feat(plotnine): implement line-annotated-events (#3014)

## Implementation: `line-annotated-events` - plotnine

Implements the **plotnine** version of `line-annotated-events`.

**File:** `plots/line-annotated-events/implementations/plotnine.py`

**Parent Issue:** #2997

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:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20617491526)*

---------

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

Author: github-actions[bot]

plots/line-annotated-events/implementations/plotnine.py

@@ -0,0 +1,83 @@
+""" pyplots.ai
+line-annotated-events: Annotated Line Plot with Event Markers
+Library: plotnine 0.15.2 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import numpy as np
+import pandas as pd
+from plotnine import (
+    aes,
+    element_line,
+    element_text,
+    geom_line,
+    geom_point,
+    geom_text,
+    geom_vline,
+    ggplot,
+    labs,
+    scale_x_datetime,
+    theme,
+    theme_minimal,
+)
+
+
+# Data - Simulated website traffic with product release events
+np.random.seed(42)
+
+# Generate daily data for one year
+dates = pd.date_range("2024-01-01", periods=365, freq="D")
+base = 50000 + np.cumsum(np.random.randn(365) * 500)
+seasonal = 5000 * np.sin(2 * np.pi * np.arange(365) / 365)
+weekly = 3000 * np.sin(2 * np.pi * np.arange(365) / 7)
+values = base + seasonal + weekly
+
+df = pd.DataFrame({"date": dates, "value": values})
+
+# Event markers - product releases and major updates
+events = pd.DataFrame(
+    {
+        "event_date": pd.to_datetime(["2024-02-15", "2024-05-01", "2024-07-20", "2024-10-10", "2024-12-01"]),
+        "event_label": ["v2.0 Release", "Mobile App Launch", "API Update", "Enterprise Tier", "Holiday Campaign"],
+        "y_offset": [0.92, 0.85, 0.92, 0.85, 0.92],  # Alternating heights to avoid overlap
+    }
+)
+
+# Calculate y positions for labels (as fraction of y range)
+y_min, y_max = df["value"].min(), df["value"].max()
+y_range = y_max - y_min
+events["y_pos"] = y_min + events["y_offset"] * y_range
+
+# Create the plot
+plot = (
+    ggplot(df, aes(x="date", y="value"))
+    + geom_line(color="#306998", size=1.2, alpha=0.9)
+    + geom_vline(aes(xintercept="event_date"), data=events, color="#FFD43B", linetype="dashed", size=1.0, alpha=0.8)
+    + geom_point(aes(x="event_date", y="y_pos"), data=events, color="#FFD43B", size=4, shape="D")
+    + geom_text(
+        aes(x="event_date", y="y_pos", label="event_label"),
+        data=events,
+        color="#333333",
+        size=10,
+        ha="center",
+        va="bottom",
+        nudge_y=1000,
+        fontweight="bold",
+    )
+    + labs(x="Date", y="Daily Visitors", title="line-annotated-events · plotnine · pyplots.ai")
+    + scale_x_datetime(date_breaks="2 months", date_labels="%b %Y")
+    + theme_minimal()
+    + theme(
+        figure_size=(16, 9),
+        text=element_text(size=14),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        axis_text_x=element_text(angle=45, ha="right"),
+        plot_title=element_text(size=24, weight="bold"),
+        panel_grid_major=element_line(color="#cccccc", size=0.3, alpha=0.3),
+        panel_grid_minor=element_line(color="#eeeeee", size=0.2, alpha=0.2),
+    )
+)
+
+# Save
+plot.save("plot.png", dpi=300, verbose=False)

plots/line-annotated-events/metadata/plotnine.yaml

@@ -0,0 +1,27 @@
+library: plotnine
+specification_id: line-annotated-events
+created: '2025-12-31T10:55:04Z'
+updated: '2025-12-31T11:00:13Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20617491526
+issue: 2997
+python_version: 3.13.11
+library_version: 0.15.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-annotated-events/plotnine/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-annotated-events/plotnine/plot_thumb.png
+preview_html: null
+quality_score: 91
+review:
+  strengths:
+  - Excellent implementation of alternating y-positions for event labels to avoid
+    overlap
+  - Clean grammar of graphics approach with well-layered geoms (line → vline → point
+    → text)
+  - 'Appropriate use of the Python color scheme (#306998 blue, #FFD43B yellow)'
+  - Good text sizing following the library guidelines (24pt title, 20pt axis labels,
+    16pt ticks)
+  - Realistic website traffic scenario with meaningful event annotations
+  weaknesses:
+  - Axis labels could include units (e.g., "Daily Visitors (count)")
+  - Event markers at alternating heights work well but the fixed y_offset values (0.85,
+    0.92) could be slightly higher to give more separation from the data line peaks