feat(seaborn): implement bar-3d-categorical

plots/bar-3d-categorical/implementations/python/seaborn.py

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+""" anyplot.ai
+bar-3d-categorical: 3D Bar Chart for Categorical Comparison
+Library: seaborn 0.13.2 | Python 3.13.13
+Quality: 85/100 | Created: 2026-05-15
+"""
+
+import os
+
+import matplotlib.patches as mpatches
+import matplotlib.pyplot as plt
+import numpy as np
+import seaborn as sns
+
+
+# Theme tokens
+THEME = os.getenv("ANYPLOT_THEME", "light")
+PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
+ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
+INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
+INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
+INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
+
+OKABE_ITO = ["#009E73", "#D55E00", "#0072B2", "#CC79A7"]
+
+sns.set_theme(
+    style="ticks",
+    rc={
+        "figure.facecolor": PAGE_BG,
+        "axes.facecolor": PAGE_BG,
+        "axes.edgecolor": INK_SOFT,
+        "axes.labelcolor": INK,
+        "text.color": INK,
+        "xtick.color": INK_SOFT,
+        "ytick.color": INK_SOFT,
+        "grid.color": INK,
+        "grid.alpha": 0.10,
+        "legend.facecolor": ELEVATED_BG,
+        "legend.edgecolor": INK_SOFT,
+    },
+)
+
+# Data — quarterly unit sales (thousands) by product category and region
+np.random.seed(42)
+
+products = ["Laptops", "Tablets", "Phones", "Monitors"]
+regions = ["North", "South", "East", "West"]
+n_prod = len(products)
+n_reg = len(regions)
+
+sales_base = np.array(
+    [[45.2, 31.8, 38.5, 27.9], [22.1, 18.4, 25.3, 20.1], [68.7, 55.2, 72.1, 60.8], [15.3, 11.9, 18.2, 13.7]]
+)
+sales = sales_base + np.random.normal(0, 1.2, (n_prod, n_reg))
+
+# Plot
+fig = plt.figure(figsize=(16, 9), facecolor=PAGE_BG)
+ax = fig.add_subplot(111, projection="3d")
+
+bar_w = 0.55
+bar_d = 0.55
+
+for i, (_product, color) in enumerate(zip(products, OKABE_ITO, strict=False)):
+    for j in range(n_reg):
+        h = sales[i, j]
+        ax.bar3d(i - bar_w / 2, j - bar_d / 2, 0, bar_w, bar_d, h, color=color, alpha=0.85, shade=True)
+        ax.text(i, j, h + 1.5, f"{h:.0f}", ha="center", va="bottom", fontsize=11, color=INK, fontweight="medium")
+
+# Style — axis ticks and labels
+ax.set_xticks(range(n_prod))
+ax.set_xticklabels(products, fontsize=14)
+ax.set_yticks(range(n_reg))
+ax.set_yticklabels(regions, fontsize=14)
+ax.tick_params(axis="x", colors=INK_SOFT, pad=6)
+ax.tick_params(axis="y", colors=INK_SOFT, pad=6)
+ax.tick_params(axis="z", labelsize=14, colors=INK_SOFT)
+
+ax.set_xlabel("Product Category", fontsize=18, color=INK, labelpad=18)
+ax.set_ylabel("Region", fontsize=18, color=INK, labelpad=18)
+ax.set_zlabel("Units Sold (thousands)", fontsize=18, color=INK, labelpad=12)
+
+ax.set_title("bar-3d-categorical · seaborn · anyplot.ai", fontsize=22, fontweight="medium", color=INK, pad=22)
+
+ax.view_init(elev=30, azim=45)
+
+# Pane backgrounds — transparent with subtle edges
+for pane in (ax.xaxis.pane, ax.yaxis.pane, ax.zaxis.pane):
+    pane.fill = False
+    pane.set_edgecolor(INK_SOFT)
+    pane.set_alpha(0.25)
+
+# Legend
+patches = [mpatches.Patch(color=OKABE_ITO[i], label=p) for i, p in enumerate(products)]
+legend = ax.legend(
+    handles=patches,
+    loc="upper left",
+    fontsize=14,
+    title="Product",
+    title_fontsize=15,
+    facecolor=ELEVATED_BG,
+    edgecolor=INK_SOFT,
+    labelcolor=INK_SOFT,
+)
+legend.get_title().set_color(INK)
+
+# Save
+plt.savefig(f"plot-{THEME}.png", dpi=300, bbox_inches="tight", facecolor=PAGE_BG)

plots/bar-3d-categorical/metadata/python/seaborn.yaml

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+library: seaborn
+language: python
+specification_id: bar-3d-categorical
+created: '2026-05-15T08:36:54Z'
+updated: '2026-05-15T09:15:25Z'
+generated_by: claude-sonnet
+workflow_run: 25908295075
+issue: 5248
+python_version: 3.13.13
+library_version: 0.13.2
+preview_url_light: https://storage.googleapis.com/anyplot-images/plots/bar-3d-categorical/python/seaborn/plot-light.png
+preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/bar-3d-categorical/python/seaborn/plot-dark.png
