np.sign() for sign detection in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find the sign of each number in the array using np.sign().

NumPy

import numpy as np
arr = np.array([-3, 0, 4])
signs = np.[1](arr)
print(signs)

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

Aabs

Bsign

Csqrt

Dlog

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.abs() which returns absolute values, not signs.

Using np.sqrt() which calculates square roots.

Using np.log() which calculates logarithms.

The np.sign() function returns -1 for negative numbers, 0 for zero, and 1 for positive numbers.

2fill in blank

medium

Complete the code to create a boolean mask for positive numbers using np.sign().

NumPy

import numpy as np
arr = np.array([-2, 5, 0, 3])
mask = np.sign(arr) [1] 1
print(mask)

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A<

B!=

C>

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' which selects non-positive numbers.

Using '<' or '>' which do not correctly select only positive signs.

Using np.sign(arr) == 1 creates a mask where only positive numbers are True.

3fill in blank

hard

Fix the error in the code to correctly compute signs of values in the list.

NumPy

import numpy as np
values = [-1, 0, 2]
signs = np.sign([1])
print(signs)

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Anp.array(values)

B[values]

Clist(values)

Dvalues

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the list directly without conversion.

Wrapping the list in another list which creates a nested list.

Using list() which does not convert to numpy array.

np.sign() works best with numpy arrays, so convert the list to an array first.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their sign of length comparison to 3 as values.

NumPy

import numpy as np
words = ['cat', 'dog', 'elephant']
sign_dict = {word: np.sign(len(word) [1] 3) for word in words if len(word) [2] 2}
print(sign_dict)

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A>

B==

C>=

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' in the first blank which returns 0 or 1 only.

Using '<' in the second blank which filters out longer words.

The dictionary comprehension uses len(word) > 3 inside np.sign() to get the sign, and filters words with length >= 2.

5fill in blank

hard

Fill both blanks to create a dictionary with uppercase words as keys, their lengths as values, and only include words with positive sign difference from 4.

NumPy

import numpy as np
words = ['apple', 'bat', 'carrot', 'dog']
result = {word[1]: len(word) for word in words if np.sign(len(word) [2] 4) == 1}
print(result)

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

A.upper()

C>

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Not converting keys to uppercase.

Using '<=' instead of '>' in the sign comparison.

Adding an operator in the value part which is not needed.

The keys are uppercase words using .upper(), values are lengths, and only words longer than 4 are included.