Colorbar is an axis that indicates the mapping of data values to the colors used in plot. The colorbar() function in pyplot module of matplotlib adds a colorbar to a plot indicating the color scale.
Sometimes it is desirable to rotate the ticklabels for better visualization and understanding. To change the rotation of colorbar ticklabels desired angle of rotation is provided in:
- cbar.ax.set_xticklabels, if colorbar orientation is horizontal
- cbar.ax.set_yticklabels, if colorbar orientation is vertical
Positive value of angle corresponds to counterclockwise rotation, while negative value corresponds to clockwise rotation. Also, we can use “vertical” and “horizontal” values for rotation instead of numeric value of angle. These are equivalent to 0° and +90° respectively.
Steps to rotate colorbar ticklabels :
- Plot a figure
- Plot corresponding colorbar
- Provide ticks and ticklabels
- Set rotation of ticklabels to desired angle
Example 1: Following program demonstrates horizontal color bar with 45 degrees rotation of colorbar ticklabels.
Python3
# Import libraries import matplotlib.pyplot as plt import numpy as np # Plot image a = np.random.random(( 10 , 10 )) plt.imshow(a, cmap = 'gray' ) # Plot horizontal colorbar cbar = plt.colorbar( orientation = "horizontal" , fraction = 0.050 ) # Set ticklabels labels = [ 0 , 0.1 , 0.2 , 0.3 , 0.4 , 0.5 , 0.6 , 0.7 , 0.8 , 0.9 , 1 ] cbar.set_ticks(labels) # Rotate colorbar ticklabels by 45 degrees # anticlockwise cbar.ax.set_xticklabels(labels, rotation = 45 ) plt.show() |
Output:
Example 2: Following program demonstrates horizontal color bar with -45 degrees rotation of colorbar ticklabels.
Python3
# Import libraries import matplotlib.pyplot as plt import numpy as np # Plot image a = np.random.random(( 10 , 10 )) plt.imshow(a, cmap = 'gray' ) # Plot horizontal colorbar cbar = plt.colorbar( orientation = "horizontal" , fraction = 0.050 ) # Set ticklabels labels = [ 0 , 0.1 , 0.2 , 0.3 , 0.4 , 0.5 , 0.6 , 0.7 , 0.8 , 0.9 , 1 ] cbar.set_ticks(labels) # Rotate colorbar ticklabels by 45 degrees clockwise cbar.ax.set_xticklabels(labels, rotation = - 45 ) plt.show() |
Output:
Example 3: Following program demonstrates vertical color bar with 30 degrees rotation of colorbar ticklabels.
Python3
# Import libraries import matplotlib.pyplot as plt import numpy as np # Plot image a = np.random.random(( 10 , 10 )) plt.imshow(a, cmap = 'gray' ) # Plot vertical colorbar cbar = plt.colorbar( orientation = "vertical" , fraction = 0.050 ) # Set ticklabels labels = [ 0 , 0.1 , 0.2 , 0.3 , 0.4 , 0.5 , 0.6 , 0.7 , 0.8 , 0.9 , 1 ] cbar.set_ticks(labels) # Rotate colorbar ticklabels by 30 degrees # anticlockwise cbar.ax.set_yticklabels(labels, rotation = 30 ) plt.show() |
Output:
Example 4: Following program demonstrates vertical color bar with -30 degrees rotation of colorbar ticklabels.
Python3
# Import libraries import matplotlib.pyplot as plt import numpy as np # Plot image a = np.random.random(( 10 , 10 )) plt.imshow(a, cmap = 'gray' ) # Plot vertical colorbar cbar = plt.colorbar( orientation = "vertical" , fraction = 0.050 ) # Set ticklabels labels = [ 0 , 0.1 , 0.2 , 0.3 , 0.4 , 0.5 , 0.6 , 0.7 , 0.8 , 0.9 , 1 ] cbar.set_ticks(labels) # Rotate colorbar ticklabels by 30 degrees clockwise cbar.ax.set_yticklabels(labels, rotation = - 30 ) plt.show() |
Output:
Example 5: Following program demonstrates horizontal color bar with vertical rotation of colorbar ticklabels.
Python3
# Import libraries import matplotlib.pyplot as plt import numpy as np # Plot image a = np.random.random(( 10 , 10 )) plt.imshow(a, cmap = 'gray' ) # Plot horizontal colorbar cbar = plt.colorbar( orientation = "horizontal" , fraction = 0.050 ) # Set ticklabels labels = [ 0 , 0.1 , 0.2 , 0.3 , 0.4 , 0.5 , 0.6 , 0.7 , 0.8 , 0.9 , 1 ] cbar.set_ticks(labels) # Rotate colorbar ticklabels by 90 degrees # anticlockwise using "vertical" value cbar.ax.set_xticklabels(labels, rotation = "vertical" ) plt.show() |
Output:
Example 6: Following program demonstrates vertical color bar with 270 degrees rotation of colorbar ticklabels.
Python3
# Import libraries import matplotlib.pyplot as plt import numpy as np # Plot image a = np.random.random(( 10 , 10 )) plt.imshow(a, cmap = 'gray' ) # Plot vertical colorbar cbar = plt.colorbar( orientation = "vertical" , fraction = 0.050 ) # Set ticklabels labels = [ 0 , 0.1 , 0.2 , 0.3 , 0.4 , 0.5 , 0.6 , 0.7 , 0.8 , 0.9 , 1 ] cbar.set_ticks(labels) # Rotate colorbar ticklabels by 270 degrees # anticlockwise cbar.ax.set_yticklabels(labels, rotation = 270 ) plt.show() |
Output: