README_EN.md

4. Median of Two Sorted Arrays

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Description

Given two sorted arrays nums1 and nums2 of size m and n respectively, return the median of the two sorted arrays.

 

Example 1:

Input: nums1 = [1,3], nums2 = [2]
Output: 2.00000
Explanation: merged array = [1,2,3] and median is 2.

Example 2:

Input: nums1 = [1,2], nums2 = [3,4]
Output: 2.50000
Explanation: merged array = [1,2,3,4] and median is (2 + 3) / 2 = 2.5.

Example 3:

Input: nums1 = [0,0], nums2 = [0,0]
Output: 0.00000

Example 4:

Input: nums1 = [], nums2 = [1]
Output: 1.00000

Example 5:

Input: nums1 = [2], nums2 = []
Output: 2.00000

 

Constraints:

• nums1.length == m
• nums2.length == n
• 0 <= m <= 1000
• 0 <= n <= 1000
• 1 <= m + n <= 2000
• -106 <= nums1[i], nums2[i] <= 106

 

Follow up: The overall run time complexity should be O(log (m+n)).

Solutions

Python3

class Solution:
    def findMedianSortedArrays(self, nums1: List[int], nums2: List[int]) -> float:
       # concatenate the 2 lists and sort them
        nums1 += nums2
        nums1.sort()
        length = len(nums1)
        value = length/2
        if length % 2 == 0:
            value = int(value)
            return (nums1[value-1] + nums1[value])/2
        else:
            return nums1[int(value)]

Java

Nim

proc medianOfTwoSortedArrays(nums1: seq[int], nums2: seq[int]): float =
  var
    fullList: seq[int] = concat(nums1, nums2)
    value: int = fullList.len div 2

  fullList.sort()

  if fullList.len mod 2 == 0:
    result = (fullList[value - 1] + fullList[value]) / 2
  else:
    result = fullList[value].toFloat()

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