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The plot displays a box plot with strip overlay showing plant growth (cm) across four soil types (Sandy, Clay, Loamy, Silty). The boxes are rendered in a muted blue color (#306998) with 40% transparency, showing median lines as darker horizontal segments. Yellow/gold circular markers (#FFD43B) with dark gold borders represent individual data points, scattered with jitter across each category. The title "cat-box-strip · bokeh · pyplots.ai" appears at the top left in dark text. The x-axis is labeled "Soil Type" and y-axis "Plant Growth (cm)". The background is a subtle off-white (#fafafa) with light gray dashed horizontal grid lines. Whiskers extend from boxes to show data range, with visible outliers in Clay (high values ~55-58) and Silty (low values ~12-14).
Quality Score: 92/100
Criteria Checklist
Visual Quality (36/40 pts)
VQ-01: Text Legibility (10/10) - Title at 36pt, axis labels at 28pt/22pt, all clearly readable at full resolution
VQ-02: No Overlap (8/8) - No overlapping text elements, category labels well-spaced
VQ-03: Element Visibility (7/8) - Strip points visible with good jitter and alpha, box elements clear. Minor: some points cluster tightly in Loamy
VQ-04: Color Accessibility (5/5) - Blue boxes and yellow points provide excellent contrast, colorblind-safe combination
VQ-05: Layout Balance (4/5) - Good canvas utilization, slight excess whitespace on right edge
DQ-02: Realistic Context (6/7) - Plant growth by soil type is plausible and neutral. Minor: values slightly generic
DQ-03: Appropriate Scale (5/5) - Plant growth 10-60cm is realistic for the scenario
Code Quality (9/10 pts)
CQ-01: KISS Structure (3/3) - Linear flow: imports → data → plot → save
CQ-02: Reproducibility (3/3) - np.random.seed(42) set
CQ-03: Clean Imports (2/2) - All imports used (numpy, pandas, bokeh components)
CQ-04: No Deprecated API (1/1) - Current Bokeh API used
CQ-05: Output Correct (0/1) - Saves plot.png but also plot.html (minor extra file)
Library Features (3/5 pts)
LF-01: Uses distinctive library features (3/5) - Good use of ColumnDataSource, Whisker annotations, jitter transform. Could leverage more Bokeh-specific features like HoverTool for interactivity
Strengths
Excellent manual box plot construction using Bokeh primitives (Whisker, vbar, segment)
Good use of jitter transform for strip points to reduce overlap
Proper colorblind-safe color scheme (blue/yellow contrast)
Well-calculated IQR-based whiskers with proper outlier handling
Clear demonstration of different distributions and outliers across categories
Font sizes properly scaled for 4800x2700 canvas
Weaknesses
No legend explaining what box/strip elements represent (minor for this plot type)
Could add HoverTool to show exact values on hover for the HTML version
The median line segment has zero width (x0=x1) which works but is technically a point not a line
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Implementation:
cat-box-strip- bokehImplements the bokeh version of
cat-box-strip.File:
plots/cat-box-strip/implementations/bokeh.py🤖 impl-generate workflow