Matplotlib.pyplot.tick_params() in Python

Matplotlib is a visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.pyplot.tick_params()

matplotlib.pyplot.tick_params() is used to change the appearance of ticks, tick labels, and gridlines.

Syntax:

matplotlib.pyplot.tick_params(axis='both', **kwargs)

Parameters :

Parameter	Value	Use
axis	{‘x’, ‘y’, ‘both’}, optional	Which axis to apply the parameters to. Default is ‘both’.
reset	bool, default: False	If True, set all parameters to defaults before processing other keyword arguments..
which	{‘major’, ‘minor’, ‘both’}	Default is ‘major’; apply arguments to which ticks.
direction	{‘in’, ‘out’, ‘inout’}	Puts ticks inside the axes, outside the axes, or both.
length	float	Tick length in points.
width	float	Default is ‘major’; apply arguments to which ticks.
color	color	Tick color.
pad	float	Distance in points between tick and label.
labelsize	float or str	Tick label font size in points or as a string (e.g., ‘large’).
labelcolor	color	Tick label color.
colors	color	Tick color and label color.
zorder	float	Tick and label zorder.
bottom, top, left, right	bool	Whether to draw the respective ticks.
labelbottom, labeltop, labelleft, labelright	bool	Whether to draw the respective tick labels.
labelrotation	float	Tick label rotation
grid_color	color	Gridline color
grid_alpha	float	Transparency of gridlines: 0 (transparent) to 1 (opaque).
grid_linewidth	float	Width of gridlines in points.
grid_linestyle	str	Any valid Line2D line style spec.

Example #1: Default plot

# importing libraries
import matplotlib.pyplot as plt

# values of x and y axes
x = [i for i in range(5, 55, 5)]
y = [1, 4, 3, 2, 7, 6, 9, 8, 10, 5]

plt.plot(x, y)
plt.xlabel('x')
plt.ylabel('y')

plt.show()

Output :


Example #2:

# importing libraries
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, ScalarFormatter

fig, ax = plt.subplots()
ax.plot([0, 10, 20, 30], [0, 2, 1, 2])

ax.xaxis.set_minor_locator(MultipleLocator(1))
ax.xaxis.set_minor_formatter(ScalarFormatter())

ax.tick_params(axis ='both', which ='major',
               labelsize = 16, pad = 12,
               colors ='r')

ax.tick_params(axis ='both', which ='minor',
               labelsize = 8, colors ='b')

plt.show()

Output: