np.savetxt() and np.loadtxt() for text in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to save the array 'data' to a text file named 'output.txt'.

NumPy

import numpy as np

data = np.array([1, 2, 3, 4, 5])
np.[1]('output.txt', data)

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

Aloadtxt

Bsave

Cload

Dsavetxt

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.loadtxt() instead of np.savetxt() to save data.

Using np.save() which saves in binary format, not text.

The np.savetxt() function saves an array to a text file. Here, it saves 'data' to 'output.txt'.

2fill in blank

medium

Complete the code to load data from the text file 'output.txt' into a numpy array.

NumPy

import numpy as np

loaded_data = np.[1]('output.txt')
print(loaded_data)

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

Aloadtxt

Bsavetxt

Csave

Dload

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.savetxt() instead of np.loadtxt() to read data.

Using np.load() which reads binary files, not text.

The np.loadtxt() function reads data from a text file and returns it as a numpy array.

3fill in blank

hard

Fix the error in the code to save a 2D array 'arr' to 'matrix.txt' with comma separators.

NumPy

import numpy as np

arr = np.array([[1, 2], [3, 4]])
np.savetxt('matrix.txt', arr, delimiter=[1])

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

A' '

B','

C';'

D':'

Attempts:

3 left

💡 Hint

Common Mistakes

Using space ' ' as delimiter when commas are needed.

Using semicolon or colon which changes the file format.

The delimiter parameter specifies the character separating values. For CSV style, use a comma ',' as delimiter.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their lengths only if length is greater than 3.

NumPy

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

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

Alen(word)

Bword

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Using '<' instead of '>' which filters shorter words.

The dictionary comprehension maps each word to its length using len(word). The condition len(word) > 3 filters words longer than 3 letters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths only if length is greater than 3.

NumPy

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

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

Aword.upper()

Blen(word)

C>

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.lower() instead of uppercase.

Using '<' instead of '>' in the condition.

Using the word itself instead of its length as the value.

The dictionary comprehension maps each word in uppercase (word.upper()) to its length (len(word)) only if the length is greater than 3 (>).