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

Comprehensive quality review improving code quality, data choice, visual design, spec compliance, and library feature usage.

Author: MarkusNeusinger

plots/violin-basic/implementations/letsplot.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 violin-basic: Basic Violin 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
@@ -16,9 +16,8 @@
 np.random.seed(42)
 
 categories = ["Engineering", "Marketing", "Sales", "Design"]
-colors = ["#306998", "#FFD43B", "#4B8BBE", "#FFE873"]
+colors = ["#306998", "#E8A317", "#4B8BBE", "#2E8B57"]
 
-# Generate realistic salary distributions per department
 data = []
 distributions = {
     "Engineering": {"mean": 95000, "std": 20000, "n": 200},
@@ -30,7 +29,7 @@
 for cat in categories:
     dist = distributions[cat]
     values = np.random.normal(dist["mean"], dist["std"], dist["n"])
-    values = np.clip(values, 30000, 200000)  # Realistic salary bounds
+    values = np.clip(values, 30000, 200000)
     for v in values:
         data.append({"Department": cat, "Salary": v})
 
@@ -40,28 +39,27 @@
 plot = (
     ggplot(df, aes(x="Department", y="Salary", fill="Department"))  # noqa: F405
     + geom_violin(  # noqa: F405
-        quantiles=[0.25, 0.5, 0.75],  # Show quartiles including median
-        quantile_lines=True,  # Draw lines at quantiles
-        size=1.5,  # Border thickness
-        alpha=0.8,
-        trim=False,  # Show full tails
+        quantiles=[0.25, 0.5, 0.75], quantile_lines=True, size=1.2, alpha=0.85, trim=False, color="#2C3E50"
     )
     + scale_fill_manual(values=colors)  # noqa: F405
+    + scale_y_continuous(  # noqa: F405
+        format="${,.0f}"
+    )
     + labs(  # noqa: F405
-        x="Department", y="Salary ($)", title="violin-basic · lets-plot · pyplots.ai"
+        x="Department", y="Salary", title="violin-basic \u00b7 letsplot \u00b7 pyplots.ai"
     )
     + 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
-        legend_position="none",  # Legend not needed, x-axis shows categories
+        legend_position="none",
+        panel_grid_major_x=element_blank(),  # noqa: F405
+        axis_ticks=element_blank(),  # noqa: F405
     )
     + ggsize(1600, 900)  # noqa: F405
 )
 
-# Save PNG (scale 3x to get 4800 × 2700 px)
+# Save
 export_ggsave(plot, filename="plot.png", path=".", scale=3)
-
-# Save HTML for interactive version
 export_ggsave(plot, filename="plot.html", path=".")

plots/violin-basic/metadata/letsplot.yaml

@@ -1,16 +1,16 @@
 library: letsplot
 specification_id: violin-basic
 created: '2025-12-23T00:36:17Z'
-updated: '2025-12-23T00:39:43Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-21T22:25:00+00:00'
+generated_by: claude-opus-4-6
 workflow_run: 20447783845
 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/violin-basic/letsplot/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/letsplot/plot_thumb.png
 preview_html: https://storage.googleapis.com/pyplots-images/plots/violin-basic/letsplot/plot.html
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies: []
   techniques: