np.prod() for product in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the product of all elements in the array.

NumPy

import numpy as np
arr = np.array([1, 2, 3, 4])
result = np.[1](arr)
print(result)

Drag options to blanks, or click blank then click option'

Aprod

Bsum

Cmean

Dmax

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.sum() instead of np.prod()

Using np.mean() which calculates average

Using np.max() which finds the largest element

The np.prod() function calculates the product of all elements in the array.

2fill in blank

medium

Complete the code to calculate the product of elements along axis 0.

NumPy

import numpy as np
arr = np.array([[1, 2], [3, 4]])
result = np.prod(arr, axis=[1])
print(result)

Drag options to blanks, or click blank then click option'

A2

B1

C0

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Using axis=1 which calculates product across columns

Using axis=2 which is out of bounds for this array

Using negative axis incorrectly

Axis 0 means calculating the product down the rows (column-wise).

3fill in blank

hard

Fix the error in the code to correctly calculate the product of array elements.

NumPy

import numpy as np
arr = [1, 2, 3, 4]
result = np.prod([1])
print(result)

Drag options to blanks, or click blank then click option'

Anp.array(arr)

Barr

Clist(arr)

Darr.tolist()

Attempts:

3 left

💡 Hint

Common Mistakes

Passing a plain list without conversion

Using list() on an already list object

Using tolist() which converts numpy array to list

np.prod() requires a numpy array or array-like. Converting list to numpy array ensures correct operation.

4fill in blank

hard

Complete the code to reshape the array and compute the product along axis 1.

NumPy

import numpy as np
arr = np.array([1,2,3,4,5,6])
reshaped = arr.[1]((2, 3))
result = np.[2](reshaped, axis=1)
print(result)

Drag options to blanks, or click blank then click option'

Areshape

Bprod

Csum

Dmean

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.sum() instead of np.prod()

Forgetting to call reshape()

Using axis=0 instead of axis=1

arr.reshape((2, 3)) reshapes to 2x3 array [[1,2,3],[4,5,6]], np.prod(..., axis=1) computes product per row: [6, 120].

5fill in blank

hard

Fill all three blanks to compute the geometric mean of the array.

NumPy

import numpy as np
arr = np.array([2, 4, 8])
geo_mean = (np.[1](arr)) ** ([2] / [3])
print(geo_mean)

Drag options to blanks, or click blank then click option'

Aprod

B1

Clen(arr)

Dsum(arr)

Attempts:

3 left

💡 Hint

Common Mistakes

Using np.sum(arr) instead of product

Computing arithmetic mean with np.mean()

Using wrong exponent like / np.sum(arr)

Geometric mean = (product of elements)^1/n, where n is the number of elements: (np.prod(arr)) ** (1 / len(arr)) = 4.0.