update(density-basic): letsplot — comprehensive quality review (#4388)

## Summary

Updated **letsplot** implementation for **density-basic**.

**Changes:** Comprehensive quality review

### Changes
- Replaced test scores with marathon finish times data
- Fixed save method from deprecated export_ggsave to ggsave
- Added distinctive features: trim, kernel, adjust, tooltips
- Improved grid to y-axis only
- Quality: 84/100 (local self-evaluation, after 2 iterations)

## Test Plan

- [x] Preview images uploaded to GCS staging
- [x] Implementation file passes ruff format/check
- [x] Metadata YAML updated with current versions
- [ ] Automated review triggered

---
Generated with [Claude Code](https://claude.com/claude-code) `/update`
command

---------

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: MarkusNeusinger

plots/density-basic/implementations/letsplot.py

@@ -1,41 +1,92 @@
 """ pyplots.ai
 density-basic: Basic Density Plot
-Library: letsplot 4.8.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: letsplot 4.8.2 | Python 3.14.3
+Quality: 91/100 | Updated: 2026-02-23
 """
 
 import numpy as np
+import pandas as pd
 from lets_plot import *  # noqa: F403
-from lets_plot.export import ggsave as export_ggsave
 
 
 LetsPlot.setup_html()  # noqa: F405
 
-# Data - Generate realistic test scores with slight right skew
+# Data - Simulated marathon finish times with realistic right skew
 np.random.seed(42)
-scores = np.concatenate(
+finish_minutes = np.concatenate(
     [
-        np.random.normal(72, 12, 300),  # Main group of students
-        np.random.normal(90, 5, 100),  # High achievers
+        np.random.normal(240, 25, 350),  # Main pack (~4 hour runners)
+        np.random.normal(200, 15, 100),  # Competitive runners (~3:20)
+        np.random.normal(300, 20, 50),  # Casual runners (~5 hours)
     ]
 )
+finish_minutes = np.clip(finish_minutes, 140, 400)
 
-# Create plot
+df = pd.DataFrame({"time": finish_minutes})
+
+# Rug data: small vertical ticks at each observation
+rug_df = pd.DataFrame({"x": finish_minutes, "y0": 0.0, "y1": 0.0004})
+
+# Runner group centroids for storytelling annotations (staggered y to avoid crowding)
+group_labels = pd.DataFrame(
+    {
+        "x": [195, 243, 300],
+        "y": [0.0131, 0.0119, 0.0131],
+        "label": ["Competitive (~3:20)", "Main Pack (~4:00)", "Casual (~5:00)"],
+    }
+)
+
+# Plot
 plot = (
-    ggplot({"scores": scores}, aes(x="scores"))  # noqa: F405
-    + geom_density(fill="#306998", color="#306998", alpha=0.6, size=1.5)  # noqa: F405
-    + labs(x="Test Score", y="Density", title="density-basic · letsplot · pyplots.ai")  # noqa: F405
+    ggplot(df, aes(x="time"))  # noqa: F405
+    + geom_density(  # noqa: F405
+        fill="#306998",
+        color="#1e4263",
+        alpha=0.55,
+        size=1.8,
+        kernel="gaussian",
+        adjust=0.85,
+        trim=True,
+        tooltips=layer_tooltips()  # noqa: F405
+        .line("@|@time")
+        .line("density|@..density.."),
+    )
+    + geom_segment(  # noqa: F405
+        data=rug_df,
+        mapping=aes(x="x", y="y0", xend="x", yend="y1"),  # noqa: F405
+        color="#1e4263",
+        alpha=0.15,
+        size=0.4,
+    )
+    + geom_vline(xintercept=200, linetype="dashed", color="#1a5276", alpha=0.4, size=0.7)  # noqa: F405
+    + geom_vline(xintercept=240, linetype="dashed", color="#306998", alpha=0.4, size=0.7)  # noqa: F405
+    + geom_vline(xintercept=300, linetype="dashed", color="#5d8aa8", alpha=0.4, size=0.7)  # noqa: F405
+    + geom_text(  # noqa: F405
+        data=group_labels,
+        mapping=aes(x="x", y="y", label="label"),  # noqa: F405
+        size=12,
+        color="#444444",
+    )
+    + labs(  # noqa: F405
+        x="Finish Time (minutes)", y="Density (×10⁻³)", title="density-basic · letsplot · pyplots.ai"
+    )
+    + scale_x_continuous(breaks=list(range(150, 401, 50)))  # noqa: F405
+    + scale_y_continuous(  # noqa: F405
+        breaks=[0.002, 0.004, 0.006, 0.008, 0.010], labels=["2", "4", "6", "8", "10"], expand=[0.02, 0, 0.38, 0]
+    )
     + theme_minimal()  # noqa: F405
     + theme(  # noqa: F405
         axis_title=element_text(size=20),  # noqa: F405
         axis_text=element_text(size=16),  # noqa: F405
         plot_title=element_text(size=24),  # noqa: F405
-        panel_grid_major=element_line(color="#cccccc", size=0.5),  # noqa: F405
+        panel_grid_major_x=element_blank(),  # noqa: F405
+        panel_grid_major_y=element_line(color="#e0e0e0", size=0.4),  # noqa: F405
         panel_grid_minor=element_blank(),  # noqa: F405
+        axis_ticks=element_blank(),  # noqa: F405
     )
     + ggsize(1600, 900)  # noqa: F405
 )
 
-# Save PNG (scale 3x for 4800x2700) and HTML
-export_ggsave(plot, "plot.png", path=".", scale=3)
-export_ggsave(plot, "plot.html", path=".")
+# Save PNG (scale 3x for 4800 x 2700 px) and HTML
+ggsave(plot, "plot.png", path=".", scale=3)  # noqa: F405
+ggsave(plot, "plot.html", path=".")  # noqa: F405