feat(matplotlib): implement bar-3d (#2879)

## Implementation: `bar-3d` - matplotlib

Implements the **matplotlib** version of `bar-3d`.

**File:** `plots/bar-3d/implementations/matplotlib.py`

**Parent Issue:** #2857

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:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20608477493)*

---------

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Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/bar-3d/implementations/matplotlib.py

@@ -0,0 +1,77 @@
+""" pyplots.ai
+bar-3d: 3D Bar Chart
+Library: matplotlib 3.10.8 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+# Data - Sales by Product and Quarter
+np.random.seed(42)
+products = ["Product A", "Product B", "Product C", "Product D", "Product E"]
+quarters = ["Q1", "Q2", "Q3", "Q4"]
+
+n_products = len(products)
+n_quarters = len(quarters)
+
+# Generate realistic sales data (in thousands)
+sales = np.array(
+    [
+        [120, 135, 142, 158],  # Product A - steady growth
+        [85, 92, 78, 95],  # Product B - fluctuating
+        [200, 185, 210, 225],  # Product C - highest performer
+        [65, 70, 82, 88],  # Product D - moderate growth
+        [150, 145, 160, 142],  # Product E - variable
+    ]
+)
+
+# Create figure with 3D projection
+fig = plt.figure(figsize=(16, 9))
+ax = fig.add_subplot(111, projection="3d")
+
+# Set up grid positions
+xpos = np.arange(n_products)
+ypos = np.arange(n_quarters)
+xpos_mesh, ypos_mesh = np.meshgrid(xpos, ypos, indexing="ij")
+
+xpos_flat = xpos_mesh.flatten()
+ypos_flat = ypos_mesh.flatten()
+zpos_flat = np.zeros_like(xpos_flat)
+
+# Bar dimensions
+dx = 0.6
+dy = 0.6
+dz = sales.flatten()
+
+# Create color gradient based on height for better depth perception
+colors = plt.cm.viridis((dz - dz.min()) / (dz.max() - dz.min()))
+
+# Plot 3D bars with transparency
+ax.bar3d(xpos_flat, ypos_flat, zpos_flat, dx, dy, dz, color=colors, alpha=0.85, edgecolor="#333333", linewidth=0.5)
+
+# Styling
+ax.set_xlabel("Product", fontsize=20, labelpad=15)
+ax.set_ylabel("Quarter", fontsize=20, labelpad=15)
+ax.set_zlabel("Sales (thousands $)", fontsize=20, labelpad=15)
+ax.set_title("bar-3d · matplotlib · pyplots.ai", fontsize=24, pad=20)
+
+# Set tick labels
+ax.set_xticks(xpos + dx / 2)
+ax.set_xticklabels(products, fontsize=14)
+ax.set_yticks(ypos + dy / 2)
+ax.set_yticklabels(quarters, fontsize=14)
+ax.tick_params(axis="z", labelsize=14)
+
+# Set viewing angle for best visibility
+ax.view_init(elev=25, azim=45)
+
+# Add colorbar to reinforce z-values
+sm = plt.cm.ScalarMappable(cmap="viridis", norm=plt.Normalize(vmin=dz.min(), vmax=dz.max()))
+sm.set_array([])
+cbar = fig.colorbar(sm, ax=ax, shrink=0.6, aspect=15, pad=0.1)
+cbar.set_label("Sales (thousands $)", fontsize=16)
+cbar.ax.tick_params(labelsize=14)
+
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/bar-3d/metadata/matplotlib.yaml

@@ -0,0 +1,26 @@
+library: matplotlib
+specification_id: bar-3d
+created: '2025-12-30T23:54:48Z'
+updated: '2025-12-31T00:00:10Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20608477493
+issue: 2857
+python_version: 3.13.11
+library_version: 3.10.8
+preview_url: https://storage.googleapis.com/pyplots-images/plots/bar-3d/matplotlib/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bar-3d/matplotlib/plot_thumb.png
+preview_html: null
+quality_score: 92
+review:
+  strengths:
+  - Excellent use of viridis colormap with colorbar for depth perception as spec recommends
+  - Semi-transparent bars (alpha=0.85) help reveal bars behind taller ones per spec
+    guidance
+  - Well-chosen viewing angle (elev=25, azim=45) provides good visibility of all bars
+  - Professional title format and axis labels with units
+  - Realistic sales data scenario with meaningful variation between products and quarters
+  - Clean, well-structured code following KISS principle
+  weaknesses:
+  - Grid styling could use alpha parameter for subtler appearance
+  - Could benefit from slightly more contrast in bar heights (all values in 65-225
+    range, some near-zero values would show more variation)