Numpy matrix.sort() Last Updated : 19 Aug, 2025 Comments Improve Suggest changes Like Article Like Report numpy.matrix.sort() is a method in NumPy sort the elements of a matrix along a specified axis. It returns a sorted copy of the matrix without changing the original matrix.Example: Python import numpy as np m = np.matrix([[9, 2, 5], [6, 4, 1]]) sorted_m = m.sort(axis=1) print(m) Output[[2 5 9] [1 4 6]] Explanation: Each row is sorted independently.Syntaxmatrix.sort(axis=-1, kind='quicksort', order=None)Parameters:axis: Direction to sort; default is 1 (last axis), 0 for columns, 1 for rows.kind: Sorting algorithm options include 'quicksort' (default), 'mergesort', 'heapsort', 'stable'.order: For structured arrays, sort.Returns: A new sorted matrix (not in-place).ExamplesExample 1: Sort a matrix column-wise Python import numpy as np m = np.matrix([[3, 1], [2, 4]]) m.sort(axis=0) print(m) Output[[2 1] [3 4]] Explanation: Each column is sorted in ascending order.Example 2: Using different sorting algorithms Python import numpy as np m = np.matrix([[5, 3, 1], [4, 2, 6]]) m.sort(axis=1, kind='mergesort') print(m) Output[[1 3 5] [2 4 6]] Explanation: The matrix is sorted row-wise using mergesort. 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