feat(pygal): implement choropleth-basic

plots/choropleth-basic/implementations/pygal.py

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+""" pyplots.ai
+choropleth-basic: Choropleth Map with Regional Coloring
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import numpy as np
+from pygal.style import Style
+from pygal_maps_world.maps import World
+
+
+# Data: GDP per capita (synthetic but realistic ranges)
+np.random.seed(42)
+
+# Select a diverse set of countries from different regions
+country_codes = [
+    # Americas
+    "us",
+    "ca",
+    "mx",
+    "br",
+    "ar",
+    "cl",
+    "co",
+    "pe",
+    # Europe
+    "de",
+    "fr",
+    "gb",
+    "it",
+    "es",
+    "nl",
+    "se",
+    "no",
+    "pl",
+    "pt",
+    # Asia
+    "cn",
+    "jp",
+    "in",
+    "kr",
+    "id",
+    "th",
+    "vn",
+    "my",
+    # Africa
+    "za",
+    "eg",
+    "ng",
+    "ke",
+    "ma",
+    "gh",
+    # Oceania
+    "au",
+    "nz",
+]
+
+# Generate realistic GDP per capita values (in thousands USD)
+high_income = ["us", "ca", "de", "fr", "gb", "nl", "se", "no", "jp", "kr", "au", "nz"]
+upper_middle = ["mx", "br", "ar", "cl", "cn", "my", "za", "pl", "pt", "it", "es"]
+
+gdp_data = {}
+for code in country_codes:
+    if code in high_income:
+        gdp_data[code] = np.random.uniform(40, 85)
+    elif code in upper_middle:
+        gdp_data[code] = np.random.uniform(10, 40)
+    else:
+        gdp_data[code] = np.random.uniform(1, 15)
+
+# Bin data into ranges for legend clarity
+bins = [
+    ("GDP < $10k", {k: v for k, v in gdp_data.items() if v < 10}),
+    ("GDP $10k-$25k", {k: v for k, v in gdp_data.items() if 10 <= v < 25}),
+    ("GDP $25k-$50k", {k: v for k, v in gdp_data.items() if 25 <= v < 50}),
+    ("GDP > $50k", {k: v for k, v in gdp_data.items() if v >= 50}),
+]
+
+# Sequential blue palette for choropleth (light to dark)
+colors = ["#a6cee3", "#6baed6", "#3182bd", "#08519c"]
+
+# Custom style for large canvas
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#111111",
+    foreground_subtle="#666666",
+    colors=tuple(colors),
+    title_font_size=80,
+    label_font_size=48,
+    legend_font_size=48,
+    major_label_font_size=40,
+    value_font_size=40,
+    tooltip_font_size=36,
+    no_data_font_size=36,
+)
+
+# Create world map
+worldmap = World(
+    style=custom_style,
+    width=4800,
+    height=2700,
+    title="choropleth-basic \u00b7 pygal \u00b7 pyplots.ai",
+    show_legend=True,
+    legend_at_bottom=True,
+    legend_at_bottom_columns=4,
+    legend_box_size=40,
+)
+
+# Add each bin as a separate series
+for label, data in bins:
+    worldmap.add(label, data)
+
+# Save outputs
+worldmap.render_to_file("plot.html")
+worldmap.render_to_png("plot.png")

plots/choropleth-basic/metadata/pygal.yaml

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+library: pygal
+specification_id: choropleth-basic
+created: '2025-12-31T13:57:54Z'
+updated: '2025-12-31T14:09:13Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20620327898
+issue: 3069
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/choropleth-basic/pygal/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent use of pygal_maps_world extension for creating a world choropleth map
+  - Sequential blue color palette is visually appealing and colorblind-accessible
+  - Good binning approach that creates clear visual distinctions between income levels
+  - Comprehensive geographic coverage spanning all major continents
+  - Custom Style properly scales fonts for the 4800x2700 canvas size
+  - Legend placement at bottom with 4 columns efficiently organizes the GDP ranges
+  weaknesses:
+  - Missing data countries shown as white rather than gray as suggested in spec
+  - Could leverage pygal's built-in tooltip/hover interactivity more prominently