Combining conditions in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of combined conditions with numpy arrays

What is the output of this code snippet that combines two conditions on a numpy array?

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4, 5])
result = arr[(arr > 2) & (arr < 5)]
print(result)

A [1 2 3 4 5]

B [2 3 4]

C [3 4]

D [4 5]

💡 Hint

Remember that & means 'and' and both conditions must be true for each element.

The code selects elements greater than 2 and less than 5, which are 3 and 4.

❓ data_output

intermediate

Number of elements matching combined conditions

How many elements in the array satisfy the combined condition (arr % 2 == 0) | (arr > 4)?

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4, 5, 6])
filtered = arr[(arr % 2 == 0) | (arr > 4)]
print(len(filtered))

A 6

B 4

C 3

D 5

💡 Hint

Check which numbers are even or greater than 4.

Elements 2, 4, 5, 6 satisfy the condition.

❓ Predict Output

advanced

Output of combined conditions with logical operators

What is the output of this code that uses combined conditions with numpy arrays?

NumPy

import numpy as np
arr = np.array([10, 15, 20, 25, 30])
result = arr[(arr >= 15) & ((arr % 10) == 0)]
print(result)

A [10 20 30]

B [15 20 25 30]

C [15 25]

D [20 30]

💡 Hint

Check elements greater or equal to 15 and divisible by 10.

Only 20 and 30 satisfy both conditions.

🔧 Debug

advanced

Identify the error in combining conditions with numpy arrays

What error does this code raise when combining conditions incorrectly?

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4])
result = arr[arr > 2 and arr < 4]
print(result)

A ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

B SyntaxError: invalid syntax

C TypeError: unsupported operand type(s) for &: 'bool' and 'bool'

D IndexError: index out of range

💡 Hint

Check how logical operators work with numpy arrays.

Using 'and' with numpy arrays causes a ValueError because it expects a single boolean, not an array.

🚀 Application

expert

Filter a numpy array with multiple combined conditions

Given the array arr = np.array([5, 10, 15, 20, 25, 30]), which option correctly filters elements that are either divisible by 5 but not by 10, or greater than 20?

NumPy

import numpy as np
arr = np.array([5, 10, 15, 20, 25, 30])

A arr[((arr % 5 == 0) & (arr % 10 != 0)) | (arr > 20)]

B arr[(arr % 5 == 0) & ((arr % 10 != 0) | (arr > 20))]

C arr[(arr % 5 == 0) | (arr % 10 != 0) & (arr > 20)]

D arr[(arr % 5 == 0) & (arr % 10 != 0) | arr > 20]

💡 Hint

Use parentheses to group conditions properly and remember operator precedence.

Option A correctly groups conditions to select elements divisible by 5 but not 10, or greater than 20.