2643. Row With Maximum Ones
Description
Given a m x n
binary matrix mat
, find the 0-indexed position of the row that contains the maximum count of ones, and the number of ones in that row.
In case there are multiple rows that have the maximum count of ones, the row with the smallest row number should be selected.
Return an array containing the index of the row, and the number of ones in it.
Example 1:
Input: mat = [[0,1],[1,0]] Output: [0,1] Explanation: Both rows have the same number of 1's. So we return the index of the smaller row, 0, and the maximum count of ones (1). So, the answer is [0,1].
Example 2:
Input: mat = [[0,0,0],[0,1,1]] Output: [1,2] Explanation: The row indexed 1 has the maximum count of ones (2). So we return its index, 1, and the count. So, the answer is [1,2].
Example 3:
Input: mat = [[0,0],[1,1],[0,0]] Output: [1,2] Explanation: The row indexed 1 has the maximum count of ones (2). So the answer is [1,2].
Constraints:
m == mat.length
n == mat[i].length
1 <= m, n <= 100
mat[i][j]
is either0
or1
.
Solutions
Solution 1: Simulation
We initialize an array \(\textit{ans} = [0, 0]\) to store the index of the row with the most \(1\)s and the count of \(1\)s.
Then, we iterate through each row of the matrix:
- Compute the number of \(1\)s in the current row, denoted as \(\textit{cnt}\) (since the matrix contains only \(0\)s and \(1\)s, we can directly sum up the row).
- If \(\textit{ans}[1] < \textit{cnt}\), update \(\textit{ans} = [i, \textit{cnt}]\).
After finishing the iteration, we return \(\textit{ans}\).
The time complexity is \(O(m \times n)\), where \(m\) and \(n\) are the number of rows and columns in the matrix, respectively. The space complexity is \(O(1)\).
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