feat(letsplot): implement line-annotated-events (#3046)

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

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

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

**Parent Issue:** #2997

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:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20617493630)*

---------

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-annotated-events/implementations/letsplot.py

@@ -0,0 +1,87 @@
+""" pyplots.ai
+line-annotated-events: Annotated Line Plot with Event Markers
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import *  # noqa: F403
+
+
+LetsPlot.setup_html()
+
+# Data - Daily product metrics with feature launch events
+np.random.seed(42)
+dates = pd.date_range("2024-01-01", periods=365, freq="D")
+
+# Create realistic user growth pattern with trend and seasonality
+trend = np.linspace(1000, 5000, 365)
+seasonality = 300 * np.sin(np.arange(365) * 2 * np.pi / 30)
+noise = np.random.normal(0, 150, 365)
+daily_users = trend + seasonality + noise
+
+# Create jumps at event dates to show impact
+daily_users[45:] += 400  # After Feature A launch
+daily_users[120:] += 600  # After Feature B launch
+daily_users[200:] += 800  # After Mobile App launch
+daily_users[280:] += 500  # After API release
+daily_users[330:] += 300  # After Integration launch
+
+df = pd.DataFrame({"date": dates, "users": daily_users})
+
+# Convert date to numeric for plotting
+df["date_num"] = (df["date"] - df["date"].min()).dt.days
+
+# Event data - Feature launches throughout the year
+events = pd.DataFrame(
+    {
+        "event_date": pd.to_datetime(["2024-02-15", "2024-05-01", "2024-07-20", "2024-10-07", "2024-11-20"]),
+        "event_label": ["Feature A", "Feature B", "Mobile App", "API v2.0", "Partners"],
+        "y_offset": [4800, 5200, 5600, 6000, 6400],  # Alternating heights to avoid overlap
+    }
+)
+events["event_num"] = (events["event_date"] - df["date"].min()).dt.days
+
+# Create the plot
+plot = (
+    ggplot()
+    # Main line - daily active users
+    + geom_line(aes(x="date_num", y="users"), data=df, color="#306998", size=1.5, alpha=0.9)
+    # Vertical lines for events
+    + geom_vline(aes(xintercept="event_num"), data=events, color="#DC2626", linetype="dashed", size=1.0, alpha=0.7)
+    # Event markers at the line
+    + geom_point(aes(x="event_num", y="y_offset"), data=events, color="#DC2626", size=5, shape=18)
+    # Event labels
+    + geom_text(
+        aes(x="event_num", y="y_offset", label="event_label"),
+        data=events,
+        color="#333333",
+        size=14,
+        hjust=0,
+        nudge_x=5,
+        fontface="bold",
+    )
+    # Labels and title
+    + labs(x="Day of Year 2024", y="Daily Active Users", title="line-annotated-events · letsplot · pyplots.ai")
+    # Styling
+    + theme_minimal()
+    + theme(
+        plot_title=element_text(size=24, face="bold"),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+        panel_grid_major=element_line(color="#CCCCCC", size=0.5),
+        panel_grid_minor=element_blank(),
+    )
+    # Set axis limits to show all data and labels
+    + scale_x_continuous(
+        breaks=[0, 60, 120, 180, 240, 300, 360], labels=["Jan", "Mar", "May", "Jul", "Sep", "Nov", "Jan"]
+    )
+    + scale_y_continuous(limits=[0, 7500])
+    # Figure size (scaled 3x on export = 4800 × 2700 px)
+    + ggsize(1600, 900)
+)
+
+# Save as PNG and HTML
+ggsave(plot, "plot.png", scale=3)
+ggsave(plot, "plot.html")

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

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+library: letsplot
+specification_id: line-annotated-events
+created: '2025-12-31T11:00:44Z'
+updated: '2025-12-31T11:53:32Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20617493630
+issue: 2997
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-annotated-events/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-annotated-events/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-annotated-events/letsplot/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent use of alternating y_offset heights for event labels prevents overlap
+  - Clean ggplot2 grammar implementation with proper layering of geoms
+  - Good color contrast between data line (blue) and event markers (red)
+  - Appropriate figure sizing with scale=3 for high-resolution output
+  - Data shows realistic growth pattern with trend, seasonality, and event impacts
+  weaknesses:
+  - X-axis label says Day of Year 2024 but displays month names - should be consistent