feat(seaborn): implement scatter-basic

plots/scatter-basic/implementations/python/seaborn.py

@@ -1,7 +1,7 @@
 """ anyplot.ai
 scatter-basic: Basic Scatter Plot
 Library: seaborn 0.13.2 | Python 3.14.4
-Quality: 85/100 | Created: 2026-04-23
+Quality: 85/100 | Updated: 2026-04-23
 """
 
 import os
@@ -19,23 +19,18 @@
 INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
 BRAND = "#009E73"  # Okabe-Ito position 1
 
-# Data — study hours vs exam scores with realistic correlation and variety
+# Data — marketing spend vs. quarterly sales revenue (r~0.75)
 np.random.seed(42)
-n = 150
-study_hours = np.random.uniform(1, 10, n)
-exam_scores = 12 * study_hours - 0.4 * study_hours**2 + np.random.randn(n) * 7 + 30
+n = 220
+marketing_spend = np.random.gamma(shape=2.2, scale=9.0, size=n) + 3
+sales_revenue = 4.1 * marketing_spend + np.random.normal(0, 18, n) + 15
+sales_revenue = np.clip(sales_revenue, 5, None)
 
-# Natural outliers: a few high-effort underperformers and gifted low-study students
-exam_scores[0], study_hours[0] = 95, 2.5
-exam_scores[5], study_hours[5] = 28, 8.5
-exam_scores[10], study_hours[10] = 88, 3.0
-exam_scores[140], study_hours[140] = 35, 7.8
-exam_scores[145], study_hours[145] = 92, 5.5
-
-df = pd.DataFrame({"Study Hours (per week)": study_hours, "Exam Score (points)": exam_scores})
+df = pd.DataFrame({"Marketing Spend ($ thousands)": marketing_spend, "Quarterly Revenue ($ thousands)": sales_revenue})
 
 # Plot
 sns.set_theme(
+    context="talk",
     style="ticks",
     rc={
         "figure.facecolor": PAGE_BG,
@@ -47,32 +42,32 @@
         "ytick.color": INK_SOFT,
         "grid.color": INK,
         "grid.alpha": 0.10,
-        "font.family": "sans-serif",
-        "axes.linewidth": 0.8,
+        "axes.linewidth": 0.9,
+        "axes.grid": True,
+        "axes.axisbelow": True,
     },
 )
 
 fig, ax = plt.subplots(figsize=(16, 9))
 
 sns.scatterplot(
     data=df,
-    x="Study Hours (per week)",
-    y="Exam Score (points)",
+    x="Marketing Spend ($ thousands)",
+    y="Quarterly Revenue ($ thousands)",
     ax=ax,
     color=BRAND,
-    s=220,
+    s=130,
     alpha=0.7,
     edgecolor=PAGE_BG,
-    linewidth=0.8,
+    linewidth=0.9,
 )
 
 # Style
-ax.set_title("scatter-basic · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK, pad=18)
-ax.set_xlabel("Study Hours (per week)", fontsize=20, color=INK)
-ax.set_ylabel("Exam Score (points)", fontsize=20, color=INK)
-ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
-ax.grid(True, linewidth=0.8)
-ax.set_axisbelow(True)
+ax.set_title("scatter-basic · seaborn · anyplot.ai", fontsize=24, fontweight="medium", color=INK, pad=20)
+ax.set_xlabel("Marketing Spend ($ thousands)", fontsize=20, color=INK, labelpad=12)
+ax.set_ylabel("Quarterly Revenue ($ thousands)", fontsize=20, color=INK, labelpad=12)
+ax.tick_params(axis="both", labelsize=16, colors=INK_SOFT, length=0)
+ax.margins(x=0.04, y=0.06)
 sns.despine(ax=ax)
 
 plt.tight_layout()

