feat: add histogram-basic implementation (9 libraries)

plots/altair/bar/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: altair
+"""
+
+import altair as alt
+import numpy as np
+import pandas as pd
+
+
+# Data
+np.random.seed(42)
+data = pd.DataFrame({"value": np.random.normal(100, 15, 500)})
+
+# Create histogram chart
+chart = (
+    alt.Chart(data)
+    .mark_bar(color="#306998", opacity=0.8)
+    .encode(alt.X("value:Q", bin=alt.Bin(maxbins=30), title="Value"), alt.Y("count()", title="Frequency"))
+    .properties(width=1600, height=900, title="Basic Histogram")
+    .configure_axis(labelFontSize=16, titleFontSize=20)
+    .configure_title(fontSize=20)
+)
+
+# Save as PNG (1600 × 900 at scale 3 = 4800 × 2700)
+chart.save("plot.png", scale_factor=3.0)

plots/bokeh/quad/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: bokeh
+"""
+
+import numpy as np
+from bokeh.io import export_png
+from bokeh.plotting import figure
+
+
+# Data - 500 normally distributed values (mean=100, std=15)
+np.random.seed(42)
+values = np.random.normal(100, 15, 500)
+
+# Compute histogram bins
+hist, edges = np.histogram(values, bins=30)
+
+# Create figure (4800 x 2700 px for high resolution)
+p = figure(width=4800, height=2700, title="Basic Histogram", x_axis_label="Value", y_axis_label="Frequency")
+
+# Draw histogram using quad glyph
+p.quad(
+    top=hist,
+    bottom=0,
+    left=edges[:-1],
+    right=edges[1:],
+    fill_color="#306998",
+    fill_alpha=0.7,
+    line_color="white",
+    line_width=1,
+)
+
+# Style title
+p.title.text_font_size = "20pt"
+p.title.align = "center"
+
+# Style axis labels
+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"
+
+# Style grid - subtle
+p.xgrid.grid_line_alpha = 0.3
+p.ygrid.grid_line_alpha = 0.3
+
+# Ensure y-axis starts at zero
+p.y_range.start = 0
+
+# Save output
+export_png(p, filename="plot.png")

plots/highcharts/histogram/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: highcharts
+"""
+
+import tempfile
+import time
+import urllib.request
+from pathlib import Path
+
+import numpy as np
+from highcharts_core.chart import Chart
+from highcharts_core.options import HighchartsOptions
+from highcharts_core.options.series.bar import ColumnSeries
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+
+
+# Data
+np.random.seed(42)
+values = np.random.normal(100, 15, 500)  # 500 values, mean=100, std=15
+
+# Calculate histogram bins
+bins = 30
+counts, bin_edges = np.histogram(values, bins=bins)
+
+# Create bin labels (center of each bin)
+bin_centers = [(bin_edges[i] + bin_edges[i + 1]) / 2 for i in range(len(counts))]
+bin_labels = [f"{bin_edges[i]:.1f}-{bin_edges[i + 1]:.1f}" for i in range(len(counts))]
+
+# Create chart with container ID
+chart = Chart(container="container")
+chart.options = HighchartsOptions()
+
+# Chart configuration
+chart.options.chart = {
+    "type": "column",
+    "width": 4800,
+    "height": 2700,
+    "backgroundColor": "#ffffff",
+    "spacingBottom": 120,  # Add space for x-axis title
+}
+
+# Title
+chart.options.title = {"text": "Basic Histogram", "style": {"fontSize": "48px", "fontWeight": "bold"}}
+
+# X-axis configuration
+chart.options.x_axis = {
+    "categories": bin_labels,
+    "title": {"text": "Value", "style": {"fontSize": "40px"}},
+    "labels": {
+        "rotation": 315,  # 315 degrees = -45 degrees
+        "style": {"fontSize": "28px"},
+        "step": 3,  # Show every 3rd label to avoid overlap
+    },
+}
+
+# Y-axis configuration
+chart.options.y_axis = {
+    "title": {"text": "Frequency", "style": {"fontSize": "40px"}},
+    "min": 0,
+    "gridLineWidth": 1,
+    "gridLineDashStyle": "Dot",
+    "gridLineColor": "rgba(0, 0, 0, 0.15)",
+    "labels": {"style": {"fontSize": "32px"}},
+}
+
+# Create series with histogram data
+series = ColumnSeries()
+series.data = counts.tolist()
+series.name = "Frequency"
+series.color = "#306998"  # Python Blue
+series.border_color = "white"
+series.border_width = 1
+
+# Plot options for histogram appearance
+chart.options.plot_options = {"column": {"pointPadding": 0, "groupPadding": 0, "borderWidth": 1, "opacity": 0.8}}
+
+chart.add_series(series)
+
+# Legend (single series, hide)
+chart.options.legend = {"enabled": False}
+
+# Credits
+chart.options.credits = {"enabled": False}
+
+# Download Highcharts JS (required for headless Chrome)
+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")
+
+# 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=4800,2800")  # Slightly larger to capture full chart
+
+driver = webdriver.Chrome(options=chrome_options)
+driver.get(f"file://{temp_path}")
+time.sleep(5)  # Wait for chart to render
+driver.save_screenshot("plot.png")
+driver.quit()
+
+Path(temp_path).unlink()  # Clean up temp file

