Recall & Review
beginner
What is a Boolean type in NumPy?
A Boolean type in NumPy represents values that can be either True or False. It is used to store truth values and is useful for filtering and conditional operations.
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beginner
How do you create a NumPy array of Boolean values?
You can create a Boolean NumPy array by passing a list of True and False values to np.array(), for example: np.array([True, False, True]).
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beginner
What is the data type name for Boolean arrays in NumPy?
The data type name for Boolean arrays in NumPy is 'bool' or 'bool_' which stores True or False values efficiently.
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intermediate
How can Boolean arrays be used in NumPy?
Boolean arrays can be used to filter data, perform element-wise logical operations, and control flow in data processing tasks.
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intermediate
What happens when you perform a logical operation between two Boolean NumPy arrays?
Performing logical operations like AND (&), OR (|), and NOT (~) between Boolean arrays results in a new Boolean array with element-wise operation results.
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Which NumPy data type stores Boolean values?
✗ Incorrect
The 'bool' data type in NumPy stores Boolean values True or False.
What is the output type when you compare two NumPy arrays element-wise?
✗ Incorrect
Element-wise comparison returns a Boolean array indicating True or False for each comparison.
Which operator is used for element-wise logical AND in NumPy Boolean arrays?
✗ Incorrect
The '&' operator performs element-wise logical AND on Boolean NumPy arrays.
How do you create a Boolean array from a condition in NumPy?
✗ Incorrect
A condition like arr > 5 returns a Boolean array where each element shows if the condition is True or False.
What does the ~ operator do on a Boolean NumPy array?
✗ Incorrect
The '~' operator performs element-wise logical NOT, flipping True to False and vice versa.
Explain what a Boolean type is in NumPy and how it can be used in data analysis.
Think about how True/False values help select or filter data.
You got /4 concepts.
Describe how to create and manipulate Boolean arrays in NumPy with examples.
Consider how conditions and logical operators work on arrays.
You got /4 concepts.