矩阵中包含重复值的行数和列数

给定一个N x N方阵arr[][] ，它只包含 1 到 N 之间的整数，任务是计算矩阵中包含重复值的行数和列数。

例子：

Input: N = 4, arr[][] = {{1, 2, 3, 4}, {2, 1, 4, 3}, {3, 4, 1, 2}, {4, 3, 2, 1}}
Output: 0 0
Explanation:
None of the rows or columns contain repeated values.

Input: N = 4, arr[][]= {{2, 2, 2, 2}, {2, 3, 2, 3}, {2, 2, 2, 3}, {2, 2, 2, 2}}
Output: 4 4
Explanation:
In every column and every row of the square matrix, the values are repeated.
Therefore, the total count is 4 for both rows and columns.

方法：想法是使用 NumPy 库。

• 为方阵中的每一行和每一列创建一个 NumPy 数组。
• 求唯一元素的长度。
• 如果长度等于N ，则该特定行或列中不存在重复值。

下面是上述方法的实现：

# Python program to count the number of 
# rows and columns in a square matrix 
# that contain repeated values
  
import numpy as np
  
# Function to count the number of rows
# and number of columns that contain 
# repeated values in a square matrix.
def repeated_val(N, matrix):
    column = 0
    row = 0
    for i in range (N):
  
    # For every row, an array is formed. 
    # The length of the unique elements 
    # is calculated, which if not equal 
    # to 'N' then the row has repeated values.
        if (len(np.unique(np.array(matrix[i])))!= N):
            row += 1 
  
    # For every column, an array is formed.
    # The length of the unique elements 
    # is calculated, which if not equal 
    # to N then the column has repeated values.
    for j in range (N):
        if (len(np.unique(np.array([m[j] for m in matrix])))!= N):
            column += 1
              
    # Returning the count of 
    # rows and columns
    return row, column
  
  
# Driver code
if __name__ == '__main__': 
  
     
    N = 3
    matrix = [ [ 2, 1, 3 ], [ 1, 3, 2 ], [ 1, 2, 3 ] ]
  
    print(repeated_val(N, matrix))  

输出：

(0, 2)

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