plots/scatter-basic/metadata/python/seaborn.yaml

@@ -2,9 +2,9 @@ library: seaborn
 language: python
 specification_id: scatter-basic
 created: '2025-12-10T20:55:10Z'
-updated: '2026-04-23T19:24:09Z'
+updated: '2026-04-23T21:35:58Z'
 generated_by: claude-opus
-workflow_run: 24853787271
+workflow_run: 24859691916
 issue: 611
 python_version: 3.14.4
 library_version: 0.13.2
@@ -15,34 +15,35 @@ preview_html_dark: null
 quality_score: 85
 review:
   strengths:
-  - 'Full theme-adaptive implementation: both renders are clean, readable, and visually
-    consistent with Okabe-Ito palette and correct background tokens'
-  - 'Excellent code quality: reproducible, KISS structure, clean imports, correct
-    output naming (plot-{THEME}.png)'
-  - edgecolor=PAGE_BG on markers is a thoughtful technique that adds visual separation
-    in the dense cluster region
-  - 'Spec compliance is perfect: correct scatter type, all required features, proper
-    title format, appropriate omission of single-series legend'
+  - Perfect spec compliance and data quality — marketing spend vs. revenue scenario
+    with realistic right-skewed distribution and natural noise
+  - Excellent code quality and theme adaptation — all chrome tokens correctly wired
+    through sns.set_theme rc params; both renders pass legibility checks
+  - 'Good visual refinements: sns.despine removes top/right spines, tick-length=0,
+    edgecolor=PAGE_BG for marker definition, subtle grid at alpha=0.10'
   weaknesses:
-  - Marker size s=220 is 2-4x larger than the recommended 50-100 for 150 data points;
-    visible overlap in dense 3-5 hour cluster
-  - 'DE-03 default (2/6): deliberately inserted outliers are indistinguishable from
-    regular data; no regression line or visual emphasis tells a richer story'
-  - 'LM-02 low (2/5): seaborn''s distinctive scatter strength is built-in statistical
-    overlays (sns.regplot with CI band) — not used here'
-  - Exam scores reach 125, slightly ambiguous for a context implying a 0-100 scale
+  - 'DE-03 (2/6): No visual storytelling — positive correlation is the insight but
+    nothing guides the viewer toward it; a regression/trend line or correlation annotation
+    would make the story immediately legible'
+  - 'DE-01 (4/8): Single-color scatter with no secondary encoding is minimal viable
+    design; adding a regression line or marginal distributions would push beyond configured-defaults
+    territory'
+  - 'LM-02 (2/5): Seaborn''s most distinctive scatter feature (sns.regplot adds trend
+    line + CI band in one call; sns.jointplot adds marginal distributions) is unused'
+  - 'VQ-03 (5/6): Marker size s=130 is above recommended s=50-100 for 220 points —
+    reducing to ~90 with alpha=0.65 would reduce clutter in the dense region'
   image_description: |-
     Light render (plot-light.png):
-      Background: Warm off-white (~#FAF8F1), not pure white — correct theme surface
-      Chrome: Title "scatter-basic · seaborn · anyplot.ai" in medium-weight dark text (readable); axis labels "Study Hours (per week)" and "Exam Score (points)" in dark INK color (readable); tick labels in softer INK_SOFT tone (readable); subtle grid lines on both axes at low opacity
-      Data: 150 scatter points in #009E73 (brand green, Okabe-Ito position 1); marker size s=220 with alpha=0.7 and PAGE_BG edge color creating visible separation; clear positive correlation from lower-left to upper-right; deliberate outliers visible (low-study high-scorers and high-study low-scorers)
-      Legibility verdict: PASS
+      Background: Warm off-white #FAF8F1 — correctly themed, not pure white
+      Chrome: Title "scatter-basic · seaborn · anyplot.ai" in dark ink, clearly readable; axis labels "Marketing Spend ($ thousands)" and "Quarterly Revenue ($ thousands)" in dark ink at appropriate size; tick labels in muted dark gray (INK_SOFT), all clearly readable
+      Data: ~220 teal-green scatter points in #009E73 (Okabe-Ito position 1); markers have PAGE_BG edge for definition; clear positive correlation visible; mild overlap in the dense lower-left region
+      Legibility verdict: PASS — all text clearly readable against warm off-white background; no light-on-light issues
 
