np.min() and np.max() in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does np.min() do in numpy?

np.min() finds the smallest value in an array or along a specified axis.

beginner

What is the purpose of np.max()?

np.max() returns the largest value in an array or along a specified axis.

intermediate

How do you find the minimum value in each column of a 2D numpy array?

Use np.min(array, axis=0). Axis 0 means down the rows, so it finds min per column.

intermediate

How to find the maximum value in each row of a 2D numpy array?

Use np.max(array, axis=1). Axis 1 means across columns, so it finds max per row.

advanced

What happens if you call np.min() or np.max() on an empty array?

It raises a ValueError because there is no data to find min or max.

What does np.min() return when used on a numpy array?

A The average value of the array

B The largest value in the array

C The smallest value in the array

D The sum of all values in the array

np.min() finds the smallest value in the array.

How do you find the maximum value in each row of a 2D numpy array named arr?

A <code>np.max(arr, axis=1)</code>

B <code>np.min(arr, axis=1)</code>

C <code>np.max(arr, axis=0)</code>

D <code>np.min(arr, axis=0)</code>

Axis 1 means across columns, so np.max(arr, axis=1) finds max per row.

What will np.min() do if the array is empty?

A Return 0

B Raise a ValueError

C Return infinity

D Return None

Calling np.min() on an empty array raises a ValueError.

Which axis should you use with np.min() to find the minimum value in each column of a 2D array?

A axis=0

B axis=1

C axis=2

D axis=None

Axis 0 means down the rows, so it finds min per column.

If you want the overall maximum value in a numpy array, which function call is correct?

A <code>array.min(axis=0)</code>

B <code>np.min(array)</code>

C <code>array.max(axis=1)</code>

D <code>np.max(array)</code>

np.max(array) returns the largest value in the whole array.

Explain how to use np.min() and np.max() to find minimum and maximum values along different axes in a 2D numpy array.

Think about rows and columns as directions to find min or max.

What error occurs if you try to find the minimum or maximum of an empty numpy array using np.min() or np.max()? Why?

Consider what happens when there is nothing to compare.