How to make colorbar orientation horizontal in Python using Matplotlib?

In Matplotlib, colorbars are displayed vertically by default. To create a horizontal colorbar, use the orientation="horizontal" parameter in the colorbar() method.

Basic Syntax

plt.colorbar(mappable, orientation="horizontal")

Example

Let's create a scatter plot with a horizontal colorbar ?

import numpy as np
import matplotlib.pyplot as plt

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

# Generate random data points
x, y, z = np.random.rand(3, 50)

# Create figure and subplot
f, ax = plt.subplots()

# Create scatter plot with color mapping
points = ax.scatter(x, y, c=z, s=50, cmap="plasma")

# Add horizontal colorbar
f.colorbar(points, orientation="horizontal")

plt.show()

Positioning the Horizontal Colorbar

You can control the position and size of the horizontal colorbar using additional parameters ?

import numpy as np
import matplotlib.pyplot as plt

# Generate data
x = np.linspace(0, 10, 100)
y = np.linspace(0, 10, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(X) * np.cos(Y)

# Create figure and plot
fig, ax = plt.subplots(figsize=(8, 6))
im = ax.contourf(X, Y, Z, levels=20, cmap='viridis')

# Add horizontal colorbar with custom positioning
cbar = fig.colorbar(im, orientation='horizontal', shrink=0.8, pad=0.1)
cbar.set_label('Values', rotation=0, labelpad=15)

plt.show()

Parameters for Horizontal Colorbar

Common Use Cases

Horizontal colorbars work well for:

• Wide plots − When you have more horizontal than vertical space
• Multiple subplots − Shared colorbar at the bottom
• Dashboard layouts − Better integration with horizontal layouts

Conclusion

Use orientation="horizontal" in colorbar() to create horizontal colorbars. Combine with shrink and pad parameters to control positioning and size for better plot layouts.