feat(altair): implement line-timeseries-rolling (#2819)

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

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

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

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20602450785)*

---------

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/altair.py

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+""" pyplots.ai
+line-timeseries-rolling: Time Series with Rolling Average Overlay
+Library: altair 6.0.0 | Python 3.13.11
+Quality: 93/100 | Created: 2025-12-30
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data - Daily temperature readings over 6 months with 7-day rolling average
+np.random.seed(42)
+dates = pd.date_range("2024-01-01", periods=180, freq="D")
+
+# Simulate temperature with seasonal trend + noise (winter to early summer)
+day_of_year = np.arange(180)
+# Temperature rises from winter (Jan) toward summer (Jun)
+seasonal_trend = 10 + 12 * np.sin(2 * np.pi * (day_of_year - 90) / 365)
+noise = np.random.normal(0, 3, 180)
+raw_values = seasonal_trend + noise
+
+df = pd.DataFrame({"date": dates, "value": raw_values})
+
+# Calculate 7-day rolling average
+df["rolling_avg"] = df["value"].rolling(window=7, center=True).mean()
+
+# Prepare data for layered chart with proper legend
+df_long = pd.melt(
+    df, id_vars=["date"], value_vars=["value", "rolling_avg"], var_name="series", value_name="temperature"
+)
+
+# Rename series for cleaner legend
+df_long["series"] = df_long["series"].map({"value": "Raw Data", "rolling_avg": "7-Day Rolling Average"})
+
+# Remove NaN values from rolling average
+df_long = df_long.dropna()
+
+# Create chart with both lines
+chart = (
+    alt.Chart(df_long)
+    .mark_line()
+    .encode(
+        x=alt.X("date:T", title="Date", axis=alt.Axis(labelFontSize=18, titleFontSize=22, format="%b %d")),
+        y=alt.Y(
+            "temperature:Q",
+            title="Temperature (°C)",
+            axis=alt.Axis(labelFontSize=18, titleFontSize=22),
+            scale=alt.Scale(zero=False),
+        ),
+        color=alt.Color(
+            "series:N",
+            scale=alt.Scale(domain=["Raw Data", "7-Day Rolling Average"], range=["#306998", "#FFD43B"]),
+            legend=alt.Legend(title="Series", labelFontSize=16, titleFontSize=18, orient="top-right", offset=10),
+        ),
+        strokeWidth=alt.condition(alt.datum.series == "7-Day Rolling Average", alt.value(4), alt.value(1.5)),
+        opacity=alt.condition(alt.datum.series == "7-Day Rolling Average", alt.value(1.0), alt.value(0.5)),
+    )
+    .properties(
+        width=1600,
+        height=900,
+        title=alt.Title("line-timeseries-rolling · altair · pyplots.ai", fontSize=28, anchor="middle"),
+    )
+    .configure_axis(gridOpacity=0.3, gridDash=[4, 4])
+    .configure_view(strokeWidth=0)
+)
+
+# Save
+chart.save("plot.png", scale_factor=3.0)
+chart.save("plot.html")

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

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+library: altair
+specification_id: line-timeseries-rolling
+created: '2025-12-30T17:49:27Z'
+updated: '2025-12-30T17:59:24Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20602450785
+issue: 0
+python_version: 3.13.11
+library_version: 6.0.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-timeseries-rolling/altair/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-timeseries-rolling/altair/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-timeseries-rolling/altair/plot.html
+quality_score: 93
+review:
+  strengths:
+  - Excellent use of Altair declarative grammar with conditional encoding for strokeWidth
+    and opacity
+  - Clean data transformation using pd.melt for tidy/long format suitable for Altair
+  - 'Well-chosen color scheme (#306998 blue, #FFD43B yellow) that is colorblind-safe'
+  - Realistic temperature data scenario with clear seasonal trend
+  - Proper use of centered rolling window (center=True) for accurate moving average
+    alignment
+  weaknesses:
+  - Legend placement overlaps slightly with data points in the upper-right corner;
+    could use orient=bottom or place outside the plot area