFPD Incidents`

, based on data previously imported into Arcadia from the
datafile sfpd_incidents.csv. [data source
`default.sfpd_incidents`

]. For an overview of shelves that specify this
visual, see Shelves for correlation heatmaps.