Line Plot with Confidence Interval — plotnine

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 plotnine

Python source (plotnine)

""" anyplot.ai
line-confidence: Line Plot with Confidence Interval
Library: plotnine 0.15.4 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-09
"""

import os
import pathlib
import sys

import numpy as np
import pandas as pd


sys.path = [p for p in sys.path if pathlib.Path(p).resolve() != pathlib.Path.cwd().resolve()]

from plotnine import (
    aes,
    element_line,
    element_rect,
    element_text,
    geom_line,
    geom_ribbon,
    ggplot,
    labs,
    scale_color_manual,
    scale_fill_manual,
    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

# Data: Simulated quarterly revenue forecast with 95% confidence interval
np.random.seed(42)
quarters = np.arange(1, 21)
trend = 45 + 1.8 * quarters + 8 * np.sin(quarters * np.pi / 5)
noise = np.random.randn(20) * 2.5
y = trend + noise

base_ci = 3.5
ci_growth = 0.25 * quarters
y_lower = y - (base_ci + ci_growth)
y_upper = y + (base_ci + ci_growth)

df = pd.DataFrame({"Quarter": quarters, "Revenue": y, "Lower": y_lower, "Upper": y_upper, "Group": "forecast"})

# Plot
plot = (
    ggplot(df, aes(x="Quarter"))
    + geom_ribbon(aes(ymin="Lower", ymax="Upper", fill="Group"), alpha=0.25)
    + geom_line(aes(y="Revenue", color="Group"), size=1.4)
    + scale_fill_manual(values={"forecast": BRAND}, labels={"forecast": "95% Confidence Interval"})
    + scale_color_manual(values={"forecast": BRAND}, labels={"forecast": "Revenue Forecast"})
    + labs(
        x="Quarter (year-over-year)",
        y="Revenue ($ millions)",
        title="line-confidence · plotnine · anyplot.ai",
        fill="",
        color="",
    )
    + theme_minimal()
    + theme(
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG),
        panel_grid_major=element_line(color=INK_SOFT, size=0.3, alpha=0.10),
        panel_grid_minor=element_line(color=INK_SOFT, 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_position="right",
        figure_size=(16, 9),
    )
)

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

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

Line Plot with Confidence Interval — plotnine

Python source (plotnine)

Other implementations