Line Plot with Confidence Interval — Pygal

A line plot with a confidence interval displays a central trend line (typically mean or median) surrounded by a shaded band representing uncertainty or variability. The combination of a clear central line and semi-transparent confidence region effectively communicates both the estimated value and its associated uncertainty, making it essential for visualizing statistical estimates, model predictions, and forecast ranges.

Line Plot with Confidence Interval rendered with Pygal

Python source (Pygal)

""" anyplot.ai
line-confidence: Line Plot with Confidence Interval
Library: pygal 3.1.0 | Python 3.13.13
Quality: 82/100 | Updated: 2026-05-09
"""

import os

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

# Data - Model predictions with 95% confidence interval
np.random.seed(42)
x = np.linspace(0, 12, 50)

# Central prediction: exponential growth pattern
y_center = 1000 + 500 * (1 - np.exp(-0.3 * x)) + np.random.randn(50) * 20
y_center = np.convolve(y_center, np.ones(5) / 5, mode="same")
y_center[0:2] = y_center[2]
y_center[-2:] = y_center[-3]

# Confidence interval widens over time
uncertainty = 30 + 15 * x
y_lower = y_center - uncertainty
y_upper = y_center + uncertainty

# Custom style for 4800x2700 canvas
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,
    stroke_width=3,
)

# Create XY chart
chart = pygal.XY(
    style=custom_style,
    width=4800,
    height=2700,
    title="line-confidence · pygal · anyplot.ai",
    x_title="Time (weeks)",
    y_title="Predicted Users",
    show_dots=False,
    show_x_guides=True,
    show_y_guides=True,
    range=(float(y_lower.min() - 50), float(y_upper.max() + 50)),
)

# Create confidence band as closed polygon for fill
confidence_band = []
for xi, yi in zip(x, y_upper, strict=True):
    confidence_band.append((float(xi), float(yi)))
for xi, yi in zip(reversed(x), reversed(y_lower), strict=True):
    confidence_band.append((float(xi), float(yi)))

# Center line data
center_data = [(float(xi), float(yi)) for xi, yi in zip(x, y_center, strict=True)]

# Add series: confidence band with solid fill (uses first color from palette)
chart.add("95% Confidence Interval", confidence_band, show_dots=False, fill=True, stroke=False)

# Add center line (uses second color from palette)
chart.add("Predicted Mean", center_data, fill=False, stroke=True, show_dots=False, stroke_width=6)

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

Part of Line Plot with Confidence Interval on anyplot.ai.

Line Plot with Confidence Interval — Pygal

Python source (Pygal)

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