feat(letsplot): implement polar-line (#2771)

## Implementation: `polar-line` - letsplot

Implements the **letsplot** version of `polar-line`.

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

---
:robot: *[impl-generate
workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20601061174)*

---------

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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/polar-line/implementations/letsplot.py

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+""" pyplots.ai
+polar-line: Polar Line Plot
+Library: letsplot 4.8.2 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-30
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import (
+    LetsPlot,
+    aes,
+    coord_fixed,
+    element_text,
+    geom_path,
+    geom_point,
+    geom_text,
+    ggplot,
+    ggsize,
+    labs,
+    scale_color_manual,
+    theme,
+    theme_void,
+)
+from lets_plot.export import ggsave
+
+
+LetsPlot.setup_html()
+
+# Data - Monthly average temperature pattern (cyclical)
+np.random.seed(42)
+months = np.arange(0, 360, 30)  # 12 months as angles (0, 30, 60, ... 330)
+month_names = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
+
+# Simulated temperature pattern (warm summer, cold winter)
+temp_city_a = np.array([2, 4, 10, 15, 20, 25, 28, 27, 22, 14, 7, 3])
+temp_city_b = np.array([5, 7, 12, 17, 22, 27, 30, 29, 24, 16, 10, 6])
+
+# Close the loop by adding the first point at the end
+angles_closed = np.append(months, 360)
+temp_a_closed = np.append(temp_city_a, temp_city_a[0])
+temp_b_closed = np.append(temp_city_b, temp_city_b[0])
+
+# Convert to radians for polar coordinates
+theta_a = np.radians(angles_closed)
+theta_b = np.radians(angles_closed)
+
+# Create x, y coordinates from polar (for lets-plot which uses Cartesian)
+x_a = temp_a_closed * np.cos(theta_a)
+y_a = temp_a_closed * np.sin(theta_a)
+x_b = temp_b_closed * np.cos(theta_b)
+y_b = temp_b_closed * np.sin(theta_b)
+
+# Create DataFrame
+df = pd.DataFrame(
+    {
+        "x": np.concatenate([x_a, x_b]),
+        "y": np.concatenate([y_a, y_b]),
+        "radius": np.concatenate([temp_a_closed, temp_b_closed]),
+        "angle": np.concatenate([angles_closed, angles_closed]),
+        "city": ["City A"] * len(x_a) + ["City B"] * len(x_b),
+    }
+)
+
+# Create concentric circles for polar grid
+grid_radii = [10, 20, 30]
+circle_points = 100
+grid_circles = []
+for r in grid_radii:
+    theta_grid = np.linspace(0, 2 * np.pi, circle_points)
+    grid_circles.append(pd.DataFrame({"x": r * np.cos(theta_grid), "y": r * np.sin(theta_grid), "radius": r}))
+grid_df = pd.concat(grid_circles, ignore_index=True)
+
+# Create radial lines for grid (every 30 degrees = each month)
+radial_lines = []
+for angle_deg in range(0, 360, 30):
+    angle_rad = np.radians(angle_deg)
+    radial_lines.append(
+        pd.DataFrame({"x": [0, 35 * np.cos(angle_rad)], "y": [0, 35 * np.sin(angle_rad)], "angle": angle_deg})
+    )
+radial_df = pd.concat(radial_lines, ignore_index=True)
+
+# Month labels positions
+label_radius = 34
+month_labels_df = pd.DataFrame(
+    {
+        "x": [label_radius * np.cos(np.radians(a)) for a in months],
+        "y": [label_radius * np.sin(np.radians(a)) for a in months],
+        "label": month_names,
+    }
+)
+
+# Plot
+plot = (
+    ggplot()
+    # Concentric grid circles
+    + geom_path(aes(x="x", y="y", group="radius"), data=grid_df, color="#CCCCCC", size=0.5, alpha=0.6)
+    # Radial grid lines
+    + geom_path(aes(x="x", y="y", group="angle"), data=radial_df, color="#CCCCCC", size=0.5, alpha=0.6)
+    # Data lines
+    + geom_path(aes(x="x", y="y", color="city"), data=df, size=2)
+    # Data points
+    + geom_point(aes(x="x", y="y", color="city"), data=df, size=5)
+    # Month labels
+    + geom_text(aes(x="x", y="y", label="label"), data=month_labels_df, size=14, color="#333333")
+    # Colors
+    + scale_color_manual(values=["#306998", "#FFD43B"])
+    # Theme and labels
+    + labs(title="polar-line · letsplot · pyplots.ai", color="Location")
+    + theme_void()
+    + theme(
+        plot_title=element_text(size=24, hjust=0.5),
+        legend_position="right",
+        legend_title=element_text(size=18),
+        legend_text=element_text(size=16),
+    )
+    + coord_fixed()
+    + ggsize(1600, 900)
+)
+
+# Save
+ggsave(plot, "plot.png", path=".", scale=3)
+
+# Also save HTML for interactive version
+ggsave(plot, "plot.html", path=".")

plots/polar-line/metadata/letsplot.yaml

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+library: letsplot
+specification_id: polar-line
+created: '2025-12-30T16:34:34Z'
+updated: '2025-12-30T16:44:24Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20601061174
+issue: 0
+python_version: 3.13.11
+library_version: 4.8.2
+preview_url: https://storage.googleapis.com/pyplots-images/plots/polar-line/letsplot/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/polar-line/letsplot/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/polar-line/letsplot/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent polar coordinate implementation using manual Cartesian transformation
+    when native coord_polar is unavailable
+  - Clean visual design with appropriate colors, grid lines, and month labels
+  - Good use of multiple series to demonstrate comparison capability
+  - Realistic temperature data with clear seasonal patterns
+  - Proper closed-loop polar lines connecting first and last points
+  - Well-balanced layout with legend positioned cleanly
+  weaknesses:
+  - Missing temperature scale labels (no indication of what the concentric circles
+    represent in °C)
+  - 'Minor: LetsPlot.setup_html() call is unnecessary for PNG-only output'