feat(plotly): implement ridgeline-basic (#546)

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

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

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

## Preview
Preview will be uploaded to GCS staging after this workflow completes.

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

Author: claude[bot]

plots/ridgeline-basic/implementations/plotly.py

@@ -0,0 +1,132 @@
+"""
+ridgeline-basic: Ridgeline Plot
+Library: plotly
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+from scipy import stats
+
+
+# Data - Monthly temperature readings (simulating seasonal patterns)
+np.random.seed(42)
+
+months = [
+    "January",
+    "February",
+    "March",
+    "April",
+    "May",
+    "June",
+    "July",
+    "August",
+    "September",
+    "October",
+    "November",
+    "December",
+]
+
+# Generate temperature data with seasonal patterns
+month_temps = {
+    "January": np.random.normal(2, 4, 200),
+    "February": np.random.normal(4, 4, 200),
+    "March": np.random.normal(9, 5, 200),
+    "April": np.random.normal(14, 4, 200),
+    "May": np.random.normal(18, 4, 200),
+    "June": np.random.normal(22, 3, 200),
+    "July": np.random.normal(25, 3, 200),
+    "August": np.random.normal(24, 3, 200),
+    "September": np.random.normal(20, 4, 200),
+    "October": np.random.normal(14, 4, 200),
+    "November": np.random.normal(8, 4, 200),
+    "December": np.random.normal(4, 4, 200),
+}
+
+# Color palette - gradient from cool to warm colors
+colors = [
+    "#306998",  # January - Python Blue
+    "#3B7BA8",
+    "#4A8DB5",
+    "#5E9EC2",
+    "#7BB0C9",
+    "#9FC5D4",
+    "#C4DBDE",
+    "#E8D5B5",
+    "#F5C48A",
+    "#F9A857",
+    "#F97316",  # Orange
+    "#DC2626",  # December - Signal Red
+]
+
+# Create figure
+fig = go.Figure()
+
+# Calculate KDE for each month and add as filled area
+x_range = np.linspace(-15, 40, 300)
+spacing = 0.15  # Vertical spacing between ridges
+max_density = 0  # Track max density for scaling
+
+# First pass: calculate all KDEs and find max density
+kde_results = []
+for month in months:
+    data = month_temps[month]
+    kde = stats.gaussian_kde(data, bw_method=0.3)
+    density = kde(x_range)
+    kde_results.append(density)
+    max_density = max(max_density, density.max())
+
+# Scale factor for ridge height
+scale_factor = spacing * 0.8 / max_density
+
+# Second pass: add traces from bottom to top (reversed for proper layering)
+for i, month in enumerate(reversed(months)):
+    idx = len(months) - 1 - i
+    density = kde_results[idx] * scale_factor
+    y_base = idx * spacing
+
+    # Create the filled area trace
+    fig.add_trace(
+        go.Scatter(
+            x=np.concatenate([x_range, x_range[::-1]]),
+            y=np.concatenate([y_base + density, np.full_like(x_range, y_base)]),
+            fill="toself",
+            fillcolor=colors[idx],
+            line={"color": "white", "width": 1.5},
+            opacity=0.75,
+            name=month,
+            hovertemplate=f"<b>{month}</b><br>Temperature: %{{x:.1f}}°C<extra></extra>",
+        )
+    )
+
+# Update layout
+fig.update_layout(
+    title={"text": "Monthly Temperature Distribution", "font": {"size": 48}, "x": 0.5, "xanchor": "center"},
+    xaxis={
+        "title": {"text": "Temperature (°C)", "font": {"size": 40}},
+        "tickfont": {"size": 32},
+        "showgrid": True,
+        "gridwidth": 1,
+        "gridcolor": "rgba(128, 128, 128, 0.2)",
+        "zeroline": False,
+        "range": [-12, 38],
+    },
+    yaxis={
+        "title": {"text": "Month", "font": {"size": 40}},
+        "tickfont": {"size": 32},
+        "tickmode": "array",
+        "tickvals": [i * spacing for i in range(len(months))],
+        "ticktext": months,
+        "showgrid": False,
+        "zeroline": False,
+    },
+    showlegend=False,
+    template="plotly_white",
+    margin={"l": 200, "r": 100, "t": 150, "b": 100},
+    plot_bgcolor="white",
+    paper_bgcolor="white",
+    hoverlabel={"font_size": 24},
+)
+
+# Save outputs
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs="cdn")