np.full() for custom-filled arrays in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the np.full() function do in NumPy?

np.full() creates a new array of a given shape and fills it with a specified value.

beginner

How do you specify the shape of the array in np.full()?

You provide the shape as the first argument, either as an integer for 1D or a tuple for multi-dimensional arrays.

beginner

What is the role of the fill_value parameter in np.full()?

fill_value is the value used to fill every element of the new array.

intermediate

Can np.full() create arrays of different data types? How?

Yes, by using the optional dtype parameter, you can specify the data type of the array elements.

beginner

Why might you use np.full() instead of np.zeros() or np.ones()?

Use np.full() when you want an array filled with a custom value other than 0 or 1.

What is the correct way to create a 3x3 array filled with the number 7 using np.full()?

A np.full(3, 3, 7)

B np.full(3, 7)

C np.full(7, (3, 3))

D np.full((3, 3), 7)

The shape must be a tuple (3, 3) and the fill value is 7.

Which parameter in np.full() controls the data type of the array elements?

A shape

B dtype

C fill_value

D order

dtype sets the data type of the array elements.

What will np.full(5, 0) create?

A A 5x5 array filled with zeros

B A scalar zero

C A 1D array of length 5 filled with zeros

D An error

Shape is 5, so a 1D array of length 5 filled with 0.

If you want a 2x2 array filled with the string 'hi', which code is correct?

A np.full((2, 2), 'hi')

B np.full((2, 2), hi)

C np.full(2, 'hi')

D np.full('hi', (2, 2))

The shape is (2, 2) and the fill value is the string 'hi'.

What happens if you do not specify dtype in np.full()?

A It infers the data type from the fill value

B It defaults to float64

C It raises an error

D It defaults to int32

NumPy guesses the data type based on the fill value.

Explain how to create a 4x4 NumPy array filled with the number 9 using np.full(). Include how to specify the shape and fill value.

Think about the first argument as shape and second as the value to fill.

Describe the difference between np.full() and np.zeros(). When would you use each?

Consider what value you want in the array.