feat(altair): implement histogram-stacked

[github-actions]

Implementation: histogram-stacked - altair

Implements the altair version of histogram-stacked.

File: plots/histogram-stacked/implementations/altair.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a stacked histogram showing test score distributions for three study methods. The X-axis shows "Test Score (points)" ranging from 40 to 100, and the Y-axis shows "Number of Students" ranging from 0 to 80. Three groups are stacked: Traditional Study (blue, #306998), Active Recall (yellow, #FFD43B), and Passive Reading (orange, #E67E22). The stacking clearly shows individual group contributions with total bar heights representing combined frequencies. The title "histogram-stacked · altair · pyplots.ai" appears at the top. A legend on the right identifies each study method. The grid uses subtle dashed lines with low opacity.

Quality Score: 92/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (10/10) - Title at 28pt, axis labels at 22pt, tick labels at 18pt - all perfectly readable
• VQ-02: No Overlap (8/8) - No overlapping text elements anywhere
• VQ-03: Element Visibility (8/8) - Bars are well-sized with good opacity (0.85), white stroke separates segments nicely
• VQ-04: Color Accessibility (4/5) - Blue, yellow, orange palette is colorblind-friendly (no red-green issues), though could be slightly more distinct
• VQ-05: Layout Balance (4/5) - Good use of canvas space, plot fills ~60% of canvas, balanced margins
• VQ-06: Axis Labels (2/2) - Descriptive with units: "Test Score (points)", "Number of Students"
• VQ-07: Grid & Legend (0/2) - Grid is subtle (alpha 0.3, dashed), but legend title font could better match overall styling

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct stacked histogram implementation
• SC-02: Data Mapping (5/5) - Continuous variable (Score) binned on X, count on Y, category for color
• SC-03: Required Features (5/5) - All spec features present: stacking, distinct colors, legend with group labels
• SC-04: Data Range (3/3) - All data visible, appropriate bin boundaries (40-100)
• SC-05: Legend Accuracy (2/2) - Legend labels match data groups correctly
• SC-06: Title Format (2/2) - Correct format: "histogram-stacked · altair · pyplots.ai"

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows three distinct distributions with different means and spreads, demonstrates stacking well
• DQ-02: Realistic Context (7/7) - Educational test scores with study methods is a neutral, relatable scenario
• DQ-03: Appropriate Scale (4/5) - Test scores 0-100 are realistic; distributions centered around 68-78 are plausible

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Clean imports → data → plot → save structure, no functions/classes
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42)
• CQ-03: Clean Imports (2/2) - Only necessary imports (altair, numpy, pandas)
• CQ-04: No Deprecated API (1/1) - Uses current Altair API
• CQ-05: Output Correct (1/1) - Saves as plot.png and plot.html

Library Features (3/5 pts)

• LF-01: Uses distinctive library features (3/5) - Good use of declarative encoding with alt.X, alt.Y, alt.Color, binning, and stack configuration, but could leverage more Altair-specific features like tooltips or selection

Strengths

• Excellent declarative encoding with proper use of Altair grammar (alt.X with bin, alt.Y with stack="zero", alt.Color with custom scale)
• Clean, readable code following KISS principles with good data generation
• Proper font sizing throughout (title 28pt, axis titles 22pt, labels 18pt, legend 16-18pt)
• Good color palette choice (blue, yellow, orange) that avoids colorblind issues
• White stroke between bar segments (strokeWidth=0.5) enhances visual separation
• Appropriate use of scale_factor=3.0 for high-resolution output
• Both PNG and HTML outputs generated for static and interactive viewing

Weaknesses

• Legend styling could be more polished (title and label fonts could be slightly larger for better visual hierarchy)
• Could add tooltips for interactive exploration showing exact counts per bin
• The order parameter could be more intentionally designed to show a specific visual story (e.g., ordering by mean score)

Verdict: APPROVED