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feat(highcharts): implement scatter-color-groups (#376)
## Summary Implements `scatter-color-groups` for **highcharts** library. **Parent Issue:** #208 **Sub-Issue:** #277 **Base Branch:** `plot/scatter-color-groups` **Attempt:** 1/3 ## Implementation - `plots/highcharts/scatter/scatter-color-groups/default.py` ## Features - Scatter plot showing iris dataset sepal dimensions grouped by species - Three distinct color groups (Setosa, Versicolor, Virginica) using the style guide palette - Proper axis labels and title - Legend positioned on the right side - Target output size: 4800 x 2700 px Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
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"""
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scatter-color-groups: Scatter Plot with Color Groups
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Library: highcharts
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Note: Highcharts requires a license for commercial use.
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"""
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import json
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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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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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# Color palette from style guide
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COLORS = ["#306998", "#FFD43B", "#DC2626", "#059669", "#8B5CF6", "#F97316"]
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# Data - Iris dataset (sepal_length, sepal_width) by species
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# fmt: off
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iris_data = {
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"setosa": [
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(5.1, 3.5), (4.9, 3.0), (4.7, 3.2), (4.6, 3.1), (5.0, 3.6), (5.4, 3.9), (4.6, 3.4), (5.0, 3.4),
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(4.4, 2.9), (4.9, 3.1), (5.4, 3.7), (4.8, 3.4), (4.8, 3.0), (4.3, 3.0), (5.8, 4.0), (5.7, 4.4),
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(5.4, 3.9), (5.1, 3.5), (5.7, 3.8), (5.1, 3.8), (5.4, 3.4), (5.1, 3.7), (4.6, 3.6), (5.1, 3.3),
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(4.8, 3.4), (5.0, 3.0), (5.0, 3.4), (5.2, 3.5), (5.2, 3.4), (4.7, 3.2), (4.8, 3.1), (5.4, 3.4),
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(5.2, 4.1), (5.5, 4.2), (4.9, 3.1), (5.0, 3.2), (5.5, 3.5), (4.9, 3.6), (4.4, 3.0), (5.1, 3.4),
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(5.0, 3.5), (4.5, 2.3), (4.4, 3.2), (5.0, 3.5), (5.1, 3.8), (4.8, 3.0), (5.1, 3.8), (4.6, 3.2),
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(5.3, 3.7), (5.0, 3.3),
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],
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"versicolor": [
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(7.0, 3.2), (6.4, 3.2), (6.9, 3.1), (5.5, 2.3), (6.5, 2.8), (5.7, 2.8), (6.3, 3.3), (4.9, 2.4),
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(6.6, 2.9), (5.2, 2.7), (5.0, 2.0), (5.9, 3.0), (6.0, 2.2), (6.1, 2.9), (5.6, 2.9), (6.7, 3.1),
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(5.6, 3.0), (5.8, 2.7), (6.2, 2.2), (5.6, 2.5), (5.9, 3.2), (6.1, 2.8), (6.3, 2.5), (6.1, 2.8),
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(6.4, 2.9), (6.6, 3.0), (6.8, 2.8), (6.7, 3.0), (6.0, 2.9), (5.7, 2.6), (5.5, 2.4), (5.5, 2.4),
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(5.8, 2.7), (6.0, 2.7), (5.4, 3.0), (6.0, 3.4), (6.7, 3.1), (6.3, 2.3), (5.6, 3.0), (5.5, 2.5),
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(5.5, 2.6), (6.1, 3.0), (5.8, 2.6), (5.0, 2.3), (5.6, 2.7), (5.7, 3.0), (5.7, 2.9), (6.2, 2.9),
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(5.1, 2.5), (5.7, 2.8),
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],
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"virginica": [
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(6.3, 3.3), (5.8, 2.7), (7.1, 3.0), (6.3, 2.9), (6.5, 3.0), (7.6, 3.0), (4.9, 2.5), (7.3, 2.9),
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(6.7, 2.5), (7.2, 3.6), (6.5, 3.2), (6.4, 2.7), (6.8, 3.0), (5.7, 2.5), (5.8, 2.8), (6.4, 3.2),
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(6.5, 3.0), (7.7, 3.8), (7.7, 2.6), (6.0, 2.2), (6.9, 3.2), (5.6, 2.8), (7.7, 2.8), (6.3, 2.7),
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(6.7, 3.3), (7.2, 3.2), (6.2, 2.8), (6.1, 3.0), (6.4, 2.8), (7.2, 3.0), (7.4, 2.8), (7.9, 3.8),
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(6.4, 2.8), (6.3, 2.8), (6.1, 2.6), (7.7, 3.0), (6.3, 3.4), (6.4, 3.1), (6.0, 3.0), (6.9, 3.1),
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(6.7, 3.1), (6.9, 3.1), (5.8, 2.7), (6.8, 3.2), (6.7, 3.3), (6.7, 3.0), (6.3, 2.5), (6.5, 3.0),
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(6.2, 3.4), (5.9, 3.0),
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],
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}
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# fmt: on
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groups = list(iris_data.keys())
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# Create chart with container ID for rendering
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chart = Chart(container="container")
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chart.options = HighchartsOptions()
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# Chart configuration - 4800 x 2700 px per style guide
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chart.options.chart = {"type": "scatter", "width": 4800, "height": 2700, "backgroundColor": "#ffffff"}
