Matplotlib is one of the most popular Python packages used for data visualization. It is a cross-platform library for making 2D plots from data in arrays.Pyplot is a collection of command style functions that make matplotlib work like MATLAB.
Note: For more information, refer to Python Matplotlib – An Overview
locator_params() is used for controlling the behaviors of tick locators. The attribute axis is for specifying on which axis is the function being applied.
# for Y axis matplotlib.pyplot.locator_params(axis='y', nbins=3) # for X axis matplotlib.pyplot.locator_params(axis='x', nbins=3) # for both, x-axis and y-axis: Default matplotlib.pyplot.locator_params(nbins=3)
Reducing the maximum number of ticks and use tight bounds:
plt.locator_params(tight=True, nbins=4)
Example 1:
# importing libraries import matplotlib.pyplot as plt # Y-axis Values y =[-1, 4, 9, 16, 25] # X-axis Values x =[1, 2, 3, 4, 5] plt.locator_params(axis ='x', nbins = 5) # adding grid to the plot axes = plt.axes() axes.grid() # defining the plot plt.plot(x, y, 'mx', color ='green') # range of y-axis in the plot plt.ylim(ymin =-1.2, ymax = 30) # Set the margins plt.margins(0.2) # printing the plot plt.show() |
Output:
Example 2:
# importing libraries import matplotlib.pyplot as plt # defining the function def for_lines(xlab, ylab, plot_title, size_x, size_y, content =[]): width = len(content[0][1:]) s = [x for x in range(1, width + 1)] # specifying the size of figure plt.figure(figsize =(size_x, size_y)) for line in content: plt.plot(s, line[1:], 'ro--', color ='green', label = line[0]) # to add title to the plot plt.title(plot_title) # for adding labels to the plot plt.xlabel(xlab) plt.ylabel(ylab) t = len(s) plt.locator_params(nbins = t) for_lines("x-axis", "y-axis", "GeeksForGeeks", 7, 7, [[1, 2, 4, 3, 5]]) |
Output:
Example 3:
# importing libraries import matplotlib.pyplot as plt plt.locator_params(nbins = 10) # defining the plot plt.plot([1, 2, 3, 5, 7], [2, 3, 9, 15, 16], 'ro-', color ='red') # printing the plot plt.show() |
Output:
