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spec: add errorbar-asymmetric specification
Created from issue #2781
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# errorbar-asymmetric: Asymmetric Error Bars Plot
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## Description
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An asymmetric error bar plot displays data points with separate upper and lower error magnitudes, allowing different-sized bars extending above and below each point. This visualization is essential for representing skewed distributions, non-symmetric confidence intervals, or data where uncertainty differs in positive and negative directions. Common applications include percentile-based intervals, log-transformed data, and Bayesian credible intervals.
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## Applications
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- Scientific research presenting results with non-symmetric confidence intervals (e.g., 5th-95th percentile)
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- Financial forecasting showing different upside and downside risk projections
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- Clinical trials displaying treatment effects with asymmetric uncertainty bounds
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- Environmental monitoring reporting measurements with different detection limits above and below
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## Data
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- `x` (categorical or numeric) - Categories or positions on the x-axis
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- `y` (numeric) - Central values representing mean, median, or point estimates
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- `error_lower` (numeric) - Error magnitude extending below each point
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- `error_upper` (numeric) - Error magnitude extending above each point
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- Size: 3-20 data points for clarity
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## Notes
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- Error bars should have visible caps (horizontal lines at ends) to clearly mark the error range
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- Consider using different colors or markers when comparing multiple series
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- Include a legend or annotation explaining what the asymmetric bounds represent (e.g., "10th-90th percentile", "95% CI")
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- Useful for log-scale axes where symmetric intervals would appear asymmetric after transformation
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# Specification-level metadata for errorbar-asymmetric
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# Auto-synced to PostgreSQL on push to main
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spec_id: errorbar-asymmetric
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title: Asymmetric Error Bars Plot
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# Specification tracking
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created: 2025-12-30T17:27:52Z
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updated: null
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issue: 2781
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suggested: MarkusNeusinger
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# Classification tags (applies to all library implementations)
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# See docs/concepts/tagging-system.md for detailed guidelines
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tags:
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plot_type:
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- errorbar
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- point
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data_type:
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- numeric
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- categorical
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domain:
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- general
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- statistics
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- science
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features:
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- asymmetric
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- uncertainty
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- confidence-interval

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