feat(plotly): implement line-markers (#2620)

## Implementation: `line-markers` - plotly

Implements the **plotly** version of `line-markers`.

**File:** `plots/line-markers/implementations/plotly.py`

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20594556252)*

---------

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

Author: github-actions[bot]

plots/line-markers/implementations/plotly.py

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+""" pyplots.ai
+line-markers: Line Plot with Markers
+Library: plotly 6.5.0 | Python 3.13.11
+Quality: 94/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data - experimental temperature readings over time
+np.random.seed(42)
+x = np.arange(0, 15)
+
+# Three sensor series with different patterns
+sensor_a = 20 + np.cumsum(np.random.randn(15) * 0.8)
+sensor_b = 22 + np.cumsum(np.random.randn(15) * 0.6) - 2
+sensor_c = 18 + np.cumsum(np.random.randn(15) * 1.0) + 1
+
+# Create figure
+fig = go.Figure()
+
+# Add traces with different marker styles
+fig.add_trace(
+    go.Scatter(
+        x=x,
+        y=sensor_a,
+        mode="lines+markers",
+        name="Sensor A",
+        line=dict(color="#306998", width=4),
+        marker=dict(size=16, symbol="circle", color="#306998", line=dict(width=2, color="white")),
+    )
+)
+
+fig.add_trace(
+    go.Scatter(
+        x=x,
+        y=sensor_b,
+        mode="lines+markers",
+        name="Sensor B",
+        line=dict(color="#FFD43B", width=4),
+        marker=dict(size=16, symbol="square", color="#FFD43B", line=dict(width=2, color="#333333")),
+    )
+)
+
+fig.add_trace(
+    go.Scatter(
+        x=x,
+        y=sensor_c,
+        mode="lines+markers",
+        name="Sensor C",
+        line=dict(color="#E55934", width=4),
+        marker=dict(size=16, symbol="diamond", color="#E55934", line=dict(width=2, color="white")),
+    )
+)
+
+# Layout
+fig.update_layout(
+    title=dict(text="line-markers · plotly · pyplots.ai", font=dict(size=32), x=0.5, xanchor="center"),
+    xaxis=dict(
+        title=dict(text="Time (hours)", font=dict(size=24)),
+        tickfont=dict(size=20),
+        showgrid=True,
+        gridwidth=1,
+        gridcolor="rgba(0,0,0,0.1)",
+        dtick=2,
+    ),
+    yaxis=dict(
+        title=dict(text="Temperature (°C)", font=dict(size=24)),
+        tickfont=dict(size=20),
+        showgrid=True,
+        gridwidth=1,
+        gridcolor="rgba(0,0,0,0.1)",
+    ),
+    legend=dict(
+        font=dict(size=20),
+        x=0.02,
+        y=0.98,
+        xanchor="left",
+        yanchor="top",
+        bgcolor="rgba(255,255,255,0.8)",
+        bordercolor="rgba(0,0,0,0.2)",
+        borderwidth=1,
+    ),
+    template="plotly_white",
+    margin=dict(l=100, r=60, t=100, b=80),
+    plot_bgcolor="white",
+)
+
+# Save as PNG and HTML
+fig.write_image("plot.png", width=1600, height=900, scale=3)
+fig.write_html("plot.html", include_plotlyjs=True, full_html=True)

plots/line-markers/metadata/plotly.yaml

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+library: plotly
+specification_id: line-markers
+created: '2025-12-30T10:38:15Z'
+updated: '2025-12-30T10:46:24Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20594556252
+issue: 0
+python_version: 3.13.11
+library_version: 6.5.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-markers/plotly/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-markers/plotly/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-markers/plotly/plot.html
+quality_score: 94
+review:
+  strengths:
+  - Excellent marker visibility with distinct shapes (circle, square, diamond) for
+    each series
+  - White border lines on markers provide excellent contrast against the lines
+  - Clean, professional layout with appropriate font sizes for high-resolution output
+  - Good use of Plotly graph_objects for fine-grained control over styling
+  - Outputs both PNG and interactive HTML, showcasing Plotly dual capability
+  - Realistic temperature sensor scenario that fits the sparse data use case well
+  weaknesses:
+  - Legend could be positioned outside the plot area (e.g., to the right) to avoid
+    any potential overlap with data
+  - Hover templates or other interactive features could better showcase Plotly distinctive
+    capabilities