feat(altair): implement area-stacked-percent (#2676)

## Implementation: `area-stacked-percent` - altair

Implements the **altair** version of `area-stacked-percent`.

**File:** `plots/area-stacked-percent/implementations/altair.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20595338920)*

---------

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/area-stacked-percent/implementations/altair.py

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+""" pyplots.ai
+area-stacked-percent: 100% Stacked Area Chart
+Library: altair 6.0.0 | Python 3.13.11
+Quality: 92/100 | Created: 2025-12-30
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data - Energy source mix evolution (percentage of total)
+np.random.seed(42)
+years = list(range(2015, 2025))
+
+# Start with base percentages and evolve them (showing transition from fossil to renewables)
+coal = [45, 42, 39, 35, 32, 28, 25, 22, 19, 16]
+natural_gas = [25, 26, 27, 28, 29, 30, 31, 31, 30, 28]
+nuclear = [12, 12, 12, 12, 12, 12, 12, 12, 12, 12]
+renewables = [18, 20, 22, 25, 27, 30, 32, 35, 39, 44]
+
+# Create DataFrame in long format for Altair
+data = []
+for i, year in enumerate(years):
+    data.append({"Year": year, "Source": "Coal", "Percentage": coal[i]})
+    data.append({"Year": year, "Source": "Natural Gas", "Percentage": natural_gas[i]})
+    data.append({"Year": year, "Source": "Nuclear", "Percentage": nuclear[i]})
+    data.append({"Year": year, "Source": "Renewables", "Percentage": renewables[i]})
+
+df = pd.DataFrame(data)
+
+# Define category order for stacking (bottom to top) using numeric order
+source_order = ["Coal", "Natural Gas", "Nuclear", "Renewables"]
+stack_order = {"Coal": 1, "Natural Gas": 2, "Nuclear": 3, "Renewables": 4}
+df["StackOrder"] = df["Source"].map(stack_order)
+
+# Color palette using Python colors and complementary
+colors = ["#306998", "#FFD43B", "#7B68EE", "#2E8B57"]
+
+# Plot - 100% Stacked Area Chart
+chart = (
+    alt.Chart(df)
+    .mark_area(opacity=0.85, line=alt.MarkConfig(strokeWidth=2))
+    .encode(
+        x=alt.X("Year:O", title="Year", axis=alt.Axis(labelFontSize=18, titleFontSize=22, labelAngle=0)),
+        y=alt.Y(
+            "Percentage:Q",
+            title="Share of Energy Mix (%)",
+            stack="normalize",
+            axis=alt.Axis(labelFontSize=18, titleFontSize=22, format=".0%"),
+        ),
+        color=alt.Color(
+            "Source:N",
+            scale=alt.Scale(domain=source_order, range=colors),
+            legend=alt.Legend(
+                title="Energy Source",
+                titleFontSize=20,
+                labelFontSize=18,
+                orient="right",
+                symbolSize=300,
+                symbolStrokeWidth=0,
+            ),
+        ),
+        order=alt.Order("StackOrder:Q", sort="ascending"),
+        tooltip=[
+            alt.Tooltip("Year:O", title="Year"),
+            alt.Tooltip("Source:N", title="Source"),
+            alt.Tooltip("Percentage:Q", title="Share", format=".1f"),
+        ],
+    )
+    .properties(
+        width=1400,
+        height=800,
+        title=alt.Title(text="area-stacked-percent · altair · pyplots.ai", fontSize=28, anchor="middle"),
+    )
+    .configure_axis(grid=True, gridOpacity=0.3, gridDash=[4, 4])
+    .configure_view(strokeWidth=0)
+)
+
+# Save
+chart.save("plot.png", scale_factor=3.0)
+chart.interactive().save("plot.html")

plots/area-stacked-percent/metadata/altair.yaml

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+library: altair
+specification_id: area-stacked-percent
+created: '2025-12-30T11:23:32Z'
+updated: '2025-12-30T11:36:09Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20595338920
+issue: 0
+python_version: 3.13.11
+library_version: 6.0.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/area-stacked-percent/altair/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/area-stacked-percent/altair/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/area-stacked-percent/altair/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent use of Altair's declarative grammar with stack="normalize" for proper
+    100% stacking
+  - Clear, compelling real-world narrative (energy transition) that perfectly demonstrates
+    the spec
+  - Clean code structure following KISS principles with well-organized long-format
+    data
+  - Good typography sizing making all text highly readable
+  - Appropriate use of tooltips and interactive HTML export
+  - Proper stacking order using explicit order encoding
+  weaknesses:
+  - Legend positioned outside creates slight whitespace imbalance; consider moving
+    inside plot area
+  - Nuclear data staying perfectly flat at 12% for all 10 years feels artificially
+    constant