feat(altair): implement histogram-density

[github-actions]

Implementation: histogram-density - altair

Implements the altair version of histogram-density.

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

---

🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a density histogram with blue rectangular bars (#306998 color with darker blue stroke) showing the distribution of reaction times in milliseconds. The x-axis is labeled "Reaction Time (ms)" ranging from approximately 100 to 540, and the y-axis shows "Density (probability per ms)" ranging from 0 to 0.0120. A yellow KDE (kernel density estimate) line (#FFD43B) smoothly overlays the histogram bars, clearly showing a bimodal distribution with a primary peak around 250ms and a secondary smaller peak around 380ms. The title "histogram-density · altair · pyplots.ai" appears at the top center. The plot has a clean white background with subtle gray gridlines.

Quality Score: 93/100

Criteria Checklist

Visual Quality (37/40 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, clean layout
• VQ-03: Element Visibility (7/8) - Bars have good visibility with stroke outlines; KDE line is prominent with 4px width
• VQ-04: Color Accessibility (5/5) - Blue bars and yellow line provide excellent contrast, colorblind-safe
• VQ-05: Layout Balance (4/5) - Good canvas utilization, plot fills majority of space; minor: left margin slightly wider than necessary
• VQ-06: Axis Labels (2/2) - Descriptive with units: "Reaction Time (ms)" and "Density (probability per ms)"
• VQ-07: Grid & Legend (1/2) - Grid is subtle (alpha 0.3), but no legend for KDE line

Spec Compliance (24/25 pts)

• SC-01: Plot Type (8/8) - Correct density histogram with normalized y-axis
• SC-02: Data Mapping (5/5) - X correctly shows continuous variable, Y shows density
• SC-03: Required Features (5/5) - Density normalization present, KDE overlay added as per spec suggestion
• SC-04: Data Range (3/3) - All data visible, appropriate axis scaling
• SC-05: Legend Accuracy (1/2) - No legend for KDE line to identify what the yellow line represents
• SC-06: Title Format (2/2) - Correct format: "histogram-density · altair · pyplots.ai"

Data Quality (19/20 pts)

• DQ-01: Feature Coverage (7/8) - Bimodal distribution excellently demonstrates density histogram; shows both peaks clearly
• DQ-02: Realistic Context (7/7) - Reaction times from baseline vs fatigued conditions - realistic cognitive psychology scenario
• DQ-03: Appropriate Scale (5/5) - 250ms and 380ms reaction times are realistic for cognitive tasks

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Imports → Data → Plot → Save structure maintained
• CQ-02: Reproducibility (3/3) - np.random.seed(42) is set
• CQ-03: Clean Imports (2/2) - All imports used (altair, numpy, pandas, scipy.stats)
• 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) - Uses mark_rect for histogram bars, layered chart composition, tooltips enabled; could have used alt.Chart().transform_density() for more idiomatic Altair

Strengths

• Excellent bimodal distribution demonstrates density histogram features very effectively
• Clean visual design with proper color contrast between histogram bars and KDE overlay
• Proper density normalization with clear axis labeling including units
• Interactive tooltips provide additional value for exploration
• Realistic cognitive psychology scenario with plausible reaction time values

Weaknesses

• Missing legend to identify the KDE line (yellow line has no label)
• Could use Altair's built-in transform_density() instead of scipy for more idiomatic implementation

Verdict: APPROVED