feat(pygal): implement line-timeseries-rolling (#2816)

## Implementation: `line-timeseries-rolling` - pygal

Implements the **pygal** version of `line-timeseries-rolling`.

**File:** `plots/line-timeseries-rolling/implementations/pygal.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20602452872)*

---------

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/line-timeseries-rolling/implementations/pygal.py

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+""" pyplots.ai
+line-timeseries-rolling: Time Series with Rolling Average Overlay
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-30
+"""
+
+import random
+from datetime import datetime, timedelta
+
+import pygal
+from pygal.style import Style
+
+
+# Seed for reproducibility
+random.seed(42)
+
+# Generate daily temperature readings for 4 months
+start_date = datetime(2024, 1, 1)
+dates = [start_date + timedelta(days=i) for i in range(120)]
+
+# Generate temperature data with seasonal trend and noise
+temperatures = []
+for i in range(120):
+    # Seasonal variation: winter to early spring
+    seasonal = 5 + 8 * (i / 120)  # Gradual warming from 5°C to 13°C
+    noise = random.gauss(0, 3)
+    temp = seasonal + noise
+    temperatures.append(round(temp, 1))
+
+# Calculate 7-day rolling average (None for first 6 days)
+window_size = 7
+rolling_avg = []
+for i in range(len(temperatures)):
+    if i < window_size - 1:
+        rolling_avg.append(None)  # pygal handles None as gaps
+    else:
+        window = temperatures[i - window_size + 1 : i + 1]
+        avg = sum(window) / window_size
+        rolling_avg.append(round(avg, 1))
+
+# Custom style for 4800x2700 canvas with larger fonts
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    colors=("#306998", "#E67E22"),  # Python Blue for raw, Orange for rolling avg (better visibility)
+    title_font_size=72,
+    label_font_size=48,
+    major_label_font_size=42,
+    legend_font_size=42,
+    value_font_size=36,
+    guide_stroke_color="#cccccc",
+    guide_stroke_dasharray="2,4",
+)
+
+# Create line chart
+chart = pygal.Line(
+    width=4800,
+    height=2700,
+    style=custom_style,
+    title="line-timeseries-rolling · pygal · pyplots.ai",
+    x_title="Date",
+    y_title="Temperature (°C)",
+    show_x_guides=False,
+    show_y_guides=True,
+    x_label_rotation=45,
+    show_legend=True,
+    legend_at_bottom=True,
+    legend_at_bottom_columns=2,  # Keep legend items together in 2 columns
+    legend_box_size=24,  # Larger legend box for visibility
+    truncate_legend=-1,
+    show_dots=False,
+    stroke_style={"width": 4},
+    margin=60,
+)
+
+# Add raw temperature data (lighter line)
+chart.add("Raw Temperature", temperatures, stroke_style={"width": 2})
+
+# Add rolling average (prominent line)
+chart.add("7-Day Rolling Average", rolling_avg, stroke_style={"width": 6})
+
+# Set x-axis labels - show every 2 weeks
+x_labels = []
+x_labels_major = []
+for d in dates:
+    if d.day in [1, 15]:  # 1st and 15th of each month
+        label = d.strftime("%b %d")
+        x_labels.append(label)
+        x_labels_major.append(label)
+    else:
+        x_labels.append("")
+
+chart.x_labels = x_labels
+chart.x_labels_major = x_labels_major
+
+# Save as HTML and PNG
+chart.render_to_file("plot.html")
+chart.render_to_png("plot.png")

plots/line-timeseries-rolling/metadata/pygal.yaml

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+library: pygal
+specification_id: line-timeseries-rolling
+created: '2025-12-30T17:49:00Z'
+updated: '2025-12-30T18:07:10Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20602452872
+issue: 0
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-timeseries-rolling/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-timeseries-rolling/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-timeseries-rolling/pygal/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent visual distinction between raw data (thin blue line) and rolling average
+    (thick orange line) following spec guidance
+  - Proper handling of rolling average with None values for first 6 days (pygal renders
+    this as gaps correctly)
+  - Good colorblind-safe color choices with Python Blue and contrasting Orange
+  - Legend clearly indicates the 7-day window size as recommended by spec
+  - Well-scaled font sizes for the 4800x2700 canvas with custom Style
+  - Clean bi-weekly x-axis labeling prevents crowding
+  weaknesses:
+  - Grid visibility could be improved - x-axis guides are disabled (show_x_guides=False)
+    while spec suggests grid lines on both axes improve readability
+  - Font sizes in custom_style are larger than pygal.md guidelines suggest, though
+    this works well for the output