Prefix Sum Array in DSA Python - Time & Space Complexity

Time Complexity: Prefix Sum Array

O(n)

Understanding Time Complexity

We want to understand how fast we can build and use a prefix sum array.

How does the time needed grow as the input array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

def prefix_sum(arr):
    n = len(arr)
    prefix = [0] * n
    prefix[0] = arr[0]
    for i in range(1, n):
        prefix[i] = prefix[i-1] + arr[i]
    return prefix

# Example usage:
# arr = [1, 2, 3, 4]
# prefix_sum(arr) returns [1, 3, 6, 10]

This code creates a new array where each element is the sum of all elements up to that position in the original array.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: A single for-loop that adds elements one by one.
• How many times: The loop runs once for each element after the first, so (n - 1) times.

How Execution Grows With Input

As the input array gets bigger, the number of additions grows roughly the same as the size of the array.

Input Size (n)	Approx. Operations
10	9 additions
100	99 additions
1000	999 additions

Pattern observation: The operations increase linearly as the input size increases.

Final Time Complexity

Time Complexity: O(n)

This means the time to build the prefix sum array grows in direct proportion to the size of the input array.

Common Mistake

[X] Wrong: "Since we add numbers repeatedly, the time must be quadratic O(n²)."

[OK] Correct: Each addition uses the previous sum, so we only do one addition per element, not a sum over all previous elements each time.

Interview Connect

Knowing how prefix sums work and their time cost helps you solve many problems efficiently, like range sums or frequency counts.

Self-Check

"What if we wanted to build a 2D prefix sum array for a matrix? How would the time complexity change?"

Practice

1. What does a prefix sum array represent for a given array arr?

easy

A. An array where each element is the product of all elements from the start up to that index in arr.

B. An array where each element is the maximum value found in arr up to that index.

C. An array where each element is the difference between consecutive elements in arr.

D. An array where each element is the sum of all elements from the start up to that index in arr.

Solution

1. Step 1: Understand prefix sum definition

   A prefix sum array stores sums of elements from the start of the original array up to each index.

2. Step 2: Compare options with definition

   Only An array where each element is the sum of all elements from the start up to that index in arr. correctly describes this sum accumulation; others describe different operations.

3. Final Answer:

   An array where each element is the sum of all elements from the start up to that index in arr. -> Option D

4. Quick Check:

   Prefix sum = cumulative sum [OK]

Hint: Prefix sum means adding elements from start to current index [OK]

Common Mistakes:

• Confusing prefix sum with product or max operations
• Thinking prefix sum stores differences
• Assuming prefix sum stores original array values

2. Which of the following Python code snippets correctly initializes a prefix sum array prefix for an input list arr?

easy

A. prefix = [arr[0]]
for i in range(1, len(arr)):
prefix.append(arr[i] - prefix[i-1])

B. prefix = []
for i in range(len(arr)):
prefix.append(arr[i] + arr[i-1])

C. prefix = [arr[0]]
for i in range(1, len(arr)):
prefix.append(prefix[i-1] + arr[i])

D. prefix = [0] * len(arr)
for i in range(len(arr)):
prefix[i] = arr[i] * prefix[i-1]

Solution

1. Step 1: Analyze code for prefix sum logic

   prefix = [arr[0]] for i in range(1, len(arr)): prefix.append(prefix[i-1] + arr[i]) starts prefix with first element and adds current element to previous prefix sum correctly.

2. Step 2: Check other options for errors

   prefix = [] for i in range(len(arr)): prefix.append(arr[i] + arr[i-1]) adds current and previous array elements incorrectly; C multiplies instead of sums; A subtracts instead of sums.

3. Final Answer:

   prefix = [arr[0]]\nfor i in range(1, len(arr)):\n prefix.append(prefix[i-1] + arr[i]) -> Option C

4. Quick Check:

   Prefix sum uses cumulative addition [OK]

Hint: Start prefix with first element, then add previous prefix sum [OK]

Common Mistakes:

• Using multiplication instead of addition
• Adding wrong elements or indices
• Initializing prefix array incorrectly

3. What is the output of the following code?

arr = [3, 1, 4, 1, 5]
prefix = [arr[0]]
for i in range(1, len(arr)):
    prefix.append(prefix[i-1] + arr[i])
print(prefix)

medium

A. [3, 4, 8, 9, 14]

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

C. [3, 3, 7, 8, 13]

D. [0, 3, 4, 8, 9]

Solution

1. Step 1: Calculate prefix sums step-by-step

   Start with prefix = [3]. Then add 1: 3+1=4, add 4: 4+4=8, add 1: 8+1=9, add 5: 9+5=14.

2. Step 2: Form the final prefix array

   prefix = [3, 4, 8, 9, 14]

3. Final Answer:

   [3, 4, 8, 9, 14] -> Option A

4. Quick Check:

   Sum accumulates correctly [OK]

Hint: Add current element to last prefix sum [OK]

Common Mistakes:

• Confusing prefix array with original array
• Off-by-one errors in indexing
• Incorrect initial prefix value

4. Find the error in this prefix sum code and choose the corrected version:

arr = [2, 4, 6]
prefix = [0]
for i in range(len(arr)):
    prefix.append(prefix[i] + arr[i])
print(prefix)

medium

A. Change prefix = [0] to prefix = [arr[0]] and loop from 1 to len(arr)-1.

B. Change prefix.append(prefix[i] + arr[i]) to prefix.append(prefix[i-1] + arr[i]).

C. Remove the initial zero from prefix and start loop from 0 as is.

D. No error; code works correctly and prints prefix sums.

Solution

1. Step 1: Identify initialization and loop issues

   Initializing prefix with [0] and looping from 0 adds an extra leading zero. Tracing: i=0 append(0+2)=2 -> [0,2]; i=1 append(2+4)=6 -> [0,2,6]; i=2 append(6+6)=12 -> [0,2,6,12]. This produces prefix sums of length n+1 with prefix[0]=0, whereas standard is length n starting from arr[0].

2. Step 2: Correct initialization and loop range

   Start prefix with first element arr[0], then loop from index 1 to end to add sums correctly.

3. Final Answer:

   Change prefix = [0] to prefix = [arr[0]] and loop from 1 to len(arr)-1. -> Option A

4. Quick Check:

   Proper start and loop fix prefix sums [OK]

Hint: Initialize prefix with first element, loop from second element [OK]

Common Mistakes:

• Starting prefix with zero instead of first element
• Looping from zero causing off-by-one errors
• Using wrong prefix index inside loop

5. Given an array arr of length n, how can you use a prefix sum array to find the sum of elements between indices l and r (inclusive) efficiently?

hard

A. Calculate sum as prefix[r] * prefix[l].

B. Calculate sum as prefix[r] - prefix[l-1] if l > 0, else prefix[r].

C. Calculate sum as prefix[r] + prefix[l] always.

D. Calculate sum by looping from l to r and adding elements.

Solution

1. Step 1: Understand prefix sum usage for range sums

   Prefix sum at index r stores sum from start to r. To get sum from l to r, subtract sum from start to l-1.

2. Step 2: Handle edge case when l is zero

   If l is zero, sum is prefix[r] directly since no subtraction needed.

3. Final Answer:

   Calculate sum as prefix[r] - prefix[l-1] if l > 0, else prefix[r]. -> Option B

4. Quick Check:

   Range sum = prefix[r] - prefix[l-1] [OK]

Hint: Subtract prefix before l from prefix at r for range sum [OK]

Common Mistakes:

• Adding prefix sums instead of subtracting
• Ignoring edge case when l = 0
• Using multiplication or looping unnecessarily