Histogram vs bar chart distinction in Matplotlib - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a histogram of the data list using matplotlib.

Matplotlib

import matplotlib.pyplot as plt

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

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

Ahist

Bbar

Cplot

Dscatter

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'bar' instead of 'hist' will create a bar chart, not a histogram.

Using 'plot' or 'scatter' won't group data into bins.

The hist function creates a histogram, which groups data into bins and shows frequency.

2fill in blank

medium

Complete the code to create a bar chart showing counts of categories using matplotlib.

Matplotlib

import matplotlib.pyplot as plt

categories = ['A', 'B', 'C']
counts = [5, 7, 3]
plt.[1](categories, counts)
plt.show()

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Ascatter

Bhist

Cbar

Dplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'hist' will try to bin numeric data, not suitable for categories.

Using 'scatter' or 'plot' won't create bars.

The bar function creates a bar chart, which shows counts or values for categories.

3fill in blank

hard

Fix the error in the code to correctly plot a histogram of the data.

Matplotlib

import matplotlib.pyplot as plt

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

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

A5

BNone

C[5]

D'5'

Attempts:

3 left

💡 Hint

Common Mistakes

Passing bins as a string like '5' causes a TypeError.

Passing bins as a list like [5] is invalid.

The bins parameter expects an integer number of bins, not a string or list.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that counts how many times each number appears in the list.

Matplotlib

data = [1, 2, 2, 3, 3, 3]
counts = {num: data.[1](num) for num in [2](data)}

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Acount

Blen

Cset

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using len instead of count causes errors.

Using list instead of set causes duplicate keys.

The count method counts occurrences of each number, and set gets unique numbers.

5fill in blank

hard

Fill all three blanks to create a bar chart showing counts of unique items from data.

Matplotlib

import matplotlib.pyplot as plt

data = ['apple', 'banana', 'apple', 'orange', 'banana', 'banana']
counts = {item: data.count(item) for item in [1](data)}
plt.bar(counts.[2](), counts.[3]())
plt.show()

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Aset

Bvalues

Ckeys

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using list instead of set causes duplicate bars.

Swapping keys() and values() causes wrong axes.

set gets unique items, keys() gets the categories for x-axis, and values() gets counts for y-axis.