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

- Improved geom_hex usage
- Better color scales and themes
- Enhanced layout and legibility

Author: MarkusNeusinger

plots/hexbin-basic/implementations/letsplot.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 hexbin-basic: Basic Hexbin Plot
-Library: letsplot 4.8.1 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: letsplot 4.8.2 | Python 3.14.3
+Quality: /100 | Updated: 2026-02-21
 """
 
 import numpy as np
@@ -16,6 +16,7 @@
     ggplot,
     ggsize,
     labs,
+    layer_tooltips,
     scale_fill_viridis,
     theme,
     theme_minimal,
@@ -25,37 +26,55 @@
 
 LetsPlot.setup_html()
 
-# Data - Generate clustered bivariate distribution for density visualization
+# Data - Simulated GPS ping density across a metro area (km from city center)
 np.random.seed(42)
 n_points = 10000
 
-# Create multiple clusters to demonstrate density patterns in hexbin visualization
-cluster1_x = np.random.randn(n_points // 2) * 1.5 + 3
-cluster1_y = np.random.randn(n_points // 2) * 1.5 + 3
-cluster2_x = np.random.randn(n_points // 3) * 1.2 - 2
-cluster2_y = np.random.randn(n_points // 3) * 1.2 + 1
-cluster3_x = np.random.randn(n_points // 6) * 0.6 + 0
-cluster3_y = np.random.randn(n_points // 6) * 0.6 - 3
+# Downtown core - dense commercial district
+downtown_east = np.random.randn(n_points // 2) * 1.5 + 4
+downtown_north = np.random.randn(n_points // 2) * 1.5 + 3
 
-x = np.concatenate([cluster1_x, cluster2_x, cluster3_x])
-y = np.concatenate([cluster1_y, cluster2_y, cluster3_y])
+# University campus - moderate foot traffic
+campus_east = np.random.randn(n_points // 3) * 1.0 - 3
+campus_north = np.random.randn(n_points // 3) * 1.0 + 1
 
-df = pd.DataFrame({"x": x, "y": y})
+# Transit hub - tight cluster of commuters
+transit_east = np.random.randn(n_points // 6) * 0.5 + 0.5
+transit_north = np.random.randn(n_points // 6) * 0.5 - 3.5
 
-# Plot - Hexagonal binning to reveal density patterns
+east_km = np.concatenate([downtown_east, campus_east, transit_east])
+north_km = np.concatenate([downtown_north, campus_north, transit_north])
+
+df = pd.DataFrame({"east_km": east_km, "north_km": north_km})
+
+# Plot - Hexagonal binning to reveal pedestrian density hotspots
 plot = (
-    ggplot(df, aes(x="x", y="y"))
-    + geom_hex(bins=[35, 35])
-    + scale_fill_viridis(name="Count", option="viridis")
-    + labs(x="X Coordinate", y="Y Coordinate", title="hexbin-basic · letsplot · pyplots.ai")
+    ggplot(df, aes(x="east_km", y="north_km"))
+    + geom_hex(
+        aes(fill="..count.."),
+        bins=[30, 30],
+        color="#FFFFFF",
+        size=0.3,
+        tooltips=layer_tooltips()
+        .title("Hex Bin")
+        .line("pings|@..count..")
+        .line("density|@..density..")
+        .format("@..density..", ".3f"),
+    )
+    + scale_fill_viridis(name="Ping Count", option="viridis")
+    + labs(
+        x="East-West (km from center)",
+        y="North-South (km from center)",
+        title="hexbin-basic \u00b7 letsplot \u00b7 pyplots.ai",
+    )
     + theme_minimal()
     + theme(
         axis_title=element_text(size=22),
         axis_text=element_text(size=18),
         plot_title=element_text(size=26),
         legend_text=element_text(size=16),
         legend_title=element_text(size=18),
-        panel_grid=element_line(color="#CCCCCC", size=0.4, linetype="dashed"),
+        panel_grid=element_line(color="#E0E0E0", size=0.3, linetype="dashed"),
         panel_background=element_rect(fill="#FAFAFA"),
     )
     + ggsize(1600, 900)
@@ -64,5 +83,5 @@
 # Save PNG (scale=3 gives 4800x2700)
 ggsave(plot, "plot.png", path=".", scale=3)
 
-# Save HTML for interactivity
+# Save HTML for interactive tooltips
 ggsave(plot, "plot.html", path=".")

plots/hexbin-basic/metadata/letsplot.yaml

@@ -1,16 +1,16 @@
 library: letsplot
 specification_id: hexbin-basic
 created: '2025-12-23T01:31:08Z'
-updated: '2025-12-23T06:54:49Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-21T21:02:15+00:00'
+generated_by: claude-opus-4-6
 workflow_run: 20448655355
 issue: 0
-python_version: 3.13.11
-library_version: 4.8.1
+python_version: 3.14.3
+library_version: 4.8.2
 preview_url: https://storage.googleapis.com/pyplots-images/plots/hexbin-basic/letsplot/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/hexbin-basic/letsplot/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/hexbin-basic/letsplot/plot.html
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies: []
   techniques: