Matplotlib.axis.XAxis.set_tick_params() in Python

The XAxis.set_tick_params() function in axis module of matplotlib library is used to set appearance parameters for ticks, ticklabels, and gridlines. 

Syntax: XAxis.set_tick_params(self, which=’major’, reset=False, **kw)

Parameters: This method accepts the following parameters.

• which: This parameter is the used to which axis to apply the parameters to.

Return value: This method does not returns any value.

 Below examples illustrate the matplotlib.axis.XAxis.set_tick_params() function in matplotlib.axis:

Example 1:

Python3

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np

t = np.arange(0.1, 3.0, 0.04)

fig, ax1 = plt.subplots()

ax1.plot(t, np.sin(4*np.pi * t))
ax1.grid(True)
ax1.set_ylim((-3, 3))

ax1.xaxis.set_tick_params(labelcolor='r')
ax1.yaxis.set_tick_params(labelcolor='g')

plt.title('matplotlib.axis.XAxis.set_tick_params() function Example',
          fontweight="bold")

plt.show()

Output:

Example 2:

Python3

# Implementation of matplotlib function
import matplotlib.pyplot as plt
from matplotlib.dates import (YEARLY,
                              DateFormatter,
                              rrulewrapper,
                              RRuleLocator,
                              drange)
import numpy as np
import datetime

np.random.seed(19680801)

Val1 = rrulewrapper(YEARLY, byeaster=1, interval=5)
Val2 = RRuleLocator(Val1)

formatter = DateFormatter('%y/%m/%d')

date1 = datetime.date(2002, 2, 3)
date2 = datetime.date(2010, 5, 14)
delta = datetime.timedelta(days=10)

dates = drange(date1, date2, delta)
s = np.random.rand(len(dates))

fig, ax = plt.subplots()
plt.plot_date(dates, s, 'go')

ax.xaxis.set_major_locator(Val2)
ax.xaxis.set_major_formatter(formatter)
ax.xaxis.set_tick_params(rotation=25,
                         labelsize=10,
                         labelcolor="g")
ax.yaxis.set_tick_params(rotation=25,
                         labelsize=12,
                         labelcolor="r")

plt.title('matplotlib.axis.XAxis.set_tick_params()\n\
function Example', fontweight="bold")

plt.show()

Output: