chore(altair): update quality score 90 and review feedback for heatmap-cohort-retention

Author: github-actions[bot]

plots/heatmap-cohort-retention/implementations/altair.py

@@ -1,7 +1,7 @@
-"""pyplots.ai
+""" pyplots.ai
 heatmap-cohort-retention: Cohort Retention Heatmap
 Library: altair 6.0.0 | Python 3.14.3
-Quality: 86/100 | Created: 2026-03-16
+Quality: 90/100 | Created: 2026-03-16
 """
 
 import altair as alt

plots/heatmap-cohort-retention/metadata/altair.yaml

@@ -1,7 +1,7 @@
 library: altair
 specification_id: heatmap-cohort-retention
 created: '2026-03-16T20:46:10Z'
-updated: '2026-03-16T20:50:10Z'
+updated: '2026-03-16T21:04:16Z'
 generated_by: claude-opus-4-5-20251101
 workflow_run: 23165007983
 issue: 4570
@@ -10,32 +10,33 @@ library_version: 6.0.0
 preview_url: https://storage.googleapis.com/pyplots-images/plots/heatmap-cohort-retention/altair/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/heatmap-cohort-retention/altair/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/heatmap-cohort-retention/altair/plot.html
-quality_score: 86
+quality_score: 90
 review:
   strengths:
-  - Perfect spec compliance — all required features implemented correctly (triangular
-    shape, cell annotations, cohort sizes, color bar)
-  - Excellent data quality with realistic SaaS retention patterns and plausible cohort
-    sizes
-  - Clean, idiomatic Altair code with good use of layer composition and conditional
-    encoding
-  - Smart conditional text coloring (white on dark, dark on light) for readability
+  - Custom 6-stop sequential palette with sophisticated color progression from light
+    to dark
+  - Separate % symbol layer at smaller font size adds typographic polish
+  - Informative subtitle that communicates the key data insight
+  - 'Expert-level Altair idioms: conditional text color, layer composition, declarative
+    encoding'
+  - Perfect spec compliance with all required features present
+  - Realistic SaaS retention data with plausible decay patterns
   weaknesses:
-  - Design excellence could be improved — the plot looks like a well-configured default
-    rather than publication-quality
-  - No visual emphasis or storytelling to highlight interesting patterns
-  - Y-axis label font size (15pt) is slightly small relative to other text elements
-  image_description: 'The plot displays a triangular cohort retention heatmap using
-    a blue sequential colormap. The title "heatmap-cohort-retention · altair · pyplots.ai"
-    is centered at the top in large font. The y-axis labeled "Signup Cohort" shows
-    10 cohorts from "Jan 2024 (n=1,926)" to "Oct 2024 (n=1,266)" with cohort sizes
-    in parentheses. The x-axis labeled "Months Since Signup" shows "Month 0" through
-    "Month 9". Each cell contains a retention percentage value displayed in bold text
-    — white text on darker (high-retention) cells and dark gray text on lighter (low-retention)
-    cells. The triangular shape is correct: Jan 2024 has all 10 periods while Oct
-    2024 has only Month 0. Cells are separated by white borders. A vertical color
-    bar legend on the right shows "Retention %" ranging from 0 to 100. Period 0 is
-    always 100% (darkest blue), with realistic decay patterns across subsequent months.'
+  - Chart width is 1400 instead of 1600, resulting in 4200px instead of the ideal
+    4800px output width
+  - The % suffix fontSize=10 (30px at 3x) is on the small side
+  image_description: The plot displays a triangular cohort retention heatmap with
+    10 monthly cohorts (Jan 2024 through Oct 2024) on the y-axis and months since
+    signup (Month 0 through Month 9) on the x-axis. The cells use a custom sequential
+    palette transitioning from light gray/white (low retention) through teals to dark
+    navy (high retention). Each cell contains a bold retention percentage with a smaller
+    "%" suffix. The triangular shape is correctly formed — Jan 2024 has all 10 periods
+    while Oct 2024 has only 1. Cohort sizes (e.g., n=1,926) appear in parentheses
+    next to each cohort label. A vertical color bar legend ("Retention %") is positioned
+    on the right. The title reads "heatmap-cohort-retention · altair · pyplots.ai"
+    with a subtitle "Monthly SaaS user retention — earliest cohorts show strongest
+    long-term engagement". Cell borders are subtle light gray with rounded corners.
+    The background is clean white.
   criteria_checklist:
     visual_quality:
       score: 28
@@ -46,64 +47,65 @@ review:
         score: 7
         max: 8
         passed: true
-        comment: Font sizes explicitly set throughout (title 28, axis titles 22, axis
-          labels 15-17, cell text 16). Y-axis labels at 15pt slightly small.
+        comment: All font sizes explicitly set (title=28, axis titles=22, tick labels=17,
+          cell text=15). The % suffix at fontSize=10 is small but readable.
       - id: VQ-02
         name: No Overlap
         score: 6
         max: 6
         passed: true
-        comment: No overlapping text anywhere
+        comment: No overlapping text. Separate % layer with dx offset avoids collision.
       - id: VQ-03
         name: Element Visibility
         score: 6
         max: 6
         passed: true
-        comment: Cells well-sized with clear color differentiation and white borders
+        comment: Rectangles well-sized with cornerRadius and subtle stroke borders.
       - id: VQ-04
         name: Color Accessibility
         score: 4
         max: 4
         passed: true
-        comment: Blues colormap is colorblind-safe with conditional text color for
-          readability
+        comment: Sequential teal-to-navy palette is colorblind-safe with good luminance
+          contrast.
       - id: VQ-05
         name: Layout & Canvas
         score: 3
         max: 4
         passed: true
-        comment: Good layout, triangular shape inherently leaves empty space in lower-right
+        comment: Width=1400 (4200px at 3x) slightly narrower than ideal 4800px. Triangular
+          shape leaves inherent empty space.
       - id: VQ-06
         name: Axis Labels & Title
         score: 2
         max: 2
         passed: true
-        comment: 'Descriptive labels: Months Since Signup, Signup Cohort'
+        comment: 'Descriptive labels: Months Since Signup, Signup Cohort.'
     design_excellence:
-      score: 11
+      score: 14
       max: 20
       items:
       - id: DE-01
         name: Aesthetic Sophistication
-        score: 5
+        score: 6
         max: 8
         passed: true
-        comment: Blues colormap well-chosen, white cell borders, conditional text
-          coloring. Above defaults but not publication-level.
+        comment: Custom 6-stop gradient palette, rounded cell corners, subtle borders,
+          separate % layer, informative subtitle.
       - id: DE-02
         name: Visual Refinement
-        score: 3
+        score: 4
         max: 6
         passed: true
-        comment: View stroke removed, white cell separators. Some refinement but could
-          be further polished.
+        comment: View stroke removed, axis domains/ticks hidden, generous padding,
+          subtle cell borders.
       - id: DE-03
         name: Data Storytelling
-        score: 3
+        score: 4
         max: 6
         passed: true
-        comment: Triangular shape and color gradient guide the eye, but no explicit
-          focal point or emphasis on key insights.
+        comment: Subtitle communicates key insight. Color gradient guides the eye.
+          Triangular shape tells temporal story.
     spec_compliance:
       score: 15
       max: 15
@@ -113,26 +115,26 @@ review:
         score: 5
         max: 5
         passed: true
-        comment: Correct triangular heatmap
+        comment: Correct triangular heatmap.
       - id: SC-02
         name: Required Features
         score: 4
         max: 4
         passed: true
-        comment: 'All spec features present: triangular shape, cell annotations, cohort
-          sizes, color bar'
+        comment: 'All features: triangular shape, retention % in cells, cohort sizes,
+          colorbar, sequential colormap.'
       - id: SC-03
         name: Data Mapping
         score: 3
         max: 3
         passed: true
-        comment: X=periods, Y=cohorts, correct mapping
+        comment: X=periods, Y=cohorts. All data correctly mapped.
       - id: SC-04
         name: Title & Legend
         score: 3
         max: 3
         passed: true
-        comment: Title format correct, color bar legend labeled Retention %
+        comment: Title format correct. Color bar legend with Retention % label.
     data_quality:
       score: 15
       max: 15
@@ -142,20 +144,20 @@ review:
         score: 6
         max: 6
         passed: true
-        comment: Full retention decay, cohort variation, triangular shape, period
-          0 always 100%
+        comment: Realistic decay, period 0=100%, varying cohort sizes, different retention
+          curves, full triangular structure.
       - id: DQ-02
         name: Realistic Context
         score: 5
         max: 5
         passed: true
-        comment: Realistic SaaS monthly cohort retention with plausible user counts
+        comment: Monthly SaaS user retention — real, neutral business scenario.
       - id: DQ-03
         name: Appropriate Scale
         score: 4
         max: 4
         passed: true
-        comment: Realistic retention values and cohort sizes
+        comment: Retention decays 100% to ~19.5%. Cohort sizes 921-2438 plausible.
     code_quality:
       score: 10
       max: 10
@@ -165,55 +167,56 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: 'Clean linear flow: imports, data, chart, save'
+        comment: 'Clean linear flow: imports, data, layers, combine, save.'
       - id: CQ-02
         name: Reproducibility
         score: 2
         max: 2
         passed: true
-        comment: np.random.seed(42) set
+        comment: np.random.seed(42) set.
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: All imports used
+        comment: Only altair, numpy, pandas — all used.
       - id: CQ-04
         name: Code Elegance
         score: 2
         max: 2
         passed: true
-        comment: Clean, well-structured, appropriate complexity
+        comment: Clean three-layer composition. Not over-engineered.
       - id: CQ-05
         name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves plot.png with scale_factor=3.0 and plot.html
+        comment: Saves plot.png and plot.html. Current Altair 6.0 API.
     library_mastery:
-      score: 7
+      score: 8
       max: 10
       items:
       - id: LM-01
         name: Idiomatic Usage
-        score: 4
+        score: 5
         max: 5
         passed: true
-        comment: 'Good declarative API usage: mark_rect + mark_text layering, proper
-          encoding types, alt.Scale/Axis'
+        comment: 'Expert Altair: mark_rect/mark_text, ordinal encoding with sort,
+          alt.condition, alt.layer, alt.Title, configure_view/axis.'
       - id: LM-02
         name: Distinctive Features
         score: 3
         max: 5
         passed: true
-        comment: Uses alt.condition for conditional text coloring, layer composition,
-          configure_view
-  verdict: REJECTED
+        comment: alt.condition for dynamic text color, tooltip interactivity, HTML
+          export, declarative layer composition.
+  verdict: APPROVED
 impl_tags:
   dependencies: []
   techniques:
   - annotations
   - layer-composition
+  - hover-tooltips
   - html-export
   patterns:
   - data-generation