Frequency Polygon for Distribution Comparison — Pygal

A frequency polygon connects the midpoints of histogram bins with straight line segments, creating a smooth outline of the distribution shape. This visualization excels at comparing multiple distributions simultaneously since lines overlap without obscuring each other, unlike stacked or overlapping histogram bars. Frequency polygons reveal differences in central tendency, spread, skewness, and modality across groups with minimal visual clutter.

Frequency Polygon for Distribution Comparison rendered with Pygal

Python source (Pygal)

""" anyplot.ai
frequency-polygon-basic: Frequency Polygon for Distribution Comparison
Library: pygal 3.1.0 | Python 3.13.13
Quality: 91/100 | Updated: 2026-05-17
"""

import os
import sys

import numpy as np


# Remove current directory from path to avoid shadowing pygal module
current_dir = os.path.dirname(os.path.abspath(__file__))
sys.path = [p for p in sys.path if os.path.abspath(p) != current_dir]

import pygal
from pygal.style import Style


# Theme tokens
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"

# Okabe-Ito palette (first series is always #009E73)
IMPRINT = ("#009E73", "#C475FD", "#4467A3")

# Data - Three groups of measurements (plant heights by soil type)
np.random.seed(42)

# Generate three distributions with different characteristics
group_a = np.random.normal(loc=45, scale=8, size=200)  # Sandy soil - lower mean
group_b = np.random.normal(loc=55, scale=10, size=200)  # Loamy soil - medium mean, wider spread
group_c = np.random.normal(loc=60, scale=6, size=200)  # Clay soil - higher mean, narrow spread

# Define bins for frequency calculation
bins = np.linspace(20, 85, 15)
bin_midpoints = (bins[:-1] + bins[1:]) / 2

# Calculate frequencies for each group
freq_a, _ = np.histogram(group_a, bins=bins)
freq_b, _ = np.histogram(group_b, bins=bins)
freq_c, _ = np.histogram(group_c, bins=bins)

# Extend lines to zero at both ends to close the polygon shape
midpoints_extended = [float(bins[0])] + [float(m) for m in bin_midpoints] + [float(bins[-1])]
freq_a_extended = [0] + [int(f) for f in freq_a] + [0]
freq_b_extended = [0] + [int(f) for f in freq_b] + [0]
freq_c_extended = [0] + [int(f) for f in freq_c] + [0]

# Custom style for large canvas (4800x2700) with theme-adaptive colors
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,
    opacity=0.8,
    opacity_hover=1.0,
)

# Create XY chart for frequency polygon with fill
chart = pygal.XY(
    width=4800,
    height=2700,
    style=custom_style,
    title="frequency-polygon-basic · pygal · anyplot.ai",
    x_title="Plant Height (cm)",
    y_title="Frequency",
    show_x_guides=True,
    show_y_guides=True,
    dots_size=10,
    stroke_style={"width": 4},
    legend_at_bottom=True,
    show_dots=True,
    fill=True,
    x_label_rotation=0,
    range=(0, int(max(max(freq_a), max(freq_b), max(freq_c))) + 5),
    xrange=(15, 90),
)

# Add data series - each point is (x, y) tuple
chart.add("Sandy Soil", list(zip(midpoints_extended, freq_a_extended, strict=True)))
chart.add("Loamy Soil", list(zip(midpoints_extended, freq_b_extended, strict=True)))
chart.add("Clay Soil", list(zip(midpoints_extended, freq_c_extended, strict=True)))

# Save as PNG and HTML with theme-suffixed filenames
chart.render_to_png(f"plot-{THEME}.png")
chart.render_to_file(f"plot-{THEME}.html")

Part of Frequency Polygon for Distribution Comparison on anyplot.ai.

Frequency Polygon for Distribution Comparison — Pygal

Python source (Pygal)

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