     Dark render (plot-dark.png):
-      Background: Warm near-black (~#1A1A17), not pure black — correct theme surface
-      Chrome: Title, axis labels, and tick labels all rendered in light cream/off-white (INK #F0EFE8 / INK_SOFT #B8B7B0) — clearly readable against the dark surface; no dark-on-dark failures detected; grid lines remain subtle
-      Data: Data point colors are identical to light render (#009E73) — only chrome flips; marker edge color maps to #1A1A17 (PAGE_BG for dark theme) which reduces visual separation vs light render but does not cause readability issues
-      Legibility verdict: PASS
+      Background: Near-black #1A1A17 — correctly themed, not pure black
+      Chrome: Title in light text clearly readable; axis labels and tick labels in light/muted-light text — all readable against dark background; no dark-on-dark failures detected
+      Data: #009E73 teal-green scatter points are identical in color to light render — only chrome has flipped; data colors consistent across themes
+      Legibility verdict: PASS — all text clearly readable against near-black background; no dark-on-dark failures
   criteria_checklist:
     visual_quality:
       score: 29
@@ -53,47 +54,47 @@ review:
         score: 8
         max: 8
         passed: true
-        comment: Title 24pt, labels 20pt, ticks 16pt all explicitly set; readable
-          in both themes
+        comment: Title 24pt, labels 20pt, ticks 16pt explicitly set; both renders
+          fully legible
       - id: VQ-02
         name: No Overlap
         score: 6
         max: 6
         passed: true
-        comment: Tick labels well-spaced, no text collisions
+        comment: No text collisions; well-spaced axes and title
       - id: VQ-03
         name: Element Visibility
         score: 5
         max: 6
         passed: true
-        comment: s=220 is 2-4x larger than 50-100 guideline for 150 points; edgecolor
-          helps but dense 3-5hr cluster shows overlap
+        comment: s=130 slightly above recommended s=50-100 for 220 points; moderate
+          overlap in dense lower-left; edgecolor mitigates
       - id: VQ-04
         name: Color Accessibility
         score: 2
         max: 2
         passed: true
-        comment: 'Single series #009E73 with sufficient contrast on both surfaces;
-          CVD-safe Okabe-Ito'
+        comment: Single Okabe-Ito color with alpha=0.7; CVD-safe, no red-green issue
       - id: VQ-05
         name: Layout & Canvas
         score: 4
         max: 4
         passed: true
-        comment: 16:9 canvas well-utilized, balanced margins, no cutoff
+        comment: Plot fills 16:9 canvas well; tight_layout + bbox_inches=tight avoids
+          waste
       - id: VQ-06
         name: Axis Labels & Title
         score: 2
         max: 2
         passed: true
-        comment: Descriptive labels with units on both axes
+        comment: Descriptive labels with units; title matches required format
       - id: VQ-07
         name: Palette Compliance
         score: 2
         max: 2
         passed: true
-        comment: 'First series #009E73; light bg ~#FAF8F1, dark bg ~#1A1A17; all chrome
-          theme-correct'
+        comment: 'First series is #009E73; backgrounds #FAF8F1 light / #1A1A17 dark;
+          chrome uses adaptive INK/INK_SOFT tokens'
     design_excellence:
       score: 10
       max: 20
@@ -103,21 +104,23 @@ review:
         score: 4
         max: 8
         passed: false
-        comment: Well-configured seaborn default; clean but not exceptionally sophisticated
+        comment: 'Well-configured defaults: brand green, adaptive theme, clean font.
+          Solid but generic single-color scatter with no design differentiation beyond
+          compliance'
       - id: DE-02
         name: Visual Refinement
         score: 4
         max: 6
         passed: false
-        comment: sns.despine, subtle grid, set_axisbelow, INK_SOFT ticks, marker edge
-          colors — good but not fully polished
+        comment: 'Good: sns.despine, grid alpha=0.10, tick length=0, edgecolor=PAGE_BG,
+          axes.axisbelow=True — not quite every detail polished'
       - id: DE-03
         name: Data Storytelling
         score: 2
         max: 6
         passed: false
-        comment: Outliers not visually distinguished; no regression line or trend
-          emphasis; uniform green cloud
+        comment: Data displayed correctly but not interpreted; no trend line, no emphasis
+          on the positive correlation; viewer must find the story themselves
     spec_compliance:
       score: 15
