feat(matplotlib): implement box-horizontal (#2562)

## Implementation: `box-horizontal` - matplotlib

Implements the **matplotlib** version of `box-horizontal`.

**File:** `plots/box-horizontal/implementations/matplotlib.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20593347218)*

---------

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

Author: github-actions[bot]

plots/box-horizontal/implementations/matplotlib.py

@@ -0,0 +1,59 @@
+""" pyplots.ai
+box-horizontal: Horizontal Box Plot
+Library: matplotlib 3.10.8 | Python 3.13.11
+Quality: 94/100 | Created: 2025-12-30
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+# Data - Response times (ms) by service type
+np.random.seed(42)
+
+# Different services with varying response time distributions
+services = [
+    "Authentication Service",
+    "Database Query",
+    "File Upload",
+    "Payment Processing",
+    "Email Notification",
+    "Image Processing",
+]
+
+# Generate data with different distributions to show variety
+data = [
+    np.random.normal(150, 30, 80),  # Auth - tight distribution
+    np.concatenate([np.random.normal(200, 40, 70), [450, 480, 520]]),  # DB - with outliers
+    np.random.normal(500, 100, 90),  # File upload - wider spread
+    np.random.exponential(180, 85) + 100,  # Payment - skewed right
+    np.random.normal(80, 15, 75),  # Email - fast and tight
+    np.random.uniform(300, 800, 60),  # Image - wide uniform spread
+]
+
+# Create figure
+fig, ax = plt.subplots(figsize=(16, 9))
+
+# Create horizontal box plot
+bp = ax.boxplot(
+    data,
+    vert=False,
+    tick_labels=services,
+    patch_artist=True,
+    widths=0.6,
+    flierprops={"marker": "o", "markersize": 8, "markerfacecolor": "#FFD43B", "markeredgecolor": "#306998"},
+    medianprops={"color": "#FFD43B", "linewidth": 2.5},
+    whiskerprops={"color": "#306998", "linewidth": 2},
+    capprops={"color": "#306998", "linewidth": 2},
+    boxprops={"facecolor": "#306998", "edgecolor": "#306998", "linewidth": 2, "alpha": 0.7},
+)
+
+# Labels and styling
+ax.set_xlabel("Response Time (ms)", fontsize=20)
+ax.set_ylabel("Service Type", fontsize=20)
+ax.set_title("box-horizontal · matplotlib · pyplots.ai", fontsize=24)
+ax.tick_params(axis="both", labelsize=16)
+ax.grid(True, alpha=0.3, linestyle="--", axis="x")
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/box-horizontal/metadata/matplotlib.yaml

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+library: matplotlib
+specification_id: box-horizontal
+created: '2025-12-30T09:30:57Z'
+updated: '2025-12-30T09:38:46Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20593347218
+issue: 0
+python_version: 3.13.11
+library_version: 3.10.8
+preview_url: https://storage.googleapis.com/pyplots-images/plots/box-horizontal/matplotlib/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/box-horizontal/matplotlib/plot_thumb.png
+preview_html: null
+quality_score: 94
+review:
+  strengths:
+  - Excellent data variety showcasing different distribution types (tight, wide, skewed,
+    with outliers)
+  - Perfect use of horizontal orientation with readable service type labels
+  - 'Strong color scheme using Python colors (#306998 blue, #FFD43B yellow) that is
+    colorblind-accessible'
+  - Comprehensive matplotlib boxplot customization demonstrating library capabilities
+  - Clean, well-structured code following KISS principles
+  weaknesses:
+  - Grid only on x-axis; adding subtle y-axis grid lines could help visually align
+    categories across the plot