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feat(highcharts): implement scatter-categorical (#2633)
## Implementation: `scatter-categorical` - highcharts Implements the **highcharts** version of `scatter-categorical`. **File:** `plots/scatter-categorical/implementations/highcharts.py` --- :robot: *[impl-generate workflow](https://github.com/MarkusNeusinger/pyplots/actions/runs/20594558958)* --------- 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/scatter-categorical/implementations/highcharts.py‎

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""" pyplots.ai
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scatter-categorical: Categorical Scatter Plot
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Library: highcharts unknown | Python 3.13.11
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Quality: 92/100 | Created: 2025-12-30
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"""
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import tempfile
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import time
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import urllib.request
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from pathlib import Path
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import numpy as np
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from highcharts_core.chart import Chart
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from highcharts_core.options import HighchartsOptions
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from highcharts_core.options.series.scatter import ScatterSeries
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from selenium import webdriver
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from selenium.webdriver.chrome.options import Options
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# Data - Plant growth study with three fertilizer types
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np.random.seed(42)
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categories = ["Fertilizer A", "Fertilizer B", "Fertilizer C"]
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colors = ["#306998", "#FFD43B", "#9467BD"] # Python Blue, Python Yellow, Purple
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# Generate data for each category with different patterns
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data_by_category = {}
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n_points = 40
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# Fertilizer A: moderate growth, medium variance
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nitrogen_a = np.random.uniform(20, 80, n_points)
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growth_a = 0.4 * nitrogen_a + np.random.normal(10, 5, n_points)
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data_by_category["Fertilizer A"] = list(zip(nitrogen_a.tolist(), growth_a.tolist(), strict=True))
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# Fertilizer B: high growth, low variance (best performer)
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nitrogen_b = np.random.uniform(25, 85, n_points)
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growth_b = 0.6 * nitrogen_b + np.random.normal(15, 3, n_points)
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data_by_category["Fertilizer B"] = list(zip(nitrogen_b.tolist(), growth_b.tolist(), strict=True))
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# Fertilizer C: lower growth, higher variance
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nitrogen_c = np.random.uniform(15, 75, n_points)
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growth_c = 0.3 * nitrogen_c + np.random.normal(5, 8, n_points)
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data_by_category["Fertilizer C"] = list(zip(nitrogen_c.tolist(), growth_c.tolist(), strict=True))
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# Create chart
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chart = Chart(container="container")
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chart.options = HighchartsOptions()
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# Chart configuration
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chart.options.chart = {
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"type": "scatter",
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"width": 4800,
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"height": 2700,
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"backgroundColor": "#ffffff",
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"marginBottom": 300,
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"spacingBottom": 80,
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}
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# Title
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chart.options.title = {
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"text": "scatter-categorical · highcharts · pyplots.ai",
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"style": {"fontSize": "48px", "fontWeight": "bold"},
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}
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# Axes
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chart.options.x_axis = {
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"title": {"text": "Nitrogen Applied (kg/ha)", "style": {"fontSize": "36px"}, "margin": 30},
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"labels": {"style": {"fontSize": "28px"}},
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"gridLineWidth": 1,
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"gridLineColor": "rgba(0, 0, 0, 0.1)",
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}
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chart.options.y_axis = {
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"title": {"text": "Plant Growth (cm)", "style": {"fontSize": "36px"}},
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"labels": {"style": {"fontSize": "28px"}},
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"gridLineWidth": 1,
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"gridLineColor": "rgba(0, 0, 0, 0.1)",
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}
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# Legend
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chart.options.legend = {
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"enabled": True,
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"align": "right",
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"verticalAlign": "top",
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"layout": "vertical",
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"x": -50,
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"y": 100,
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"itemStyle": {"fontSize": "28px"},
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}
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# Plot options for scatter series
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chart.options.plot_options = {
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"scatter": {"marker": {"radius": 12, "symbol": "circle"}, "states": {"hover": {"marker": {"enabled": True}}}}
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}
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# Add series for each category
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for i, category in enumerate(categories):
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series = ScatterSeries()
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series.name = category
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series.data = data_by_category[category]
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series.color = colors[i]
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series.marker = {"radius": 12, "fillColor": colors[i], "lineWidth": 2, "lineColor": "#ffffff"}
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chart.add_series(series)
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# Download Highcharts JS
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highcharts_url = "https://code.highcharts.com/highcharts.js"
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with urllib.request.urlopen(highcharts_url, timeout=30) as response:
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highcharts_js = response.read().decode("utf-8")
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# Generate HTML with inline scripts
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html_str = chart.to_js_literal()
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html_content = f"""<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<script>{highcharts_js}</script>
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</head>
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<body style="margin:0;">
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<div id="container" style="width: 4800px; height: 2700px;"></div>
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<script>{html_str}</script>
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</body>
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</html>"""
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# Write temp HTML and take screenshot
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with tempfile.NamedTemporaryFile(mode="w", suffix=".html", delete=False, encoding="utf-8") as f:
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f.write(html_content)
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temp_path = f.name
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chrome_options = Options()
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chrome_options.add_argument("--headless")
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chrome_options.add_argument("--no-sandbox")
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chrome_options.add_argument("--disable-dev-shm-usage")
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chrome_options.add_argument("--disable-gpu")
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chrome_options.add_argument("--window-size=4800,2700")
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driver = webdriver.Chrome(options=chrome_options)
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driver.get(f"file://{temp_path}")
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time.sleep(5)
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driver.save_screenshot("plot.png")
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driver.quit()
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Path(temp_path).unlink()
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# Also save HTML for interactive version
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with open("plot.html", "w", encoding="utf-8") as f:
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interactive_html = f"""<!DOCTYPE html>
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<html>
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<head>
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<meta charset="utf-8">
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<title>scatter-categorical · highcharts · pyplots.ai</title>
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<script src="https://code.highcharts.com/highcharts.js"></script>
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</head>
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<body style="margin:0; display:flex; justify-content:center; align-items:center; min-height:100vh; background:#f5f5f5;">
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<div id="container" style="width: 1200px; height: 675px;"></div>
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<script>{html_str}</script>
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</body>
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</html>"""
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f.write(interactive_html)

‎plots/scatter-categorical/metadata/highcharts.yaml‎

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library: highcharts
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specification_id: scatter-categorical
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created: '2025-12-30T10:40:05Z'
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updated: '2025-12-30T10:46:20Z'
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generated_by: claude-opus-4-5-20251101
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workflow_run: 20594558958
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issue: 0
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python_version: 3.13.11
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library_version: unknown
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preview_url: https://storage.googleapis.com/pyplots-images/plots/scatter-categorical/highcharts/plot.png
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preview_thumb: https://storage.googleapis.com/pyplots-images/plots/scatter-categorical/highcharts/plot_thumb.png
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preview_html: https://storage.googleapis.com/pyplots-images/plots/scatter-categorical/highcharts/plot.html
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quality_score: 92
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review:
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strengths:
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- Excellent colorblind-safe palette (blue/yellow/purple)
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- Clear visual separation between categories with distinct patterns
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- Proper title format following pyplots.ai convention
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- Realistic plant growth study scenario with meaningful data
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- Good marker sizing with white borders for distinction
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- Both static PNG and interactive HTML outputs generated
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weaknesses:
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- Interactive HTML reuses the 4800x2700 chart JS literal instead of regenerating
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at smaller size, causing potential sizing issues
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- No alpha transparency on markers despite spec suggestion for overlapping points
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- Legend positioned at fixed pixel offset rather than responsive positioning

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