From b94361a8fd5143c3b5347804792f8add77e1633a Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 24 May 2026 07:30:39 +0000 Subject: [PATCH 1/5] feat(pygal): implement linked-views-selection MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Regen from quality 81. Addressed: - Font sizes corrected to sub_style values (44/32/26/26) matching pygal library prompt - Switched from Okabe-Ito to canonical ANYPLOT_PALETTE (#009E73 first series) - Fixed PIL composite bug (hex color string → RGB tuple), composite is exactly 3200×1800 - View 3 changed from Line to pygal.Box (Tukey box plot) — distinctive pygal feature, LM-02 - Scatter uses stroke=False for true dot-only scatter (no connecting lines) - Bar chart per-species (serie-0/1/2 = setosa/versicolor/virginica) enables correct JS selection sync - HTML interaction upgraded: custom species-selector buttons with CSS-class-based highlight across all three SVG charts - Storytelling improved: scatter shows 2D petal cluster separation; bar confirms 1D petal spread; box reveals sepal length overlap — coherent scientific narrative Co-Authored-By: Claude Sonnet 4.6 --- .../implementations/python/pygal.py | 561 ++++++------------ 1 file changed, 183 insertions(+), 378 deletions(-) diff --git a/plots/linked-views-selection/implementations/python/pygal.py b/plots/linked-views-selection/implementations/python/pygal.py index fb0ef5e3c1..7d074235f9 100644 --- a/plots/linked-views-selection/implementations/python/pygal.py +++ b/plots/linked-views-selection/implementations/python/pygal.py @@ -1,20 +1,20 @@ -""" anyplot.ai +"""anyplot.ai linked-views-selection: Multiple Linked Views with Selection Sync -Library: pygal 3.1.0 | Python 3.13.13 -Quality: 81/100 | Created: 2026-05-17 +Library: pygal | Python 3.13 +Quality: pending | Updated: 2026-05-24 """ import os import sys -# Ensure proper module loading by prioritizing venv packages +# Prioritize venv packages over the current directory (script is named pygal.py) venv_path = [p for p in sys.path if ".venv" in p] sys.path = venv_path + [p for p in sys.path if ".venv" not in p and p != ""] -import numpy as np # noqa: E402 import pandas as pd # noqa: E402 import pygal # noqa: E402 +from PIL import Image # noqa: E402 from pygal.style import Style # noqa: E402 from sklearn.datasets import load_iris # noqa: E402 @@ -27,401 +27,206 @@ INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0" INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F" -OKABE_ITO = ("#009E73", "#D55E00", "#0072B2", "#CC79A7", "#E69F00", "#56B4E9", "#F0E442") +ANYPLOT_PALETTE = ("#009E73", "#9418DB", "#B71D27", "#16B8F3", "#99B314", "#D359A7", "#BA843E") -# Create custom style -custom_style = Style( +# Canvas layout (3200 × 1800 exact) +CANVAS_W, CANVAS_H = 3200, 1800 +MARGIN, GAP = 40, 20 +TOP_H = 860 +BOT_H = CANVAS_H - 2 * MARGIN - TOP_H - GAP # 840 +HALF_W = (CANVAS_W - 2 * MARGIN - GAP) // 2 # 1550 +FULL_W = CANVAS_W - 2 * MARGIN # 3120 + +# Sub-chart style (sized for partial-canvas charts) +sub_style = Style( background=PAGE_BG, plot_background=PAGE_BG, foreground=INK, foreground_strong=INK, foreground_subtle=INK_MUTED, - colors=OKABE_ITO, - title_font_size=24, - label_font_size=18, - major_label_font_size=16, - legend_font_size=14, - value_font_size=12, - stroke_width=2, + colors=ANYPLOT_PALETTE, + title_font_size=44, + label_font_size=32, + major_label_font_size=26, + legend_font_size=26, + value_font_size=20, + stroke_width=2.5, ) # Data: Iris dataset iris = load_iris() -X = iris.data -y = iris.target -target_names = iris.target_names -feature_names = ["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"] - -df = pd.DataFrame(X, columns=feature_names) -df["species"] = [target_names[i] for i in y] -df["index"] = range(len(df)) +df = pd.DataFrame(iris.data, columns=["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"]) +df["species"] = [iris.target_names[i] for i in iris.target] +means = df.groupby("species")[["Petal Length", "Sepal Length"]].mean() -# Prepare data for linked views -species_colors = {target_names[0]: OKABE_ITO[0], target_names[1]: OKABE_ITO[1], target_names[2]: OKABE_ITO[2]} - -# View 1: Scatter plot (Petal Width vs Petal Length, colored by species) +# View 1 (top-left): Scatter — Petal Length vs Petal Width (clearest cluster separation) scatter = pygal.XY( - width=1500, - height=900, - title="Petal Dimensions · linked-views-selection · pygal · anyplot.ai", + width=HALF_W, + height=TOP_H, + title="Petal Length vs Petal Width", x_title="Petal Length (cm)", y_title="Petal Width (cm)", - style=custom_style, + style=sub_style, show_legend=True, + dots_size=5, + stroke=False, + show_x_guides=True, + show_y_guides=True, ) - -for sp in target_names: - species_data = df[df["species"] == sp] - data_points = [(row["Petal Length"], row["Petal Width"]) for _, row in species_data.iterrows()] - scatter.add(sp, data_points, dots_size=5) - +for sp in iris.target_names: + sub = df[df["species"] == sp] + scatter.add(sp, list(zip(sub["Petal Length"].round(2), sub["Petal Width"].round(2), strict=True))) scatter_svg = scatter.render() +scatter.render_to_png(f"scatter-{THEME}.png") -# View 2: Bar chart (species counts) -bar_chart = pygal.Bar( - width=1500, - height=900, - title="Species Distribution · linked-views-selection · pygal · anyplot.ai", - y_title="Count", - style=custom_style, - show_legend=False, +# View 2 (top-right): Bar — mean Petal Length per species (confirms 1-D separation) +bar = pygal.Bar( + width=HALF_W, + height=TOP_H, + title="Mean Petal Length by Species", + y_title="Petal Length (cm)", + style=sub_style, + show_legend=True, ) - -species_counts = df["species"].value_counts().sort_index() -for sp in target_names: - if sp in species_counts.index: - bar_chart.add(sp, [species_counts[sp]]) - -bar_chart.x_labels = ["Count"] -bar_svg = bar_chart.render() - -# View 3: Histogram-like plot (Sepal Length distribution by species) -histogram = pygal.Line( - width=1500, - height=900, - title="Sepal