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Number of Islands

amazongooglemicrosoftbloomberglinkedin

Given an m x n 2D binary grid grid which represents a map of '1's (land) and '0's (water), return the number of islands.

An island is surrounded by water and is formed by connecting adjacent lands horizontally or vertically. You may assume all four edges of the grid are all surrounded by water.

Example 1:

Input: grid = [
  ["1","1","1","1","0"],
  ["1","1","0","1","0"],
  ["1","1","0","0","0"],
  ["0","0","0","0","0"]
]
Output: 1

Example 2:

Input: grid = [
  ["1","0","1","1","0"],
  ["1","0","1","0","0"],
  ["0","0","0","0","1"],
  ["0","0","0","1","1"]
]
Output: 3

Examples

Example 1

Input: grid = [["1","1","1","1","0"],["1","1","0","1","0"],["1","1","0","0","0"],["0","0","0","0","0"]]

Output: 1

Explanation: All connected '1' cells form a single island. There are no other disconnected land cells.

Example 2

Input: grid = [["1","1","0","0","0"],["1","1","0","0","0"],["0","0","1","0","0"],["0","0","0","1","1"]]

Output: 3

Explanation: There are three separate groups of connected land cells: top-left 2x2 block, center cell at (2,2), and bottom-right two cells at (3,3) and (3,4).

Constraints

  • -m == grid.length
  • -n == grid[i].length
  • -1 <= m, n <= 300
  • -grid[i][j] is '0' or '1'.

Optimal Complexity

Time

O(m * n)

Space

O(m * n)

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