feat(plotly): implement bar-3d (#2885)

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

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

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

**Parent Issue:** #2857

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20608477432)*

---------

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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/plotly.py

@@ -0,0 +1,152 @@
+""" pyplots.ai
+bar-3d: 3D Bar Chart
+Library: plotly 6.5.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data - Quarterly sales by product category (5 products x 4 quarters)
+np.random.seed(42)
+
+products = ["Electronics", "Clothing", "Food", "Home", "Sports"]
+quarters = ["Q1", "Q2", "Q3", "Q4"]
+
+# Create sales data with realistic patterns (values in thousands)
+base_sales = np.array([120, 85, 95, 70, 55])
+seasonal_factors = np.array([0.8, 1.0, 0.9, 1.3])  # Q4 holiday boost
+sales_matrix = np.outer(base_sales, seasonal_factors) + np.random.randn(5, 4) * 10
+sales_matrix = np.maximum(sales_matrix, 10)  # Ensure positive values
+
+# Create 3D bar coordinates
+x_coords = []
+y_coords = []
+z_coords = []
+colors = []
+
+# Python-inspired colorscale
+colorscale = ["#306998", "#4A8BB2", "#6AADCC", "#FFD43B", "#FFE873"]
+
+for i, _product in enumerate(products):
+    for j, _quarter in enumerate(quarters):
+        x_coords.append(i)
+        y_coords.append(j)
+        z_coords.append(sales_matrix[i, j])
+        colors.append(colorscale[i])
+
+# Create 3D bars using Mesh3d for each bar
+fig = go.Figure()
+
+bar_width = 0.35
+bar_depth = 0.35
+
+for i in range(len(x_coords)):
+    x, y, z = x_coords[i], y_coords[i], z_coords[i]
+
+    # Define the 8 vertices of each bar
+    vertices_x = [
+        x - bar_width,
+        x + bar_width,
+        x + bar_width,
+        x - bar_width,
+        x - bar_width,
+        x + bar_width,
+        x + bar_width,
+        x - bar_width,
+    ]
+    vertices_y = [
+        y - bar_depth,
+        y - bar_depth,
+        y + bar_depth,
+        y + bar_depth,
+        y - bar_depth,
+        y - bar_depth,
+        y + bar_depth,
+        y + bar_depth,
+    ]
+    vertices_z = [0, 0, 0, 0, z, z, z, z]
+
+    # Define faces using triangular indices
+    faces_i = [0, 0, 4, 4, 0, 0, 1, 1, 0, 0, 3, 3]
+    faces_j = [1, 2, 5, 6, 1, 4, 2, 5, 3, 4, 2, 6]
+    faces_k = [2, 3, 6, 7, 4, 5, 5, 6, 4, 7, 6, 7]
+
+    fig.add_trace(
+        go.Mesh3d(
+            x=vertices_x,
+            y=vertices_y,
+            z=vertices_z,
+            i=faces_i,
+            j=faces_j,
+            k=faces_k,
+            color=colors[i],
+            opacity=0.9,
+            flatshading=True,
+            showlegend=False,
+            hovertemplate=f"{products[x_coords[i]]}<br>{quarters[y_coords[i]]}<br>Sales: ${z:.0f}K<extra></extra>",
+        )
+    )
+
+# Add legend traces for products
+for i, product in enumerate(products):
+    fig.add_trace(
+        go.Scatter3d(
+            x=[None],
+            y=[None],
+            z=[None],
+            mode="markers",
+            marker=dict(size=16, color=colorscale[i]),
+            name=product,
+            showlegend=True,
+        )
+    )
+
+# Update layout
+fig.update_layout(
+    title=dict(
+        text="bar-3d \u00b7 plotly \u00b7 pyplots.ai", font=dict(size=32, color="#333333"), x=0.5, xanchor="center"
+    ),
+    scene=dict(
+        xaxis=dict(
+            title=dict(text="Product Category", font=dict(size=20)),
+            ticktext=products,
+            tickvals=list(range(len(products))),
+            tickfont=dict(size=14),
+            gridcolor="rgba(0,0,0,0.1)",
+            showbackground=True,
+            backgroundcolor="rgba(240,240,240,0.9)",
+        ),
+        yaxis=dict(
+            title=dict(text="Quarter", font=dict(size=20)),
+            ticktext=quarters,
+            tickvals=list(range(len(quarters))),
+            tickfont=dict(size=14),
+            gridcolor="rgba(0,0,0,0.1)",
+            showbackground=True,
+            backgroundcolor="rgba(240,240,240,0.9)",
+        ),
+        zaxis=dict(
+            title=dict(text="Sales ($K)", font=dict(size=20)),
+            tickfont=dict(size=14),
+            gridcolor="rgba(0,0,0,0.1)",
+            showbackground=True,
+            backgroundcolor="rgba(240,240,240,0.9)",
+        ),
+        camera=dict(eye=dict(x=1.8, y=1.8, z=1.2)),
+        aspectmode="manual",
+        aspectratio=dict(x=1.2, y=1, z=0.8),
+    ),
+    legend=dict(
+        font=dict(size=16), x=0.92, y=0.9, bgcolor="rgba(255,255,255,0.9)", bordercolor="rgba(0,0,0,0.2)", borderwidth=1
+    ),
+    margin=dict(l=20, r=20, t=80, b=20),
+    paper_bgcolor="white",
+    width=1600,
+    height=900,
+)
+
+# Save as PNG and HTML
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs="cdn")

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

@@ -0,0 +1,26 @@
+library: plotly
+specification_id: bar-3d
+created: '2025-12-30T23:55:43Z'
+updated: '2025-12-31T00:02:01Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20608477432
+issue: 2857
+python_version: 3.13.11
+library_version: 6.5.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/bar-3d/plotly/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/bar-3d/plotly/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/bar-3d/plotly/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent implementation of 3D bars using Mesh3d with proper vertex and face definitions
+  - Good color scheme following Python-inspired palette that is colorblind-safe
+  - Interactive hover templates with detailed information (product, quarter, sales
+    value)
+  - Dual output format (PNG + HTML) leveraging Plotly interactive capabilities
+  - Realistic business scenario with seasonal sales patterns (Q4 holiday boost)
+  - Semi-transparent bars (opacity=0.9) help with depth perception
+  weaknesses:
+  - Legend marker style (circular) does not match the bar chart style
+  - Some minor occlusion of back rows inherent to 3D visualization could be mitigated
+    with more transparency