Case 3.

Conditional
Mark Labels

Conditional mark labels eliminate "visual noise" on visualizations. The conditions of labeling can be completely different. For example, to label only non-repeating values, every third mark, only those bars in which there is a specific dimension division, and so on.

How do conditional mark labels help?

  • Conditional mark labels are a helpful tool in data visualization. They allow users to quickly and easily identify the meaning of each mark on a chart or graph.
  • Conditional mark labels allow data points to be identified without reading long text descriptions or charts. It makes data easier to understand and enables users to identify trends and patterns quickly. For example, mark labels can be used in a scatter plot to identify points with different colors, sizes, or shapes. It helps users quickly identify data patterns, clusters, and trends.

  • In addition, conditional mark labels make data more accessible and understandable to a broader audience. By providing labels to each mark, users can quickly identify which data point they are looking at, thus making data more accessible to those who may not be familiar with the data.

How to implement conditional mark labels

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