Counting with boolean arrays in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does a boolean array represent in numpy?

A boolean array in numpy contains True or False values, often used to mark conditions or filters on data.

beginner

How can you count the number of True values in a numpy boolean array?

You can use the np.sum() function on the boolean array because True is treated as 1 and False as 0.

intermediate

Why does np.sum() work for counting True values in a boolean array?

Because in numpy, True is equivalent to 1 and False is equivalent to 0, so summing counts how many True values exist.

intermediate

What is the difference between np.count_nonzero() and np.sum() when used on boolean arrays?

np.count_nonzero() counts all non-zero (True) elements, similar to np.sum() on boolean arrays. Both give the count of True values.

beginner

How can boolean arrays help in real-life data analysis?

Boolean arrays help filter data, count conditions met, and quickly summarize information like how many entries meet a rule.

What does np.sum() return when applied to a boolean numpy array?

A The count of True values

B The count of False values

C The sum of True and False as strings

D An error because sum can't be used on booleans

np.sum() treats True as 1 and False as 0, so it returns the count of True values.

Which numpy function can also count True values in a boolean array besides np.sum()?

A np.unique()

B np.count_nonzero()

C np.min()

D np.mean()

np.count_nonzero() counts all non-zero (True) elements in the array.

In numpy, what numeric value does False correspond to when used in calculations?

A -1

B 1

C 0

D None

False is treated as 0 in numpy numeric operations.

If you have a boolean array [True, False, True], what does np.sum() return?

A 3

B 0

C 1

D 2

There are two True values, so the sum is 2.

Why are boolean arrays useful in data science?

A They help filter and count data based on conditions

B They store large text data efficiently

C They replace all numeric data

D They slow down calculations

Boolean arrays let you quickly find and count data entries that meet specific conditions.

Explain how you can count how many values in a numpy array meet a certain condition using boolean arrays.

Think about how True and False behave as numbers in numpy.

Describe two numpy functions that can count True values in a boolean array and how they work.

Both functions treat True as a positive count.