Counting with boolean arrays in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to count how many values in the array are True.

NumPy

import numpy as np
arr = np.array([True, False, True, True, False])
count_true = np.[1](arr)

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

Asum

Bcount

Cmean

Dlen

Attempts:

3 left

💡 Hint

Common Mistakes

Using count() which does not exist for numpy arrays.

Using len() which returns total length, not count of True.

Using mean() which returns average, not count.

Using np.sum() on a boolean array counts how many values are True because True is treated as 1 and False as 0.

2fill in blank

medium

Complete the code to count how many values in the array are False.

NumPy

import numpy as np
arr = np.array([True, False, True, False, False])
count_false = np.[1](~arr)

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

Asum

Blen

Ccount

Dmean

Attempts:

3 left

💡 Hint

Common Mistakes

Using count() which is not a numpy function.

Using mean() which calculates average, not count.

Using len() which returns total length.

Using np.sum() on the negated array ~arr counts how many values are False in the original array.

3fill in blank

hard

Fix the error in the code to count True values along axis 0.

NumPy

import numpy as np
arr = np.array([[True, False], [False, True], [True, True]])
count_true_axis0 = np.sum(arr, axis=[1])

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

A1

B2

C0

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=1 counts per row, not per column.

Using axis=2 causes error because array is 2D.

Using axis=-1 counts last axis but may confuse beginners.

Axis 0 means counting down the rows for each column. So axis=0 sums True values column-wise.

4fill in blank

hard

Fill both blanks to create a dictionary counting words longer than 3 letters.

NumPy

words = ['apple', 'bat', 'car', 'door', 'egg']
lengths = {word: [1] for word in words if [2]

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

Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using word > 3 compares strings to numbers, causing error.

Using word instead of len(word) for length.

Missing the condition to filter words.

The dictionary comprehension stores the length of each word. The condition filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths if length > 3.

NumPy

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

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

Aword.upper()

Blen(word)

Cword

Dwords

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'words' instead of 'word' in the loop variable.

Using 'words.upper()' which is invalid.

Not filtering words by length.

The dictionary comprehension uses uppercase words as keys and their lengths as values, filtering words longer than 3 letters.

Practice

1. What does summing a boolean array in NumPy do?
arr = np.array([True, False, True])
What is arr.sum()?

easy

A. Returns the length of the array

B. Counts how many False values are in the array

C. Counts how many True values are in the array

D. Returns an error because booleans cannot be summed

Solution

1. Step 1: Understand boolean values in NumPy

   In NumPy, True is treated as 1 and False as 0 when summed.

2. Step 2: Sum the boolean array

   Summing [True, False, True] is 1 + 0 + 1 = 2.

3. Final Answer:

   Counts how many True values are in the array -> Option C

4. Quick Check:

   True count = 2 [OK]

Hint: Sum boolean arrays to count True values quickly [OK]

Common Mistakes:

• Thinking sum counts False values
• Believing sum returns array length
• Expecting an error when summing booleans

2. Which of the following is the correct syntax to count how many elements in arr = np.array([1, 2, 3, 4]) are greater than 2 using boolean arrays?

easy

A. (arr > 2).sum()

B. arr > 2.sum()

C. arr.sum() > 2

D. arr > 2).sum()

Solution

1. Step 1: Create boolean array for condition

   arr > 2 creates a boolean array: [False, False, True, True].

2. Step 2: Sum the boolean array correctly

   We must sum the boolean array, so use parentheses: (arr > 2).sum().

3. Final Answer:

   (arr > 2).sum() -> Option A

4. Quick Check:

   Correct syntax uses parentheses [OK]

Hint: Use parentheses around condition before sum() [OK]

Common Mistakes:

• Missing parentheses causing wrong order
• Using sum() on condition without parentheses
• Confusing comparison and sum order

3. What is the output of this code?

import numpy as np
arr = np.array([5, 3, 8, 1, 6])
count = (arr % 2 == 0).sum()
print(count)

medium

A. 3

B. 0

C. 5

D. 2

Solution

1. Step 1: Create boolean array for even numbers

   arr % 2 == 0 checks which elements are even: [False, False, True, False, True].

2. Step 2: Sum True values to count evens

   Sum is 0 + 0 + 1 + 0 + 1 = 2.

3. Final Answer:

   2 -> Option D

4. Quick Check:

   Count of even numbers = 2 [OK]

Hint: Sum boolean condition to count matching elements [OK]

Common Mistakes:

• Counting odd numbers instead
• Forgetting to use parentheses
• Misunderstanding modulo operator

4. The code below is intended to count how many values in arr are less than 10, but it raises an error. What is the error and how to fix it?

import numpy as np
arr = np.array([7, 12, 5, 20])
count = arr < 10.sum()
print(count)

medium

A. Error: Missing import statement

B. Error: 10.sum() is invalid; fix by using (arr < 10).sum()

C. No error; output is boolean array

D. Error: arr < 10 is invalid; fix by using arr.sum() < 10

Solution

1. Step 1: Identify the error in expression

   10.sum() is invalid because 10 is an integer, not an array.

2. Step 2: Correct the syntax to sum boolean array

   Use parentheses to sum the boolean array: (arr < 10).sum().

3. Final Answer:

   Error: 10.sum() is invalid; fix by using (arr < 10).sum() -> Option B

4. Quick Check:

   Parentheses needed before sum() [OK]

Hint: Always put parentheses around condition before sum() [OK]

Common Mistakes:

• Calling sum() on number instead of boolean array
• Confusing comparison and sum order
• Ignoring error message details

5. Given a 2D NumPy array data = np.array([[3, 7, 2], [5, 1, 8], [6, 4, 9]]), how can you count how many elements are greater than 5 across the entire array?

hard

A. (data > 5).sum()

B. data[data > 5].count()

C. data.sum() > 5

D. np.count(data > 5)

Solution

1. Step 1: Create boolean array for elements > 5

   data > 5 creates a boolean array marking elements greater than 5.

2. Step 2: Sum True values to count elements

   Use (data > 5).sum() to count all True values in the 2D array.

3. Final Answer:

   (data > 5).sum() -> Option A

4. Quick Check:

   Sum boolean mask counts elements > 5 [OK]

Hint: Sum boolean mask over entire array to count matches [OK]

Common Mistakes:

• Using sum() on data directly
• Trying to use count() method on NumPy array
• Using non-existent np.count() function