[errorbar-basic] Basic Error Bar Plot

[MarkusNeusinger]

Description

An error bar plot displays data points with associated uncertainty or variability represented by bars extending above and below (or left and right of) each point. Error bars commonly represent standard deviation, standard error, confidence intervals, or min/max ranges.

Key Features

• Central point or bar showing mean/median value
• Error bars showing uncertainty range
• Can be combined with bar charts, line charts, or scatter plots
• Asymmetric error bars supported for non-symmetric distributions

Applications

• Scientific research showing measurement uncertainty
• Statistical analysis displaying confidence intervals
• Quality control showing acceptable tolerance ranges
• Comparing group means with variability

Data Requirements

• x (categorical or numeric) - Categories or positions
• y (numeric) - Central values (mean, median)
• error (numeric) - Error magnitude (can be symmetric or asymmetric)
• Size: Any number of groups/points

Visual Elements

• Markers or bars for central tendency
• Vertical or horizontal error bars with caps
• Clear distinction between error bars and data markers
• Optional: different colors for groups

[claude]

✅ Spec ID: errorbar-basic

Rationale: Error bar plots are a fundamental statistical visualization type not yet in the collection. The ID follows the standard format with "errorbar" as the plot type and "basic" as the variant.

No duplicates found - this is a new plot type distinct from existing specs.

[github-actions]

✅ Specification Ready: errorbar-basic

PR: #983

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specification.md

errorbar-basic: Basic Error Bar Plot

Description

An error bar plot displays data points with associated uncertainty or variability represented by bars extending above and below (or left and right of) each point. Error bars commonly represent standard deviation, standard error, confidence intervals, or min/max ranges. This visualization is essential for communicating the reliability and precision of measurements or statistical estimates.

Applications

• Scientific research presenting experimental results with measurement uncertainty
• Statistical analysis comparing group means with confidence intervals
• Quality control monitoring showing acceptable tolerance ranges around targets
• Clinical trials displaying treatment effects with error margins

Data

• x (categorical or numeric) - Categories or positions on the x-axis
• y (numeric) - Central values representing mean, median, or measured values
• error (numeric) - Error magnitude for symmetric error bars, or tuple/pair for asymmetric errors
• Size: 3-20 groups/points for clarity

Notes

• Error bars should have visible caps (horizontal lines at ends) to clearly mark the error range
• Use consistent error bar widths across all data points
• Consider using different colors to distinguish between groups when comparing multiple series
• Asymmetric error bars may be needed for skewed distributions or log-transformed data

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Next: Add approved label to merge this specification to main.

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