       max: 15
@@ -127,49 +130,53 @@ review:
         score: 5
         max: 5
         passed: true
-        comment: Correct scatter plot
+        comment: Correct scatter plot via sns.scatterplot
       - id: SC-02
         name: Required Features
         score: 4
         max: 4
         passed: true
-        comment: Alpha 0.7, grid lines, axis labels, descriptive title all present
+        comment: alpha=0.7, grid lines, axis labels, descriptive title, point size
+          all present
       - id: SC-03
         name: Data Mapping
         score: 3
         max: 3
         passed: true
-        comment: X (study hours), Y (exam scores), all 150 points visible
+        comment: X/Y correctly assigned; all data within canvas; positive correlation
+          visible
       - id: SC-04
         name: Title & Legend
         score: 3
         max: 3
         passed: true
-        comment: Title 'scatter-basic · seaborn · anyplot.ai' correct; no legend for
-          single-series (appropriate)
+        comment: Title matches required format; single-series needs no legend — correct
+          omission
     data_quality:
-      score: 14
+      score: 15
       max: 15
       items:
       - id: DQ-01
         name: Feature Coverage
         score: 6
         max: 6
         passed: true
-        comment: Positive correlation, variance, and deliberate outliers in both directions
+        comment: Gamma-distributed spend creates realistic heteroscedasticity; 220
+          points show full scatter patterns; noise gives realistic variability
       - id: DQ-02
         name: Realistic Context
         score: 5
         max: 5
         passed: true
-        comment: Study hours vs exam scores — neutral, real-world, educationally plausible
+        comment: Marketing Spend vs. Quarterly Revenue is a neutral, real-world business
+          scenario
       - id: DQ-03
         name: Appropriate Scale
-        score: 3
+        score: 4
         max: 4
         passed: true
-        comment: Study hours 1-10/week plausible; exam scores reach 125 which is slightly
-          ambiguous if 0-100 scale intended
+        comment: Marketing spend $3-72K, revenue $5-310K — plausible B2B business
+          values
     code_quality:
       score: 10
       max: 10
@@ -179,51 +186,51 @@ review:
         score: 3
         max: 3
         passed: true
-        comment: Linear Imports → Data → Plot → Save; no functions or classes
+        comment: 'Linear flow: imports → tokens → data → plot → style → save; no functions
+          or classes'
       - id: CQ-02
         name: Reproducibility
         score: 2
         max: 2
         passed: true
-        comment: np.random.seed(42) present
+        comment: np.random.seed(42) set
       - id: CQ-03
         name: Clean Imports
         score: 2
         max: 2
         passed: true
-        comment: All 5 imports (os, matplotlib.pyplot, numpy, pandas, seaborn) are
-          used
+        comment: All imports (os, matplotlib, numpy, pandas, seaborn) are used
       - id: CQ-04
         name: Code Elegance
         score: 2
         max: 2
         passed: true
-        comment: Clean, Pythonic; no over-engineering; no fake functionality
+        comment: Clean, Pythonic; appropriate complexity for the task
       - id: CQ-05
         name: Output & API
         score: 1
         max: 1
         passed: true
-        comment: Saves plot-{THEME}.png with dpi=300, bbox_inches=tight, facecolor=PAGE_BG;
-          current seaborn API
+        comment: Saves as plot-{THEME}.png; uses current seaborn 0.13+ API
     library_mastery:
-      score: 7
+      score: 6
       max: 10
       items:
       - id: LM-01
         name: Idiomatic Usage
-        score: 5
+        score: 4
         max: 5
         passed: true
-        comment: sns.scatterplot (axes-level preferred), sns.set_theme for global
-          rc, sns.despine — all idiomatic
+        comment: sns.set_theme with context=talk, axes-level sns.scatterplot, sns.despine
+          — idiomatic seaborn pattern
       - id: LM-02
         name: Distinctive Features
         score: 2
         max: 5
         passed: false
-        comment: set_theme and despine are seaborn-specific but basic; sns.regplot
-          with CI band (the truly distinctive seaborn scatter feature) not used
+        comment: sns.despine and set_theme context system are seaborn-distinctive,
+          but core visualization is bare scatter replicable in matplotlib. sns.regplot
+          statistical overlay unused.
   verdict: REJECTED
 impl_tags:
   dependencies: []