When to use NumPy over Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a NumPy array from a list.

Pandas

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

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

Aarray

BDataFrame

CSeries

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using pandas functions like DataFrame or Series instead of NumPy array.

Trying to use list() which is a Python built-in, not NumPy.

Use np.array() to create a NumPy array from a list.

2fill in blank

medium

Complete the code to calculate the mean of a NumPy array.

Pandas

import numpy as np
arr = np.array([10, 20, 30, 40])
mean_value = arr.[1]()
print(mean_value)

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

Amean

Bmode

Cmedian

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum() which adds all elements but does not calculate average.

Using median() which finds the middle value, not the average.

Use mean() method on a NumPy array to calculate the average value.

3fill in blank

hard

Fix the error in the code to create a NumPy array of zeros with length 5.

Pandas

import numpy as np
zeros = np.[1](5)
print(zeros)

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

Azeroes

Bones

Cempty

Dzeros

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'zeroes' which is a common misspelling.

Using 'empty' which creates an uninitialized array, not zeros.

The correct function to create an array of zeros is np.zeros().

4fill in blank

hard

Fill both blanks to create a NumPy array and calculate its standard deviation.

Pandas

import numpy as np
arr = np.[1]([2, 4, 6, 8])
std_dev = arr.[2]()
print(std_dev)

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

Aarray

Bmean

Cstd

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using mean() instead of std() for standard deviation.

Using sum() which adds elements but does not calculate deviation.

Use np.array() to create the array and std() to find standard deviation.

5fill in blank

hard

Fill all three blanks to create a NumPy array, filter values greater than 3, and calculate their sum.

Pandas

import numpy as np
arr = np.[1]([1, 2, 3, 4, 5])
filtered = arr[arr [2] 3]
result = filtered.[3]()
print(result)

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

Aarray

B>

Csum

Dmean

Attempts:

3 left

💡 Hint

Common Mistakes

Using < instead of > for filtering.

Using mean() instead of sum() for the final calculation.

Create the array with np.array(), filter with >, and sum with sum().