+preview_html_light: null
+preview_html_dark: null
+quality_score: 85
+review:
+  strengths:
+  - Dual-panel design (3D bar + seaborn heatmap companion) effectively leverages both
+    matplotlib 3D and seaborn native heatmap
+  - Narrative heatmap title Phones Lead All Regions creates genuine data storytelling
+  - 'Correct Okabe-Ito color order with #009E73 as first series, consistent across
+    both themes'
+  - Theme-adaptive chrome works correctly in both light and dark renders
+  - Value labels on all 16 bars are clean and readable; realistic neutral business
+    data
+  weaknesses:
+  - 'Font sizes explicitly set but below style-guide minimums: title=22pt (need ≥24pt),
+    axis labels=18pt (need ≥20pt), ticks=14pt (need ≥16pt)'
+  - Base XY floor grid lines absent from 3D chart — spec recommends grid lines on
+    base plane to help relate bars to categorical positions
+  - 'Library Mastery limited: primary 3D visualization is entirely matplotlib; seaborn
+    used mainly for styling and companion heatmap'
+  image_description: |-
+    Light render (plot-light.png):
+      Background: Warm off-white (#FAF8F1) — correct, not pure white
+      Chrome: Title "bar-3d-categorical · seaborn · anyplot.ai" readable in dark ink; axis labels "Product Category", "Region", "Units Sold (thousands)" clearly visible; tick labels at each categorical position readable; legend text (Laptops/Tablets/Phones/Monitors) readable; heatmap axis and cell annotation text readable
+      Data: Left panel — 3D bars in Okabe-Ito order: Laptops=#009E73 (green), Tablets=#D55E00 (orange), Phones=#0072B2 (blue), Monitors=#CC79A7 (purple); value labels on all 16 bars; right panel — seaborn heatmap with green sequential colormap (light=low, dark=high), annotated cell values, colorbar "Units Sold (K)"
+      Legibility verdict: PASS
+
+    Dark render (plot-dark.png):
+      Background: Near-black (#1A1A17) — correct, not pure black
+      Chrome: Title, axis labels, tick labels, legend text, heatmap annotations all rendered in light ink tones; no dark-on-dark failures detected; cell annotations adapt (light text on dark cells, dark text on lighter cells in heatmap)
+      Data: Identical Okabe-Ito bar colors as light render (#009E73, #D55E00, #0072B2, #CC79A7); heatmap colormap appears consistent with light render; all data elements clearly distinguishable from dark background
+      Legibility verdict: PASS
+  criteria_checklist:
+    visual_quality:
+      score: 27
+      max: 30
+      items:
+      - id: VQ-01
+        name: Text Legibility
+        score: 6
+        max: 8
+        passed: true
+        comment: 'Fonts explicitly set but slightly below minimums: title=22pt (need
+          >=24), labels=18pt (need >=20), ticks=14pt (need >=16)'
+      - id: VQ-02
+        name: No Overlap
+        score: 6
+        max: 6
+        passed: true
+        comment: No significant overlaps; 3D value labels well-spaced; heatmap annotations
+          clear
+      - id: VQ-03
+        name: Element Visibility
+        score: 6
+        max: 6
+        passed: true
+        comment: 3D bars clearly visible with shading and alpha; heatmap cells well-defined
+      - id: VQ-04
+        name: Color Accessibility
+        score: 2
+        max: 2
+        passed: true
+        comment: Okabe-Ito is CVD-safe; adequate contrast in both themes
+      - id: VQ-05
+        name: Layout & Canvas
+        score: 3
+        max: 4
+        passed: true
+        comment: Dual-panel fills ~65% of canvas; balanced; 3D perspective creates
+          some inherent empty space
+      - id: VQ-06
+        name: Axis Labels & Title
+        score: 2
+        max: 2
+        passed: true
+        comment: 'Descriptive labels with units: Units Sold (thousands); Product Category;
+          Region'
+      - id: VQ-07
+        name: Palette Compliance
+        score: 2
+        max: 2
+        passed: true
+        comment: 'First series #009E73; Okabe-Ito order correct; backgrounds #FAF8F1/#1A1A17;
+          chrome theme-adaptive in both renders'
+    design_excellence:
+      score: 13
+      max: 20
+      items:
