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Matplotlib.pyplot.loglog() function in Python

Prerequisites: Matplotlib

Matplotlib is a comprehensive library for creating interactive, static and animated visualizations in python. Using general-purpose GUI toolkits like wxPython, SciPy, Tkinter or SciPy, it provides an object-oriented API for embedding plots into applications. Matplotlib.pyplot is a collection of functions that makes Matplotlib work like MATLAB.

Here, we will be exploring loglog() function of Matplotlib.pyplot. It is used to plot a log scale over both x and y-axis.

Syntax:

loglog(X,Y)

Where,

X and Y refer to x and y coordinates respectively.

Other function used is linespace(). It returns evenly spaced numbers over a specified interval.

Syntax:

np.linspace(start, stop, num, endpoint, retstep, dtype, axis)

Where,

  • Start : The starting value of sequence from where you want to show the line, or we can say starting point of line
  • Stop : It is the end value of the sequence at where the line stops, unless ‘endpoint’ is set to False.
  • Num : Number of samples to generate. Must be non-negative. By default, it is 50.
  • Endpoint : It works same as stop. If it is True then stop is the last sample else stop is excluded from the sequence.
  • Retstep : If True, return (‘samples’, ‘step’), where `step` is the spacing between samples.
  • Dtype : The type of the output array.
  • Axis : The axis in the result to store the samples and it is relevant only if start or stop are array-like

Example : Without loglog()

Python




# importing required modules
import matplotlib.pyplot as plt
import numpy as np
 
 
# inputs to plot using loglog plot
x_input = np.linspace(0, 10, 50000)
 
y_input = x_input**8
 
# plotting the value of x_input and y_input using plot function
plt.plot(x_input, y_input)


Output: 

Example : With loglog()

Python3




# importing required modules
import matplotlib.pyplot as plt
import numpy as np
 
 
# inputs to plot using loglog plot
x_input = np.linspace(0, 10, 50000)
 
y_input = x_input**8
 
# plotting the value of x_input and y_input using loglog plot
plt.loglog(x_input, y_input)


Output:

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