How to Flatten a Matrix using NumPy Flatten Function?

Follow this NumPy code example to seamlessly flatten a NumPy matrix, offering a comprehensive guide for intuitive data transformation. | ProjectPro

Matrices are fundamental in various scientific and engineering applications. However, there are situations where a flattened representation is more practical. Flattening a matrix simplifies data handling, making it easier to perform operations like vectorization, statistical analysis, and machine learning tasks. This numpy code example will help you understand the NumPy flatten function, uncovering the complexity of matrix flattening with ease. 

NumPy Flatten Function: An Introduction

The NumPy flatten function is a straightforward and efficient way to convert a multi-dimensional array into a one-dimensional array. Its syntax is simple:

Flatten a matrix in NumPy

Here, 'order' specifies the index order to read the elements. 'C' stands for C-style, reading elements in row-major order. 

How to Flatten a Matrix in NumPy? - A Step-by-Step Guide 

Here is a stepwise implementation on how to flatten a matrix in NumPy -

Step 1 - Import the library

    import numpy as np

We have only imported numpy which is needed.

Step 2 - Setting up the Data

We have created a matrix using an array and we will flatten this.

     matrixA = np.array([[1, 2, 3, 97],

                       [4, 5, 6, 98],

                       [7, 8, 9, 99],

                       [10, 11, 12, 100]])

    matrixB = np.array([[2, 3, 4],

                       [5, 6, 9],

                       [7, 8, 1]])

Step 3 - NumPy Flatten Matrix using np.flatten

We can flatten the matrix by using a flatten function with no parameters.

    print(matrixA.flatten())

    print(matrixB.flatten())

So, the output comes as

[  1   2   3  97   4   5   6  98   7   8   9  99  10  11  12 100]

[2 3 4 5 6 9 7 8 1]

NumPy Flatten: Best Practices and Tips

Here are the best ways to use NumPy Flatten with some helpful tips! These simple tricks will make it easier for you to work with arrays in Python and improve your coding skills.

  • Specify Order: The 'order' parameter in the flatten function allows you to choose between 'C' (default) and 'F' (Fortran-style) order. Experiment with both to find the most efficient option for your use case.

Flatten NumPy matrix - Best Practices

  • Avoid Copying: The flatten function returns a copy of the original array. If memory efficiency is crucial, consider using the ravel function, which returns a flattened view of the array.

NumPy flatten matrix

Master Practical NumPy Matrix Operations with ProjectPro!

Learning to flatten matrices with NumPy is cool, but it's even cooler when you can actually do it in real projects! ProjectPro has over 270+ projects on data science, big data, and data engineering that make learning fun and practical. You get to try out what you've learned and see how it works in the real world. ProjectPro is like your friendly guide, allowing you to practice and improve at NumPy matrix operations. So, why read about it when you can play with it? Let's get hands-on with ProjectPro and make learning super exciting! 


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