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35 Python scripts generated for fan chart this week

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.

Example Visualization

Fan chart with a solid central forecast line and nested shaded bands at 50, 80, and 95 percent prediction intervals fanning outward into the future

Create This Chart Now

Generate publication-ready fan charts with AI in seconds. No coding required – just describe your data and let AI do the work.

View example prompt
Example AI Prompt

"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."

How to create this chart in 30 seconds

1

Upload Data

Drag & drop your Excel or CSV file. Plotivy securely processes it in your browser.

2

AI Generation

Our AI analyzes your data and generates the Fan Chart code automatically.

3

Customize & Export

Tweak the design with natural language, then export as high-res PNG, SVG or PDF.

Python Code Example

Loading code...

Console Output

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

Free Cheat Sheet

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.

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