Categorical scatter with jitter in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib plotting library.

Matplotlib

import [1] as plt

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Amatplotlib.pyplot

Bseaborn

Cpandas

Dnumpy

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the wrong library like seaborn or numpy.

Forgetting to import pyplot specifically.

We import matplotlib.pyplot as plt to create plots.

2fill in blank

medium

Complete the code to add random jitter to the x-axis positions.

Matplotlib

import numpy as np
x = np.array([1, 2, 3, 4, 5])
jitter = np.random.uniform(-[1], [1], size=x.size)
x_jittered = x + jitter

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A0.5

B1.0

C0.1

D2.0

Attempts:

3 left

💡 Hint

Common Mistakes

Using too large jitter which scatters points too far.

Using zero jitter which causes overlapping points.

Small jitter like 0.1 keeps points close to their categories but avoids overlap.

3fill in blank

hard

Fix the error in the scatter plot code to plot jittered points.

Matplotlib

plt.scatter([1], y, alpha=0.7)
plt.show()

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Ax

Bx_jittered

Cy_jittered

Dy

Attempts:

3 left

💡 Hint

Common Mistakes

Plotting original x without jitter causes overlapping points.

Using y for x-axis values causes wrong plot.

We plot the jittered x positions against y to show spread in categories.

4fill in blank

hard

Fill both blanks to create a categorical scatter plot with jitter and labels.

Matplotlib

categories = ['A', 'B', 'C', 'D']
values = [5, 7, 6, 8]
x = np.arange(len(categories))
jitter = np.random.uniform(-0.1, 0.1, size=len(x))
plt.scatter(x + [1], values, color='blue')
plt.xticks(x, [2])
plt.show()

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Ajitter

Bcategories

Cvalues

Dx

Attempts:

3 left

💡 Hint

Common Mistakes

Using values instead of categories for x-axis labels.

Not adding jitter causing overlapping points.

Adding jitter to x spreads points horizontally. plt.xticks uses category names for labels.

5fill in blank

hard

Fill all three blanks to create a jittered scatter plot with customized marker size and transparency.

Matplotlib

x = np.array([1, 2, 3, 4])
y = np.array([10, 15, 13, 17])
jitter = np.random.uniform(-0.15, 0.15, size=x.size)
plt.scatter(x + [1], y, s=[2], alpha=[3], color='green')
plt.show()

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

Ajitter

B100

C0.6

D10

Attempts:

3 left

💡 Hint

Common Mistakes

Using original x without jitter.

Setting alpha to 1 (opaque) or too low (invisible).

Using too small marker size.

Jitter is added to x for spread. Marker size s=100 makes points bigger. Alpha 0.6 sets transparency.