feat(letsplot): implement scatter-regression-lowess (#2873)

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

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

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

**Parent Issue:** #2855

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:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20608465143)*

---------

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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/letsplot.py

@@ -0,0 +1,55 @@
+""" pyplots.ai
+scatter-regression-lowess: Scatter Plot with LOWESS Regression
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 93/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import (
+    LetsPlot,
+    aes,
+    element_text,
+    geom_point,
+    geom_smooth,
+    ggplot,
+    ggsave,
+    ggsize,
+    labs,
+    theme,
+    theme_minimal,
+)
+
+
+LetsPlot.setup_html()
+
+# Data - Complex non-linear relationship (plant growth vs temperature)
+np.random.seed(42)
+n = 200
+x = np.linspace(5, 40, n)
+# Growth peaks at moderate temps, drops at extremes
+y = 15 + 8 * np.sin((x - 5) * np.pi / 35) + 3 * np.cos((x - 10) * np.pi / 15) + np.random.randn(n) * 2.5
+
+df = pd.DataFrame({"temperature": x, "growth_rate": y})
+
+# Plot
+plot = (
+    ggplot(df, aes(x="temperature", y="growth_rate"))
+    + geom_point(color="#306998", size=4, alpha=0.6)
+    + geom_smooth(method="loess", span=0.4, color="#FFD43B", size=2.5, se=True, fill="#FFD43B", alpha=0.2)
+    + labs(x="Temperature (°C)", y="Growth Rate (cm/day)", title="scatter-regression-lowess · letsplot · pyplots.ai")
+    + theme_minimal()
+    + theme(
+        plot_title=element_text(size=24),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        legend_text=element_text(size=16),
+    )
+    + ggsize(1600, 900)
+)
+
+# Save PNG (scale 3x for 4800 x 2700 px)
+ggsave(plot, "plot.png", path=".", scale=3)
+
+# Save HTML for interactive version
+ggsave(plot, "plot.html", path=".")

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

@@ -0,0 +1,26 @@
+library: letsplot
+specification_id: scatter-regression-lowess
+created: '2025-12-30T23:53:52Z'
+updated: '2025-12-30T23:58:59Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20608465143
+issue: 2855
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-regression-lowess/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-regression-lowess/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-regression-lowess/letsplot/plot.html
+quality_score: 93
+review:
+  strengths:
+  - Excellent LOWESS implementation using geom_smooth with loess method and confidence
+    band (se=True)
+  - Perfect title format and descriptive axis labels with units
+  - Realistic plant growth vs temperature scenario that naturally demonstrates LOWESS
+    benefits
+  - Good color contrast between blue points and yellow curve with appropriate transparency
+  - Clean code structure following KISS principles with reproducible seed
+  weaknesses:
+  - Confidence band fill color (#FFD43B) same as line color - could use a lighter/different
+    shade for better visual distinction
+  - Some imports listed individually could be consolidated (minor style issue)