Flatten a Matrix in Python using NumPy

Flattening means converting a 2D matrix into a 1D array. In NumPy, this is done using the ndarray.flatten() function.

flatten() Function

The flatten() function creates a copy of the array and returns it in 1D form.

Example 1: Flattening a 2×3 Matrix

import numpy as np
matrix = np.array([[10, 20, 30], [40, 50, 60]])
flat = matrix.flatten()
print(flat)

[10 20 30 40 50 60]

The values are read row by row and stacked into a 1D array.

Syntax

numpy_array.flatten(order='C')

Parameters:

• order='C' Flatten in row-major order (default).
• order='F' Flatten in column-major order.
• order='A' Flatten in column-major if memory is Fortran-contiguous, else row-major.
• order='K' Flatten in the order elements occur in memory.

Return: A new flattened 1D array.

Example 2: Flattening a 3×2 Matrix

import numpy as np
matrix = np.array([[6, 9], [8, 5], [18, 21]])
flat = matrix.flatten()
print(flat)

[ 6  9  8  5 18 21]

Again, elements are read row by row and merged into 1D.

Example 3: Flatten with order Parameter

import numpy as np
matrix = np.array([[6, 9, 12],
                   [8, 5, 2],
                   [18, 21, 24]])
flat = matrix.flatten(order='A')
print(flat)

[ 6  9 12  8  5  2 18 21 24]

Here, since the array is stored in row-major order, the result is the same as 'C'.