Hat Graph by iFour

The Hat Graph is a custom visual designed to compare values across categories and groups. It is ideal for scenarios where you want to analyze the performance or metrics of multiple categories (e.g., players, products, or teams) within specific groups (e.g., games, regions, or time intervals). The visual uses vertical bars with caps to highlight thresholds or baselines, simplifying comparisons

Types of users:

1) Data Analysts
2) Business Intelligence Developers
3) Financial Analysts
4) Power BI developers

Best Practices for Using Hat Graph

Highlight Comparisons Across Categories: Hat Graphs are ideal for comparing values across categories within specific groups, such as how different players, products, or regions perform within games, periods, or locations. Use Hat Graphs to emphasize relative differences and thresholds rather than absolute values.

Focus on Key Groups: To maintain clarity and readability, limit the number of categories displayed per group. Too many bars can make comparisons difficult.

Interactive Tooltips for Better Context: Enhance insights by including tooltips that provide detailed information for each bar, such as category name, value, and comparisons to thresholds or baselines. For example, hovering over a bar can display metrics like performance scores, group details, or comparisons to benchmarks.

When to use Hat Graph?

Hat Graphs are particularly effective for comparing values across categories within grouped contexts. Here are some scenarios where Hat Graphs are most beneficial:

Comparing Performance Across Groups: Use Hat Graphs to analyze how different entities (such as players, products, or teams) perform within specific groups, like games, regions, or time periods. This is useful for highlighting differences and identifying patterns within each group.

Visualizing Thresholds or Benchmarks: Hat Graphs are ideal when you want to showcase comparisons relative to a baseline or threshold, such as sales targets, scores, or quotas. The "caps" on the bars make it easy to identify which categories exceed or fall short of the benchmark.