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feat(plotnine): implement violin-grouped-swarm (#3545)
## Implementation: `violin-grouped-swarm` - plotnine Implements the **plotnine** version of `violin-grouped-swarm`. **File:** `plots/violin-grouped-swarm/implementations/plotnine.py` **Parent Issue:** #3529 --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20858843569)* --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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‎plots/violin-grouped-swarm/implementations/plotnine.py‎

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""" pyplots.ai
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violin-grouped-swarm: Grouped Violin Plot with Swarm Overlay
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Library: plotnine 0.15.2 | Python 3.13.11
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Quality: 91/100 | Created: 2026-01-09
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"""
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import numpy as np
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import pandas as pd
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from plotnine import (
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aes,
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element_line,
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element_text,
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geom_jitter,
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geom_violin,
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ggplot,
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guide_legend,
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guides,
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labs,
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position_dodge,
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scale_color_manual,
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scale_fill_manual,
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theme,
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theme_minimal,
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)
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# Data - Response times (ms) across task types and expertise levels
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np.random.seed(42)
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categories = ["Simple", "Moderate", "Complex"]
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groups = ["Novice", "Expert"]
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n_per_combination = 40
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data = []
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for category in categories:
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for group in groups:
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# Base response time varies by complexity
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base = {"Simple": 400, "Moderate": 700, "Complex": 1100}[category]
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# Experts are faster
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if group == "Expert":
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base -= 150
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# Generate data with varying spreads
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spread = {"Simple": 60, "Moderate": 100, "Complex": 150}[category]
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values = np.random.normal(base, spread, n_per_combination)
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# Add some variation for visual interest
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values = np.clip(values, base - 3 * spread, base + 3 * spread)
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for v in values:
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data.append({"task_type": category, "expertise": group, "response_time": v})
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df = pd.DataFrame(data)
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# Set category order
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df["task_type"] = pd.Categorical(df["task_type"], categories=categories, ordered=True)
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df["expertise"] = pd.Categorical(df["expertise"], categories=groups, ordered=True)
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# Colors - Python Blue and Yellow
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colors = {"Novice": "#306998", "Expert": "#FFD43B"}
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# Create plot
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plot = (
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ggplot(df, aes(x="task_type", y="response_time", fill="expertise", color="expertise"))
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+ geom_violin(position=position_dodge(width=0.8), alpha=0.5, size=0.8)
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+ geom_jitter(position=position_dodge(width=0.8), size=2.5, alpha=0.8)
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+ scale_fill_manual(values=colors, name="Expertise")
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+ scale_color_manual(values=colors, name="Expertise")
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+ guides(fill=guide_legend(), color=guide_legend())
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+ labs(title="violin-grouped-swarm · plotnine · pyplots.ai", x="Task Type", y="Response Time (ms)")
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+ theme_minimal()
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+ theme(
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figure_size=(16, 9),
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text=element_text(size=14),
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axis_title=element_text(size=20),
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axis_text=element_text(size=16),
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plot_title=element_text(size=24),
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legend_title=element_text(size=18),
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legend_text=element_text(size=16),
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panel_grid_major=element_line(alpha=0.3),
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panel_grid_minor=element_line(alpha=0.15),
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)
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)
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# Save
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plot.save("plot.png", dpi=300, verbose=False)

