What is the purpose of a heat map in data visualization?

A heat map is primarily used to depict values through varying colors, which makes it easier to identify patterns, trends, and anomalies within the data. By assigning different colors to different ranges of values, a heat map provides a visual representation that can reveal concentrated areas of activity, frequency of occurrence, or intensity of a variable across a dataset.

This capability is crucial in many analytical contexts, as it allows quick assessment and comparison of data at a glance. For instance, in a business setting, a heat map can help visualize customer behavior or sales performance over time and by region, making it easier to draw insights and make informed decisions.

The other options do not quite capture the unique functionality and visual methodology of heat maps. While they pertain to essential data visualization aspects, they do not specifically encompass the primary focus on color gradation for representing value intensity. Therefore, the correct understanding of the function of a heat map aligns well with its role in depicting values with varying colors to aid in pattern identification.