Logarithmic Scale - ( Advanced Plotting Techniques )

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Syntax

import matplotlib.pyplot as plt

plt.xscale('log')
plt.yscale('log')

Example

import matplotlib.pyplot as plt
import numpy as np

x = np.logspace(0, 4, 100)
y = x ** 2

plt.plot(x, y)
plt.xscale('log')
plt.yscale('log')
plt.show()

Output

Explanation

A logarithmic scale is a scale where the values are logarithmically distributed rather than linearly distributed. This is useful when we have a large range of values and want to display them on a plot in a way that all the features are visible.

In Matplotlib, we can set the X and Y axis to a logarithmic scale using the plt.xscale() and plt.yscale() functions respectively. We pass in the argument 'log' to set the scale to a logarithmic scale.

In the above example, we first generate some data x and y where y is the square of x. We then plot the data and set both the X and Y axis to a logarithmic scale using the plt.xscale() and plt.yscale() functions respectively. We show the plot using the plt.show() function.

Use

A logarithmic scale is useful in displaying data with a large range of values. It is commonly used in scientific and engineering applications to display data such as sound pressure levels, earthquake magnitudes, and astronomical data.

Important Points

• A logarithmic scale is a scale where the values are logarithmically distributed rather than linearly distributed
• The plt.xscale() and plt.yscale() functions can be used to set the X and Y axis to a logarithmic scale respectively
• The argument 'log' is passed to these functions to set the scale to a logarithmic scale

Summary

In conclusion, a logarithmic scale is a useful way to display data with a large range of values. Matplotlib provides the plt.xscale() and plt.yscale() functions to set the X and Y axis to a logarithmic scale respectively. This technique is commonly used in scientific and engineering applications to display data with large ranges of values.