Why statistical plots reveal data patterns in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the plotting library.

Matplotlib

import [1] as plt

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Amatplotlib.pyplot

Bseaborn

Cpandas

Dnumpy

Attempts:

3 left

💡 Hint

Common Mistakes

Importing numpy or pandas instead of matplotlib.pyplot

Using seaborn without importing matplotlib.pyplot

We use matplotlib.pyplot as the standard library for plotting in Python.

2fill in blank

medium

Complete the code to create a simple line plot of data.

Matplotlib

plt.[1]([1, 2, 3, 4], [10, 20, 25, 30])
plt.show()

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Ahist

Bplot

Cscatter

Dbar

Attempts:

3 left

💡 Hint

Common Mistakes

Using scatter instead of plot for line graphs

Using hist which is for histograms

The plot function draws a line plot connecting points.

3fill in blank

hard

Fix the error in the code to display a histogram of data.

Matplotlib

data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
plt.hist([1])
plt.show()

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Alist

Bplt

Chist

Ddata

Attempts:

3 left

💡 Hint

Common Mistakes

Passing plt or hist instead of the data list

Passing a string instead of the variable

The histogram function needs the data list as input to plot the frequency.

4fill in blank

hard

Fill both blanks to create a scatter plot with labels.

Matplotlib

plt.[1](x, y)
plt.[2]()

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Ascatter

Bshow

Cplot

Dhist

Attempts:

3 left

💡 Hint

Common Mistakes

Using plot instead of scatter for points

Forgetting to call show()

Use scatter to plot points and show to display the plot.

5fill in blank

hard

Fill all three blanks to create a bar chart with labels and title.

Matplotlib

plt.bar([1], [2])
plt.xlabel([3])
plt.show()

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Acategories

Bvalues

C"Category Names"

D"Values"

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping categories and values

Not labeling the axes

Bar charts need categories and values. Labels help explain the axes.