✦ Dive Deeper
How to Read a Dive Deeper Trend Chart
When a story involves real numbers tracked over time or compared across categories, Dive Deeper generates a chart directly from the reported figures.
By Headlinne Editorial Team · Updated on
Two chart types, chosen automatically
A line chart is used when a number changes over time — a price, a count, a percentage tracked across dates. A bar chart is used instead when the comparison is across categories rather than time, like different regions or groups.
Every point is a real reported figure
Nothing on the chart is estimated or interpolated — each plotted point corresponds to a specific number that actually appeared in a cited source, matching the figures in the statistics section of the report.
Simple by design
The chart favors clarity over density — clean axes, a legend when more than one series is shown, and enough labeling to understand the numbers at a glance without needing to zoom or interact.
Absent without real numbers
If a story does not include at least a couple of genuinely comparable reported figures, no chart is generated — a single isolated statistic is shown as text instead, not forced into a chart with only one data point.
Key takeaways
- ✓Line charts show a number over time; bar charts show a comparison across categories.
- ✓Every plotted point is a real figure from a cited source, matching the statistics section.
- ✓A chart only appears when there are enough genuinely comparable reported numbers.
Frequently asked questions
Does Dive Deeper ever combine numbers from different sources into one chart?
Yes, when they measure the same thing — for example tracking one figure across several reports over time — but each point still traces back to the specific source that reported it.
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How Dive Deeper Surfaces Statistics and Supporting Evidence
Numbers matter, and Dive Deeper only shows the ones its sources actually reported. Here is how the statistics section works.
When Dive Deeper Shows a Chart vs. a Timeline vs. a Map
Dive Deeper picks each visualization based on what the underlying data actually looks like. Here is the logic behind those choices.
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