feat(altair): implement histogram-stacked (#2618)

## Implementation: `histogram-stacked` - altair

Implements the **altair** version of `histogram-stacked`.

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

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20594559490)*

---------

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

Author: github-actions[bot]

plots/histogram-stacked/implementations/altair.py

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+""" pyplots.ai
+histogram-stacked: Stacked Histogram
+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 - Test scores from three different study methods
+np.random.seed(42)
+
+# Generate realistic test score distributions for three study methods
+method_a = np.random.normal(loc=72, scale=10, size=150)  # Traditional study
+method_b = np.random.normal(loc=78, scale=8, size=120)  # Active recall
+method_c = np.random.normal(loc=68, scale=12, size=100)  # Passive reading
+
+# Clip to valid score range (0-100)
+method_a = np.clip(method_a, 0, 100)
+method_b = np.clip(method_b, 0, 100)
+method_c = np.clip(method_c, 0, 100)
+
+# Create DataFrame
+df = pd.DataFrame(
+    {
+        "Score": np.concatenate([method_a, method_b, method_c]),
+        "Study Method": (
+            ["Traditional Study"] * len(method_a)
+            + ["Active Recall"] * len(method_b)
+            + ["Passive Reading"] * len(method_c)
+        ),
+    }
+)
+
+# Create stacked histogram using binned bar chart
+chart = (
+    alt.Chart(df)
+    .mark_bar(opacity=0.85, stroke="white", strokeWidth=0.5)
+    .encode(
+        x=alt.X(
+            "Score:Q",
+            bin=alt.Bin(maxbins=20),
+            title="Test Score (points)",
+            axis=alt.Axis(labelFontSize=18, titleFontSize=22),
+        ),
+        y=alt.Y(
+            "count():Q", title="Number of Students", stack="zero", axis=alt.Axis(labelFontSize=18, titleFontSize=22)
+        ),
+        color=alt.Color(
+            "Study Method:N",
+            scale=alt.Scale(
+                domain=["Traditional Study", "Active Recall", "Passive Reading"],
+                range=["#306998", "#FFD43B", "#E67E22"],
+            ),
+            legend=alt.Legend(title="Study Method", titleFontSize=18, labelFontSize=16, orient="right"),
+        ),
+        order=alt.Order("Study Method:N", sort="ascending"),
+    )
+    .properties(
+        width=1600, height=900, title=alt.Title("histogram-stacked · altair · pyplots.ai", fontSize=28, anchor="middle")
+    )
+    .configure_axis(grid=True, gridOpacity=0.3, gridDash=[2, 2])
+    .configure_view(strokeWidth=0)
+)
+
+# Save as PNG (scale_factor=3 gives 4800x2700)
+chart.save("plot.png", scale_factor=3.0)
+
+# Save interactive HTML version
+chart.save("plot.html")

plots/histogram-stacked/metadata/altair.yaml

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+library: altair
+specification_id: histogram-stacked
+created: '2025-12-30T10:38:08Z'
+updated: '2025-12-30T10:45:48Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20594559490
+issue: 0
+python_version: 3.13.11
+library_version: 6.0.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/histogram-stacked/altair/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/histogram-stacked/altair/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/histogram-stacked/altair/plot.html
+quality_score: 92
+review:
+  strengths:
+  - Excellent declarative encoding with proper use of Altair grammar (alt.X with bin,
+    alt.Y with stack="zero", alt.Color with custom scale)
+  - Clean, readable code following KISS principles with good data generation
+  - Proper font sizing throughout (title 28pt, axis titles 22pt, labels 18pt, legend
+    16-18pt)
+  - Good color palette choice (blue, yellow, orange) that avoids colorblind issues
+  - White stroke between bar segments (strokeWidth=0.5) enhances visual separation
+  - Appropriate use of scale_factor=3.0 for high-resolution output
+  - Both PNG and HTML outputs generated for static and interactive viewing
+  weaknesses:
+  - Legend styling could be more polished (title and label fonts could be slightly
+    larger for better visual hierarchy)
+  - Could add tooltips for interactive exploration showing exact counts per bin
+  - The order parameter could be more intentionally designed to show a specific visual
+    story (e.g., ordering by mean score)