Counting with boolean arrays in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Counting True values in a boolean NumPy array

What is the output of this code snippet that counts True values in a boolean NumPy array?

NumPy

import numpy as np
arr = np.array([True, False, True, True, False])
count = np.sum(arr)
print(count)

A 4

B 2

C 5

D 3

💡 Hint

Remember that True is treated as 1 and False as 0 in NumPy when summing.

The array has three True values. Summing treats True as 1, so the sum is 3.

❓ data_output

intermediate

Counting True values along an axis in a 2D boolean array

Given this 2D boolean array, what is the output of counting True values along axis 1?

NumPy

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

A [1 2 3]

B [2 1 3]

C [3 1 2]

D [2 2 2]

💡 Hint

Sum along axis 1 means count True values in each row.

Row 1 has 2 True, row 2 has 1 True, row 3 has 3 True values.

🔧 Debug

advanced

Identify the error in counting True values with incorrect axis

What error does this code raise when trying to count True values along axis 2 in a 2D boolean array?

NumPy

import numpy as np
arr = np.array([[True, False], [False, True]])
count = np.sum(arr, axis=2)
print(count)

A AxisError: axis 2 is out of bounds for array of dimension 2

B TypeError: unsupported operand type(s) for +: 'bool' and 'int'

C ValueError: operands could not be broadcast together

D No error, output is [1 1]

💡 Hint

Check the dimensions of the array and the axis argument.

The array is 2D, so valid axes are 0 and 1. Axis 2 is invalid and causes AxisError.

🚀 Application

advanced

Counting values greater than a threshold using boolean arrays

Given a NumPy array of numbers, which option correctly counts how many values are greater than 10?

NumPy

import numpy as np
arr = np.array([5, 12, 7, 20, 15])
count = ???
print(count)

A np.sum(arr > 10)

B np.sum(arr >= 10)

C np.count_nonzero(arr < 10)

D np.count_nonzero(arr == 10)

💡 Hint

Create a boolean array where values are greater than 10, then sum True values.

arr > 10 creates a boolean array. Summing counts True values, which are values > 10.

🧠 Conceptual

expert

Understanding boolean array counting with np.count_nonzero vs np.sum

Which statement best describes the difference between np.count_nonzero(boolean_array) and np.sum(boolean_array) when counting True values?

A np.count_nonzero counts False values; np.sum counts True values.

B np.count_nonzero returns the total number of elements; np.sum counts only True values.

C np.count_nonzero counts True values directly; np.sum treats True as 1 and sums them, both give the same result for boolean arrays.

D np.count_nonzero returns a boolean array; np.sum returns an integer count.

💡 Hint

Think about how True and False are treated in NumPy arithmetic and counting.

Both functions count True values in boolean arrays, but np.count_nonzero counts non-zero elements, which are True, and np.sum adds True as 1.