Length Distribution · linked-views-selection · pygal · anyplot.ai", - x_title="Sepal Length (cm)", - y_title="Frequency", - style=custom_style, +bar.x_labels = ["Mean Petal Length"] +for sp in iris.target_names: + bar.add(sp, [round(means.loc[sp, "Petal Length"], 2)]) +bar_svg = bar.render() +bar.render_to_png(f"bar-{THEME}.png") + +# View 3 (bottom, full width): Box — Sepal Length distribution (species overlap visible) +title_main = "linked-views-selection · python · pygal · anyplot.ai" +box = pygal.Box( + width=FULL_W, + height=BOT_H, + title=title_main, + y_title="Sepal Length (cm)", + style=sub_style, show_legend=True, - dots_size=4, + box_mode="tukey", ) - -# Create histogram data -bins = np.linspace(df["Sepal Length"].min(), df["Sepal Length"].max(), 12) - -for sp in target_names: - species_data = df[df["species"] == sp]["Sepal Length"] - hist, bin_edges = np.histogram(species_data, bins=bins) - histogram.add(sp, list(hist.astype(int))) - -histogram.x_labels = [f"{b:.1f}" for b in bins[:-1]] -histogram_svg = histogram.render() - -# Create combined HTML with linked selection JavaScript -html_content = ( - """ - - - - linked-views-selection · pygal · anyplot.ai - - - - -
-

Multiple Linked Views with Selection Sync

- -
-

Explore linked data: Click on bars or lines to highlight corresponding species across all views.

-

Selected: All species

- -
- -
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- - - -""" +for sp in iris.target_names: + box.add(sp, df[df["species"] == sp]["Sepal Length"].tolist()) +box_svg = box.render() +box.render_to_png(f"box-{THEME}.png") + +# Composite PNG: exactly 3200 × 1800 px +page_bg_rgb = tuple(int(PAGE_BG.lstrip("#")[i : i + 2], 16) for i in (0, 2, 4)) +canvas = Image.new("RGB", (CANVAS_W, CANVAS_H), page_bg_rgb) + +img_scatter = Image.open(f"scatter-{THEME}.png").resize((HALF_W, TOP_H), Image.LANCZOS) +img_bar = Image.open(f"bar-{THEME}.png").resize((HALF_W, TOP_H), Image.LANCZOS) +img_box = Image.open(f"box-{THEME}.png").resize((FULL_W, BOT_H), Image.LANCZOS) + +canvas.paste(img_scatter, (MARGIN, MARGIN)) +canvas.paste(img_bar, (MARGIN + HALF_W + GAP, MARGIN)) +canvas.paste(img_box, (MARGIN, MARGIN + TOP_H + GAP)) +canvas.save(f"plot-{THEME}.png") + +# Interactive HTML with linked species selection +scatter_svg_str = scatter_svg.decode("utf-8") +bar_svg_str = bar_svg.decode("utf-8") +box_svg_str = box_svg.decode("utf-8") + +html_open = ( + "\n\n\n" + ' \n' + " linked-views-selection · pygal · anyplot.ai\n" + " \n\n\n" + "

Multiple Linked Views with Selection Sync

\n" + '

linked-views-selection · python · pygal · anyplot.ai

\n' + '
\n' + " \n" + ' \n' + ' \n' + ' \n' + ' \n' + ' Selected: All species\n' + "
\n" + '
\n' + '
\n' ) -# Save HTML file -with open(f"plot-{THEME}.html", "w") as f: - f.write(html_content) - -# For PNG output, create a composite image with all three views -# First, render each chart as PNG -scatter.render_to_png(f"scatter-{THEME}.png") -bar_chart.render_to_png(f"bar-{THEME}.png") -histogram.render_to_png(f"histogram-{THEME}.png") - -# Load the PNG images and combine them using PIL -try: - from PIL import Image - - # Open images - img_scatter = Image.open(f"scatter-{THEME}.png") - img_bar = Image.open(f"bar-{THEME}.png") - img_histogram = Image.open(f"histogram-{THEME}.png") - - # Create a new image for the composite (2x2 grid) - width = img_scatter.width + img_bar.width + 60 - height = img_scatter.height + img_histogram.height + 60 - - composite = Image.new("RGB", (width, height), PAGE_BG.replace("#", "0x")) - - # Paste images - composite.paste(img_scatter, (10, 10)) - composite.paste(img_bar, (img_scatter.width + 20, 10)) - composite.paste(img_histogram, (10, img_scatter.height + 20)) - - # Save composite - composite.save(f"plot-{THEME}.png") +html_mid1 = '\n
\n
\n' + +html_mid2 = '\n
\n
\n
\n' + +html_close = ( + "\n
\n\n" + " \n" + "\n" +) -except Exception: - # If PIL is not available, just use the scatter plot as fallback - import shutil +html_content = html_open + scatter_svg_str + html_mid1 + bar_svg_str + html_mid2 + box_svg_str + html_close - shutil.copy(f"scatter-{THEME}.png", f"plot-{THEME}.png") +with open(f"plot-{THEME}.html", "w", encoding="utf-8") as f: + f.write(html_content) From 22befce5923d04203a86f8094a5f62becd11d405 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 24 May 2026 07:30:52 +0000 Subject: [PATCH 2/5] chore(pygal): add metadata for linked-views-selection --- .../metadata/python/pygal.yaml | 252 +----------------- 1 file changed, 9 insertions(+), 243 deletions(-) diff --git a/plots/linked-views-selection/metadata/python/pygal.yaml b/plots/linked-views-selection/metadata/python/pygal.yaml index 46fed9976a..1b095e41ba 100644 --- a/plots/linked-views-selection/metadata/python/pygal.yaml +++ b/plots/linked-views-selection/metadata/python/pygal.yaml @@ -1,10 +1,13 @@ +# Per-library metadata for pygal implementation of linked-views-selection +# Auto-generated by impl-generate.yml + library: pygal language: python specification_id: linked-views-selection created: '2026-05-17T00:37:37Z' -updated: '2026-05-17T00:47:49Z' -generated_by: claude-haiku -workflow_run: 25976974141 +updated: '2026-05-24T07:30:52Z' +generated_by: claude-sonnet +workflow_run: 26354894419 issue: 3344 language_version: 3.13.13 library_version: 3.1.0 @@ -12,244 +15,7 @@ preview_url_light: https://storage.googleapis.com/anyplot-images/plots/linked-vi preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-dark.png preview_html_light: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-light.html preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-dark.html -quality_score: 81 +quality_score: null review: - strengths: - - Theme-correct implementation with perfect palette compliance in both light and - dark renders - - 'All spec-required features present: three coordinated views with working JavaScript-based - linked selection' - - Clean, maintainable code with proper theme token handling and no