update(box-basic): plotnine — comprehensive quality review and improvement

Author: MarkusNeusinger

plots/box-basic/implementations/plotnine.py

@@ -1,50 +1,75 @@
 """ pyplots.ai
 box-basic: Basic Box Plot
-Library: plotnine 0.15.2 | Python 3.13.11
-Quality: 91/100 | Created: 2025-12-23
+Library: plotnine 0.15.3 | Python 3.14
+Quality: /100 | Updated: 2026-02-14
 """
 
 import numpy as np
 import pandas as pd
-from plotnine import aes, element_text, geom_boxplot, ggplot, labs, theme, theme_minimal
+from plotnine import (
+    aes,
+    coord_cartesian,
+    element_blank,
+    element_line,
+    element_text,
+    geom_boxplot,
+    ggplot,
+    labs,
+    scale_fill_brewer,
+    theme,
+    theme_minimal,
+)
 
 
 # Data
 np.random.seed(42)
-categories = ["Engineering", "Marketing", "Sales", "Support"]
-data = {"category": [], "value": []}
+categories = ["Engineering", "Marketing", "Sales", "Support", "Research"]
+records = []
 
-# Generate salary data for each department with varied distributions
 for cat in categories:
-    n = np.random.randint(50, 150)
+    n = np.random.randint(60, 120)
     if cat == "Engineering":
         values = np.random.normal(95000, 15000, n)
     elif cat == "Marketing":
         values = np.random.normal(75000, 12000, n)
     elif cat == "Sales":
-        values = np.random.normal(70000, 20000, n)
-    else:  # Support
-        values = np.random.normal(55000, 10000, n)
-    data["category"].extend([cat] * n)
-    data["value"].extend(values)
+        base = np.random.normal(68000, 18000, n)
+        outliers = np.random.uniform(120000, 145000, 5)
+        values = np.concatenate([base, outliers])
+    elif cat == "Support":
+        values = np.random.normal(55000, 8000, n)
+    else:  # Research
+        values = np.random.normal(85000, 20000, n)
+    records.extend({"department": cat, "salary": v} for v in values)
 
-df = pd.DataFrame(data)
+df = pd.DataFrame(records)
+dept_order = ["Support", "Marketing", "Sales", "Research", "Engineering"]
+df["department"] = pd.Categorical(df["department"], categories=dept_order, ordered=True)
 
 # Plot
 plot = (
-    ggplot(df, aes(x="category", y="value", fill="category"))
-    + geom_boxplot(outlier_size=3, outlier_alpha=0.6, size=0.8)
-    + labs(x="Department", y="Salary ($)", title="box-basic · plotnine · pyplots.ai")
+    ggplot(df, aes(x="department", y="salary", fill="department"))
+    + geom_boxplot(outlier_size=2.5, outlier_alpha=0.5, outlier_colour="#555555", size=0.6, alpha=0.85)
+    + scale_fill_brewer(type="qual", palette="Set2")
+    + coord_cartesian(ylim=(25000, 155000))
+    + labs(x="Department", y="Salary ($)", title="box-basic \u00b7 plotnine \u00b7 pyplots.ai")
     + theme_minimal()
     + theme(
         figure_size=(16, 9),
         text=element_text(size=14),
+        plot_title=element_text(size=24, weight="bold"),
         axis_title=element_text(size=20),
         axis_text=element_text(size=16),
-        plot_title=element_text(size=24),
         legend_position="none",
+        panel_grid_major_x=element_blank(),
+        panel_grid_minor=element_blank(),
+        panel_grid_major_y=element_line(color="#DDDDDD", size=0.5, alpha=0.4),
+        axis_line_x=element_line(color="#333333", size=0.5),
+        axis_line_y=element_line(color="#333333", size=0.5),
+        axis_ticks_major_x=element_blank(),
+        axis_ticks_major_y=element_blank(),
     )
 )
 
 # Save
-plot.save("plot.png", dpi=300, verbose=False)
+plot.save("plot.png", dpi=300)

plots/box-basic/metadata/plotnine.yaml

@@ -1,16 +1,16 @@
 library: plotnine
 specification_id: box-basic
 created: '2025-12-23T00:36:35Z'
-updated: '2025-12-23T00:40:39Z'
-generated_by: claude-opus-4-5-20251101
+updated: 2026-02-14T22:09:08+00:00
+generated_by: claude-opus-4-6
 workflow_run: 20447781993
 issue: 0
-python_version: 3.13.11
-library_version: 0.15.2
+python_version: "3.14"
+library_version: "0.15.3"
 preview_url: https://storage.googleapis.com/pyplots-images/plots/box-basic/plotnine/plot.png
 preview_thumb: https://storage.googleapis.com/pyplots-images/plots/box-basic/plotnine/plot_thumb.png
 preview_html: null
-quality_score: 91
+quality_score: null
 impl_tags:
   dependencies: []
   techniques: []