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Discover a simple method to add two matrices of varying dimensions in Python using NumPy without writing complex functions.
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How to Easily Add Two Matrices with Different Sizes in Python

When working with matrices in Python, you may encounter situations where you need to add two matrices that do not share the same dimensions. It can be frustrating if you aren't familiar with how to handle this in a straightforward manner. This guide will guide you through the process of adding two matrices with different numbers of rows and columns using Python's powerful NumPy library, ensuring you get the results you need without diving deep into custom functions.

The Problem

Imagine you have two matrices:

Matrix 1:

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Matrix 2:

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You want to find the sum of these matrices but, as you might already know, simply adding them won't work because they have different shapes (or sizes). The goal is to add them together to produce a resulting matrix like this:

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The Solution Using NumPy

Fortunately, NumPy provides an efficient way to handle operations on matrices, including resizing them for operations like addition. Below, we'll walk through the steps required to add these two matrices easily.

Step 1: Import NumPy

First, make sure you have NumPy installed in your Python environment. You can install it using pip if you haven’t already:

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Then, import the library in your script:

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Step 2: Create the Matrices

Next, define the two matrices using NumPy's array() function:

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Step 3: Resize the Matrices

To prepare them for addition, we need to ensure that both matrices have the same shape. You can do this using the resize() method. Here’s the code snippet:

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Step 4: Add the Matrices

Once the matrices are resized to the same shape, you can easily add them together:

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Step 5: Print the Result

Finally, output the resulting matrix:

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Complete Code Example

Putting it all together, here’s how the complete code looks:

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Expected Output

When you run the above code, you will see the following output:

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Conclusion

And there you have it! Using NumPy, we have successfully added two matrices of different sizes. By resizing one of the matrices to match the dimensions of the other, we prevented errors and seamlessly computed the sum.

Whether you're working with small matrices or large datasets, NumPy is a reliable ally in your Python programming journey. Now, you can apply this knowledge to efficiently handle any matrix addition task you may encounter!