unnecessary abstraction - - Perfect data quality using iris dataset with clear variation across species and - realistic scientific context - - 'Correct Okabe-Ito color scheme (#009E73, #D55E00, #0072B2) applied consistently - across all three views' - - Pragmatic HTML/JavaScript solution for pygal's static nature, enabling functional - interactive selection - weaknesses: - - Font sizes slightly undersized (24/18/16/14 vs recommended 28/22/18/16 for pixel-based - libraries) - - Design relies on library defaults rather than custom sophistication or visual - refinement - - Limited use of distinctive pygal features - JavaScript linking is DOM-based approach - rather than leveraging pygal's native capabilities - - Chart dimensions (1500×900 per view, composite ~3000×1800px) smaller than recommended - 4800×2700 or 3600×3600 guidance - - Minimal visual hierarchy or data storytelling - three views presented functionally - but without compelling visual emphasis - image_description: |- - Light render (plot-light.png): - Background: Warm off-white (#FAF8F1), exactly as specified - Chrome: Title, axis labels, tick labels all visible in dark text against light background. Clear contrast and readability. - Data: Three coordinated plots arranged in 2-column grid (scatter plot top-left, histogram top-right, bar chart full-width bottom). Scatter shows petal dimensions with three colored species (green #009E73, orange #D55E00, blue #0072B2). Bar chart shows species counts in same colors. Histogram shows sepal length distribution by species with same colors. - Legibility verdict: PASS - All text readable and visible; no legibility issues - - Dark render (plot-dark.png): - Background: Warm near-black (#1A1A17), exactly as specified - Chrome: Title, axis labels, tick labels all visible in light text against dark background. Excellent contrast. - Data: Same three-view layout with identical colors to light render (green #009E73, orange #D55E00, blue #0072B2) - confirming color consistency across themes. Only chrome has flipped to light tones. - Legibility verdict: PASS - All text visible and readable; no dark-on-dark issues detected. Grid lines subtle but visible. - - Both renders properly implement theme-adaptive chrome with consistent data colors across themes. - criteria_checklist: - visual_quality: - score: 28 - max: 30 - items: - - id: VQ-01 - name: Text Legibility - score: 7 - max: 8 - passed: true - comment: All text clearly readable in both themes, but font sizes slightly - undersized (24 vs 28 recommended for title, etc.) - - id: VQ-02 - name: No Overlap - score: 6 - max: 6 - passed: true - comment: Grid layout cleanly separates three charts with no overlapping text - - id: VQ-03 - name: Element Visibility - score: 6 - max: 6 - passed: true - comment: All markers, lines, bars clearly visible and appropriately sized - for data density - - id: VQ-04 - name: Color Accessibility - score: 2 - max: 2 - passed: true - comment: Okabe-Ito palette is colorblind-safe; good contrast between series - - id: VQ-05 - name: Layout & Canvas - score: 3 - max: 4 - passed: true - comment: Good 2-column grid layout with full-width bar chart; dimensions ~3000×1800px - (slightly smaller than recommended 4800×2700) - - id: VQ-06 - name: Axis Labels & Title - score: 2 - max: 2 - passed: true - comment: All titles descriptive, axis labels include units (e.g., 'Petal Length - (cm)') - - id: VQ-07 - name: Palette Compliance - score: 2 - max: 2 - passed: true - comment: 'Perfect: first series is #009E73; colors identical across light/dark; - backgrounds correct (#FAF8F1 light, #1A1A17 dark); theme-adaptive chrome - in both renders' - design_excellence: - score: 8 - max: 20 - items: - - id: DE-01 - name: Aesthetic Sophistication - score: 3 - max: 8 - passed: false - comment: Uses Okabe-Ito palette and clean layout, but styling relies on library - defaults without custom design thought - - id: DE-02 - name: Visual Refinement - score: 2 - max: 6 - passed: false - comment: Minimal customization beyond pygal defaults; standard grid, no special - visual refinements - - id: DE-03 - name: Data Storytelling - score: 3 - max: 6 - passed: false - comment: Layout creates some structure (species distribution, then dimensional - spread), but lacks strong visual hierarchy or emphasis to guide insight - spec_compliance: - score: 15 - max: 15 - items: - - id: SC-01 - name: Plot Type - score: 5 - max: 5 - passed: true - comment: 'Correct: scatter (XY), bar, and histogram-like (Line with bins)' - - id: SC-02 - name: Required Features - score: 4 - max: 4 - passed: true - comment: 'All present: 3 coordinated views, selection sync (JavaScript), consistent - colors, de-emphasis (opacity 0.2), reset button, selection count' - - id: SC-03 - name: Data Mapping - score: 3 - max: 3 - passed: true - comment: 'Scatter: petal length vs width, colored by species; Bar: species - counts; Histogram: sepal length distribution by species' - - id: SC-04 - name: Title & Legend - score: 3 - max: 3 - passed: true - comment: Titles include spec-id, library, and site; legends present where - appropriate - data_quality: - score: 15 - max: 15 - items: - - id: DQ-01 - name: Feature Coverage - score: 6 - max: 6 - passed: true - comment: 'Iris dataset shows all aspects: three species, multiple dimensions, - clear variation' - - id: DQ-02 - name: Realistic Context - score: 5 - max: 5 - passed: true - comment: Real, well-known scientific dataset with neutral, educational context - - id: DQ-03 - name: Appropriate Scale - score: 4 - max: 4 - passed: true - comment: Factually correct iris measurements in cm with accurate ranges and - proportions - code_quality: - score: 10 - max: 10 - items: - - id: CQ-01 - name: KISS Structure - score: 3 - max: 3 - passed: true - comment: 'Simple linear flow: imports → theme setup → data loading → plot - creation → HTML generation → save' - - id: CQ-02 - name: Reproducibility - score: 2 - max: 2 - passed: true - comment: Uses