np.sqrt() for square roots in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.sqrt() on a 1D array

What is the output of this code?

import numpy as np
arr = np.array([1, 4, 9, 16])
result = np.sqrt(arr)
print(result)

NumPy

import numpy as np
arr = np.array([1, 4, 9, 16])
result = np.sqrt(arr)
print(result)

A [1 4 9 16]

B [1 2 3 4]

C [1.0 2.0 3.0 4.0]

D [1. 2. 3. 4.]

💡 Hint

np.sqrt() returns floating point numbers even if input is integers.

np.sqrt() calculates the square root element-wise and returns floats. So the output is an array of floats: [1. 2. 3. 4.]

❓ data_output

intermediate

Shape and values after np.sqrt() on 2D array

Given this code, what is the shape and content of result?

import numpy as np
arr = np.array([[4, 9], [16, 25]])
result = np.sqrt(arr)
print(result.shape)
print(result)

NumPy

import numpy as np
arr = np.array([[4, 9], [16, 25]])
result = np.sqrt(arr)
print(result.shape)
print(result)

A

(2, 2) and [[4. 9.]
 [16. 25.]]

B (4,) and [2. 3. 4. 5.]

C

(2, 2) and [[2. 3.]
 [4. 5.]]

D

(2, 2) and [[2 3]
 [4 5]]

💡 Hint

np.sqrt keeps the shape of the input array and returns floats.

The input is a 2x2 array. np.sqrt returns the square root element-wise, keeping the shape (2,2) and converting values to floats.

🔧 Debug

advanced

Error when applying np.sqrt() to negative numbers

What error or warning does this code produce?

import numpy as np
arr = np.array([-1, 4, 9])
result = np.sqrt(arr)
print(result)

NumPy

import numpy as np
arr = np.array([-1, 4, 9])
result = np.sqrt(arr)
print(result)

A

RuntimeWarning: invalid value encountered in sqrt
[nan 2. 3.]

B ValueError: math domain error

C TypeError: unsupported operand type(s) for sqrt

D [-1. 2. 3.]

💡 Hint

Square root of negative numbers is not defined in real numbers, numpy returns nan with a warning.

np.sqrt on negative values returns nan and raises a RuntimeWarning about invalid value encountered.

🧠 Conceptual

advanced

Understanding np.sqrt() output type

If you apply np.sqrt() to an integer numpy array, what is the data type of the output array?

A Float type array

B Integer type array

C Boolean type array

D Complex type array

💡 Hint

Square roots often produce decimal numbers, so output must support decimals.

np.sqrt converts integer inputs to floats because square roots can be decimal numbers.

🚀 Application

expert

Using np.sqrt() to normalize data

You have a numpy array of positive values representing counts:

counts = np.array([1, 4, 9, 16, 25])

You want to apply square root transformation to reduce skewness before analysis.
Which code snippet correctly applies this transformation and stores the result in transformed?

A transformed = counts ** 2

B transformed = np.sqrt(counts)

C transformed = np.square(counts)

D transformed = np.sqrt(counts) * 2

💡 Hint

Square root transformation means applying np.sqrt directly.

Applying np.sqrt reduces skewness by compressing large values more than small ones.