Fan Chart
Chart overview
A fan chart overlays multiple nested confidence or prediction intervals around a forecast trajectory, with progressively lighter shading at wider probability levels, creating a fan-like shape that widens with forecast horizon.
Key points
- Climate scientists, epidemiologists, and economists use it to communicate both the central projection and the growing uncertainty of model-based forecasts.
- It is more informative than a single confidence band because it conveys the full probability distribution of future outcomes.
Python Tutorial
How to create a fan chart in Python
Use the full tutorial for implementation details, troubleshooting, and chart variations in matplotlib, seaborn, and plotly.
How to Create a Bar Chart in PythonExample Visualization
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Generate publication-ready fan charts with AI in seconds. No coding required – just describe your data and let AI do the work.
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"Create a fan chart from my forecast data. Plot a solid central estimate line, shade nested prediction intervals at 50%, 80%, and 95% with progressively lighter fills, mark the forecast horizon with a vertical dashed line, and format as a publication-quality figure."
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Python Code Example
Console Output
Figure saved: plotivy-fan-chart.png
Common Use Cases
- 1Displaying ensemble climate model temperature projections with uncertainty bands
- 2Showing epidemiological disease incidence forecasts with credible intervals
- 3Communicating economic GDP growth projections from central bank models
- 4Presenting Bayesian pharmacokinetic model time-course predictions with posteriors
Pro Tips
Use at least three nested bands at distinct probability levels such as 50%, 80%, and 95%
Choose fill colours from a single hue at different opacities rather than multiple hues
Separate the historical observed period from the forecast period with a vertical dashed line
Include a clear legend mapping each shaded band to its probability level
Long-tail keyword opportunities
High-intent chart variations
Library comparison for this chart
matplotlib
Best when you need full control over axis formatting, annotation placement, and journal-specific styling for fan-chart.
numpy
Useful in specialized workflows that complement core Python plotting libraries for fan-chart analysis tasks.
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.