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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