feat(matplotlib): implement violin-basic (#1359)

## Implementation: `violin-basic` - matplotlib

Implements the **matplotlib** version of `violin-basic`.

**File:** `plots/violin-basic/implementations/matplotlib.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20447775895)*

---------

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

Author: github-actions[bot]

plots/violin-basic/implementations/matplotlib.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 violin-basic: Basic Violin Plot
 Library: matplotlib 3.10.8 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-14
+Quality: 92/100 | Created: 2025-12-23
 """
 
 import matplotlib.pyplot as plt
@@ -53,7 +53,7 @@
 ax.set_xticks(range(len(categories)))
 ax.set_xticklabels(categories)
 ax.set_xlabel("School", fontsize=20)
-ax.set_ylabel("Test Score", fontsize=20)
+ax.set_ylabel("Test Score (points)", fontsize=20)
 ax.set_title("violin-basic · matplotlib · pyplots.ai", fontsize=24)
 ax.tick_params(axis="both", labelsize=16)
 ax.grid(True, alpha=0.3, linestyle="--", axis="y")

plots/violin-basic/metadata/matplotlib.yaml

@@ -1,17 +1,26 @@
 library: matplotlib
 specification_id: violin-basic
-created: 2025-12-14 09:50:11+00:00
-updated: 2025-12-14 09:50:11+00:00
+created: '2025-12-23T00:35:08Z'
+updated: '2025-12-23T00:38:15Z'
 generated_by: claude-opus-4-5-20251101
-workflow_run: 20206149623
-issue: 722
+workflow_run: 20447775895
+issue: 0
 python_version: 3.13.11
 library_version: 3.10.8
 preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/matplotlib/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/matplotlib/plot_thumb.png
 preview_html: null
 quality_score: 92
 review:
-  strengths: []
-  weaknesses: []
-  improvements: []
+  strengths:
+  - Excellent data scenario with test scores across schools - immediately comprehensible
+  - Clear visual hierarchy with yellow median lines contrasting well against blue
+    violins
+  - Proper quartile visualization with IQR bars inside violins
+  - Text sizes perfectly calibrated for 4800x2700 output
+  - Good variation in distributions showing different spread and center characteristics
+  weaknesses:
+  - Test score values exceeding 100 are unrealistic for typical percentage-based scoring
+  - Could use matplotlib built-in quartile visualization (showquartiles parameter)
+    instead of manual vlines
+  - Missing legend element (though not critical for this plot type)