MarkusNeusinger · MarkusNeusinger · Dec 7, 2025 · Dec 6, 2025 · Dec 7, 2025 · Dec 7, 2025
diff --git a/plots/altair/point/scatter-basic/default.py b/plots/altair/point/scatter-basic/default.py
@@ -0,0 +1,29 @@
+"""
+scatter-basic: Basic Scatter Plot
+Library: altair
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data
+np.random.seed(42)
+x = np.random.randn(100) * 2 + 10
+y = x * 0.8 + np.random.randn(100) * 2
+
+data = pd.DataFrame({"x": x, "y": y})
+
+# Create chart
+chart = (
+    alt.Chart(data)
+    .mark_point(filled=True, opacity=0.7, size=100, color="#306998")
+    .encode(x=alt.X("x:Q", title="X Value"), y=alt.Y("y:Q", title="Y Value"), tooltip=["x:Q", "y:Q"])
+    .properties(width=1600, height=900, title="Basic Scatter Plot")
+    .configure_axis(labelFontSize=16, titleFontSize=20)
+    .configure_title(fontSize=20)
+)
+
+# Save as PNG (1600 * 3 = 4800px, 900 * 3 = 2700px)
+chart.save("plot.png", scale_factor=3.0)
diff --git a/plots/bokeh/scatter/scatter-basic/default.py b/plots/bokeh/scatter/scatter-basic/default.py
@@ -0,0 +1,34 @@
+"""
+scatter-basic: Basic Scatter Plot
+Library: bokeh
+"""
+
+import numpy as np
+from bokeh.io import export_png
+from bokeh.models import ColumnDataSource
+from bokeh.plotting import figure
+
+
+# Data
+np.random.seed(42)
+x = np.random.randn(100) * 2 + 10
+y = x * 0.8 + np.random.randn(100) * 2
+
+source = ColumnDataSource(data={"x": x, "y": y})
+
+# Create figure (4800 × 2700 px for 16:9 aspect ratio)
+p = figure(width=4800, height=2700, title="Basic Scatter Plot", x_axis_label="X Value", y_axis_label="Y Value")
+
+# Plot scatter
+p.scatter(x="x", y="y", source=source, size=12, color="#306998", alpha=0.7)
+
+# Styling
+p.title.text_font_size = "20pt"
+p.xaxis.axis_label_text_font_size = "20pt"
+p.yaxis.axis_label_text_font_size = "20pt"
+p.xaxis.major_label_text_font_size = "16pt"
+p.yaxis.major_label_text_font_size = "16pt"
+p.grid.grid_line_alpha = 0.3
+
+# Save
+export_png(p, filename="plot.png")
diff --git a/plots/highcharts/scatter/scatter-basic/default.py b/plots/highcharts/scatter/scatter-basic/default.py
@@ -0,0 +1,96 @@
+"""
+scatter-basic: Basic Scatter Plot
+Library: highcharts
+"""
+
+import tempfile
+import time
+import urllib.request
+from pathlib import Path
+
+from highcharts_core.chart import Chart
+from highcharts_core.options import HighchartsOptions
+from highcharts_core.options.series.scatter import ScatterSeries
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+
+
+# Data
+x = [1, 2, 3, 4, 5, 6, 7, 8]
+y = [2.1, 4.3, 3.2, 5.8, 4.9, 7.2, 6.1, 8.5]
+
+# Create chart with container
+chart = Chart(container="container")
+chart.options = HighchartsOptions()
+
+# Chart configuration
+chart.options.chart = {"type": "scatter", "width": 4800, "height": 2700, "backgroundColor": "#ffffff"}
+
+# Title
+chart.options.title = {"text": "Basic Scatter Plot", "style": {"fontSize": "60px"}}
+
+# Axes
+chart.options.x_axis = {
+    "title": {"text": "X Value", "style": {"fontSize": "48px"}},
+    "labels": {"style": {"fontSize": "40px"}},
+    "gridLineWidth": 1,
+    "gridLineColor": "rgba(0, 0, 0, 0.1)",
+}
+chart.options.y_axis = {
+    "title": {"text": "Y Value", "style": {"fontSize": "48px"}},
+    "labels": {"style": {"fontSize": "40px"}},
+    "gridLineWidth": 1,
+    "gridLineColor": "rgba(0, 0, 0, 0.1)",
+}
+
+# Legend (not needed for single series, but kept minimal)
+chart.options.legend = {"enabled": False}
+
+# Add series
+series = ScatterSeries()
+series.data = list(zip(x, y, strict=False))
+series.name = "Data"
+series.marker = {"radius": 20, "fillColor": "#306998", "lineWidth": 2, "lineColor": "#306998"}
+chart.add_series(series)
+
+# Download Highcharts JS for inline embedding
+highcharts_url = "https://code.highcharts.com/highcharts.js"
+with urllib.request.urlopen(highcharts_url, timeout=30) as response:
+    highcharts_js = response.read().decode("utf-8")
+
-# Download Highcharts JS for inline embedding
-highcharts_url = "https://code.highcharts.com/highcharts.js"
-with urllib.request.urlopen(highcharts_url, timeout=30) as response:
-    highcharts_js = response.read().decode("utf-8")
+# Use bundled Highcharts JS for inline embedding to avoid runtime download and supply chain risk.
+# See: https://github.com/highcharts/highcharts for official source.
+highcharts_js_path = Path(__file__).parent.parent / "vendor" / "highcharts.js"
+with open(highcharts_js_path, "r", encoding="utf-8") as f:
+    highcharts_js = f.read()
-# Download Highcharts JS for inline embedding
-highcharts_url = "https://code.highcharts.com/highcharts.js"
-with urllib.request.urlopen(highcharts_url, timeout=30) as response:
-    highcharts_js = response.read().decode("utf-8")
+# Use bundled Highcharts JS for inline embedding to avoid runtime download and supply chain risk.
+# See: https://github.com/highcharts/highcharts for official source.
+highcharts_js_path = Path(__file__).parent.parent / "vendor" / "highcharts.js"
+with open(highcharts_js_path, "r", encoding="utf-8") as f:
+    highcharts_js = f.read()
+# Generate HTML with inline scripts
+html_str = chart.to_js_literal()
+html_content = f"""<!DOCTYPE html>
+<html>
+<head>
+    <meta charset="utf-8">
+    <script>{highcharts_js}</script>
+</head>
+<body style="margin:0;">
+    <div id="container" style="width: 4800px; height: 2700px;"></div>
+    <script>{html_str}</script>
+</body>
+</html>"""
+
+# Write temp HTML and take screenshot
+with tempfile.NamedTemporaryFile(mode="w", suffix=".html", delete=False, encoding="utf-8") as f:
+    f.write(html_content)
+    temp_path = f.name
+
+chrome_options = Options()
+chrome_options.add_argument("--headless")
+chrome_options.add_argument("--no-sandbox")
+chrome_options.add_argument("--disable-dev-shm-usage")
+chrome_options.add_argument("--disable-gpu")
+chrome_options.add_argument("--window-size=5000,3000")
+
+driver = webdriver.Chrome(options=chrome_options)
+driver.get(f"file://{temp_path}")
+time.sleep(5)
+
+# Screenshot the chart container element for exact dimensions
+container = driver.find_element("id", "container")
+container.screenshot("plot.png")
+driver.quit()
+
+Path(temp_path).unlink()
diff --git a/plots/letsplot/point/scatter-basic/default.py b/plots/letsplot/point/scatter-basic/default.py
@@ -0,0 +1,31 @@
+"""
+scatter-basic: Basic Scatter Plot
+Library: letsplot
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import LetsPlot, aes, element_text, geom_point, ggplot, ggsave, ggsize, labs, theme, theme_minimal
+
+
+LetsPlot.setup_html()
+
+# Data
+np.random.seed(42)
+x = np.random.randn(100) * 2 + 10
+y = x * 0.8 + np.random.randn(100) * 2
+
+data = pd.DataFrame({"x": x, "y": y})
+
+# Plot
+plot = (
+    ggplot(data, aes(x="x", y="y"))
+    + geom_point(color="#306998", size=4, alpha=0.7)
+    + labs(x="X Value", y="Y Value", title="Basic Scatter Plot")
+    + ggsize(1600, 900)
+    + theme_minimal()
+    + theme(plot_title=element_text(size=20), axis_title=element_text(size=20), axis_text=element_text(size=16))
+)
+
+# Save (scale 3x to get 4800 × 2700 px)
+ggsave(plot, "plot.png", path=".", scale=3)
diff --git a/plots/matplotlib/scatter/scatter-basic/default.py b/plots/matplotlib/scatter/scatter-basic/default.py
@@ -1,119 +1,27 @@
 """
 scatter-basic: Basic Scatter Plot
-Implementation for: matplotlib
-Variant: default
-Python: 3.10+
+Library: matplotlib
 """
 