deterministic load_iris(); no random seed needed - - id: CQ-03 - name: Clean Imports - score: 2 - max: 2 - passed: true - comment: All imports used; sklearn.datasets allowed for data loading - - id: CQ-04 - name: Code Elegance - score: 2 - max: 2 - passed: true - comment: Clean, pragmatic approach; JavaScript in HTML (not Python); no fake - UI or over-engineering - - id: CQ-05 - name: Output & API - score: 1 - max: 1 - passed: true - comment: 'Correct file naming: plot-{THEME}.png and plot-{THEME}.html' - library_mastery: - score: 5 - max: 10 - items: - - id: LM-01 - name: Idiomatic Usage - score: 4 - max: 5 - passed: true - comment: 'Good idiomatic pygal usage: chart classes, Style object for theming, - .add() for series, standard rendering' - - id: LM-02 - name: Distinctive Features - score: 1 - max: 5 - passed: false - comment: JavaScript linking is DOM-based DOM-based workaround, not leveraging - distinctive pygal features; could use custom SVG manipulation or native - pygal capabilities - verdict: APPROVED -impl_tags: - dependencies: - - sklearn - - pillow - techniques: - - html-export - - subplots - patterns: - - dataset-loading - - iteration-over-groups - dataprep: - - binning - styling: [] + strengths: [] + weaknesses: [] From 16b7488e6f8f194de8fee27cf7cc8404bc580b0b Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 24 May 2026 07:38:45 +0000 Subject: [PATCH 3/5] chore(pygal): update quality score 80 and review feedback for linked-views-selection --- .../implementations/python/pygal.py | 6 +- .../metadata/python/pygal.yaml | 244 +++++++++++++++++- 2 files changed, 240 insertions(+), 10 deletions(-) diff --git a/plots/linked-views-selection/implementations/python/pygal.py b/plots/linked-views-selection/implementations/python/pygal.py index 7d074235f9..137089c5c2 100644 --- a/plots/linked-views-selection/implementations/python/pygal.py +++ b/plots/linked-views-selection/implementations/python/pygal.py @@ -1,7 +1,7 @@ -"""anyplot.ai +""" anyplot.ai linked-views-selection: Multiple Linked Views with Selection Sync -Library: pygal | Python 3.13 -Quality: pending | Updated: 2026-05-24 +Library: pygal 3.1.0 | Python 3.13.13 +Quality: 80/100 | Updated: 2026-05-24 """ import os diff --git a/plots/linked-views-selection/metadata/python/pygal.yaml b/plots/linked-views-selection/metadata/python/pygal.yaml index 1b095e41ba..abfcb96e56 100644 --- a/plots/linked-views-selection/metadata/python/pygal.yaml +++ b/plots/linked-views-selection/metadata/python/pygal.yaml @@ -1,11 +1,8 @@ -# Per-library metadata for pygal implementation of linked-views-selection -# Auto-generated by impl-generate.yml - library: pygal language: python specification_id: linked-views-selection created: '2026-05-17T00:37:37Z' -updated: '2026-05-24T07:30:52Z' +updated: '2026-05-24T07:38:44Z' generated_by: claude-sonnet workflow_run: 26354894419 issue: 3344 @@ -15,7 +12,240 @@ preview_url_light: https://storage.googleapis.com/anyplot-images/plots/linked-vi preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-dark.png preview_html_light: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-light.html preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-dark.html -quality_score: null +quality_score: 80 review: - strengths: [] - weaknesses: [] + strengths: + - Excellent use of the Iris dataset — real, factually correct, neutral scientific + dataset that clearly demonstrates multi-view linked selection + - 'Creative SVG export pattern: capturing raw SVG bytes and exploiting pygal''s + .serie-N CSS classes for JavaScript-driven cross-chart selection sync is a genuinely + distinctive pygal technique' + - 'Perfect palette compliance in both themes — first series is #009E73, canonical + order maintained, backgrounds #FAF8F1/#1A1A17 correct, identical data colors across + light/dark' + - Complete interactive HTML with species filter buttons, reset button, and selection + count display + - Clean KISS code structure with no functions or classes; all 10 code quality points + earned + weaknesses: + - Sub-chart font sizes (title=44, label=32, major_label=26) are below the pygal + style-guide recommendation (66/56/44); raise to at least title=54, label=44, major_label=36 + in sub-charts so text is more prominent in the composite view + - Linked selection is via external species buttons, not within-chart brushing or + clicking — the spec requires selection FROM within a view to propagate to others; + make legend items or series elements clickable via injected JavaScript onClick + handlers that sync active selection across all three charts + - Box chart y-axis starts at 0 but sepal lengths start at ~4.3; reduce y_range_min + to ~3.5 so data occupies at least 70% of the chart area vertically + - Dashed grid lines present on all charts; disable grid on bar and box charts (show_x_guides=False, + show_y_guides=False) and keep grid only on scatter chart where it aids readability + image_description: |- + Light render (plot-light.png): + Background: Warm off-white #FAF8F1 — correct anyplot light surface + Chrome: Title "linked-views-selection · python · pygal · anyplot.ai" in box chart — dark text, readable. Scatter sub-title "Petal Length vs Petal Width" and bar sub-title "Mean Petal Length by Species" both readable in dark text. Axis labels "Petal Length (cm)", "Petal Width (cm)", "Sepal Length (cm)" readable in dark text. Tick labels readable but small (major_label_font_size=26). Legend entries (setosa, versicolor, virginica) readable in each sub-chart. + Data: First series setosa in #009E73 (teal) — correct. Second series versicolor in #9418DB (purple). Third series virginica in #B71D27 (red). All scatter dots visible, bar heights clearly distinct, box plots well-separated. + Legibility verdict: PASS — all text readable against light background; font sizes below style-guide recommendation but still legible + + Dark render (plot-dark.png): + Background: Near-black #1A1A17 — correct anyplot dark surface + Chrome: All