Comparison operations in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a boolean array where elements of arr are greater than 5.

NumPy

import numpy as np
arr = np.array([3, 7, 2, 9, 5])
result = arr [1] 5
print(result)

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

A<

B==

C>

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' which checks for smaller values.

Using '==' which checks for equality, not greater than.

The '>' operator compares each element of the array to 5, returning True where the element is greater than 5.

2fill in blank

medium

Complete the code to find elements in arr that are equal to 10.

NumPy

import numpy as np
arr = np.array([10, 15, 10, 20, 25])
mask = arr [1] 10
print(mask)

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

A>

B!=

C<

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' which checks for inequality.

Using '>' or '<' which check for greater or smaller values.

The '==' operator checks element-wise equality with 10, returning True where elements equal 10.

3fill in blank

hard

Fix the error in the code to correctly create a mask for elements less than or equal to 7.

NumPy

import numpy as np
arr = np.array([5, 8, 7, 10, 3])
mask = arr [1] 7
print(mask)

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

A<

B<=

C=>

D==

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=>' which is not a valid Python operator.

Using '<' which excludes equality.

The correct operator for 'less than or equal to' is '<=', not '=>'.

4fill in blank

hard

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

NumPy

words = ['cat', 'elephant', 'dog', 'horse']
lengths = {word: [1] for word in words if [2]

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

Alen(word)

Blen(word) > 3

Clen(word) < 3

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using the wrong condition like length less than 3.

We map each word to its length using len(word), and filter words where length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths only if length is less than 5.

NumPy

words = ['tree', 'sun', 'flower', 'sky']
result = { [1]: [2] for w in words if [3] }
print(result)

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

Aw.upper()

Blen(w)

Clen(w) < 5

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() instead of w.upper() for keys.

Using wrong condition like length greater than 5.

Using the word itself as value instead of length.

We use w.upper() as the key, len(w) as the value, and filter words with length less than 5.

Practice

1. What does the numpy expression arr == 5 return when arr is a numpy array?

easy

A. The sum of all elements equal to 5

B. An array of True/False values showing where elements equal 5

C. The count of elements equal to 5

D. A single True or False value

Solution

1. Step 1: Understand element-wise comparison

   The expression arr == 5 compares each element of the array to 5 individually.

2. Step 2: Result type of comparison

   This returns a new array of the same shape with True where the element equals 5, and False otherwise.

3. Final Answer:

   An array of True/False values showing where elements equal 5 -> Option B

4. Quick Check:

   Element-wise comparison = Boolean array [OK]

Hint: Remember == returns True/False array element-wise [OK]

Common Mistakes:

• Thinking it returns a count or sum
• Expecting a single True/False value
• Confusing == with assignment =

2. Which of the following is the correct syntax to check if elements in numpy array arr are greater than 10?

easy

A. arr >> 10

B. arr => 10

C. arr > 10

D. arr >= 10

Solution

1. Step 1: Identify correct comparison operator

   The operator for 'greater than' is >, so arr > 10 checks elements greater than 10.

2. Step 2: Check other options

   arr => 10 is invalid syntax, arr >> 10 is a bitwise shift, and arr >= 10 checks greater or equal, not strictly greater.

3. Final Answer:

   arr > 10 -> Option C

4. Quick Check:

   Greater than operator is > [OK]

Hint: Use > for greater than, >= for greater or equal [OK]

Common Mistakes:

• Using => instead of >
• Confusing bitwise >> with comparison
• Using >= when > is asked

3. What is the output of the following code?

import numpy as np
arr = np.array([3, 7, 2, 9])
result = arr >= 5
print(result)

medium

A. [False False False False]

B. [True False True False]

C. [True True True True]

D. [False True False True]

Solution

1. Step 1: Compare each element with 5

   Elements: 3, 7, 2, 9. Check if each is >= 5: 3>=5 is False, 7>=5 is True, 2>=5 is False, 9>=5 is True.

2. Step 2: Form boolean array

   The result is [False, True, False, True].

3. Final Answer:

   [False True False True] -> Option D

4. Quick Check:

   Element-wise >= 5 = [False True False True] [OK]

Hint: Check each element against 5 carefully [OK]

Common Mistakes:

• Mixing up >= with >
• Misreading element values
• Expecting integer output instead of boolean

4. Identify the error in this numpy comparison code:

import numpy as np
arr = np.array([1, 2, 3])
result = arr = 2
print(result)

medium

A. Using single = instead of == for comparison

B. Array must be converted to list before comparison

C. print() cannot display numpy arrays

D. Missing parentheses in print statement

Solution

1. Step 1: Check comparison syntax

   The code uses arr = 2 which assigns 2 to arr, not compares. Comparison needs ==.

2. Step 2: Understand effect of assignment

   Assignment overwrites arr with 2, so print(result) prints 2, not a boolean array.

3. Final Answer:

   Using single = instead of == for comparison -> Option A

4. Quick Check:

   Comparison needs ==, not = [OK]

Hint: Use == for comparison, = is assignment [OK]

Common Mistakes:

• Confusing = and ==
• Thinking print can't show arrays
• Believing arrays must convert to lists

5. Given two numpy arrays:

import numpy as np
arr1 = np.array([1, 4, 6, 8])
arr2 = np.array([2, 4, 5, 10])

Which expression returns a boolean array showing where elements in arr1 are less than or equal to elements in arr2?

hard

A. arr1 <= arr2

B. arr1 < arr2

C. arr1 == arr2

D. arr1 >= arr2

Solution

1. Step 1: Understand element-wise comparison between arrays

   Comparing two arrays with operators like <= compares each element pair at the same index.

2. Step 2: Identify operator for 'less than or equal'

   The operator <= checks if elements in arr1 are less than or equal to corresponding elements in arr2.

3. Final Answer:

   arr1 <= arr2 -> Option A

4. Quick Check:

   Use <= for less or equal element-wise [OK]

Hint: Use <= to compare arrays element-wise for less or equal [OK]

Common Mistakes:

• Using < instead of <= when equal counts
• Using == which only checks equality
• Using >= which is opposite