feat(letsplot): implement violin-box (#2690)

## Implementation: `violin-box` - letsplot

Implements the **letsplot** version of `violin-box`.

**File:** `plots/violin-box/implementations/letsplot.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20595343277)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/violin-box/implementations/letsplot.py

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+""" pyplots.ai
+violin-box: Violin Plot with Embedded Box Plot
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import *
+
+
+LetsPlot.setup_html()
+
+# Data - Response times (ms) for different server configurations
+np.random.seed(42)
+
+n_per_group = 150
+groups = ["Standard", "Optimized", "Premium", "Enterprise"]
+
+data = []
+# Standard: higher mean, moderate spread
+data.extend([(np.random.normal(85, 15), "Standard") for _ in range(n_per_group)])
+# Optimized: lower mean, some outliers
+vals = np.concatenate([np.random.normal(55, 12, n_per_group - 5), np.random.normal(100, 5, 5)])
+data.extend([(v, "Optimized") for v in vals])
+# Premium: bimodal distribution
+vals = np.concatenate([np.random.normal(40, 8, n_per_group // 2), np.random.normal(60, 8, n_per_group // 2)])
+data.extend([(v, "Premium") for v in vals])
+# Enterprise: low mean, tight spread, few outliers
+vals = np.concatenate([np.random.normal(30, 6, n_per_group - 3), np.random.normal(70, 3, 3)])
+data.extend([(v, "Enterprise") for v in vals])
+
+df = pd.DataFrame(data, columns=["response_time", "configuration"])
+
+# Create violin plot with embedded box plot
+plot = (
+    ggplot(df, aes(x="configuration", y="response_time", fill="configuration"))
+    + geom_violin(alpha=0.7, color="#306998", size=1.0, trim=False)
+    + geom_boxplot(width=0.15, fill="white", color="#306998", alpha=0.9, outlier_shape=21, outlier_size=3)
+    + scale_fill_manual(values=["#306998", "#FFD43B", "#4A90A4", "#7CB342"])
+    + labs(x="Server Configuration", y="Response Time (ms)", title="violin-box · letsplot · pyplots.ai")
+    + theme_minimal()
+    + theme(
+        plot_title=element_text(size=24, face="bold"),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        legend_position="none",
+        panel_grid_major_x=element_blank(),
+        panel_grid_minor=element_blank(),
+    )
+    + ggsize(1600, 900)
+)
+
+# Save as PNG (scale 3x for 4800x2700 px)
+ggsave(plot, "plot.png", path=".", scale=3)
+
+# Save as HTML for interactive version
+ggsave(plot, "plot.html", path=".")

plots/violin-box/metadata/letsplot.yaml

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+library: letsplot
+specification_id: violin-box
+created: '2025-12-30T11:30:38Z'
+updated: '2025-12-30T11:37:21Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20595343277
+issue: 0
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-box/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-box/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-box/letsplot/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent combination of violin and box plot showing both KDE density and summary
+    statistics
+  - Clean ggplot2-style grammar implementation with proper layering
+  - Colorblind-friendly palette with four distinct colors
+  - Realistic server response time scenario with varied distributions
+  - Proper font sizing following lets-plot guidelines (24pt title, 20pt labels, 16pt
+    ticks)
+  - Outliers clearly visible as hollow circles
+  weaknesses:
+  - Legend is hidden (legend_position=none) - while x-axis labels work as identifiers,
+    keeping a legend could add clarity
+  - Could leverage lets-plot interactive tooltip features for the HTML export
+  - Bimodal distribution in Premium group is somewhat subtle, could be more pronounced