update(hexbin-basic): seaborn — comprehensive quality review

- Simplified code, improved hexbin styling
- Better color palette and density visualization
- Enhanced layout and legibility

Author: MarkusNeusinger

plots/hexbin-basic/implementations/seaborn.py

@@ -1,63 +1,58 @@
 """ pyplots.ai
 hexbin-basic: Basic Hexbin Plot
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 90/100 | Created: 2025-12-23
+Library: seaborn 0.13.2 | Python 3.14.3
+Quality: /100 | Updated: 2026-02-21
 """
 
 import numpy as np
-import pandas as pd
 import seaborn as sns
+from matplotlib.colors import LogNorm
 
 
 # Data - simulate GPS coordinates for urban traffic hotspot analysis
 np.random.seed(42)
 
-# Create realistic GPS coordinate clusters representing traffic hotspots
-# Using a larger dataset (50,000 points) to demonstrate hexbin advantage over scatter
+# 50,000 points to demonstrate hexbin advantage over scatter
 n_points = 50000
 
-# Downtown business district - high density
+# Downtown business district - high density cluster
 downtown = np.random.multivariate_normal([-73.985, 40.748], [[0.0001, 0.00005], [0.00005, 0.0001]], n_points // 2)
 
-# Airport area - medium density
+# Airport area - medium density cluster
 airport = np.random.multivariate_normal([-73.875, 40.775], [[0.00008, -0.00003], [-0.00003, 0.00008]], n_points // 3)
 
 # Shopping district - smaller cluster
 shopping = np.random.multivariate_normal([-73.965, 40.785], [[0.00004, 0], [0, 0.00006]], n_points // 6)
 
-# Combine clusters into DataFrame for seaborn
 longitude = np.concatenate([downtown[:, 0], airport[:, 0], shopping[:, 0]])
 latitude = np.concatenate([downtown[:, 1], airport[:, 1], shopping[:, 1]])
-df = pd.DataFrame({"Longitude": longitude, "Latitude": latitude})
 
-# Set seaborn style for clean aesthetics
+# Plot - seaborn JointGrid with hexbin and marginal distributions
 sns.set_theme(style="whitegrid", context="talk", font_scale=1.2)
 
-# Create JointGrid for hexbin with marginal distributions
-g = sns.JointGrid(data=df, x="Longitude", y="Latitude", height=12, ratio=5, space=0.2)
+g = sns.JointGrid(x=longitude, y=latitude, height=12, ratio=5, space=0.15)
 
-# Main hexbin plot using plot_joint
-hb = g.ax_joint.hexbin(df["Longitude"], df["Latitude"], gridsize=35, cmap="viridis", mincnt=1, edgecolors="none")
+# Main hexbin with log-normalized color scale for wide density variation
+hb = g.ax_joint.hexbin(longitude, latitude, gridsize=35, cmap="viridis", mincnt=1, norm=LogNorm(), edgecolors="none")
 
-# Marginal distributions using seaborn's histplot
-g.plot_marginals(sns.histplot, kde=True, color="#306998", alpha=0.6, linewidth=0)
+# Marginal distributions - distinctive seaborn feature
+g.plot_marginals(sns.kdeplot, color="#306998", fill=True, alpha=0.4, linewidth=2)
 
-# Add colorbar to show density scale
+# Colorbar for density scale
 cbar = g.figure.colorbar(hb, ax=g.ax_joint, pad=0.02, shrink=0.8)
-cbar.set_label("Point Count", fontsize=20)
+cbar.set_label("Point Count (log scale)", fontsize=20)
 cbar.ax.tick_params(labelsize=16)
 
-# Labels and title with proper sizing
+# Style
 g.ax_joint.set_xlabel("Longitude (°W)", fontsize=20)
 g.ax_joint.set_ylabel("Latitude (°N)", fontsize=20)
 g.ax_joint.tick_params(axis="both", labelsize=16)
+g.ax_joint.grid(True, alpha=0.2, linestyle="--", linewidth=0.8)
+g.ax_joint.spines["top"].set_visible(False)
+g.ax_joint.spines["right"].set_visible(False)
 
-# Subtle grid on main plot
-g.ax_joint.grid(True, alpha=0.3, linestyle="--", linewidth=0.8)
-
-# Title at top of figure
 g.figure.suptitle("hexbin-basic · seaborn · pyplots.ai", fontsize=24, y=0.98)
 
-# Adjust layout to prevent clipping
+# Save
 g.figure.tight_layout(rect=[0, 0, 1, 0.96])
 g.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/hexbin-basic/metadata/seaborn.yaml

@@ -1,16 +1,16 @@
 library: seaborn
 specification_id: hexbin-basic
 created: '2025-12-23T01:30:30Z'
-updated: '2025-12-23T07:01:09Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-21T21:02:15+00:00'
+generated_by: claude-opus-4-6
 workflow_run: 20448651717
 issue: 0
-python_version: 3.13.11
+python_version: 3.14.3
 library_version: 0.13.2
 preview_url: https://storage.googleapis.com/pyplots-images/plots/hexbin-basic/seaborn/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/hexbin-basic/seaborn/plot_thumb.png
 preview_html: null
-quality_score: 90
+quality_score: null
 impl_tags:
   dependencies: []
   techniques: