Sparse matrix operations in SciPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a 3x3 sparse matrix with scipy.

SciPy

from scipy.sparse import [1]

matrix = [1]([[0, 0, 1], [1, 0, 0], [0, 0, 0]])
print(matrix)

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Adok_matrix

Bcsc_matrix

Ccsr_matrix

Dlil_matrix

Attempts:

3 left

💡 Hint

Common Mistakes

Using dense matrix instead of sparse format.

Choosing a sparse format not suitable for arithmetic.

The csr_matrix is a common sparse matrix format for efficient arithmetic and matrix vector operations.

2fill in blank

medium

Complete the code to convert a dense numpy array to a sparse matrix.

SciPy

import numpy as np
from scipy.sparse import csr_matrix

dense = np.array([[0, 2, 0], [3, 0, 0], [0, 0, 4]])
sparse = csr_matrix([1])
print(sparse)

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Adense

Bsparse

Cnp.array

Dnp.zeros

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the sparse matrix variable to the constructor again.

Passing a function instead of the array.

To convert a dense numpy array to a sparse matrix, pass the dense array to csr_matrix.

3fill in blank

hard

Fix the error in the code to add two sparse matrices correctly.

SciPy

from scipy.sparse import csr_matrix

A = csr_matrix([[1, 0], [0, 2]])
B = csr_matrix([[0, 3], [4, 0]])

result = A [1] B
print(result.toarray())

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A*

B-

C/

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using multiplication instead of addition.

Using subtraction or division which are not intended here.

To add two sparse matrices, use the + operator.

4fill in blank

hard

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

SciPy

words = ['data', 'science', 'ai', 'ml', 'python']
lengths = {word: [1] for word in words if len(word) [2] 3}
print(lengths)

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself instead of its length.

Using < instead of > in the condition.

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

5fill in blank

hard

Fill all three blanks to create a filtered dictionary with uppercase keys and values greater than 2.

SciPy

data = {'a': 1, 'b': 3, 'c': 5, 'd': 2}
filtered = { [1]: [2] for k, v in data.items() if v [3] 2 }
print(filtered)

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Not converting keys to uppercase.

Using wrong comparison operator.

Using key instead of value in the dictionary values.

This dictionary comprehension creates keys as uppercase letters and includes only items where the value is greater than 2.