Recall & Review
beginner
What is a boolean array in numpy?
A boolean array in numpy is an array where each element is either True or False. It is often used for filtering or masking data.
Click to reveal answer
beginner
How do you create a boolean array from a numpy array based on a condition?
You apply a condition directly to a numpy array, which returns a boolean array. For example,
arr > 5 returns True for elements greater than 5 and False otherwise.Click to reveal answer
beginner
What numpy function can create a boolean array filled with True or False?
You can use
numpy.ones(shape, dtype=bool) to create a boolean array filled with True, or numpy.zeros(shape, dtype=bool) to create one filled with False.Click to reveal answer
beginner
How can boolean arrays help in real-life data filtering?
Boolean arrays let you select or ignore data easily. For example, in a list of temperatures, you can create a boolean array to find all days hotter than 30°C and then extract those days' data.Click to reveal answer
beginner
What does the expression
arr % 2 == 0 return when applied to a numpy array?It returns a boolean array where each element is True if the corresponding element in
arr is even, and False if it is odd.Click to reveal answer
What type of values does a numpy boolean array contain?
✗ Incorrect
Boolean arrays contain only True or False values.
Which numpy function creates a boolean array filled with False?
✗ Incorrect
numpy.zeros(shape, dtype=bool) creates a boolean array filled with False.What does the expression
arr > 10 return?✗ Incorrect
Applying a condition returns a boolean array indicating which elements satisfy it.
How can boolean arrays be used in data filtering?
✗ Incorrect
Boolean arrays help select elements that meet specific conditions.
What is the dtype of a boolean numpy array?
✗ Incorrect
Boolean arrays have dtype 'bool' in numpy.
Explain how to create a boolean array from a numpy array using a condition. Give a simple example.
Think about how you check if numbers are bigger than a value.
You got /3 concepts.
Describe two ways to create boolean arrays in numpy and when you might use each.
One way uses existing data, the other creates new arrays filled with True or False.
You got /3 concepts.