# How to subtract row means in NumPy and implement it?

I came across this term as I was exploring the different functionalities of NumPy. The term itself means subtracting the mean of each row from each element of the corresponding row in a matrix which I completely understand what are we trying to do and can visualize in my head, though I can’t make out the logic in my head to type out code for it, can anyone help out in this?

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Sure @safiaa.02, here is an example code that uses the technique of `NumPy vectorization` to achieve the task you explained:

• NumPy vectorization is a technique to perform mathematical operations on an array in a faster and more efficient way, by operating on the entire array rather than individual elements.
• In this example code, the mean of each row of a 3x3 matrix is calculated using `np.mean()`. Then, NumPy vectorization is used to subtract the row means from each element in the row by adding a new axis to `row_means` with `[:, np.newaxis]`.

I hope this code is useful and helps you understand the logic of this technique in code!