Density Histogram — plotnine

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 plotnine

Python source (plotnine)

""" anyplot.ai
histogram-density: Density Histogram
Library: plotnine 0.15.4 | Python 3.13.13
Quality: 89/100 | Updated: 2026-05-11
"""

import os
import sys

import numpy as np
import pandas as pd
for path in list(sys.path):
    if path.endswith("histogram-density/implementations/python"):
        sys.path.remove(path)

from plotnine import (
    aes,
    after_stat,
    element_line,
    element_rect,
    element_text,
    geom_density,
    geom_histogram,
    ggplot,
    labs,
    theme,
    theme_minimal,
)


# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"

BRAND = "#009E73"  # Okabe-Ito position 1
ACCENT = "#C475FD"  # Okabe-Ito position 2

# Data - bimodal distribution for compelling visualization
np.random.seed(42)
n_samples = 500

group1 = np.random.normal(loc=65, scale=8, size=n_samples // 2)
group2 = np.random.normal(loc=85, scale=6, size=n_samples // 2)
values = np.concatenate([group1, group2])

df = pd.DataFrame({"values": values})

# Theme configuration
anyplot_theme = theme(
    plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
    panel_background=element_rect(fill=PAGE_BG),
    panel_grid_major_y=element_line(color=INK, size=0.3, alpha=0.10),
    panel_grid_minor=element_line(color=INK, size=0.2, alpha=0.05),
    panel_border=element_rect(color=INK_SOFT, fill=None),
    axis_title=element_text(color=INK, size=20),
    axis_text=element_text(color=INK_SOFT, size=16),
    axis_line=element_line(color=INK_SOFT),
    plot_title=element_text(color=INK, size=24),
    legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
    legend_text=element_text(color=INK_SOFT, size=16),
    legend_title=element_text(color=INK, size=16),
    figure_size=(16, 9),
)

# Plot
plot = (
    ggplot(df, aes(x="values"))
    + geom_histogram(aes(y=after_stat("density")), bins=30, fill=BRAND, color="white", alpha=0.7)
    + geom_density(color=ACCENT, size=2, alpha=0.8)
    + labs(x="Test Score (points)", y="Density", title="histogram-density · plotnine · anyplot.ai")
    + theme_minimal()
    + anyplot_theme
)

# Save
plot.save(f"plot-{THEME}.png", dpi=300, verbose=False)

Part of Density Histogram on anyplot.ai.

Other implementations