How to get multiple overlapping plots with independent scaling in Matplotlib?

When creating visualizations with multiple data series that have different scales, you need overlapping plots with independent Y-axis scaling. Matplotlib's twinx() method allows you to create twin axes that share the same X-axis but have separate Y-axis scales.

Basic Approach

The key steps are ?

• Create the primary subplot with plt.subplots()

• Plot the first dataset on the primary Y-axis

• Create a twin axis using twinx() that shares the X-axis

• Plot the second dataset on the twin Y-axis

• Customize colors and labels for clarity

Example

import matplotlib.pyplot as plt

# Set figure size
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

# Create the primary subplot
fig, ax1 = plt.subplots()

# Plot first dataset on primary Y-axis (left)
x_data = [1, 2, 3, 4, 5]
y1_data = [10, 20, 15, 25, 30]
ax1.plot(x_data, y1_data, color='red', label='Dataset 1')
ax1.set_ylabel('Primary Y-axis', color='red')
ax1.tick_params(axis='y', labelcolor='red')

# Create twin axis sharing the same X-axis
ax2 = ax1.twinx()

# Plot second dataset on secondary Y-axis (right)
y2_data = [100, 150, 300, 400, 200]
ax2.plot(x_data, y2_data, color='blue', label='Dataset 2')
ax2.set_ylabel('Secondary Y-axis', color='blue')
ax2.tick_params(axis='y', labelcolor='blue')

# Add title and show
plt.title('Multiple Overlapping Plots with Independent Scaling')
plt.show()

Output

Advanced Example with Different Data Types

Here's a more practical example showing temperature and rainfall data ?

import matplotlib.pyplot as plt

# Sample data
months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
temperature = [5, 7, 12, 18, 22, 25]  # Celsius
rainfall = [80, 60, 45, 30, 40, 20]   # mm

fig, ax1 = plt.subplots(figsize=(10, 6))

# Temperature plot (left Y-axis)
color = 'tab:red'
ax1.set_xlabel('Months')
ax1.set_ylabel('Temperature (°C)', color=color)
ax1.plot(months, temperature, color=color, marker='o', linewidth=2)
ax1.tick_params(axis='y', labelcolor=color)

# Rainfall plot (right Y-axis)
ax2 = ax1.twinx()
color = 'tab:blue'
ax2.set_ylabel('Rainfall (mm)', color=color)
ax2.bar(months, rainfall, color=color, alpha=0.6, width=0.4)
ax2.tick_params(axis='y', labelcolor=color)

plt.title('Temperature vs Rainfall - Independent Scaling')
plt.tight_layout()
plt.show()

Key Points

• twinx() creates a twin axis sharing the X-axis but with independent Y-axis scaling

• Each axis can have different data ranges without affecting the other

• Use different colors for each axis to avoid confusion

• Set tick_params(axis='y', labelcolor=color) to match axis colors

• Both line plots and bar charts can be overlapped effectively

Conclusion

Use twinx() to create overlapping plots with independent Y-axis scaling. This technique is perfect for comparing datasets with different units or scales on the same timeline or category axis.