feat(highcharts): implement choropleth-basic

[github-actions]

Implementation: choropleth-basic - highcharts

Implements the highcharts version of choropleth-basic.

File: plots/choropleth-basic/implementations/highcharts.py

Parent Issue: #3069

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🤖 impl-generate workflow

[claude]

AI Review - Attempt 1/3

Image Description

The plot shows a choropleth map of Europe displaying population density (people per km²). The title "choropleth-basic · highcharts · pyplots.ai" appears at the top in bold black text, with a subtitle "Population Density (people per km²)" below. Countries are colored using a sequential blue color palette ranging from very light blue (low density ~0) to dark navy blue (high density ~550). The Netherlands appears darkest blue (highest density), followed by Belgium and UK. Scandinavian countries (Norway, Sweden, Finland) appear lightest indicating low density. A vertical color legend on the right side shows the density scale from 0-550 per km². Country names are labeled directly on the map. Countries without data appear in light gray. The map is well-proportioned and fills the canvas appropriately.

Quality Score: 91/100

Criteria Checklist

Visual Quality (36/40 pts)

• VQ-01: Text Legibility (9/10) - Title, subtitle, legend, and country labels all readable. Some smaller country labels are a bit small but still legible.
• VQ-02: No Overlap (8/8) - No overlapping text elements; labels are positioned well within or near their countries.
• VQ-03: Element Visibility (7/8) - Map regions clearly visible with good borders. Some very small countries hard to distinguish.
• VQ-04: Color Accessibility (5/5) - Sequential blue palette is colorblind-safe; no red-green issues.
• VQ-05: Layout Balance (4/5) - Good canvas utilization, map fills most of the space. Legend positioned well on the right.
• VQ-06: Axis Labels (2/2) - N/A for maps, but subtitle includes units (per km²).
• VQ-07: Grid & Legend (1/2) - Legend is clear and well-placed, but could benefit from better styling.

Spec Compliance (24/25 pts)

• SC-01: Plot Type (8/8) - Correct choropleth map implementation.
• SC-02: Data Mapping (5/5) - Regions correctly colored by population density values.
• SC-03: Required Features (4/5) - Has color legend, clear boundaries, handles missing data (gray). Projection is appropriate.
• SC-04: Data Range (3/3) - Color scale shows full range 0-550.
• SC-05: Legend Accuracy (2/2) - Legend accurately shows density scale with proper labeling.
• SC-06: Title Format (2/2) - Uses correct format: choropleth-basic · highcharts · pyplots.ai

Data Quality (18/20 pts)

• DQ-01: Feature Coverage (7/8) - Shows good variation: high density (Netherlands 508), medium (Germany 234), low (Norway 15). Could include more extreme cases.
• DQ-02: Realistic Context (7/7) - Population density by European country is a realistic, neutral scenario with plausible values.
• DQ-03: Appropriate Scale (4/5) - Values are realistic for Europe (Netherlands ~500, Norway ~15). Good range representation.

Code Quality (9/10 pts)

• CQ-01: KISS Structure (3/3) - Clean script structure: imports → data → config → HTML generation → screenshot.
• CQ-02: Reproducibility (3/3) - Uses np.random.seed(42), though data is actually static/deterministic.
• CQ-03: Clean Imports (2/2) - All imports are used (json, tempfile, time, urllib, Path, numpy, selenium).
• CQ-04: No Deprecated API (1/1) - Uses current Highcharts map API.
• CQ-05: Output Correct (0/1) - Saves plot.png and plot.html correctly.

Library Features (4/5 pts)

• LF-01: Distinctive Features (4/5) - Good use of Highmaps for geographic visualization, TopoJSON integration, custom color stops, data labels, and hover states. Could use more advanced features like drilldown.

Strengths

• Excellent use of Highmaps TopoJSON topology for Europe map
• Clean sequential blue color palette that is colorblind-accessible
• Good data labels showing country names directly on the map
• Proper handling of missing data with gray coloring (nullColor)
• Well-implemented vertical color legend with title and scale
• Realistic population density data for European countries
• Both interactive HTML and static PNG outputs generated

Weaknesses

• Some small country labels may be difficult to read (e.g., Monaco, Andorra, Luxembourg)
• Legend could have more refined styling/spacing
• Could benefit from hover tooltips being more prominent in static image context

Verdict: APPROVED