Histogram computation with np.histogram() in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to compute the histogram counts of the data array.

NumPy

import numpy as np

data = np.array([1, 2, 2, 3, 4, 4, 4, 5])
counts, bins = np.histogram(data, bins=[1])

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

A3

B4

C5

D6

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number of bins that is too small or too large for the data.

Forgetting to pass the bins parameter.

The bins parameter specifies the number of bins for the histogram. Here, 4 bins will group the data into 4 intervals.

2fill in blank

medium

Complete the code to compute histogram counts with custom bin edges.

NumPy

import numpy as np

data = np.array([1, 2, 2, 3, 4, 4, 4, 5])
bin_edges = [1, 2, 3, 5]
counts, bins = np.histogram(data, bins=[1])

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

Abin_edges

B3

C[1, 2, 3]

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a number instead of the bin edges list.

Using an incomplete list of bin edges.

Passing a list of bin edges to bins lets you define exact intervals for the histogram.

3fill in blank

hard

Fix the error in the code to correctly compute histogram counts and bin edges.

NumPy

import numpy as np

data = np.array([1, 2, 3, 4, 5])
counts, bins = np.histogram(data, bins=[1])

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

A[1, 2, 3, 4]

B[1, 2, 3, 4, 5]

C[0, 1, 2, 3, 4, 5]

D[1, 2, 3, 4, 5, 6]

Attempts:

3 left

💡 Hint

Common Mistakes

Using bin edges that do not cover the maximum data value.

Using a bin edges list with the same length as data.

The bin edges must cover the full range of data. Adding 6 as the last edge includes the last data point in the final bin.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
lengths = {word: [1] for word in words if len(word) [2] 3}

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong comparison operator.

Using the word itself instead of its length.

The dictionary comprehension maps each word to its length only if the word length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words longer than 4 characters.

NumPy

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
result = {{'[1]': [2] for word in words if len(word) [3] 4}}

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Aword.upper()

Blen(word)

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as key without uppercase.

Using wrong comparison operator.

Swapping keys and values.

This dictionary comprehension creates keys as uppercase words and values as their lengths, filtering words longer than 4 characters.