np.sqrt() for square roots in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the function np.sqrt() do in numpy?

np.sqrt() calculates the square root of each element in a numpy array or a single number.

beginner

How do you calculate the square root of 16 using numpy?

You use np.sqrt(16), which returns 4.0.

beginner

Can np.sqrt() handle arrays? Give an example.

Yes, it can. For example, np.sqrt(np.array([1, 4, 9])) returns [1. 2. 3.].

intermediate

What happens if you use np.sqrt() on a negative number?

It returns nan (not a number) and raises a warning because square root of negative numbers is not defined in real numbers.

beginner

Why is np.sqrt() useful in data science?

It helps to transform data, calculate distances, or normalize values by finding square roots quickly and efficiently.

What is the output of np.sqrt(25)?

A 25

B 5.0

C 12.5

D Error

The square root of 25 is 5, so np.sqrt(25) returns 5.0.

Which of these inputs can np.sqrt() accept?

A Single numbers and numpy arrays

B Only lists

C Only single numbers

D Only strings

np.sqrt() works with single numbers and numpy arrays, calculating square roots element-wise.

What does np.sqrt(np.array([4, 16, 36])) return?

A [1 2 3]

B [4 16 36]

C [2. 4. 6.]

D Error

It returns the square roots of each element: 2, 4, and 6.

What happens if you try np.sqrt(-9)?

A Returns nan or warning

B Returns 3

C Returns -3

D Returns 0

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

Why might data scientists use np.sqrt()?

A To remove missing values

B To sort data

C To convert data to strings

D To calculate square roots for data transformation

Square roots help in data transformation, normalization, and distance calculations.

Explain how np.sqrt() works with both single numbers and arrays.

Think about how it handles one number versus many numbers.

Describe what happens when np.sqrt() is used on negative numbers and why.

Consider the math behind square roots and negative inputs.