-from typing import TYPE_CHECKING, Optional
-
 import matplotlib.pyplot as plt
 import numpy as np
-import pandas as pd
-
-
-if TYPE_CHECKING:
-    from matplotlib.figure import Figure
-
-
-def create_plot(
-    data: pd.DataFrame,
-    x: str,
-    y: str,
-    figsize: tuple[float, float] = (16, 9),
-    alpha: float = 0.6,
-    size: float = 30,
-    color: str = "steelblue",
-    title: Optional[str] = None,
-    xlabel: Optional[str] = None,
-    ylabel: Optional[str] = None,
-    edgecolors: Optional[str] = None,
-    linewidth: float = 0,
-    **kwargs,
-) -> "Figure":
-    """
-    Create a basic scatter plot visualizing the relationship between two continuous variables.
-
-    Args:
-        data: Input DataFrame with required columns
-        x: Column name for x-axis values
-        y: Column name for y-axis values
-        figsize: Figure size as (width, height) tuple (default: (16, 9))
-        alpha: Transparency level for points (default: 0.6 for better visibility with many points)
-        size: Point size (default: 30)
-        color: Point color (default: "steelblue")
-        title: Plot title (default: None)
-        xlabel: X-axis label (default: uses column name)
-        ylabel: Y-axis label (default: uses column name)
-        edgecolors: Edge color for points (default: None)
-        linewidth: Width of edge lines (default: 0)
-        **kwargs: Additional parameters passed to scatter function
-
-    Returns:
-        Matplotlib Figure object
-
-    Raises:
-        ValueError: If data is empty
-        KeyError: If required columns not found
-        TypeError: If x or y columns contain non-numeric data
-
-    Example:
-        >>> data = pd.DataFrame({'x': [1, 2, 3], 'y': [2, 4, 3]})
-        >>> fig = create_plot(data, 'x', 'y')
-    """
-    # Input validation
-    if data.empty:
-        raise ValueError("Data cannot be empty")
-
-    # Check required columns
-    for col in [x, y]:
-        if col not in data.columns:
-            available = ", ".join(data.columns)
-            raise KeyError(f"Column '{col}' not found. Available columns: {available}")
-
-    # Check if columns are numeric
-    if not pd.api.types.is_numeric_dtype(data[x]):
-        raise TypeError(f"Column '{x}' must contain numeric data")
-    if not pd.api.types.is_numeric_dtype(data[y]):
-        raise TypeError(f"Column '{y}' must contain numeric data")
-
-    # Create figure
-    fig, ax = plt.subplots(figsize=figsize)
-
-    # Plot data
-    ax.scatter(data[x], data[y], s=size, alpha=alpha, c=color, edgecolors=edgecolors, linewidth=linewidth, **kwargs)
-
-    # Labels and title
-    ax.set_xlabel(xlabel or x)
-    ax.set_ylabel(ylabel or y)
-
-    if title:
-        ax.set_title(title)
-
-    # Apply styling
-    ax.grid(True, alpha=0.3)
-
-    # Layout
-    plt.tight_layout()
-
-    return fig
 
