feat(matplotlib): implement scatter-regression-lowess (#2871)

## Implementation: `scatter-regression-lowess` - matplotlib

Implements the **matplotlib** version of `scatter-regression-lowess`.

**File:**
`plots/scatter-regression-lowess/implementations/matplotlib.py`

**Parent Issue:** #2855

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20608460913)*

---------

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

Author: github-actions[bot]

plots/scatter-regression-lowess/implementations/matplotlib.py

@@ -0,0 +1,42 @@
+""" pyplots.ai
+scatter-regression-lowess: Scatter Plot with LOWESS Regression
+Library: matplotlib 3.10.8 | Python 3.13.11
+Quality: 95/100 | Created: 2025-12-30
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+from statsmodels.nonparametric.smoothers_lowess import lowess
+
+
+# Data - create a non-linear relationship that varies across x-axis range
+np.random.seed(42)
+n_points = 200
+x = np.linspace(0, 10, n_points)
+# Complex non-linear pattern: sine wave + quadratic trend + noise
+y = 2 * np.sin(x * 0.8) + 0.15 * x**2 + np.random.normal(0, 0.8, n_points)
+
+# Compute LOWESS smoothed curve
+lowess_result = lowess(y, x, frac=0.3, return_sorted=True)
+x_smooth = lowess_result[:, 0]
+y_smooth = lowess_result[:, 1]
+
+# Create plot
+fig, ax = plt.subplots(figsize=(16, 9))
+
+# Scatter points with transparency
+ax.scatter(x, y, s=100, alpha=0.6, color="#306998", edgecolors="white", linewidth=0.5, label="Data points")
+
+# LOWESS regression curve
+ax.plot(x_smooth, y_smooth, color="#FFD43B", linewidth=4, label="LOWESS fit", solid_capstyle="round")
+
+# Labels and styling
+ax.set_xlabel("Measurement Index", fontsize=20)
+ax.set_ylabel("Response Value", fontsize=20)
+ax.set_title("scatter-regression-lowess · matplotlib · pyplots.ai", fontsize=24)
+ax.tick_params(axis="both", labelsize=16)
+ax.legend(fontsize=16, loc="upper left")
+ax.grid(True, alpha=0.3, linestyle="--")
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/scatter-regression-lowess/metadata/matplotlib.yaml

@@ -0,0 +1,28 @@
+library: matplotlib
+specification_id: scatter-regression-lowess
+created: '2025-12-30T23:53:29Z'
+updated: '2025-12-30T23:56:03Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20608460913
+issue: 2855
+python_version: 3.13.11
+library_version: 3.10.8
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-regression-lowess/matplotlib/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-regression-lowess/matplotlib/plot_thumb.png
+preview_html: null
+quality_score: 95
+review:
+  strengths:
+  - Excellent visualization of LOWESS smoothing on complex non-linear data (sine +
+    quadratic + noise)
+  - LOWESS curve is visually distinct with contrasting yellow color and thick line
+    (linewidth=4)
+  - Appropriate smoothing bandwidth (frac=0.3) as recommended in spec
+  - Marker transparency (alpha=0.6) shows data density while keeping LOWESS curve
+    visible
+  - Clean, readable code following KISS principles
+  - All text elements properly sized for high-resolution output
+  weaknesses:
+  - Axis labels lack units (e.g., could be "Measurement Index (samples)" or similar)
+  - Data context is generic "Measurement Index" / "Response Value" - could be more
+    domain-specific