What is a heatmap used for in data visualization?

A heatmap is a powerful tool in data visualization used to display data values in a matrix format where colors represent different magnitudes or values. This allows for a quick visual interpretation of complex data sets. Each cell in a heatmap corresponds to a specific data point, and the color intensity or hue signifies the value of that point, making it easy to identify patterns, trends, or anomalies.

Heatmaps are particularly useful in scenarios such as showing correlations between variables, visualizing frequency distributions, or even representing data in relation to geographical areas. By using color gradients to depict variations in data, heatmaps facilitate easier comprehension of otherwise dense information, enabling better insights at a glance.

In contrast, a three-dimensional model may clutter the perception of data without allowing for the same level of straightforward interpretation that a heatmap provides. Interactive dashboards focus on real-time tracking and may use multiple visualization methods but do not specifically embody the essence of how heatmaps operate. Condensing data into summary statistics serves a different purpose by simplifying the data rather than visualizing the distribution and relationships across multiple variables simultaneously. Therefore, the use of colors in a matrix format uniquely identifies heatmaps' primary function in data visualization.