Bar Chart with Error Bars — lets-plot

A bar chart with error bars displays categorical data as rectangular bars with vertical (or horizontal) lines extending from each bar to indicate uncertainty or variability. Error bars typically represent standard deviation, standard error, confidence intervals, or min/max ranges. This visualization is essential for comparing group means while communicating the reliability and precision of each measurement.

Bar Chart with Error Bars rendered with lets-plot

Python source (lets-plot)

""" anyplot.ai
bar-error: Bar Chart with Error Bars
Library: letsplot 4.9.0 | Python 3.13.13
Quality: 85/100 | Updated: 2026-05-10
"""

import os

import pandas as pd
from lets_plot import (
    LetsPlot,
    aes,
    element_line,
    element_rect,
    element_text,
    geom_bar,
    geom_errorbar,
    ggplot,
    ggsave,
    ggsize,
    labs,
    scale_fill_manual,
    theme,
)


LetsPlot.setup_html()

# 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"
GRID_COLOR = "rgba(26,26,23,0.08)" if THEME == "light" else "rgba(240,239,232,0.08)"

# Okabe-Ito palette - first series is brand green
IMPRINT = ["#009E73", "#C475FD", "#4467A3", "#BD8233", "#AE3030"]

# Data: A/B test results showing conversion rates with 95% CI
categories = ["Control", "Variant A", "Variant B", "Variant C", "Variant D"]
values = [12.3, 14.8, 11.2, 16.5, 13.9]
errors_lower = [1.2, 1.5, 1.0, 1.8, 1.4]
errors_upper = [1.4, 1.6, 1.1, 2.0, 1.5]

df = pd.DataFrame(
    {
        "category": categories,
        "value": values,
        "ymin": [v - el for v, el in zip(values, errors_lower, strict=True)],
        "ymax": [v + eu for v, eu in zip(values, errors_upper, strict=True)],
    }
)

# Create bar chart with error bars and enhanced design
plot = (
    ggplot(df, aes(x="category", y="value", fill="category"))
    + geom_bar(stat="identity", width=0.68, show_legend=False, alpha=0.92)
    + geom_errorbar(aes(ymin="ymin", ymax="ymax"), width=0.23, size=1.3, color=INK_SOFT, alpha=0.85)
    + scale_fill_manual(values=IMPRINT)
    + labs(
        title="bar-error · letsplot · anyplot.ai",
        x="Test Group",
        y="Conversion Rate (%)",
        caption="Error bars show 95% CI | Interactive HTML export available",
    )
    + 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=GRID_COLOR, size=0.22),
        panel_grid_major_x=element_line(color="transparent"),
        panel_grid_minor=element_line(color="transparent"),
        axis_title=element_text(size=20, color=INK),
        axis_text=element_text(size=16, color=INK_SOFT),
        plot_title=element_text(size=24, color=INK),
        plot_caption=element_text(size=14, color=INK_SOFT),
    )
    + ggsize(1600, 900)
)

# Save as PNG and HTML with theme suffix
ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)
ggsave(plot, f"plot-{THEME}.html", path=".")

Part of Bar Chart with Error Bars on anyplot.ai.

Bar Chart with Error Bars — lets-plot

Python source (lets-plot)

Other implementations