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Matplotlib.axis.Axis.set_tick_params() in Python

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  • Last Updated : 01 Jun, 2020
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Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.

Matplotlib.axis.Axis.set_tick_params() Function

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

Syntax: Axis.set_tick_params(self, axis=’major’, reset=False, \*\*kw)

Parameters: This method accepts the following parameters.

  • axis: 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.Axis.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(0.0, 2.0, 0.02)
  
fig, ax1 = plt.subplots()
  
ax1.plot(t, np.sin(4*np.pi * t))
ax1.grid(True)
ax1.set_ylim((-2, 2))
  
ax1.xaxis.set_tick_params(labelcolor='r')
ax1.yaxis.set_tick_params(labelcolor='g')
  
plt.title('matplotlib.axis.Axis.set_tick_params()\n\
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(2000, 1, 1)
date2 = datetime.date(2014, 4, 12)
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=8 ,
                         labelcolor = "g")
ax.yaxis.set_tick_params(rotation=25,
                         labelsize=12 ,
                         labelcolor = "r")
  
plt.title('matplotlib.axis.Axis.set_tick_params()\n\
function Example', fontweight ="bold"
    
plt.show()

Output:


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