Vox Charts: Handling Complex Data
Simple charts are easy. But the real world is messy. You often have hundreds of data points, multiple categories, and conflicting trends.
In this guide, we’ll explore how to use our Vox-Style Components to handle complex datasets while maintaining clarity and impact.
1. Dense Time Series
When you have a lot of data points (e.g., daily or monthly data over years), you can’t label every point. Our VoxLineChart now automatically handles label density.
The “Spaghetti” Chart (Tamed)
Visualizing three competing trends over a 20-point timeline. Notice how the direct labels eliminate the need for a mental lookup table (legend).
The Streaming Wars Subscription Growth
Millions of Subscribers (Simulated projection)
2. Deep Composition: Stacked Bars
Sometimes you need to show the breakdown of a total across many categories.
Global Energy Mix
A look at how energy sources evolve over decades. This uses the stackedData prop with 5 different segments.
Global Energy Consumption by Source
Transitioning to renewables (TWh)
3. Small Multiples
When comparing disparate regions or categories, putting them all on one chart can be confusing. “Small Multiples” is a technique where you repeat the same chart structure for different slices of data.
We can achieve this using a CSS Grid layout in MDX.
North America
GDP Growth %
Europe
GDP Growth %
Asia (Emerging)
GDP Growth %
4. Mixing Data Types
A powerful narrative device is to show the Total in one chart, and then the Breakdown in another.
The “Part-to-Whole” Story
Total Revenue
Steady growth year over year
2023 Revenue Split
Dominance of Digital Services
Conclusion
Complex data doesn’t have to look complex. By using smart labeling, grouping, stacking, and layout, you can tell sophisticated stories that remain accessible.
Vox-style charts excel here because their clean lines and direct labeling reduce the cognitive load on the reader, letting the data speak for itself.