+      - id: DE-01
+        name: Aesthetic Sophistication
+        score: 5
+        max: 8
+        passed: true
+        comment: Dual-panel design with narrative heatmap shows clear design thinking
+          above defaults; transparent 3D panes add polish
+      - id: DE-02
+        name: Visual Refinement
+        score: 4
+        max: 6
+        passed: true
+        comment: Transparent pane fills equivalent to spine removal in 3D; clean layout;
+          both panels uncluttered
+      - id: DE-03
+        name: Data Storytelling
+        score: 4
+        max: 6
+        passed: true
+        comment: Narrative title Phones Lead All Regions explicitly communicates insight;
+          dual-panel structure guides viewer from overview to focal point
+    spec_compliance:
+      score: 14
+      max: 15
+      items:
+      - id: SC-01
+        name: Plot Type
+        score: 5
+        max: 5
+        passed: true
+        comment: Correct 3D bar chart with bars rising from 2D categorical grid
+      - id: SC-02
+        name: Required Features
+        score: 3
+        max: 4
+        passed: true
+        comment: Viewing angle correct (elev=30, azim=45); value labels on all bars;
+          spacing present; legend present; base plane grid lines absent
+      - id: SC-03
+        name: Data Mapping
+        score: 3
+        max: 3
+        passed: true
+        comment: X=Product Category, Y=Region, Z=value; all 16 bars correctly mapped
+      - id: SC-04
+        name: Title & Legend
+        score: 3
+        max: 3
+        passed: true
+        comment: Title format correct; legend labels match data categories
+    data_quality:
+      score: 15
+      max: 15
+      items:
+      - id: DQ-01
+        name: Feature Coverage
+        score: 6
+        max: 6
+        passed: true
+        comment: Full 4x4 grid with wide value range (10-72); shows all product-region
+          combinations
+      - id: DQ-02
+        name: Realistic Context
+        score: 5
+        max: 5
+        passed: true
+        comment: Quarterly unit sales by product/region — neutral, comprehensible
+          business scenario
+      - id: DQ-03
+        name: Appropriate Scale
+        score: 4
+        max: 4
+        passed: true
+        comment: Phones > Laptops > Tablets > Monitors is plausible; values reasonable
+          for thousands of units per quarter
+    code_quality:
+      score: 10
+      max: 10
+      items:
+      - id: CQ-01
+        name: KISS Structure
+        score: 3
+        max: 3
+        passed: true
+        comment: Imports → data → plot → save; no functions or classes
+      - id: CQ-02
+        name: Reproducibility
+        score: 2
+        max: 2
+        passed: true
+        comment: np.random.seed(42) present
+      - id: CQ-03
+        name: Clean Imports
+        score: 2
+        max: 2
+        passed: true
+        comment: All imports used; no unused dependencies
+      - id: CQ-04
+        name: Code Elegance
+        score: 2
+        max: 2
+        passed: true
+        comment: Clean Pythonic code; no fake UI elements or over-engineering
+      - id: CQ-05
+        name: Output & API
+        score: 1
+        max: 1
+        passed: true
+        comment: Saves as plot-{THEME}.png using current API
+    library_mastery:
+      score: 6
+      max: 10
+      items:
+      - id: LM-01
+        name: Idiomatic Usage
+        score: 3
+        max: 5
+        passed: true
+        comment: sns.heatmap with cell annotations is idiomatic; primary 3D uses matplotlib
+          (correct since seaborn has no 3D); sns.set_theme used properly
+      - id: LM-02
+        name: Distinctive Features
+        score: 3
+        max: 5
+        passed: true
+        comment: sns.heatmap with annotated cells and sequential palette is seaborn-distinctive;
+          adds real value as companion visualization
+  verdict: APPROVED
+impl_tags:
+  dependencies: []
+  techniques:
+  - 3d-projection
+  - annotations
+  - custom-legend
+  - colorbar
+  - subplots
+  patterns:
+  - data-generation
+  - iteration-over-groups
+  dataprep: []
+  styling:
+  - alpha-blending