plots/letsplot/histogram/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: letsplot
+"""
+
+import numpy as np
+import pandas as pd
+from lets_plot import LetsPlot, aes, element_text, geom_histogram, ggplot, ggsave, ggsize, labs, theme, theme_minimal
+
+
+LetsPlot.setup_html()
+
+# Data
+np.random.seed(42)
+data = pd.DataFrame({"value": np.random.normal(100, 15, 500)})
+
+# Plot
+plot = (
+    ggplot(data, aes(x="value"))
+    + geom_histogram(bins=30, fill="#306998", color="white", alpha=0.8)
+    + labs(x="Value", y="Frequency", title="Basic Histogram")
+    + theme_minimal()
+    + theme(plot_title=element_text(size=20), axis_title=element_text(size=20), axis_text=element_text(size=16))
+    + ggsize(1600, 900)
+)
+
+# Save - scale 3x to get 4800 x 2700 px
+ggsave(plot, "plot.png", path=".", scale=3)

plots/matplotlib/hist/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: matplotlib
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+
+# Data
+np.random.seed(42)
+data = pd.DataFrame({"value": np.random.normal(100, 15, 500)})
+
+# Create plot
+fig, ax = plt.subplots(figsize=(16, 9))
+ax.hist(data["value"], bins=30, alpha=0.8, color="#306998", edgecolor="white", linewidth=0.5)
+
+# Labels and styling
+ax.set_xlabel("Value", fontsize=20)
+ax.set_ylabel("Frequency", fontsize=20)
+ax.set_title("Basic Histogram", fontsize=20)
+ax.tick_params(axis="both", labelsize=16)
+ax.grid(True, alpha=0.3, axis="y")
+
+plt.tight_layout()
+plt.savefig("plot.png", dpi=300, bbox_inches="tight")

plots/plotly/histogram/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: plotly
+"""
+
+import numpy as np
+import plotly.graph_objects as go
+
+
+# Data
+np.random.seed(42)
+values = np.random.normal(100, 15, 500)  # 500 values, mean=100, std=15
+
+# Create figure
+fig = go.Figure()
+fig.add_trace(go.Histogram(x=values, marker={"color": "#306998", "line": {"color": "white", "width": 1}}, opacity=0.85))
+
+# Layout
+fig.update_layout(
+    title={"text": "Basic Histogram", "font": {"size": 40}, "x": 0.5, "xanchor": "center"},
+    xaxis_title="Value",
+    yaxis_title="Frequency",
+    template="plotly_white",
+    font={"size": 32},
+    xaxis={"title_font": {"size": 40}, "tickfont": {"size": 32}, "showgrid": True, "gridcolor": "rgba(0,0,0,0.1)"},
+    yaxis={"title_font": {"size": 40}, "tickfont": {"size": 32}, "showgrid": True, "gridcolor": "rgba(0,0,0,0.1)"},
+    bargap=0.05,
+)
+
+# Save
+fig.write_image("plot.png", width=1600, height=900, scale=3)

plots/plotnine/histogram/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: plotnine
+"""
+
+import numpy as np
+import pandas as pd
+from plotnine import aes, element_text, geom_histogram, ggplot, labs, theme, theme_minimal
+
+
+# Data
+np.random.seed(42)
+data = pd.DataFrame({"value": np.random.normal(100, 15, 500)})
+
+# Plot
+plot = (
+    ggplot(data, aes(x="value"))
+    + geom_histogram(bins=30, fill="#306998", color="white", alpha=0.8)
+    + labs(x="Value", y="Frequency", title="Basic Histogram")
+    + theme_minimal()
+    + theme(
+        figure_size=(16, 9),
+        plot_title=element_text(size=20),
+        axis_title=element_text(size=20),
+        axis_text=element_text(size=16),
+    )
+)
+
+# Save
+plot.save("plot.png", dpi=300)

plots/pygal/histogram/histogram-basic/default.py

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+"""
+histogram-basic: Basic Histogram
+Library: pygal
+"""
+
+import numpy as np
+import pygal
+from pygal.style import Style
+
+
+# Data
+np.random.seed(42)
+values = np.random.normal(100, 15, 500)  # 500 values, mean=100, std=15
+
+# Calculate histogram bins
+counts, bin_edges = np.histogram(values, bins=20)
+
+# Convert to pygal histogram format: (height, start, end)
+histogram_data = [(int(count), float(bin_edges[i]), float(bin_edges[i + 1])) for i, count in enumerate(counts)]
+
+# Custom style matching default style guide colors
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    opacity="0.8",
+    opacity_hover="0.9",
+    colors=("#306998",),  # Python Blue
+    guide_stroke_color="#cccccc",
+    major_guide_stroke_color="#cccccc",
+    title_font_size=48,
+    label_font_size=36,
+    major_label_font_size=36,
+)
+
+# Create histogram chart
+chart = pygal.Histogram(
+    width=4800,
+    height=2700,
+    title="Basic Histogram",
+    x_title="Value",
+    y_title="Frequency",
+    style=custom_style,
+    show_legend=False,
+    show_y_guides=True,
+    show_x_guides=False,
+)
+
+# Add histogram data
+chart.add("Distribution", histogram_data)
+
+# Save to PNG
+chart.render_to_png("plot.png")