Logical operations (and, or, not) in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the numpy.logical_and() function do?

It performs an element-wise logical AND operation between two arrays, returning True only where both elements are True.

beginner

How does numpy.logical_or() differ from numpy.logical_and()?

numpy.logical_or() returns True if at least one element in the pair is True, unlike logical_and() which requires both to be True.

beginner

What is the purpose of numpy.logical_not()?

It returns the element-wise logical NOT of an array, flipping True to False and vice versa.

intermediate

Why use numpy.logical_and() instead of Python's and with arrays?

Python's and does not work element-wise on arrays. numpy.logical_and() applies the operation to each pair of elements, which is needed for array data.

intermediate

How can you combine multiple logical operations in NumPy?

You can nest numpy.logical_and(), numpy.logical_or(), and numpy.logical_not() calls to create complex conditions applied element-wise.

What will numpy.logical_and([True, False], [True, True]) return?

A [True, False]

B [False, True]

C [True, True]

D [False, False]

Element-wise AND: True AND True is True; False AND True is False.

Which function flips True to False and False to True in NumPy?

A numpy.logical_not()

B numpy.logical_or()

C numpy.logical_and()

D numpy.invert()

numpy.logical_not() performs element-wise logical NOT.

What does numpy.logical_or([False, False], [True, False]) return?

A [False, True]

B [False, False]

C [True, False]

D [True, True]

Element-wise OR: False OR True is True; False OR False is False.

Why can't you use Python's and directly on NumPy arrays?

A It works but is slow

B It returns the first array always

C It converts arrays to lists first

D It raises an error because <code>and</code> expects single booleans

Python's and expects single boolean values, not arrays, so it raises an error.

How do you combine logical_and and logical_not in NumPy?

A By using <code>numpy.logical_not(numpy.logical_and(a, b))</code>

B By using <code>numpy.logical_and(a, numpy.logical_not(b))</code>

C By using <code>a and not b</code>

D By using <code>numpy.and_not(a, b)</code>

You can nest logical functions like numpy.logical_and(a, numpy.logical_not(b)) for combined conditions.

Explain how to perform element-wise logical AND, OR, and NOT operations on NumPy arrays.

Think about how to check conditions for each item in a list.

Describe why Python's built-in logical operators cannot be used directly on NumPy arrays and how NumPy solves this.

Consider how Python handles single values vs lists.