feat(seaborn): implement polar-line

[github-actions]

Implementation: polar-line - seaborn

Implements the seaborn version of polar-line.

File: plots/polar-line/implementations/seaborn.py

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot displays a polar line chart showing monthly temperature patterns for two cities. A blue line with circular markers represents "Coastal City" while a yellow/gold line with square markers represents "Inland City". The months (Jan-Dec) are arranged clockwise around the perimeter starting from the top (12 o'clock position). The radial axis shows temperature values from 0°C to 30°C with concentric circle grid lines. Both series have semi-transparent filled areas beneath the lines. The title "Monthly Temperature Patterns · polar-line · seaborn · pyplots.ai" is displayed at the top. The legend is positioned in the upper right corner outside the main plot area.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title is large and readable (fontsize=22), month labels are clear (fontsize=18), radial labels visible (fontsize=14). Slightly below ideal 24pt for title.
• VQ-02: No Overlap (8/8) - No overlapping text elements, all labels are clearly separated
• VQ-03: Element Visibility (8/8) - Markers are well-sized (12px), lines are thick (3.5px), both series clearly distinguishable
• VQ-04: Color Accessibility (5/5) - Blue (#306998) and yellow (#FFD43B) provide excellent contrast and are colorblind-safe
• VQ-05: Layout Balance (4/5) - Good use of square canvas for polar plot, slight imbalance with legend placement outside
• VQ-06: Axis Labels (2/2) - Radial axis shows units (°C), month labels are descriptive
• VQ-07: Grid & Legend (0/2) - Legend overlaps with title area due to bbox_to_anchor placement

Spec Compliance (25/25 pts)

• SC-01: Plot Type (8/8) - Correct polar line plot
• SC-02: Data Mapping (5/5) - Theta=months (cyclical), radius=temperature (magnitude) correctly assigned
• SC-03: Required Features (5/5) - Multiple series with different colors, lines connect points in theta order
• SC-04: Data Range (3/3) - All data visible within 0-35 range
• SC-05: Legend Accuracy (2/2) - Legend labels match the data series
• SC-06: Title Format (2/2) - Follows "{description} · {spec-id} · {library} · pyplots.ai" format

Data Quality (20/20 pts)

• DQ-01: Feature Coverage (8/8) - Shows cyclical seasonal patterns, two series with different characteristics (temperate vs extreme variation)
• DQ-02: Realistic Context (7/7) - Monthly temperature data is a real, neutral, comprehensible scenario
• DQ-03: Appropriate Scale (5/5) - Temperature values 0-30°C are realistic for seasonal variation

Code Quality (10/10 pts)

• CQ-01: KISS Structure (3/3) - Simple linear structure: imports → data → plot → save
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42) for deterministic data
• CQ-03: Clean Imports (2/2) - Only necessary imports (matplotlib, numpy, seaborn)
• CQ-04: No Deprecated API (1/1) - Uses current seaborn/matplotlib API
• CQ-05: Output Correct (1/1) - Saves as 'plot.png'

Library Features (0/5 pts)

• LF-01: Uses distinctive library features (0/5) - Only uses sns.set_theme() and sns.color_palette(). Does not use any seaborn plotting functions (like sns.lineplot). The actual plotting is done with matplotlib's ax.plot()

Strengths

• Excellent use of polar projection for cyclical monthly data
• Clear visual distinction between two temperature series with contrasting colors and marker shapes
• Good use of filled areas to enhance visual comparison
• Proper clockwise month arrangement starting from January at top
• Clean, readable code structure following KISS principles
• Realistic and educational data scenario (coastal vs inland temperature patterns)
• Appropriate radial axis labels with temperature units (°C)

Weaknesses

• Does not use seaborn plotting functions (only styling utilities); implementation relies entirely on matplotlib for actual plotting
• Legend placement (bbox_to_anchor=(1.15, 1.1)) causes overlap with title area

Verdict: APPROVED