One error you may encounter when using Python is:

ValueError: operands could not be broadcast together with shapes (2,2) (2,3)

This error occurs when you attempt to perform matrix multiplication using a multiplication sign (*****) in Python instead of the **numpy.dot()** function.

The following examples shows how to fix this error in each scenario.

**How to Reproduce the Error**

Suppose we have a 2×2 matrix C, which has 2 rows and 2 columns:

Suppose we also have a 2×3 matrix D, which has 2 rows and 3 columns:

Here is how to multiply matrix C by matrix D:

This results in the following matrix:

Suppose we attempt to perform this matrix multiplication in Python using a multiplication sign (*) as follows:

import numpy as np #define matrices C = np.array([7, 5, 6, 3]).reshape(2, 2) D = np.array([2, 1, 4, 5, 1, 2]).reshape(2, 3) #print matrices print(C) [[7 5] [6 3]] print(D) [[2 1 4] [5 1 2]] #attempt to multiply two matrices together C*D ValueError: operands could not be broadcast together with shapes (2,2) (2,3)

We receive a **ValueError**. We can refer to the NumPy documentation to understand why we received this error:

When operating on two arrays, NumPy compares their shapes element-wise. It starts with the trailing (i.e. rightmost) dimensions and works its way left. Two dimensions are compatible when

- they are equal, or
- one of them is 1
If these conditions are not met, a

ValueError: operands could not be broadcast togetherexception is thrown, indicating that the arrays have incompatible shapes.

Since our two matrices do not have the same value for their trailing dimensions (matrix C has a trailing dimension of 2 and matrix D has a trailing dimension of 3), we receive an error.

**How to Fix the Error**

The easiest way to fix this error is to simply using the **numpy.dot()** function to perform the matrix multiplication:

import numpy as np #define matrices C = np.array([7, 5, 6, 3]).reshape(2, 2) D = np.array([2, 1, 4, 5, 1, 2]).reshape(2, 3) #perform matrix multiplication C.dot(D) array([[39, 12, 38], [27, 9, 30]])

Notice that we avoid a **ValueError** and we’re able to successfully multiply the two matrices.

Also note that the results match the results that we calculated by hand earlier.

**Additional Resources**

The following tutorials explain how to fix other common errors in Python:

How to Fix: columns overlap but no suffix specified

How to Fix: ‘numpy.ndarray’ object has no attribute ‘append’

How to Fix: if using all scalar values, you must pass an index

How to Fix: ValueError: cannot convert float NaN to integer