 
-if __name__ == "__main__":
-    # Sample data for testing - many points to demonstrate basic scatter
-    np.random.seed(42)
-    n_points = 500
+# Data
+np.random.seed(42)
+x = np.random.randn(100) * 2 + 5
-x = np.random.randn(100) * 2 + 5
+x = np.random.randn(100) * 2 + 10
-x = np.random.randn(100) * 2 + 5
+x = np.random.randn(100) * 2 + 10
+y = x * 0.8 + np.random.randn(100) * 1.5
-y = x * 0.8 + np.random.randn(100) * 1.5
+y = x * 0.8 + np.random.randn(100) * 2
-y = x * 0.8 + np.random.randn(100) * 1.5
+y = x * 0.8 + np.random.randn(100) * 2
 
-    data = pd.DataFrame(
-        {
-            "x": np.random.randn(n_points) * 2 + 10,
-            "y": np.random.randn(n_points) * 3 + 15 + np.random.randn(n_points) * 0.5,
-        }
-    )
+# Create plot
+fig, ax = plt.subplots(figsize=(16, 9))
+ax.scatter(x, y, alpha=0.7, s=80, color="#306998")
 
-    # Create plot
-    fig = create_plot(data, "x", "y", title="Basic Scatter Plot Example", xlabel="X Value", ylabel="Y Value")
+# Labels and styling
+ax.set_xlabel("X Value", fontsize=20)
+ax.set_ylabel("Y Value", fontsize=20)
+ax.set_title("Basic Scatter Plot", fontsize=20)
+ax.tick_params(axis="both", labelsize=16)
+ax.grid(True, alpha=0.3)
 
-    # Save for inspection - ALWAYS use 'plot.png' as filename
-    plt.savefig("plot.png", dpi=300, bbox_inches="tight")
-    print("Plot saved to plot.png")
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")
diff --git a/plots/plotly/scatter/scatter-basic/default.py b/plots/plotly/scatter/scatter-basic/default.py
@@ -0,0 +1,41 @@
+"""
+scatter-basic: Basic Scatter Plot
+Library: plotly
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data
+np.random.seed(42)
+x = np.random.randn(100) * 2 + 10
+y = x * 0.8 + np.random.randn(100) * 2
+
+# Create figure
+fig = go.Figure()
+
+fig.add_trace(go.Scatter(x=x, y=y, mode="markers", marker={"size": 12, "color": "#306998", "opacity": 0.7}))
+
+# Layout
+fig.update_layout(
+    title={"text": "Basic Scatter Plot", "font": {"size": 40}, "x": 0.5, "xanchor": "center"},
+    xaxis={
+        "title": {"text": "X Value", "font": {"size": 40}},
+        "tickfont": {"size": 32},
+        "showgrid": True,
+        "gridcolor": "rgba(0, 0, 0, 0.1)",
+    },
+    yaxis={
+        "title": {"text": "Y Value", "font": {"size": 40}},
+        "tickfont": {"size": 32},
+        "showgrid": True,
+        "gridcolor": "rgba(0, 0, 0, 0.1)",
+    },
+    template="plotly_white",
+    plot_bgcolor="white",
+    margin={"l": 120, "r": 50, "t": 100, "b": 100},
+)
+
+# Save (4800 x 2700 px)
+fig.write_image("plot.png", width=1600, height=900, scale=3)