feat(pygal): implement scatter-size-mapped (#2425)

## Implementation: `scatter-size-mapped` - pygal

Implements the **pygal** version of `scatter-size-mapped`.

**File:** `plots/scatter-size-mapped/implementations/pygal.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20543371845)*

---------

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

plots/scatter-size-mapped/implementations/pygal.py

@@ -0,0 +1,96 @@
+""" pyplots.ai
+scatter-size-mapped: Bubble Chart
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-27
+"""
+
+import numpy as np
+import pygal
+from pygal.style import Style
+
+
+# Data: Country economic indicators
+np.random.seed(42)
+
+# Generate 40 synthetic countries across different regions
+n_countries = 40
+regions = ["Europe", "Asia", "Americas", "Africa"]
+
+# Assign regions with some variation
+region_assignments = np.random.choice(regions, n_countries)
+
+# GDP per capita (1,000 - 80,000)
+gdp_per_capita = np.random.uniform(5000, 75000, n_countries)
+# Adjust by region for realism
+for i, region in enumerate(region_assignments):
+    if region == "Europe":
+        gdp_per_capita[i] = np.random.uniform(25000, 75000)
+    elif region == "Asia":
+        gdp_per_capita[i] = np.random.uniform(5000, 60000)
+    elif region == "Americas":
+        gdp_per_capita[i] = np.random.uniform(8000, 70000)
+    else:  # Africa
+        gdp_per_capita[i] = np.random.uniform(1000, 20000)
+
+# Life expectancy (50-85) correlated with GDP
+life_expectancy = 50 + 30 * (gdp_per_capita / 80000) + np.random.uniform(-5, 5, n_countries)
+life_expectancy = np.clip(life_expectancy, 50, 85)
+
+# Population (log scale, 1M - 1.4B)
+population = 10 ** np.random.uniform(6, 9.2, n_countries)
+
+# Create custom style with larger font sizes for better rendering
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    colors=("#306998", "#FFD43B", "#E74C3C", "#27AE60", "#9B59B6"),
+    title_font_size=84,
+    label_font_size=56,
+    major_label_font_size=48,
+    legend_font_size=44,
+    value_font_size=40,
+    opacity=0.6,
+    opacity_hover=0.8,
+)
+
+# Title with size legend information
+title = "scatter-size-mapped · pygal · pyplots.ai\nBubble Size = Population (1M to 1B+)"
+
+# Create XY chart for scatter plot
+chart = pygal.XY(
+    width=4800,
+    height=2700,
+    style=custom_style,
+    title=title,
+    x_title="GDP per Capita (USD)",
+    y_title="Life Expectancy (years)",
+    show_legend=True,
+    legend_at_bottom=True,
+    legend_at_bottom_columns=4,
+    dots_size=15,
+    show_x_guides=True,
+    show_y_guides=True,
+    stroke=False,
+    explicit_size=True,
+    truncate_legend=-1,
+)
+
+# Group data by region and add as series
+# Pygal XY chart uses value dict with 'value' for coordinates
+for region in regions:
+    mask = region_assignments == region
+    points = []
+    for i in np.where(mask)[0]:
+        # Scale population to reasonable dot size (log scale)
+        # Population ranges from 1M to 1.4B, scale to 12-70 for better visibility
+        # Increased minimum size from 5 to 12 so smaller bubbles are visible
+        size = 12 + 58 * (np.log10(population[i]) - 6) / 3.2
+        points.append({"value": (float(gdp_per_capita[i]), float(life_expectancy[i])), "node": {"r": size}})
+    chart.add(region, points)
+
+# Render to files
+chart.render_to_png("plot.png")
+chart.render_to_file("plot.html")

plots/scatter-size-mapped/metadata/pygal.yaml

@@ -0,0 +1,29 @@
+library: pygal
+specification_id: scatter-size-mapped
+created: '2025-12-27T19:31:03Z'
+updated: '2025-12-27T19:43:26Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20543371845
+issue: 0
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-size-mapped/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-size-mapped/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-size-mapped/pygal/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent realistic data generation with regional economic patterns (Europe higher
+    GDP, Africa lower GDP)
+  - Proper use of pygal XY chart with custom node sizes via the node dict parameter
+    for bubble sizing
+  - Well-implemented semi-transparency (opacity=0.6) for distinguishing overlapping
+    bubbles
+  - Clean code structure following KISS principles with proper seed for reproducibility
+  - Size legend integrated into title subtitle (Bubble Size = Population 1M to 1B+)
+  - Improved minimum bubble size (12) from previous attempt makes smaller populations
+    more visible
+  weaknesses:
+  - Grid lines are too subtle and barely visible - could use more prominent guide
+    styling
+  - Title format includes subtitle which slightly deviates from the exact spec format