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# Title
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chart.options.title = {
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"text": "Iris Dataset: Sepal Dimensions by Species",
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"style": {"fontSize": "48px", "fontWeight": "bold"},
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}
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# X-axis configuration
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chart.options.x_axis = {
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"title": {"text": "Sepal Length (cm)", "style": {"fontSize": "36px"}},
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"labels": {"style": {"fontSize": "28px"}},
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"gridLineWidth": 1,
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"gridLineDashStyle": "Dot",
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"gridLineColor": "rgba(0, 0, 0, 0.15)",
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}
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# Y-axis configuration
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chart.options.y_axis = {
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"title": {"text": "Sepal Width (cm)", "style": {"fontSize": "36px"}},
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"labels": {"style": {"fontSize": "28px"}},
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"gridLineWidth": 1,
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"gridLineDashStyle": "Dot",
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"gridLineColor": "rgba(0, 0, 0, 0.15)",
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}
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# Plot options for scatter
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chart.options.plot_options = {
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"scatter": {
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"marker": {"radius": 12, "states": {"hover": {"enabled": True, "lineColor": "rgb(100,100,100)"}}},
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"states": {"hover": {"marker": {"enabled": False}}},
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}
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}
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# Add a series for each group with distinct colors
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for i, group in enumerate(groups):
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series = ScatterSeries()
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series.name = group.capitalize()
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series.data = iris_data[group]
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series.color = COLORS[i % len(COLORS)]
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chart.add_series(series)
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# Legend configuration
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chart.options.legend = {
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"enabled": True,
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"align": "right",
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"verticalAlign": "middle",
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"layout": "vertical",
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"itemStyle": {"fontSize": "28px"},
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}
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# Tooltip configuration
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chart.options.tooltip = {
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"headerFormat": "<b>{series.name}</b><br>",
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"pointFormat": "Sepal Length: {point.x} cm<br>Sepal Width: {point.y} cm",
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"style": {"fontSize": "24px"},
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}
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# Disable credits
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chart.options.credits = {"enabled": False}
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# Export to PNG via Selenium screenshot
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# Download Highcharts JS (required for headless Chrome which can't load CDN)
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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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# Get chart options as JSON
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opts_json = json.dumps(chart.options.to_dict())
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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; padding:0; overflow:hidden;">
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<div id="container" style="width: 4800px; height: 2700px;"></div>
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<script>
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Highcharts.chart('container', {opts_json});
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</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=4800,2800")
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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) # Wait for chart to render
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driver.save_screenshot("plot.png")
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driver.quit()
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Path(temp_path).unlink() # Clean up temp file
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print("Plot saved to plot.png")

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