What is the primary function of the depth value in a circle pack visualization?

In a circle pack visualization, the depth value plays a significant role in managing hierarchical data by indicating the levels of detail for different clusters of data points. Specifically, the depth value helps to reveal more sub-clusters within the main clusters, allowing users to drill down into the data's structure. This ability to visualize sub-clusters is crucial for understanding complex datasets, as it provides insight into how data points relate to one another at various levels.

For instance, as one navigates through the visualization, the depth value can determine which sub-clusters are displayed, effectively highlighting relationships and hierarchies that are essential for data analysis. By utilizing the depth value in this way, users can focus on specific portions of data or explore broader trends, enhancing their overall comprehension of the dataset.

The other options do not align with the primary function of the depth value in this context, as they pertain to different aspects of data processing and visualization rather than its main purpose in revealing structural hierarchy through sub-clusters.