Log scale and symlog scale in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to set the y-axis to a logarithmic scale.

Matplotlib

import matplotlib.pyplot as plt
plt.plot([1, 10, 100, 1000])
plt.yscale([1])
plt.show()

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Alog

Blinear

Csymlog

Dsqrt

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'linear' instead of 'log' for logarithmic scale.

Forgetting to call plt.show() to display the plot.

Use plt.yscale('log') to set the y-axis to a logarithmic scale.

2fill in blank

medium

Complete the code to set the x-axis to a symmetric logarithmic scale.

Matplotlib

import matplotlib.pyplot as plt
plt.plot([-1000, -10, 0, 10, 1000])
plt.xscale([1])
plt.show()

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Alinear

Blog

Csymlog

Dsqrt

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'log' scale which cannot handle zero or negative values.

Not importing matplotlib.pyplot as plt.

Use plt.xscale('symlog') to set the x-axis to a symmetric logarithmic scale, which handles negative and zero values.

3fill in blank

hard

Fix the error in the code to correctly set the y-axis to a symmetric logarithmic scale with a linear threshold of 1.

Matplotlib

import matplotlib.pyplot as plt
plt.plot([-5, -1, 0, 1, 5])
plt.yscale([1], linthresh=1)
plt.show()

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Alinear

Bsymlog

Clog

Dlogit

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'log' scale with zero or negative values causes errors.

Forgetting to set linthresh parameter for symlog scale.

Use plt.yscale('symlog', linthresh=1) to set a symmetric log scale with a linear region around zero.

4fill in blank

hard

Fill both blanks to create a plot with x-axis on symmetric log scale and y-axis on log scale.

Matplotlib

import matplotlib.pyplot as plt
plt.plot([-100, -10, 0, 10, 100], [1, 10, 100, 1000, 10000])
plt.xscale([1])
plt.yscale([2])
plt.show()

Drag options to blanks, or click blank then click option'

Asymlog

Blinear

Clog

Dsqrt

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'log' scale on x-axis with negative values causes errors.

Mixing up xscale and yscale calls.

Set plt.xscale('symlog') for symmetric log on x-axis and plt.yscale('log') for log scale on y-axis.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each number to its log scale value, but uses linear scale for values near zero.

Matplotlib

import numpy as np
numbers = [-10, -1, 0, 1, 10]
scale_map = {n: np.sign(n) * np.log10(abs(n)) if abs(n) > [1] else n for n in numbers if n != [2] or n == [3]

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A1

B0

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using zero as threshold causes log10(0) error.

Not excluding zero from log calculation.

The comprehension uses a threshold of 1 to apply log10 only for values with absolute value greater than 1. It excludes zero from log calculation but includes it linearly.