A diverging bar chart displays bars extending in opposite directions from a central baseline, typically at zero. This visualization is ideal for comparing positive and negative values, showing responses above and below a neutral point, or contrasting opposing categories. Different colors distinguish positive from negative values, making it easy to identify magnitude and direction at a glance.

""" anyplot.ai
bar-diverging: Diverging Bar Chart
Library: altair 6.1.0 | Python 3.13.13
Quality: 93/100 | Updated: 2026-05-08
"""
import os
import sys
# Prevent import collision with this script's filename
sys.path = [p for p in sys.path if not p.endswith("/python")]
import altair as alt
import pandas as pd
# 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"
# Okabe-Ito palette
POSITIVE_COLOR = "#009E73" # Okabe-Ito position 1 (brand green)
NEGATIVE_COLOR = "#AE3030" # imprint red — negative
# Data - Customer satisfaction survey results by department
data = pd.DataFrame(
{
"department": [
"Customer Service",
"Engineering",
"Sales",
"Marketing",
"HR",
"Finance",
"Operations",
"IT Support",
"R&D",
"Quality Assurance",
"Legal",
"Logistics",
],
"satisfaction_score": [42, 35, 28, 15, 8, -5, -12, -18, -25, -32, -38, -45],
}
)
# Add color indicator for positive/negative
data["sentiment"] = data["satisfaction_score"].apply(lambda x: "Positive" if x >= 0 else "Negative")
# Sort by value for better pattern recognition
data = data.sort_values("satisfaction_score", ascending=True)
# Create diverging bar chart
chart = (
alt.Chart(data)
.mark_bar(cornerRadius=3, height=35)
.encode(
x=alt.X(
"satisfaction_score:Q",
title="Net Satisfaction Score",
axis=alt.Axis(titleFontSize=22, labelFontSize=18, tickCount=10),
scale=alt.Scale(domain=[-60, 60]),
),
y=alt.Y(
"department:N",
title=None,
sort=alt.EncodingSortField(field="satisfaction_score", order="ascending"),
axis=alt.Axis(labelFontSize=18),
),
color=alt.Color(
"sentiment:N",
scale=alt.Scale(domain=["Positive", "Negative"], range=[POSITIVE_COLOR, NEGATIVE_COLOR]),
legend=alt.Legend(title="Sentiment", titleFontSize=20, labelFontSize=18, orient="bottom-right", offset=10),
),
tooltip=[alt.Tooltip("department:N", title="Department"), alt.Tooltip("satisfaction_score:Q", title="Score")],
)
.properties(
width=1400, height=800, title=alt.Title("bar-diverging · altair · anyplot.ai", fontSize=28, anchor="middle")
)
)
# Add zero baseline rule with theme-adaptive color
zero_line = alt.Chart(pd.DataFrame({"x": [0]})).mark_rule(color=INK_SOFT, strokeWidth=2).encode(x="x:Q")
# Combine chart and zero line with theme-adaptive styling
final_chart = (
(chart + zero_line)
.properties(background=PAGE_BG)
.configure_view(fill=PAGE_BG, stroke=INK_SOFT, strokeWidth=0)
.configure_axis(
grid=True,
gridOpacity=0.10,
gridColor=INK,
domainColor=INK_SOFT,
tickColor=INK_SOFT,
labelColor=INK_SOFT,
titleColor=INK,
)
.configure_title(color=INK, anchor="middle")
.configure_legend(fillColor=ELEVATED_BG, strokeColor=INK_SOFT, labelColor=INK_SOFT, titleColor=INK)
)
# Save as PNG and HTML with theme-suffixed filenames
final_chart.save(f"plot-{THEME}.png", scale_factor=3.0)
final_chart.save(f"plot-{THEME}.html")
Part of Diverging Bar Chart on anyplot.ai.