text renders in light/off-white tones against dark background. Title, axis labels, tick labels, and legend labels all clearly readable. No dark-on-dark failures detected. Grid lines adapt to muted light tone via INK_MUTED token. + Data: Colors identical to light render — setosa #009E73, versicolor #9418DB, virginica #B71D27. Only chrome elements (backgrounds, text, grid) have flipped themes. + Legibility verdict: PASS — no dark-on-dark failures; all text clearly readable against dark background + criteria_checklist: + visual_quality: + score: 25 + max: 30 + items: + - id: VQ-01 + name: Text Legibility + score: 5 + max: 8 + passed: true + comment: Font sizes explicitly set but below recommendation (title=44 vs 66, + label=32 vs 56, major_label=26 vs 44); text readable but small in composite + sub-charts + - id: VQ-02 + name: No Overlap + score: 6 + max: 6 + passed: true + comment: No text or element overlaps in any of the three sub-charts + - id: VQ-03 + name: Element Visibility + score: 5 + max: 6 + passed: true + comment: Scatter dots at size=5 visible for 150 points; slightly below optimal + for this density + - id: VQ-04 + name: Color Accessibility + score: 2 + max: 2 + passed: true + comment: Anyplot palette is CVD-safe; teal/purple/red clearly distinguishable + - id: VQ-05 + name: Layout & Canvas + score: 3 + max: 4 + passed: true + comment: Good composite layout; bar chart has sparse horizontal space; box + chart has large empty lower area (y-axis 0-4.3 unused) + - id: VQ-06 + name: Axis Labels & Title + score: 2 + max: 2 + passed: true + comment: 'All axes include units: Petal Length (cm), Petal Width (cm), Sepal + Length (cm)' + - id: VQ-07 + name: Palette Compliance + score: 2 + max: 2 + passed: true + comment: 'First series #009E73 correct; canonical palette order; backgrounds + #FAF8F1/#1A1A17 correct; identical data colors across themes' + design_excellence: + score: 10 + max: 20 + items: + - id: DE-01 + name: Aesthetic Sophistication + score: 4 + max: 8 + passed: true + comment: Custom Style object with anyplot palette; thoughtfully configured + but not publication-ready + - id: DE-02 + name: Visual Refinement + score: 3 + max: 6 + passed: true + comment: INK_MUTED grid colors good; grid lines are dashed (guide prefers + solid); spines not removed + - id: DE-03 + name: Data Storytelling + score: 3 + max: 6 + passed: true + comment: Three complementary views tell coherent Iris story; above default + but no focal point or visual hierarchy + spec_compliance: + score: 14 + max: 15 + items: + - id: SC-01 + name: Plot Type + score: 5 + max: 5 + passed: true + comment: 'Three coordinated views: XY scatter, Bar, Box — all correct' + - id: SC-02 + name: Required Features + score: 3 + max: 4 + passed: true + comment: 'Selection mechanism, reset, count display all present; deduction: + selection via external buttons not within-chart brushing' + - id: SC-03 + name: Data Mapping + score: 3 + max: 3 + passed: true + comment: All spec data dimensions correctly mapped across three views + - id: SC-04 + name: Title & Legend + score: 3 + max: 3 + passed: true + comment: Mandated title format correct in box chart; legends correctly label + all three species + data_quality: + score: 14 + max: 15 + items: + - id: DQ-01 + name: Feature Coverage + score: 5 + max: 6 + passed: true + comment: Three chart types covering 2D clustering, mean comparison, and distribution; + dynamic selection only visible in HTML + - id: DQ-02 + name: Realistic Context + score: 5 + max: 5 + passed: true + comment: 'Iris dataset: canonical real scientific botany dataset, neutral + and comprehensible' + - id: DQ-03 + name: Appropriate Scale + score: 4 + max: 4 + passed: true + comment: 'Factually correct iris measurements: petal 1-7cm, sepal 4-8cm' + code_quality: + score: 10 + max: 10 + items: + - id: CQ-01 + name: KISS Structure + score: 3 + max: 3 + passed: true + comment: Flat top-level flow, no functions or classes + - id: CQ-02 + name: Reproducibility + score: 2 + max: 2 + passed: true + comment: Deterministic Iris dataset, no random generation + - id: CQ-03 + name: Clean Imports + score: 2 + max: 2 + passed: true + comment: All 7 imports are used + - id: CQ-04 + name: Code Elegance + score: 2 + max: 2 + passed: true + comment: Appropriate complexity for multi-SVG HTML generation; no fake functionality + - id: CQ-05 + name: Output & API + score: 1 + max: 1 + passed: true + comment: Saves plot-{THEME}.png and plot-{THEME}.html correctly + library_mastery: + score: 7 + max: 10 + items: + - id: LM-01 + name: Idiomatic Usage + score: 4 + max: 5 + passed: true + comment: Correct Style object usage, correct XY tuple format, chart.render() + for SVG bytes + - id: LM-02 + name: Distinctive Features + score: 3 + max: 5 + passed: true + comment: Exploits pygal's SVG architecture and .serie-N CSS classes for cross-chart + JavaScript selection sync + verdict: REJECTED +impl_tags: + dependencies: + - sklearn + - pillow + techniques: + - subplots + - html-export + patterns: + - dataset-loading + - iteration-over-groups + - groupby-aggregation + dataprep: [] + styling: [] From 8f85d0e3abcd3affaa362f27d45785c46510b3b0 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 24 May 2026 07:43:19 +0000 Subject: [PATCH 4/5] fix(pygal): address review feedback for linked-views-selection Attempt 1/3 - fixes based on AI review --- .../implementations/python/pygal.py | 46 +++++++++++++++---- 1 file changed, 38 insertions(+), 8 deletions(-) diff --git a/plots/linked-views-selection/implementations/python/pygal.py b/plots/linked-views-selection/implementations/python/pygal.py index 137089c5c2..9b14d9bf26 100644 --- a/plots/linked-views-selection/implementations/python/pygal.py +++ b/plots/linked-views-selection/implementations/python/pygal.py @@ -1,4 +1,4 @@ -""" anyplot.ai +"""anyplot.ai linked-views-selection: Multiple Linked Views with Selection Sync Library: pygal 3.1.0 | Python 3.13.13 Quality: 80/100 | Updated: 2026-05-24 @@ -45,11 +45,11 @@ foreground_strong=INK, foreground_subtle=INK_MUTED, colors=ANYPLOT_PALETTE, - title_font_size=44, - label_font_size=32, - major_label_font_size=26, - legend_font_size=26, - value_font_size=20, + title_font_size=54, + label_font_size=44, + major_label_font_size=36, + legend_font_size=36, + value_font_size=28, stroke_width=2.5, ) @@ -87,6 +87,8 @@ y_title="Petal Length (cm)", style=sub_style, show_legend=True, + show_x_guides=False, + show_y_guides=False, ) bar.x_labels = ["Mean Petal Length"] for sp in iris.target_names: @@ -104,9 +106,13 @@ style=sub_style, show_legend=True, box_mode="tukey", + show_x_guides=False, + show_y_guides=False, ) for sp in iris.target_names: box.add(sp, df[df["species"] == sp]["Sepal Length"].tolist()) +# Force y-axis ticks from 4–8 so data fills chart (sepal length 4.3–7.9; avoids wasted 0-4 blank) +box.y_labels = [4, 5, 6, 7, 8] box_svg = box.render() box.render_to_png(f"box-{THEME}.png") @@ -164,7 +170,7 @@ "

Multiple Linked Views with Selection Sync

\n" '

linked-views-selection · python · pygal · anyplot.ai

\n' '
\n' - " \n" + " \n" ' \n' ' \n' ' \n' @@ -221,7 +227,31 @@ " applySelection();\n" " });\n" " });\n\n" - " applySelection();\n" + " applySelection();\n\n" + " function addSeriesClickHandlers() {\n" + " ['scatter', 'bar', 'box'].forEach(function(chartId) {\n" + " var wrap = document.getElementById(chartId);\n" + " if (!wrap) return;\n" + " for (var i = 0; i < 3; i++) {\n" + " (function(serIdx) {\n" + " var seriesEls = wrap.querySelectorAll('.serie-' + serIdx);\n" + " seriesEls.forEach(function(el) {\n" + " el.style.cursor = 'pointer';\n" + " el.addEventListener('click', function(e) {\n" + " e.stopPropagation();\n" + " if (active.has(serIdx)) {\n" + " if (active.size > 1) active.delete(serIdx);\n" + " } else {\n" + " active.add(serIdx);\n" + " }\n" + " applySelection();\n" + " });\n" + " });\n" + " })(i);\n" + " }\n" + " });\n" + " }\n\n" + " addSeriesClickHandlers();\n" " \n" "\n" ) From 04af0ad8d82a9748813d22f7a36bf4f7220967b8 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Sun, 24 May 2026 07:50:41 +0000 Subject: [PATCH 5/5] chore(pygal): update quality score 85 and review feedback for linked-views-selection --- .../implementations/python/pygal.py | 4 +- .../metadata/python/pygal.yaml | 176 ++++++++++-------- 2 files changed, 96 insertions(+), 84 deletions(-) diff --git a/plots/linked-views-selection/implementations/python/pygal.py b/plots/linked-views-selection/implementations/python/pygal.py index 9b14d9bf26..d76f9402de 100644 --- a/plots/linked-views-selection/implementations/python/pygal.py +++ b/plots/linked-views-selection/implementations/python/pygal.py @@ -1,7 +1,7 @@ -"""anyplot.ai +""" anyplot.ai linked-views-selection: Multiple Linked Views with Selection Sync Library: pygal 3.1.0 | Python 3.13.13 -Quality: 80/100 | Updated: 2026-05-24 +Quality: 85/100 | Updated: 2026-05-24 """ import os diff --git a/plots/linked-views-selection/metadata/python/pygal.yaml b/plots/linked-views-selection/metadata/python/pygal.yaml index abfcb96e56..80e4384d9b 100644 --- a/plots/linked-views-selection/metadata/python/pygal.yaml +++ b/plots/linked-views-selection/metadata/python/pygal.yaml @@ -2,7 +2,7 @@ library: pygal language: python specification_id: linked-views-selection created: '2026-05-17T00:37:37Z' -updated: '2026-05-24T07:38:44Z' +updated: '2026-05-24T07:50:41Z' generated_by: claude-sonnet workflow_run: 26354894419 issue: 3344 @@ -12,100 +12,99 @@ preview_url_light: https://storage.googleapis.com/anyplot-images/plots/linked-vi preview_url_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-dark.png preview_html_light: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-light.html preview_html_dark: https://storage.googleapis.com/anyplot-images/plots/linked-views-selection/python/pygal/plot-dark.html -quality_score: 80 +quality_score: 85 review: strengths: - - Excellent use of the Iris dataset — real, factually correct, neutral scientific - dataset that clearly demonstrates multi-view linked selection - - 'Creative SVG export pattern: capturing raw SVG bytes and exploiting pygal''s - .serie-N CSS classes for JavaScript-driven cross-chart selection sync is a genuinely - distinctive pygal technique' - - 'Perfect palette compliance in both themes — first series is #009E73, canonical - order maintained, backgrounds #FAF8F1/#1A1A17 correct, identical data colors across - light/dark' - - Complete interactive HTML with species filter buttons, reset button, and selection - count display - - Clean KISS code structure with no functions or classes; all 10 code quality points - earned + - 'Perfect spec compliance: 3 coordinated views (scatter + bar + box) with real + HTML/JS linked selection implementing all spec requirements' + - 'Consistent anyplot palette across all three views with correct theme adaptation + (light #FAF8F1 / dark #1A1A17)' + - 'Excellent data choice: Iris dataset revealing different structural aspects — + cluster separation (scatter), magnitude differences (bar), distribution overlap + (box)' + - Real interactive linked selection in HTML output with species filter buttons, + reset functionality, click handlers on SVG chart elements, and selection count + display + - 'Idiomatic pygal usage: box_mode=tukey for Tukey whiskers, selective grid control + (scatter-only), Style object for full theme token propagation' weaknesses: - - Sub-chart font sizes (title=44, label=32, major_label=26) are below the pygal - style-guide recommendation (66/56/44); raise to at least title=54, label=44, major_label=36 - in sub-charts so text is more prominent in the composite view - - Linked selection is via external species buttons, not within-chart brushing or - clicking — the spec requires selection FROM within a view to propagate to others; - make legend items or series elements clickable via injected JavaScript onClick - handlers that sync active selection across all three charts - - Box chart y-axis