‎plots/violin-grouped-swarm/metadata/plotnine.yaml‎

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library: plotnine
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specification_id: violin-grouped-swarm
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created: '2026-01-09T16:48:57Z'
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updated: '2026-01-09T16:52:15Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 20858843569
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issue: 3529
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python_version: 3.13.11
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library_version: 0.15.2
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preview_url: https://storage.googleapis.com/pyplots-images/plots/violin-grouped-swarm/plotnine/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/violin-grouped-swarm/plotnine/plot_thumb.png
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preview_html: null
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quality_score: 91
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review:
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strengths:
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- Excellent color palette with high contrast (blue/yellow) that is colorblind-safe
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- Clean layered grammar of graphics approach with geom_violin + geom_jitter
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- Realistic and well-thought-out data scenario with varying complexity levels and
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expertise
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- Proper use of position_dodge to align grouped elements
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- Text sizing follows guidelines perfectly for 4800x2700 output
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weaknesses:
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- Legend appears with duplicate Expertise entries (both fill and color scales create
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separate legend items)
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- Uses geom_jitter for swarm points rather than true swarm positioning - plotnine
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lacks native geom_beeswarm
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- The guides() call with guide_legend() does not effectively merge the legends
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image_description: 'The plot displays a grouped violin chart with swarm overlay
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showing response times (in milliseconds) across three task types (Simple, Moderate,
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Complex) and two expertise levels (Novice in steel blue, Expert in golden yellow).
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Each violin shape effectively shows the distribution of data, with individual
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data points rendered as jittered markers inside the violins. The Novice group
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consistently shows higher response times than Expert across all task complexity
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levels. Response times increase from Simple (~300-500ms) to Moderate (~400-900ms)
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to Complex (~600-1400ms). The violins have semi-transparent fills (alpha ~0.5)
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allowing the swarm points to remain visible. The title uses the correct format:
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''violin-grouped-swarm · plotnine · pyplots.ai''. The legend is positioned on
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the right side, clearly labeling the two expertise levels with matching colors.'
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criteria_checklist:
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visual_quality:
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score: 37
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max: 40
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items:
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- id: VQ-01
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name: Text Legibility
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score: 10
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max: 10
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passed: true
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comment: Title at 24pt, axis labels at 20pt, tick labels at 16pt - all perfectly
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readable
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- id: VQ-02
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name: No Overlap
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score: 8
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max: 8
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passed: true
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comment: No overlapping text elements, violins well-spaced
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- id: VQ-03
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name: Element Visibility
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score: 7
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max: 8
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passed: true
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comment: Swarm points visible, though slightly small for the data density;
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violins well-sized
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- id: VQ-04
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name: Color Accessibility
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score: 5
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max: 5
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passed: true
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comment: Blue and yellow palette is colorblind-safe, excellent contrast
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- id: VQ-05
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name: Layout Balance
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score: 5
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max: 5
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passed: true
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comment: Good proportions, plot fills canvas well, balanced margins
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- id: VQ-06
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name: Axis Labels
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score: 2
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max: 2
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passed: true
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comment: Y-axis includes units 'Response Time (ms)', X-axis labeled 'Task
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Type'
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- id: VQ-07
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name: Grid & Legend
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score: 0
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max: 2
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passed: false
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comment: Grid is subtle (alpha 0.3), but legend shows duplicate entries (Expertise
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appears twice with same colors)
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spec_compliance:
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score: 23
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max: 25
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items:
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- id: SC-01
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name: Plot Type
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score: 8
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max: 8
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passed: true
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comment: Correct grouped violin plot with swarm overlay
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- id: SC-02
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name: Data Mapping
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score: 5
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max: 5
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passed: true
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comment: Category on x-axis, values on y-axis, grouping by color/hue
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- id: SC-03
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name: Required Features
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score: 3
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max: 5
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passed: true
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comment: Has violins, swarm points, grouping, transparency; however swarm
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points use jitter rather than true swarm positioning
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- id: SC-04
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name: Data Range
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score: 3
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max: 3
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passed: true
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comment: All data visible within axes
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- id: SC-05
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name: Legend Accuracy
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score: 2
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max: 2
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passed: true
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comment: Legend correctly identifies Novice and Expert groups
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- id: SC-06
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name: Title Format
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score: 2
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max: 2
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passed: true
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comment: Correct format '{spec-id} · {library} · pyplots.ai'
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data_quality:
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score: 20
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max: 20
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items:
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- id: DQ-01
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name: Feature Coverage
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score: 8
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max: 8
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passed: true
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comment: Shows varying distributions across complexity levels and expertise,
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different spreads visible
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- id: DQ-02
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name: Realistic Context
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score: 7
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max: 7
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passed: true
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comment: Response time across task complexity is a real, neutral, plausible
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scenario
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- id: DQ-03
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name: Appropriate Scale
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score: 5
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max: 5
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passed: true
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comment: Response times in 200-1400ms range are realistic for cognitive tasks
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code_quality:
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score: 9
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max: 10
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items:
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- id: CQ-01
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name: KISS Structure
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score: 3
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max: 3
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passed: true
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comment: Simple imports -> data -> plot -> save structure
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- id: CQ-02
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name: Reproducibility
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score: 3
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max: 3
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passed: true
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comment: np.random.seed(42) set
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- id: CQ-03
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name: Clean Imports
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score: 1
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max: 2
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passed: true
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comment: All imports used, but guide_legend import may be unnecessary
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- id: CQ-04
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name: No Deprecated API
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score: 1
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max: 1
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passed: true
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comment: Uses current plotnine API
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- id: CQ-05
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name: Output Correct
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score: 1
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max: 1
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passed: true
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comment: Saves as 'plot.png'
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library_features:
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score: 2
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max: 5
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items:
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- id: LF-01
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name: Distinctive Features
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score: 2
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max: 5
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passed: false
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comment: Uses plotnine grammar of graphics with layered geoms and position_dodge,
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but uses geom_jitter instead of proper swarm positioning
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verdict: APPROVED
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impl_tags:
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dependencies: []
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techniques:
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- layer-composition
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patterns:
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- data-generation
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- iteration-over-groups
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dataprep: []
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styling:
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- alpha-blending
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- grid-styling

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