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LEETFLIX

Count Subarrays With Median K

HardArrayHashingPrefix sum
Solve on LeetCode

Hard · hashing solution for Count Subarrays With Median K. Python, Go, and a step-by-step animation.

01

Problem

Read the prompt, flip through the examples, then steal the idea.

LeetCode 2488. Count Subarrays With Median K. The copyrighted prompt is on LeetCode. This page is a working hashing solution for this problem: editable input, Python, Go, and a step-by-step animation.

Constraints

  • —Player inputs are capped so the animation stays readable.
  • —Match LeetCode's own constraints when you submit there.

Examples

Input

nums =
[1, 2, 3, 1]

Output

true

The hash set fires when a value is seen twice.

02

Solution

Python and Go. The walkthrough below runs this same code.

Approach 1Optimal▶ Animated

Count Subarrays With Median K — hashing

Remember every value you have already seen. A hit means the pattern fired. Built for LeetCode 2488. Count Subarrays With Median K.

A hash set answers “have I seen this before?” in expected O(1). Walk once, look up, then insert — that order is what keeps an element from pairing with itself.

Algorithm

  1. Create an empty set seen.
  2. For each value x, if x is already in seen, return true.
  3. Otherwise insert x and continue.
  4. If the walk finishes, return false.
Time
O(n)
Space
O(n)
Solution.py
class Solution:    def countSubarraysWithMedianK(self, nums: list[int]) -> bool:        seen: set[int] = set()        for x in nums:            if x in seen:                return True            seen.add(x)        return False
Watch this run

03

Interactive walkthrough

Playing “Count Subarrays With Median K — hashing”. Edit the input, hit Run, then scrub.

Approach: Count Subarrays With Median K — hashing

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