feat(pygal): implement elbow-curve

plots/elbow-curve/implementations/pygal.py

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+""" pyplots.ai
+elbow-curve: Elbow Curve for K-Means Clustering
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-26
+"""
+
+import pygal
+from pygal.style import Style
+
+
+# Simulated K-means inertia data showing clear elbow at k=4
+# Represents clustering analysis on customer segmentation dataset
+k_values = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+inertias = [4200, 2100, 1200, 680, 580, 510, 460, 420, 390, 365]
+
+# Custom style for pyplots
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    colors=("#306998", "#FFD43B", "#E74C3C"),
+    title_font_size=48,
+    label_font_size=36,
+    major_label_font_size=32,
+    legend_font_size=32,
+    value_font_size=24,
+    stroke_width=4,
+    value_label_font_size=24,
+    tooltip_font_size=24,
+)
+
+# Create XY chart for line plot with markers
+chart = pygal.XY(
+    width=4800,
+    height=2700,
+    style=custom_style,
+    title="elbow-curve · pygal · pyplots.ai",
+    x_title="Number of Clusters (k)",
+    y_title="Inertia (Within-cluster Sum of Squares)",
+    show_legend=True,
+    legend_at_bottom=True,
+    legend_at_bottom_columns=2,
+    show_x_guides=False,
+    show_y_guides=True,
+    dots_size=12,
+    stroke_style={"width": 4, "linecap": "round", "linejoin": "round"},
+    truncate_legend=-1,
+    x_labels=k_values,
+    range=(0, max(inertias) * 1.05),
+    include_x_axis=True,
+    explicit_size=True,
+    margin=50,
+    spacing=30,
+)
+
+# Prepare data as (x, y) tuples
+elbow_data = [(k, inertia) for k, inertia in zip(k_values, inertias, strict=True)]
+
+# Add elbow curve data
+chart.add("Inertia", elbow_data, stroke_style={"width": 4})
+
+# Highlight optimal elbow point (k=4 based on the generated data)
+elbow_k = 4
+elbow_inertia = inertias[elbow_k - 1]
+chart.add("Optimal k", [(elbow_k, elbow_inertia)], dots_size=20)
+
+# Save as PNG and HTML
+chart.render_to_png("plot.png")
+chart.render_to_file("plot.html")

plots/elbow-curve/metadata/pygal.yaml

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+library: pygal
+specification_id: elbow-curve
+created: '2025-12-26T19:57:22Z'
+updated: '2025-12-26T19:59:31Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20528466148
+issue: 0
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/elbow-curve/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/elbow-curve/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/elbow-curve/pygal/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Clear visualization of the elbow curve with excellent readability
+  - Optimal k value (elbow point) is highlighted with a distinct larger yellow marker
+  - Proper title format and descriptive axis labels with full context
+  - Clean KISS code structure following pygal best practices
+  - Good color contrast between the main line and elbow highlight
+  - Data realistically demonstrates the diminishing returns pattern
+  weaknesses:
+  - Legend positioned quite far from the plot area at the bottom
+  - Could use pygal built-in annotation or tooltip features to enhance the elbow point
+    indication