Boolean indexing in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Boolean indexing in numpy?

Boolean indexing is a way to select elements from a numpy array using a condition that returns True or False for each element. Only elements where the condition is True are selected.

beginner

How do you create a Boolean array for indexing?

You create a Boolean array by applying a condition to a numpy array, for example: arr > 5 returns True for elements greater than 5 and False otherwise.

beginner

Example: Select all elements greater than 10 from array arr = np.array([5, 12, 7, 15])

Use Boolean indexing: arr[arr > 10] returns array([12, 15]) because only 12 and 15 are greater than 10.

intermediate

Can Boolean indexing be used to modify elements in a numpy array?

Yes, you can use Boolean indexing to select elements and assign new values. For example, arr[arr < 5] = 0 sets all elements less than 5 to zero.

intermediate

What happens if the Boolean array has a different shape than the original array?

The Boolean array must have the same shape as the original array for Boolean indexing to work. Otherwise, numpy will raise a ValueError.

What does arr[arr > 3] do if arr = np.array([1, 4, 3, 6])?

A Returns the original array

B Selects elements greater than 3

C Selects elements equal to 3

D Selects elements less than 3

arr > 3 creates a Boolean array where elements greater than 3 are True. Using this to index arr selects those elements.

Which of these is a valid Boolean indexing expression?

A arr[arr == 5]

B arr[5]

C arr["5"]

D arr[5 > arr]

Both A (arr == 5) and D (5 > arr) return Boolean arrays, which can be used to index arr. B is integer indexing, C is invalid.

What type of array is needed for Boolean indexing?

A Boolean array

B Float array

C Integer array

D String array

Boolean indexing requires a Boolean array where each element is True or False.

If arr = np.array([2, 8, 5]), what does arr[arr < 5] = 0 do?

A Deletes elements less than 5

B Sets elements greater than 5 to zero

C Raises an error

D Sets elements less than 5 to zero

Boolean indexing selects elements less than 5 and assigns zero to them.

What error occurs if Boolean array shape does not match original array?

A IndexError

B TypeError

C ValueError

D KeyError

Numpy raises a ValueError if the Boolean array shape is different from the original array shape.

Explain how Boolean indexing works in numpy with an example.

Think about how True/False values select elements.

Describe how you can use Boolean indexing to modify elements in a numpy array.

Consider changing values where condition is True.