Diverging Bar Chart
Chart overview
A diverging bar chart anchors bars at a meaningful zero or neutral midpoint and extends them in opposite directions for positive and negative values, making asymmetry and net direction immediately visible.
Key points
- Scientists and survey researchers use it for Likert scale responses, log fold-change comparisons, and any dataset where deviation from a reference value is the primary message.
- It outperforms a standard bar chart when communicating balance or imbalance around a central reference.
Example Visualization
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"Create a diverging bar chart from my data. Arrange categories horizontally, extend bars left for negative and right for positive values from a centre zero line, colour-code direction, sort by value, and apply a clean journal-quality style."
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Python Code Example
import numpy as np
import matplotlib.pyplot as plt
categories = ['Question A', 'Question B', 'Question C', 'Question D']
negative_vals = [-30, -15, -45, -20]
positive_vals = [25, 40, 10, 50]
plt.figure(figsize=(10, 6))
y_pos = np.arange(len(categories))
plt.barh(y_pos, negative_vals, color='#ef4444', label='Disagree')
plt.barh(y_pos, positive_vals, color='#22c55e', label='Agree')
plt.axvline(0, color='black', linewidth=1.5)
plt.yticks(y_pos, categories, fontweight='bold')
plt.title('Diverging Bar Chart (Survey Results)', fontsize=14, fontweight='bold', pad=20)
plt.xlabel('Percentage / Score Deviation', fontsize=12)
plt.legend()
plt.tight_layout()
plt.savefig('plotivy-diverging-bar-chart.png', dpi=150)
print("Diverging bar chart generated successfully.")
Opens the Analyze page with this code pre-loaded and ready to execute
Console Output
Diverging bar chart generated successfully.
Common Use Cases
- 1Displaying Likert-scale survey agreement or satisfaction data by item
- 2Showing log2 fold-change values in differential gene expression analysis
- 3Comparing standardised effect sizes relative to a null or control reference
- 4Visualising budget surplus and deficit by department or fiscal year
Pro Tips
Sort categories by magnitude so the most extreme values appear at top and bottom
Place value labels at bar tips to eliminate the need to read the axis precisely
Use a single-hue diverging palette (e.g. orange-grey-teal) for accessibility
Add a bold vertical line at zero to reinforce the neutral reference point
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.