Chart Selection Tool
Match the analytical question and data structure to an effective visualization, then see why alternative chart types are stronger or weaker.
Choose the chart that best answers the question—not the chart that looks most decorative.
This tool recommends visualization types using analytical purpose, data structure, category count, label length, time horizon, composition structure and precision needs.
Chart Selection Tool — Step by Step
Eight locked stages move from analytical purpose through data structure, comparison, trend, composition, distribution, relationships, a constraint challenge and management review.
Chart Recommendation and Visual Preview
Reveal the recommendation context to begin.
Understand why the recommendation changes.
Build Your Own Chart-Selection Scenario
Experiment Mode is isolated from the guided demonstration. Change the analytical purpose and constraints without changing guided progress.
Test chart-selection judgement.
Chart-selection cues
Comparison
Use bars or dots for categories. Prefer horizontal bars when there are many categories or long labels.
Trend
Use lines for ordered time-series movement. Columns can work for a small number of discrete periods.
Composition
Use pie only for a few parts of one meaningful whole. Use stacked bars when comparing composition across groups.
Distribution
Use histograms for shape, box plots for compact robust summaries and dot plots for manageable individual observations.
Relationship
Use scatter plots for paired numeric variables. Add trend or reference lines only when they support the analytical question.
Uncertainty
Use interval or error-bar charts when the uncertainty around estimates is itself a decision-relevant message.
Use the simplest chart that preserves the comparison, trend, composition, distribution, relationship or uncertainty the user actually needs to understand.