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DSA Pythonprogramming~5 mins

Non Overlapping Intervals Minimum Removal in DSA Python - Time & Space Complexity

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Time Complexity: Non Overlapping Intervals Minimum Removal
O(n log n)
Understanding Time Complexity

We want to find out how fast the algorithm runs when removing intervals to avoid overlaps.

How does the time needed grow as the number of intervals increases?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.


def eraseOverlapIntervals(intervals):
    intervals.sort(key=lambda x: x[1])
    count = 0
    end = float('-inf')
    for interval in intervals:
        if interval[0] >= end:
            end = interval[1]
        else:
            count += 1
    return count
    

This code sorts intervals by their end time and counts how many intervals must be removed to avoid overlaps.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

  • Primary operation: Sorting the intervals and then looping through them once.
  • How many times: Sorting takes multiple comparisons depending on number of intervals; the loop runs once for each interval.
How Execution Grows With Input

Sorting takes more time as intervals increase, and the loop grows linearly.

Input Size (n)Approx. Operations
10About 30 to 40 operations
100About 700 to 800 operations
1000About 10,000 to 12,000 operations

Pattern observation: Sorting grows faster than looping, roughly n log n, while the loop grows linearly.

Final Time Complexity

Time Complexity: O(n log n)

This means the time needed grows a bit faster than the number of intervals because of sorting, but the main loop adds only a simple pass.

Common Mistake

[X] Wrong: "The loop alone decides the time complexity, so it must be O(n)."

[OK] Correct: Sorting the intervals before looping takes more time, and it dominates the total time, making it O(n log n).

Interview Connect

Understanding how sorting affects time helps you explain your solution clearly and shows you know how to analyze real problems efficiently.

Self-Check

"What if the intervals were already sorted by end time? How would the time complexity change?"

Practice

(1/5)
1. What is the main goal of the Non Overlapping Intervals Minimum Removal problem?
easy
A. To find the minimum number of intervals to remove so that the rest do not overlap
B. To find the maximum number of overlapping intervals
C. To sort intervals by their start time
D. To merge all overlapping intervals into one

Solution

  1. Step 1: Understand the problem goal

    The problem asks to remove the fewest intervals so that no two intervals overlap.
  2. Step 2: Differentiate from related problems

    Unlike merging intervals or counting overlaps, here we minimize removals to avoid overlaps.
  3. Final Answer:

    To find the minimum number of intervals to remove so that the rest do not overlap -> Option A
  4. Quick Check:

    Minimum removals = non-overlapping intervals [OK]
Hint: Focus on removing intervals to avoid overlaps, not merging [OK]
Common Mistakes:
  • Confusing with merging intervals problem
  • Trying to maximize overlaps instead of minimizing removals
  • Sorting intervals incorrectly
2. Which of the following Python code snippets correctly sorts a list of intervals by their end time?
easy
A. intervals.sort(key=lambda x: x[0])
B. intervals.sort(reverse=True)
C. intervals.sort(key=lambda x: x[1])
D. intervals.sort(key=lambda x: x[1], reverse=True)

Solution

  1. Step 1: Identify sorting by end time

    Sorting by end time means using the second element of each interval, which is index 1.
  2. Step 2: Check the correct syntax

    Using intervals.sort(key=lambda x: x[1]) sorts intervals ascending by end time.
  3. Final Answer:

    intervals.sort(key=lambda x: x[1]) -> Option C
  4. Quick Check:

    Sort by end time = key=lambda x: x[1] [OK]
Hint: Sort intervals by end time using key=lambda x: x[1] [OK]
Common Mistakes:
  • Sorting by start time instead of end time
  • Using reverse=True when not needed
  • Incorrect lambda syntax
3. What is the output of the following code?
intervals = [[1,3],[2,4],[3,5]]
intervals.sort(key=lambda x: x[1])
count = 0
end = float('-inf')
for interval in intervals:
    if interval[0] >= end:
        end = interval[1]
    else:
        count += 1
print(count)
medium
A. 2
B. 1
C. 0
D. 3

Solution

  1. Step 1: Sort intervals by end time

    Sorted intervals: [[1,3],[2,4],[3,5]] (already sorted by end time)
  2. Step 2: Iterate and count overlaps

    Start with end = -inf
    Interval [1,3]: 1 >= -inf true, update end=3
    Interval [2,4]: 2 >= 3 false, count=1
    Interval [3,5]: 3 >= 3 true, update end=5
  3. Final Answer:

    1 -> Option B
  4. Quick Check:

    One interval removed to avoid overlap [OK]
Hint: Count intervals that start before current end to find removals [OK]
Common Mistakes:
  • Not updating end correctly
  • Counting non-overlapping intervals instead of removals
  • Sorting by start time instead of end time
4. Find the error in this code snippet that tries to solve the minimum removal of overlapping intervals:
def eraseOverlapIntervals(intervals):
    intervals.sort(key=lambda x: x[0])
    count = 0
    end = float('-inf')
    for interval in intervals:
        if interval[0] >= end:
            end = interval[1]
        else:
            count += 1
    return count
medium
A. The function should return intervals, not count
B. Using float('-inf') for end causes errors
C. The count variable should be initialized to 1
D. Sorting by start time instead of end time causes incorrect results

Solution

  1. Step 1: Check sorting key

    The code sorts intervals by start time, but to minimize removals, sorting by end time is needed.
  2. Step 2: Understand impact of sorting

    Sorting by start time can cause wrong overlap checks and incorrect count of removals.
  3. Final Answer:

    Sorting by start time instead of end time causes incorrect results -> Option D
  4. Quick Check:

    Sort by end time to minimize removals [OK]
Hint: Always sort intervals by end time for this problem [OK]
Common Mistakes:
  • Sorting by start time
  • Incorrect initialization of end
  • Returning wrong value
5. Given intervals [[1,2],[2,3],[3,4],[1,3]], what is the minimum number of intervals to remove to make the rest non-overlapping?
hard
A. 1
B. 2
C. 3
D. 0

Solution

  1. Step 1: Sort intervals by end time

    Sorted intervals: [[1,2],[2,3],[1,3],[3,4]]
  2. Step 2: Select intervals greedily and count removals

    Start end = -inf
    [1,2]: 1 >= -inf true, end=2
    [2,3]: 2 >= 2 true, end=3
    [1,3]: 1 >= 3 false, count=1 (remove this)
    [3,4]: 3 >= 3 true, end=4
  3. Final Answer:

    1 -> Option A
  4. Quick Check:

    One interval removed to avoid overlap [OK]
Hint: Sort by end time, greedily pick intervals, count removals [OK]
Common Mistakes:
  • Not sorting by end time
  • Counting non-overlapping intervals instead of removals
  • Removing wrong intervals
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