NumPy array vs Python list performance - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the NumPy library with its common alias.

NumPy

import [1] as np

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

Anumpy

Bnp

Cnum

Dnpy

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'np' instead of 'numpy' in the import statement.

Using incorrect library names like 'num' or 'npy'.

NumPy is imported using the name numpy and commonly aliased as np.

2fill in blank

medium

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

NumPy

arr = np.[1]([1, 2, 3, 4, 5])

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

Atolist

Barray

Casarray

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'list' which is a Python type, not a NumPy function.

Using 'tolist' which converts arrays to lists, not the other way.

The np.array() function creates a NumPy array from a Python list.

3fill in blank

hard

Fix the error in the code to measure the time taken to sum elements in a Python list.

NumPy

import time
lst = list(range(1000000))
start = time.[1]()
total = sum(lst)
end = time.time()
print(end - start)

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

Aclock

Bsleep

Ctime

Dperf_counter

Attempts:

3 left

💡 Hint

Common Mistakes

Using time.clock() which is deprecated.

Using time.sleep() which pauses execution.

The time.time() function returns the current time in seconds, suitable for measuring elapsed time.

4fill in blank

hard

Fill both blanks to create a NumPy array and measure the time taken to sum its elements.

NumPy

import time
arr = np.[1](range(1000000))
start = time.[2]()
total = np.sum(arr)
end = time.perf_counter()
print(end - start)

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

Aarray

Btime

Cperf_counter

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using list instead of array for NumPy arrays.

Using time.time() instead of time.perf_counter() for better precision.

Use np.array() to create the array and time.perf_counter() for precise timing.

5fill in blank

hard

Fill all three blanks to create a Python list, a NumPy array, and measure their sum times for comparison.

NumPy

import time
lst = list(range(1000000))
arr = np.[1](lst)
start_lst = time.[2]()
sum_lst = sum(lst)
end_lst = time.time()
start_arr = time.[3]()
sum_arr = np.sum(arr)
end_arr = time.perf_counter()
print('List sum time:', end_lst - start_lst)
print('Array sum time:', end_arr - start_arr)

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

Aarray

Btime

Cperf_counter

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using list instead of array for NumPy array creation.

Using the same timing function for both measurements.

Create the NumPy array with np.array(), use time.time() for list timing, and time.perf_counter() for array timing for better precision.