Why Do I Get a 'operands could not be broadcast together' Error in NumPy and How Can I Fix It?

Broadcasting in Numpy: Understanding the "operands could not be broadcast together" Error

The numpy library provides powerful data structures and operations for numerical computations. One common operation is matrix multiplication, which can be performed using the * operator. However, when attempting to multiply two arrays with different shapes, you may encounter the following error:

ValueError: operands could not be broadcast together with shapes (97,2) (2,1)

To understand this error, we must first delve into the concept of broadcasting in numpy. Broadcasting allows arrays of different shapes to be used in operations by expanding or replicating dimensions to match the dimensions of the other array.

In the example provided, array X has the shape (97, 2), indicating it has 97 rows and 2 columns. Array y has the shape (2, 1), indicating it has 2 rows and 1 column. When performing X * y, a ValueError is raised because these shapes cannot be broadcast together. The issue arises because there is a conflict in the first dimension: X has 97 elements, while y has only 2. Broadcasting cannot resolve this conflict, so the operation fails.

Alternatively, we can use the dot product operator (numpy.dot) for matrix multiplication. The dot product is specifically designed for matrix multiplication and handles broadcasting correctly. In the corrected example, X.dot(y) returns a vector with a shape of (97, 1), as desired.

By understanding the rules of broadcasting and using the correct matrix multiplication operator, we can effectively perform numerical operations and avoid the "operands could not be broadcast together" error in numpy.

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