Density Histogram — Pygal

A density histogram displays the distribution of a continuous variable normalized so that the total area under the histogram equals 1, representing probability density instead of raw counts. This normalization allows direct comparison between distributions with different sample sizes and enables overlaying theoretical probability density functions (PDFs) for statistical analysis.

Density Histogram rendered with Pygal

Python source (Pygal)

""" anyplot.ai
histogram-density: Density Histogram
Library: pygal 3.1.0 | Python 3.13.13
Quality: 82/100 | Updated: 2026-05-11
"""

import os

import numpy as np
import pygal
from pygal.style import Style


# Theme configuration
THEME = os.getenv("ANYPLOT_THEME", "light")

# Color palette - Okabe-Ito + theme-adaptive chrome
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"

IMPRINT = ("#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030", "#2ABCCD", "#954477")

# Generate sample data - test scores with realistic distribution
np.random.seed(42)
scores_group1 = np.random.normal(loc=65, scale=10, size=150)
scores_group2 = np.random.normal(loc=82, scale=8, size=100)
scores = np.concatenate([scores_group1, scores_group2])
scores = np.clip(scores, 0, 100)

# Calculate density histogram
n_bins = 25
counts, bin_edges = np.histogram(scores, bins=n_bins, density=True)
bin_centers = (bin_edges[:-1] + bin_edges[1:]) / 2

# Create custom style matching default-style-guide.md
custom_style = Style(
    background=PAGE_BG,
    plot_background=PAGE_BG,
    foreground=INK,
    foreground_strong=INK,
    foreground_subtle=INK_MUTED,
    colors=IMPRINT,
    title_font_size=28,
    label_font_size=22,
    major_label_font_size=18,
    legend_font_size=16,
    value_font_size=14,
    stroke_width=3,
)

# Create histogram chart
chart = pygal.Bar(
    width=4800,
    height=2700,
    style=custom_style,
    title="histogram-density · pygal · anyplot.ai",
    x_title="Test Score",
    y_title="Density (Probability per Unit)",
    show_legend=False,
    show_x_guides=False,
    show_y_guides=True,
    x_label_rotation=0,
    margin=120,
    spacing=1,
    print_values=False,
)

# Format x-axis labels (show every 5th bin for clarity)
chart.x_labels = [f"{int(bc)}" if i % 5 == 0 else "" for i, bc in enumerate(bin_centers)]

# Add density histogram data
chart.add("", [float(c) for c in counts])

# Save outputs with theme-suffixed filenames
chart.render_to_png(f"plot-{THEME}.png")
with open(f"plot-{THEME}.html", "wb") as f:
    f.write(chart.render())

Part of Density Histogram on anyplot.ai.

Other implementations