update(heatmap-basic): seaborn — comprehensive quality review (#4253)

## Summary

Updated **seaborn** implementation for **heatmap-basic**.

**Changes:** Comprehensive quality review — fix weaknesses from prior
reviews, preserve strengths, improve quality across all dimensions.

### Changes
- Addressed review weaknesses from prior quality assessment
- Improved data choice and visual design
- Enhanced library-specific feature usage
- Updated to current library and Python versions
- Quality self-assessment: pending CI review

## 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/heatmap-basic/implementations/seaborn.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 heatmap-basic: Basic Heatmap
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 93/100 | Created: 2025-12-23
+Library: seaborn 0.13.2 | Python 3.14.3
+Quality: 92/100 | Updated: 2026-02-15
 """
 
 import matplotlib.pyplot as plt
@@ -24,35 +24,53 @@
 # Clip to valid performance range
 data = np.clip(data, 5, 95)
 
-# Plot - using square format for heatmap
-fig, ax = plt.subplots(figsize=(12, 12))
-sns.heatmap(
+# Plot - clustermap groups similar departments via hierarchical clustering
+g = sns.clustermap(
     data,
     annot=True,
     fmt=".0f",
-    cmap="RdBu",
+    cmap="coolwarm",
     center=50,
     xticklabels=months,
     yticklabels=departments,
-    linewidths=1,
+    linewidths=1.5,
     linecolor="white",
-    cbar_kws={"label": "Performance Score", "shrink": 0.75},
-    annot_kws={"fontsize": 16},
-    ax=ax,
+    annot_kws={"fontsize": 16, "fontweight": "medium"},
+    figsize=(16, 10),
+    row_cluster=True,
+    col_cluster=False,
+    dendrogram_ratio=0.08,
+    cbar_pos=(0.02, 0.15, 0.03, 0.6),
+    cbar_kws={"label": "Performance Score", "ticks": [0, 25, 50, 75, 100]},
     vmin=0,
     vmax=100,
 )
 
-# Style
-ax.set_xlabel("Month", fontsize=20)
-ax.set_ylabel("Department", fontsize=20)
-ax.set_title("heatmap-basic · seaborn · pyplots.ai", fontsize=24, pad=20)
-ax.tick_params(axis="both", labelsize=16)
+# Colorbar styling
+g.cax.set_ylabel("Performance Score", fontsize=18, labelpad=10)
+g.cax.tick_params(labelsize=14)
+g.cax.yaxis.set_label_position("left")
 
-# Adjust colorbar label size
-cbar = ax.collections[0].colorbar
-cbar.ax.tick_params(labelsize=14)
-cbar.ax.set_ylabel("Performance Score", fontsize=18)
+# Labels and title
+g.ax_heatmap.set_xlabel("Month", fontsize=20, labelpad=12)
+g.ax_heatmap.set_ylabel("Department", fontsize=20, labelpad=12)
+g.ax_heatmap.tick_params(axis="x", labelsize=16)
+g.ax_heatmap.tick_params(axis="y", labelsize=16, rotation=0)
 
-plt.tight_layout()
-plt.savefig("plot.png", dpi=300, bbox_inches="tight")
+# Visual refinement - remove heatmap spines for cleaner look
+for spine in g.ax_heatmap.spines.values():
+    spine.set_visible(False)
+
+# Style the dendrogram
+g.ax_row_dendrogram.set_facecolor("#f8f8f8")
+for spine in g.ax_row_dendrogram.spines.values():
+    spine.set_visible(False)
+
+# Background refinement
+g.fig.patch.set_facecolor("#fafafa")
+g.ax_heatmap.set_facecolor("white")
+
+# Title
+g.fig.suptitle("heatmap-basic · seaborn · pyplots.ai", fontsize=24, fontweight="medium", y=1.02, color="#333333")
+
+plt.savefig("plot.png", dpi=300, bbox_inches="tight", facecolor=g.fig.get_facecolor())