Why Sorting Matters and How It Unlocks Other Algorithms in DSA Python - Test Your Knowledge

Practice - 5 Tasks

1fill in blank

easy

Complete the code to sort the list in ascending order.

DSA Python

numbers = [5, 3, 8, 1, 2]
numbers.[1]()
print(numbers)

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

Apop

Bappend

Creverse

Dsort

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'append' instead of 'sort' adds elements instead of sorting.

Using 'pop' removes elements, not sorting.

Using 'reverse' flips the list but does not sort it.

The sort() method arranges the list elements in ascending order.

2fill in blank

medium

Complete the code to find the middle element after sorting the list.

DSA Python

data = [7, 2, 9, 4, 5]
data.sort()
middle = data[[1]]
print(middle)

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

Alen(data) + 2

Blen(data) // 2

Clen(data) * 2

Dlen(data) - 1

Attempts:

3 left

💡 Hint

Common Mistakes

Using length plus 2 goes out of range.

Multiplying length by 2 is too large for an index.

Using length minus 1 gives the last element, not the middle.

Using len(data) // 2 gives the middle index for an odd-length sorted list.

3fill in blank

hard

Fix the error in the code to merge two sorted lists correctly.

DSA Python

list1 = [1, 3, 5]
list2 = [2, 4, 6]
merged = []
i = j = 0
while i < len(list1) and j < len(list2):
    if list1[i] < list2[[1]]:
        merged.append(list1[i])
        i += 1
    else:
        merged.append(list2[j])
        j += 1
merged.extend(list1[i:])
merged.extend(list2[j:])
print(merged)

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

Alen(list2)

Bi

Cj

Dlen(list1)

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'i' for both lists causes wrong comparisons.

Using list lengths instead of indices causes errors.

The comparison should be between list1[i] and list2[j] to merge correctly.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 letters.

DSA Python

words = ['apple', 'bat', 'carrot', 'dog', 'elephant']
lengths = {word: [1] for word in words if len(word) [2] 3}
print(lengths)

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

Alen(word)

Bword

C>

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as value instead of its length.

Using '<=' instead of '>' filters the wrong words.

The dictionary comprehension uses len(word) as value and filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words longer than 4 letters.

DSA Python

words = ['tree', 'house', 'river', 'sky', 'mountain']
result = { [1]: [2] for word in words if len(word) [3] 4 }
print(result)

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

Aword.upper()

Blen(word)

C>

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using lowercase instead of uppercase for keys.

Using '<' instead of '>' filters the wrong words.

Using the word itself as value instead of length.

The dictionary comprehension uses uppercase words as keys, their lengths as values, and filters words longer than 4 letters.

Practice

1. Why is sorting an important step before applying many algorithms in data processing?

easy

A. Because sorting compresses the data to save space

B. Because sorting removes duplicate data automatically

C. Because sorting encrypts the data for security

D. Because sorting organizes data to make searching and comparisons faster

Solution

1. Step 1: Understand the role of sorting

   Sorting arranges data in order, which helps algorithms like searching and merging work efficiently.

2. Step 2: Recognize benefits of sorted data

   Sorted data allows faster lookups and simpler logic, reducing time complexity.

3. Final Answer:

   Because sorting organizes data to make searching and comparisons faster -> Option D

4. Quick Check:

   Sorting improves algorithm speed = Because sorting organizes data to make searching and comparisons faster [OK]

Hint: Sorting arranges data to speed up other algorithms [OK]

Common Mistakes:

• Thinking sorting removes duplicates
• Confusing sorting with encryption
• Assuming sorting compresses data

2. Which of the following Python code snippets correctly sorts the list nums = [4, 2, 9, 1] in ascending order?

easy

A. nums.sort()

B. sort(nums)

C. nums.sorted()

D. nums.order()

Solution

1. Step 1: Recall Python list sorting method

   Python lists have a built-in method called sort() that sorts the list in place.

2. Step 2: Check each option

   nums.sort() is correct. The other options use invalid syntax or non-existent methods.

3. Final Answer:

   nums.sort() -> Option A

4. Quick Check:

   Use list.sort() to sort in place = nums.sort() [OK]

Hint: Use list.sort() to sort lists in Python [OK]

Common Mistakes:

• Using sort(nums) which is not a function
• Trying nums.sorted() which does not exist
• Using nums.order() which is invalid

3. What is the output of the following Python code?

nums = [3, 1, 4, 1, 5]
nums.sort()
print(nums)

medium

A. [3, 1, 4, 1, 5]

B. [1, 1, 3, 4, 5]

C. [5, 4, 3, 1, 1]

D. Error: sort() is not a function

Solution

1. Step 1: Understand what nums.sort() does

   The sort() method sorts the list in ascending order.

2. Step 2: Apply sorting to the list

   Sorting [3, 1, 4, 1, 5] results in [1, 1, 3, 4, 5].

3. Final Answer:

   [1, 1, 3, 4, 5] -> Option B

4. Quick Check:

   Sorted list output = [1, 1, 3, 4, 5] [OK]

Hint: sort() arranges list elements in ascending order by default [OK]

Common Mistakes:

• Expecting original list order after sort()
• Thinking sort() returns a new list
• Confusing sort() with sorted() function

4. The following code is intended to sort a list and print it, but nums remains unsorted. What is the problem?

nums = [7, 3, 9]
sorted(nums)
print(nums)

medium

A. sorted() does not sort the list in place, so nums remains unsorted

B. sorted() is not a valid Python function

C. print(nums) should be print(sorted(nums))

D. nums.sort() should be used instead of sorted()

Solution

1. Step 1: Understand difference between sorted() and sort()

   sorted() returns a new sorted list but does not change the original list.

2. Step 2: Analyze code behavior

   The code calls sorted(nums) but does not assign or print its result, so nums stays unsorted.

3. Final Answer:

   sorted() does not sort the list in place, so nums remains unsorted -> Option A

4. Quick Check:

   sorted() returns new list, original unchanged = sorted() does not sort the list in place, so nums remains unsorted [OK]

Hint: sorted() returns new list; sort() changes list in place [OK]

Common Mistakes:

• Assuming sorted() changes original list
• Thinking sorted() is invalid function
• Ignoring return value of sorted()

5. You have two sorted lists: a = [1, 3, 5] and b = [2, 4, 6]. Which approach best merges them into a single sorted list efficiently?

hard

A. Sort each list again before merging

B. Concatenate both lists and then sort the combined list

C. Use two pointers to compare elements and build a new sorted list

D. Reverse both lists and then merge

Solution

1. Step 1: Understand merging of sorted lists

   Since both lists are already sorted, merging by comparing elements with two pointers is efficient.

2. Step 2: Compare options for merging

   Concatenate both lists and then sort the combined list sorts combined list, which is less efficient (O(n log n)). Use two pointers to compare elements and build a new sorted list merges in O(n) time by comparing elements step-by-step.

3. Final Answer:

   Use two pointers to compare elements and build a new sorted list -> Option C

4. Quick Check:

   Two-pointer merge is efficient for sorted lists = Use two pointers to compare elements and build a new sorted list [OK]

Hint: Merge sorted lists with two pointers for best efficiency [OK]

Common Mistakes:

• Sorting after concatenation wastes time
• Sorting each list again is unnecessary
• Reversing lists breaks sorted order