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# What is the difference between 'log' and 'symlog' in matplotlib?

Log helps to make a plot with log scaling on both the X and Y axis, whereas symlog (symmetric log) is used for axis scaling.

## Steps

First, we can adjust the subplot layout parameters.

Return an evenly spaced value (t) within a given interval, using the numpy.arrange() method.

Add a subplot to the current figure, with nrows = 1, ncols = 2 and current index is 1.

Make a plot with log scaling on the Y axis, using the semilogy() method.

Set the title for the axes, using the plt.title() method.

Configure the grid lines, using the grid(True) method.

Create two evenly spaced values within a given interval using the numpy.arrange() method.

Add a subplot to the current figure with nrows = 1, ncols = 2 and current index is 2.

Plot using the plt.plot() method with two lists that have been created in step 7.

Set the X-axis scale, using xscale.

Set the title for the axes, using the plt.title() method.

Configure the grid lines, using the grid(True) method.

To show the figure, use the plt.show() method.

## Example

import numpy as np import matplotlib.pyplot as plt plt.subplots_adjust(hspace=0.4) t = np.arange(0.01, 20.0, 0.01) # log y axis plt.subplot(121) plt.semilogy(t, np.exp(-t/5.0)) plt.title('Log') plt.grid(True) x = np.arange(-50.0, 50.0, 0.01) y = np.arange(0, 100.0, 0.01) plt.subplot(122) plt.plot(x, y) plt.xscale('symlog') plt.title('Symmetry Log') plt.grid(True) plt.show()

## Output

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