starts at 0 but sepal lengths start at ~4.3; reduce y_range_min - to ~3.5 so data occupies at least 70% of the chart area vertically - - Dashed grid lines present on all charts; disable grid on bar and box charts (show_x_guides=False, - show_y_guides=False) and keep grid only on scatter chart where it aids readability + - Sub-chart font sizes (title=54, label=44, major_label=36, legend=36) are slightly + below the pygal style guide defaults (66/56/44/44) — at final composite scale + the tick labels read as slightly small; consider increasing to guide-recommended + values for sub-charts + - Bar chart uses a single x-category ('Mean Petal Length') with three bars side-by-side, + leaving horizontal axis space underutilized — x-labels for each species (setosa, + versicolor, virginica) as separate bar groups would better communicate the comparison + - 'DE-01/DE-02: Design is well-configured but not publication-ready — could be elevated + with annotation callouts highlighting key insights (e.g. ''Setosa cleanly separates + by petal dims'') or more refined grid-free chart area in sub-charts' image_description: |- Light render (plot-light.png): - Background: Warm off-white #FAF8F1 — correct anyplot light surface - Chrome: Title "linked-views-selection · python · pygal · anyplot.ai" in box chart — dark text, readable. Scatter sub-title "Petal Length vs Petal Width" and bar sub-title "Mean Petal Length by Species" both readable in dark text. Axis labels "Petal Length (cm)", "Petal Width (cm)", "Sepal Length (cm)" readable in dark text. Tick labels readable but small (major_label_font_size=26). Legend entries (setosa, versicolor, virginica) readable in each sub-chart. - Data: First series setosa in #009E73 (teal) — correct. Second series versicolor in #9418DB (purple). Third series virginica in #B71D27 (red). All scatter dots visible, bar heights clearly distinct, box plots well-separated. - Legibility verdict: PASS — all text readable against light background; font sizes below style-guide recommendation but still legible + Background: Warm off-white (#FAF8F1 confirmed) — correct anyplot light surface, not pure white + Layout: Three sub-charts composited: scatter (top-left 1550×860), bar (top-right 1550×860), box plot (bottom 3120×840) + Chrome: Sub-chart titles ("Petal Length vs Petal Width", "Mean Petal Length by Species") in dark ink, readable. Axis labels with units ("Petal Length (cm)", "Petal Width (cm)", "Sepal Length (cm)") visible. Tick labels (numeric values) are small but legible. Main anyplot title in box plot: "linked-views-selection · python · pygal · anyplot.ai" readable. + Data: Scatter shows three species clusters: setosa (green #009E73) tight cluster at low petal values, versicolor (purple #9418DB) mid-range, virginica (red #B71D27) upper-right. Bar chart shows three bars with correctly ordered heights (setosa ~1.4cm, versicolor ~4.2cm, virginica ~5.6cm). Box plot shows Tukey-style boxes with y-axis range 4–8, one outlier visible for virginica. + Legibility verdict: PASS — all text readable against the light background, no light-on-light failures Dark render (plot-dark.png): - Background: Near-black #1A1A17 — correct anyplot dark surface - Chrome: All text renders in light/off-white tones against dark background. Title, axis labels, tick labels, and legend labels all clearly readable. No dark-on-dark failures detected. Grid lines adapt to muted light tone via INK_MUTED token. - Data: Colors identical to light render — setosa #009E73, versicolor #9418DB, virginica #B71D27. Only chrome elements (backgrounds, text, grid) have flipped themes. - Legibility verdict: PASS — no dark-on-dark failures; all text clearly readable against dark background + Background: Warm near-black (#1A1A17 confirmed) — correct anyplot dark surface, not pure black + Chrome: Sub-chart titles and axis labels render in light/cream text against the dark surface — all clearly readable. Tick labels legible. Main title visible. + Data: Data colors are IDENTICAL to light render — setosa=green, versicolor=purple, virginica=red — confirming only chrome (background, text) flipped, not data palette. + Legibility verdict: PASS — no dark-on-dark failures observed; all text elements use theme-adaptive light ink on dark surface criteria_checklist: visual_quality: - score: 25 + score: 27 max: 30 items: - id: VQ-01 name: Text Legibility - score: 5 + score: 7 max: 8 passed: true - comment: Font sizes explicitly set but below recommendation (title=44 vs 66, - label=32 vs 56, major_label=26 vs 44); text readable but small in composite - sub-charts + comment: Font sizes explicitly set (title=54, label=44, major_label=36, legend=36); + readable in both themes. Slightly below style guide defaults (66/56/44) + — tick labels appear somewhat small in the composited sub-charts - id: VQ-02 name: No Overlap score: 6 max: 6 passed: true - comment: No text or element overlaps in any of the three sub-charts + comment: No overlapping elements across any of the three views - id: VQ-03 name: Element Visibility score: 5 max: 6 passed: true - comment: Scatter dots at size=5 visible for 150 points; slightly below optimal - for this density + comment: Scatter dots (dots_size=5) visible but slightly small for 150 points; + bars and boxes are prominent - id: VQ-04 name: Color Accessibility score: 2 max: 2 passed: true - comment: Anyplot palette is CVD-safe; teal/purple/red clearly distinguishable + comment: anyplot palette is CVD-safe; three species clearly distinguishable - id: VQ-05 name: Layout & Canvas score: 3 max: 4 passed: true - comment: Good composite layout; bar chart has sparse horizontal space; box - chart has large empty lower area (y-axis 0-4.3 unused) + comment: Multi-chart layout fills canvas well; bar chart uses single x-category + leaving some horizontal space underutilized - id: VQ-06 name: Axis Labels & Title score: 2 max: 2 passed: true - comment: 'All axes include units: Petal Length (cm), Petal Width (cm), Sepal - Length (cm)' + comment: All axis labels include units (cm). Title format correct. - id: VQ-07 name: Palette Compliance score: 2 max: 2 passed: true - comment: 'First series #009E73 correct; canonical palette order; backgrounds - #FAF8F1/#1A1A17 correct; identical data colors across themes' + comment: 'anyplot palette correctly applied; backgrounds #FAF8F1/#1A1A17; + theme-adaptive chrome in both renders; data colors identical across themes' design_excellence: - score: 10 + score: 11 max: 20 items: - id: DE-01 @@ -113,24 +112,25 @@ review: score: 4 max: 8 passed: true - comment: Custom Style object with anyplot palette; thoughtfully configured - but not publication-ready + comment: Multi-chart layout with consistent theming above defaults; not reaching + publication-quality due to pygal default chart chrome - id: DE-02 name: Visual Refinement score: 3 max: 6 passed: true - comment: INK_MUTED grid colors good; grid lines are dashed (guide prefers - solid); spines not removed + comment: Selective grid (scatter-only), theme-adaptive backgrounds, custom + font sizes; limited by pygal's refinement options (no spine removal) - id: DE-03 name: Data Storytelling - score: 3 + score: 4 max: 6 passed: true - comment: Three complementary views tell coherent Iris story; above default - but no focal point or visual hierarchy + comment: 'Intentional chart selection: scatter for clustering, bar for magnitude, + box for distribution — each view reveals different structure. Consistent + color coding aids cross-view comparison.' spec_compliance: - score: 14 + score: 15 max: 15 items: - id: SC-01 @@ -138,51 +138,55 @@ review: score: 5 max: 5 passed: true - comment: 'Three coordinated views: XY scatter, Bar, Box — all correct' + comment: 'Three coordinated views: scatter (XY), bar (Bar), and box plot (Box)' - id: SC-02 name: Required Features - score: 3 + score: 4 max: 4 passed: true - comment: 'Selection mechanism, reset, count display all present; deduction: - selection via external buttons not within-chart brushing' + comment: Linked selection via HTML/JS buttons + click handlers; reset button; + unselected opacity=0.08; selection count label; consistent color encoding - id: SC-03 name: Data Mapping score: 3 max: 3 passed: true - comment: All spec data dimensions correctly mapped across three views + comment: 'Correct mappings: scatter (PetalLength×PetalWidth), bar (species→MeanPetalLength), + box (species→SepalLength)' - id: SC-04 name: Title & Legend score: 3 max: 3 passed: true - comment: Mandated title format correct in box chart; legends correctly label - all three species + comment: Title 'linked-views-selection · python · pygal · anyplot.ai' correct + in box chart. Species legend labels (setosa/versicolor/virginica) match + data. data_quality: - score: 14 + score: 15 max: 15 items: - id: DQ-01 name: Feature Coverage - score: 5 + score: 6 max: 6 passed: true - comment: Three chart types covering 2D clustering, mean comparison, and distribution; - dynamic selection only visible in HTML + comment: 'Three views collectively show all aspects: cluster separation, magnitude + differences, distribution overlap, outliers (Tukey whiskers reveal one virginica + outlier)' - id: DQ-02 name: Realistic Context score: 5 max: 5 passed: true - comment: 'Iris dataset: canonical real scientific botany dataset, neutral - and comprehensible' + comment: 'Iris dataset: canonical real-world scientific dataset, neutral and + comprehensible' - id: DQ-03 name: Appropriate Scale score: 4 max: 4 passed: true - comment: 'Factually correct iris measurements: petal 1-7cm, sepal 4-8cm' + comment: Biologically accurate Iris measurements (petal 1–7cm, sepal 4–8cm); + y-axis range 4–8 avoids wasted 0–4 blank space code_quality: score: 10 max: 10 @@ -192,31 +196,34 @@ review: score: 3 max: 3 passed: true - comment: Flat top-level flow, no functions or classes + comment: 'Linear structure: imports → data → three sub-charts → composite + PNG → HTML output. No functions or classes.' - id: CQ-02 name: Reproducibility score: 2 max: 2 passed: true - comment: Deterministic Iris dataset, no random generation + comment: Iris dataset from sklearn is fully deterministic - id: CQ-03 name: Clean Imports score: 2 max: 2 passed: true - comment: All 7 imports are used + comment: All imports (os, sys, pandas, pygal, PIL, Style, load_iris) are used - id: CQ-04 name: Code Elegance score: 2 max: 2 passed: true - comment: Appropriate complexity for multi-SVG HTML generation; no fake functionality + comment: Well-structured; HTML string concatenation is verbose but appropriate + for the complex multi-chart interactive output. No fake functionality. - id: CQ-05 name: Output & API score: 1 max: 1 passed: true - comment: Saves plot-{THEME}.png and plot-{THEME}.html correctly + comment: Saves plot-{THEME}.png and plot-{THEME}.html correctly using current + pygal API library_mastery: score: 7 max: 10 @@ -226,16 +233,19 @@ review: score: 4 max: 5 passed: true - comment: Correct Style object usage, correct XY tuple format, chart.render() - for SVG bytes + comment: 'Idiomatic pygal: XY for scatter, Box with box_mode=tukey, Bar, Style + object for theme tokens, show_x/y_guides for selective grid, render() for + SVG bytes' - id: LM-02 name: Distinctive Features score: 3 max: 5 passed: true - comment: Exploits pygal's SVG architecture and .serie-N CSS classes for cross-chart - JavaScript selection sync - verdict: REJECTED + comment: 'Distinctive: SVG output embedded in multi-chart HTML dashboard with + JS linking (pygal-specific SVG class names .serie-N used for selection), + box_mode=tukey (pygal-specific Tukey whiskers), PIL compositing of pygal + sub-charts' + verdict: APPROVED impl_tags: dependencies: - sklearn @@ -243,9 +253,11 @@ impl_tags: techniques: - subplots - html-export + - hover-tooltips + - manual-ticks patterns: - dataset-loading - - iteration-over-groups - groupby-aggregation + - iteration-over-groups dataprep: [] styling: []