Tornado Chart
Chart overview
Tornado charts display the sensitivity of a model output to variation in each input parameter as horizontal diverging bars centered on the base-case value, sorted from widest to narrowest.
Key points
- Health economists, pharmacometricians, and decision analysts use tornado diagrams to identify the most influential variables in cost-effectiveness and risk models, guiding where to focus data collection efforts.
- They are a required component of health technology assessment submissions.
Python Tutorial
How to create a tornado 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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View example prompt
"Create a tornado chart from my data. Plot horizontal diverging bars centered at the base-case output value showing the low and high estimate for each parameter. Sort bars from widest at the top to narrowest at the bottom. Label each bar with the parameter name on the left y-axis. Add a vertical dashed line at the base-case value. Use journal formatting with Arial font and no top or right spines."
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Python Code Example
Console Output
Figure saved: plotivy-tornado-chart.png
Common Use Cases
- 1Identifying dominant drivers of uncertainty in cost-effectiveness models for health technology assessment
- 2Guiding data collection priorities in early-phase drug development decision models
- 3Communicating risk factor impact in environmental health impact assessment reports
- 4Presenting deterministic sensitivity analysis results in pharmacoeconomic manuscripts
Pro Tips
Center all bars on the base-case estimate and use diverging colors to show direction of impact
Sort parameters strictly by bar total width to maintain the defining tornado shape
Truncate parameter names consistently and add a footnote table if abbreviations are used
Overlay a shaded reference band around the base case value to visually anchor the diverging bars
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 tornado-chart.
numpy
Useful in specialized workflows that complement core Python plotting libraries for tornado-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.