update(violin-basic): seaborn — 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/seaborn.py

@@ -1,7 +1,7 @@
 """ pyplots.ai
 violin-basic: Basic Violin Plot
-Library: seaborn 0.13.2 | Python 3.13.11
-Quality: 92/100 | Created: 2025-12-23
+Library: seaborn 0.13.2 | Python 3.14.3
+Quality: /100 | Updated: 2026-02-21
 """
 
 import matplotlib.pyplot as plt
@@ -12,25 +12,23 @@
 
 # Data - Salary distributions across departments
 np.random.seed(42)
-categories = ["Engineering", "Marketing", "Sales", "Support"]
-data = []
-
-for cat in categories:
-    # Different distribution shapes per category
-    if cat == "Engineering":
-        values = np.random.normal(85000, 15000, 150)
-    elif cat == "Marketing":
-        values = np.random.normal(70000, 12000, 150)
-    elif cat == "Sales":
-        # Bimodal distribution for sales (junior vs senior)
-        values = np.concatenate([np.random.normal(55000, 8000, 75), np.random.normal(90000, 10000, 75)])
-    else:  # Support
-        values = np.random.normal(55000, 10000, 150)
-
-    for v in values:
-        data.append({"Department": cat, "Salary": v})
-
-df = pd.DataFrame(data)
+departments = ["Engineering", "Marketing", "Sales", "Support"]
+records = []
+
+for dept in departments:
+    if dept == "Engineering":
+        salaries = np.random.normal(85000, 15000, 150)
+    elif dept == "Marketing":
+        salaries = np.random.normal(70000, 12000, 150)
+    elif dept == "Sales":
+        # Bimodal distribution (junior vs senior) — showcases KDE strength
+        salaries = np.concatenate([np.random.normal(55000, 8000, 75), np.random.normal(90000, 10000, 75)])
+    else:
+        salaries = np.random.normal(55000, 10000, 150)
+    for s in salaries:
+        records.append({"Department": dept, "Salary": s})
+
+df = pd.DataFrame(records)
 
 # Plot
 fig, ax = plt.subplots(figsize=(16, 9))
@@ -40,19 +38,24 @@
     x="Department",
     y="Salary",
     hue="Department",
-    palette=["#306998", "#FFD43B", "#306998", "#FFD43B"],
-    inner="quart",  # Show quartiles inside violin
-    linewidth=2,
+    palette=["#306998", "#4A90C4", "#2D5F8A", "#5BA3D9"],
+    inner="box",
+    cut=0,
+    linewidth=1.5,
+    saturation=0.9,
     legend=False,
     ax=ax,
 )
 
 # Style
 ax.set_xlabel("Department", fontsize=20)
 ax.set_ylabel("Salary ($)", fontsize=20)
-ax.set_title("violin-basic · seaborn · pyplots.ai", fontsize=24)
+ax.set_title("violin-basic \u00b7 seaborn \u00b7 pyplots.ai", fontsize=24, fontweight="medium")
 ax.tick_params(axis="both", labelsize=16)
-ax.grid(True, alpha=0.3, linestyle="--", axis="y")
+ax.spines["top"].set_visible(False)
+ax.spines["right"].set_visible(False)
+ax.yaxis.grid(True, alpha=0.2, linewidth=0.8)
+ax.set_axisbelow(True)
 
 # Format y-axis as currency
 ax.yaxis.set_major_formatter(plt.FuncFormatter(lambda x, p: f"${x / 1000:.0f}k"))

plots/violin-basic/metadata/seaborn.yaml

@@ -1,16 +1,16 @@
 library: seaborn
 specification_id: violin-basic
 created: '2025-12-23T00:36:01Z'
-updated: '2025-12-23T00:39:02Z'
-generated_by: claude-opus-4-5-20251101
+updated: '2026-02-21T22:25:00+00:00'
+generated_by: claude-opus-4-6
 workflow_run: 20447774216
 issue: 0
-python_version: 3.13.11
-library_version: 0.13.2
+python_version: '3.14.3'
+library_version: '0.13.2'
 preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-basic/seaborn/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-basic/seaborn/plot_thumb.png
 preview_html: null
-quality_score: 92
+quality_score: null
 impl_tags:
   dependencies: []
   techniques: []