feat(altair): implement ridgeline-basic (#544)

## Summary
Implements `ridgeline-basic` for **altair**.

**Parent Issue:** #539
**Base Branch:** `plot/ridgeline-basic`

## Files
- `plots/ridgeline-basic/implementations/altair.py`

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

Author: claude[bot]

plots/ridgeline-basic/implementations/altair.py

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+"""
+ridgeline-basic: Ridgeline Plot
+Library: altair
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data - Monthly temperature distributions
+np.random.seed(42)
+months = [
+    "January",
+    "February",
+    "March",
+    "April",
+    "May",
+    "June",
+    "July",
+    "August",
+    "September",
+    "October",
+    "November",
+    "December",
+]
+
+# Generate temperature data with seasonal patterns
+data = []
+for i, month in enumerate(months):
+    # Seasonal temperature pattern (Northern Hemisphere)
+    base_temp = 5 + 20 * np.sin(np.pi * (i - 3) / 6)  # Peak in July
+    temps = np.random.normal(base_temp, 5, 150)
+    for temp in temps:
+        data.append({"month": month, "temperature": temp})
+
+df = pd.DataFrame(data)
+
+# Create a step value for vertical positioning
+month_order = {month: i for i, month in enumerate(months)}
+df["month_num"] = df["month"].map(month_order)
+
+# Define colors - seasonal gradient (blue=cold, orange=warm)
+# Colors match temperature patterns: cold winters (blue) to warm summers (orange)
+colors = [
+    "#306998",  # January - Python Blue (cold)
+    "#3b7ba8",  # February
+    "#59a0c4",  # March
+    "#8cc4d4",  # April
+    "#b4d4d8",  # May
+    "#f0b070",  # June
+    "#f97316",  # July - Orange (peak summer)
+    "#f99548",  # August
+    "#e0c9a8",  # September
+    "#8cc4d4",  # October
+    "#59a0c4",  # November
+    "#306998",  # December - Python Blue (cold)
+]
+
+# Create ridgeline using faceted area charts
+# Each row is a separate density chart, vertically offset
+chart = (
+    alt.Chart(df)
+    .transform_density(density="temperature", as_=["temperature", "density"], groupby=["month"], extent=[-15, 45])
+    .mark_area(fillOpacity=0.7, stroke="white", strokeWidth=1)
+    .encode(
+        x=alt.X("temperature:Q", title="Temperature (°C)", scale=alt.Scale(domain=[-15, 45])),
+        y=alt.Y("density:Q", title=None, scale=alt.Scale(range=[80, 0]), axis=None),
+        fill=alt.Fill("month:N", scale=alt.Scale(domain=months, range=colors), legend=None),
+        row=alt.Row(
+            "month:N",
+            title=None,
+            header=alt.Header(labelAngle=0, labelAlign="right", labelFontSize=14, labelPadding=10),
+            sort=months,
+            spacing=-30,  # Negative spacing creates overlap
+        ),
+    )
+    .properties(width=1400, height=60, title="Monthly Temperature Distributions")
+    .configure_view(stroke=None)
+    .configure_facet(spacing=0)
+    .configure_title(fontSize=24, anchor="middle")
+)
+
+# Save outputs
+chart.save("plot.png", scale_factor=3.0)
+chart.save("plot.html")