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DSA Pythonprogramming~10 mins

Counting Sort Algorithm in DSA Python - Interactive Practice

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to initialize the count array with zeros for counting sort.

DSA Python
count = [0] * [1]
Drag options to blanks, or click blank then click option'
Amax(arr) + 1
Blen(arr)
Csum(arr)
Dmin(arr)
Attempts:
3 left
💡 Hint
Common Mistakes
Using length of array instead of max value for count array size.
2fill in blank
medium

Complete the code to count the occurrences of each element in the input array.

DSA Python
for num in arr:
    count[[1]] += 1
Drag options to blanks, or click blank then click option'
Aarr
Bi
Cnum
Dcount
Attempts:
3 left
💡 Hint
Common Mistakes
Using the whole array or wrong variable as index.
3fill in blank
hard

Fix the error in updating the count array to store cumulative counts.

DSA Python
for i in range(1, len(count)):
    count[i] = count[i] [1] count[i - 1]
Drag options to blanks, or click blank then click option'
A//
B-
C*
D+
Attempts:
3 left
💡 Hint
Common Mistakes
Using subtraction or multiplication instead of addition.
4fill in blank
hard

Fill both blanks to place elements in the output array in correct order.

DSA Python
for num in reversed(arr):
    output[count[[1]] - 1] = num
    count[[2]] -= 1
Drag options to blanks, or click blank then click option'
Anum
Bcount
Doutput
Attempts:
3 left
💡 Hint
Common Mistakes
Using wrong variable names for indexing count array.
5fill in blank
hard

Fill all three blanks to copy the sorted elements back to the original array.

DSA Python
for i in range(len(arr)):
    arr[[1]] = output[[2]]
    [3]
Drag options to blanks, or click blank then click option'
Ai
Cpass
Di += 1
Attempts:
3 left
💡 Hint
Common Mistakes
Trying to increment 'i' manually inside the loop.

Practice

(1/5)
1. What is the main idea behind the Counting Sort algorithm?
easy
A. Swapping adjacent elements if they are in wrong order
B. Comparing each element with every other element to sort
C. Dividing the list into halves and sorting recursively
D. Counting the occurrences of each element and using that to place elements in order

Solution

  1. Step 1: Understand Counting Sort principle

    Counting Sort counts how many times each value appears in the list.
  2. Step 2: Use counts to place elements

    It then uses these counts to place elements directly in the sorted order without comparisons.
  3. Final Answer:

    Counting the occurrences of each element and using that to place elements in order -> Option D
  4. Quick Check:

    Counting occurrences = A [OK]
Hint: Counting Sort uses counts, not comparisons, to sort [OK]
Common Mistakes:
  • Thinking Counting Sort compares elements
  • Confusing Counting Sort with comparison-based sorts
  • Assuming Counting Sort works on all data types
2. Which of the following is the correct way to initialize the count array for Counting Sort in Python for input values ranging from 0 to 5?
easy
A. count = [0] * 6
B. count = [0] * 5
C. count = [null] * 6
D. count = []

Solution

  1. Step 1: Determine count array size

    For values 0 to 5 inclusive, we need 6 slots (0,1,2,3,4,5).
  2. Step 2: Initialize count array with zeros

    Using [0] * 6 creates a list of six zeros to count occurrences.
  3. Final Answer:

    count = [0] * 6 -> Option A
  4. Quick Check:

    Length 6 with zeros = D [OK]
Hint: Count array size = max value + 1 [OK]
Common Mistakes:
  • Using wrong size for count array
  • Initializing with null instead of 0
  • Leaving count array empty
3. What will be the output of the following Python code using Counting Sort on the list [4, 2, 2, 8, 3, 3, 1]?
def counting_sort(arr):
    max_val = max(arr)
    count = [0] * (max_val + 1)
    for num in arr:
        count[num] += 1
    sorted_arr = []
    for i in range(len(count)):
        sorted_arr.extend([i] * count[i])
    return sorted_arr

print(counting_sort([4, 2, 2, 8, 3, 3, 1]))
medium
A. [1, 2, 2, 3, 3, 4, 8]
B. [8, 4, 3, 3, 2, 2, 1]
C. [1, 2, 3, 4, 8]
D. [0, 1, 2, 2, 3, 3, 4, 8]

Solution

  1. Step 1: Count occurrences of each number

    Count array for max_val=8: counts for 1=1, 2=2, 3=2, 4=1, 8=1, others=0.
  2. Step 2: Build sorted list using counts

    Extend sorted_arr with each number repeated by its count: [1, 2, 2, 3, 3, 4, 8].
  3. Final Answer:

    [1, 2, 2, 3, 3, 4, 8] -> Option A
  4. Quick Check:

    Sorted list matches counting sort output = B [OK]
Hint: Counting Sort output is sorted list with duplicates in order [OK]
Common Mistakes:
  • Forgetting to repeat elements by their count
  • Returning unsorted or reversed list
  • Including zeros for missing elements
4. The following code attempts to implement Counting Sort but has a bug. What is the error?
def counting_sort_bug(arr):
    max_val = max(arr)
    count = [0] * max_val
    for num in arr:
        count[num] += 1
    sorted_arr = []
    for i in range(len(count)):
        sorted_arr.extend([i] * count[i])
    return sorted_arr

print(counting_sort_bug([3, 1, 2, 3]))
medium
A. Count array initialized with zeros incorrectly
B. Loop to build sorted_arr uses wrong range
C. Count array size is too small, missing last element count
D. Function does not return anything

Solution

  1. Step 1: Check count array size

    Count array size is max_val, but should be max_val + 1 to include max element index.
  2. Step 2: Understand impact on counting

    Missing last index causes error when counting max element (3), leading to IndexError or wrong counts.
  3. Final Answer:

    Count array size is too small, missing last element count -> Option C
  4. Quick Check:

    Count array size = max_val + 1 [OK]
Hint: Count array size must be max value + 1 [OK]
Common Mistakes:
  • Using max_val instead of max_val + 1 for count array size
  • Ignoring IndexError from out-of-range access
  • Not initializing count array properly
5. You have a list of exam scores ranging from 0 to 100, but some scores are missing. How can you modify Counting Sort to efficiently sort this list and also find how many students scored exactly 75?
hard
A. Use a comparison sort and count 75s during sorting
B. Use Counting Sort normally, then check count[75] for number of students scoring 75
C. Sort with Counting Sort and then scan sorted list to count 75s
D. Use Counting Sort but ignore counts for missing scores

Solution

  1. Step 1: Apply Counting Sort on scores 0-100

    Create count array of size 101, count occurrences of each score.
  2. Step 2: Use count array to find number of 75 scores

    Count at index 75 directly gives number of students scoring 75 without scanning sorted list.
  3. Final Answer:

    Use Counting Sort normally, then check count[75] for number of students scoring 75 -> Option B
  4. Quick Check:

    Counting array index = score count, access directly [OK]
Hint: Counting array index = score count, access directly [OK]
Common Mistakes:
  • Scanning sorted list instead of using count array
  • Ignoring missing scores in count array
  • Using slower comparison sorts unnecessarily
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