This **Valueerror operands could not be broadcast together with shapes** error typically occurs when performing mathematical operations on arrays with incompatible shapes.

It is a common issue faced by developers and data scientists working with numerical computations and data manipulation.

In this article, we will dive deep into this error, understand its causes, and explore examples and solutions to resolve it effectively.

## What is the ValueError operands could not be broadcast together with shapes error?

The **ValueError operands could not be broadcast together with shapes** error is a specific type of ValueError in Python. It occurs when you try to perform arithmetic or mathematical operations on arrays or tensors that have incompatible shapes.

**Example 1: Addition of arrays with different shapes**

**import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5])
c = a + b # Raises ValueError: operands could not be broadcast together with shapes
**

**Output:**

**Traceback (most recent call last):File “C:\Users\Dell\PycharmProjects\Python-Code-Example\main.py”, line 6, inc = a + bValueError: operands could not be broadcast together with shapes (3,) (2,)**

In this example, we have two arrays a and b with different shapes. Array a has three elements, while array b has only two elements.

When we try to perform element-wise addition using the **+ **operator, it raises the ValueError because the arrays cannot be broadcast together due to their incompatible shapes.

**Example 2: Multiplication of arrays with incompatible shapes**

**import numpy as np
a = np.array([[1, 2], [3, 4]])
b = np.array([5, 6, 7])
c = a * b **

**Output:**

**Traceback (most recent call last):File “C:\Program Files\JetBrains\PyCharm Community Edition 2022.3.2\plugins\python-ce\helpers\pydev\pydevd.py”, line 1496, in _execpydev_imports.execfile(file, globals, locals) # execute the scriptFile “C:\Program Files\JetBrains\PyCharm Community Edition 2022.3.2\plugins\python-ce\helpers\pydev_pydev_imps_pydev_execfile.py”, line 18, in execfileexec(compile(contents+”\n”, file, ‘exec’), glob, loc)File “C:\Users\Dell\PycharmProjects\Python-Code-Example\main.py”, line 6, inc = a * bValueError: operands could not be broadcast together with shapes (2,2) (3,)**

## Solutions to ValueError: operands could not be broadcast together with shapes

To resolve the **operands could not be broadcast together with shapes** error, you can apply the following solutions:

**Solution 1: Reshape or expand the arrays**

One way to resolve the error is to reshape or expand the arrays to ensure compatibility. You can use the **reshape()** function from NumPy to change the shape of an array.

**Example Program:**

**import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5])
# Reshape array b to have the same shape as array a
b_reshaped = b.reshape((2, 1))
c = a + b_reshaped # Perform element-wise addition
print(c)
**

**Output:**

**[[5 6 7][6 7 8]]**

In the example above, we reshape the array b to have the shape (2, 1) using the reshape() function.

This allows the arrays a and **b_reshaped **to have compatible shapes for element-wise addition.

**Solution 2: Expand dimensions using np.newaxis**

Another solution to solve this error is to expand the dimensions of the array using **np.newaxis**.

This method adds a new axis to the array, effectively changing its shape.

```
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5])
# Expand dimensions of array b
b_expanded = b[:, np.newaxis]
c = a + b_expanded # Perform element-wise addition
print(c)
```

Here, the **np.newaxis** is used to add a new axis to the array b, resulting in a shape of (2, 1).

The arrays a and **b_expanded** now have compatible shapes, allowing the addition operation to be performed successfully.

## FAQs

**Why am I getting the ValueError: operands could not be broadcast together with shapes error?**

This error occurs when you try to perform arithmetic or mathematical operations on arrays with incompatible shapes.

**Can I perform arithmetic operations on arrays with different shapes in Python?**

Yes, you can perform arithmetic operations on arrays with different shapes using broadcasting.

**Are there any limitations to broadcasting in NumPy?**

Yes, broadcasting has certain limitations. The arrays must have compatible shapes, which means they need to satisfy certain rules for broadcasting.

**Can I apply the solutions mentioned here to higher-dimensional arrays?**

Yes, the solutions mentioned here can be applied to higher-dimensional arrays as well. Reshaping or expanding dimensions can help make arrays compatible for broadcasting in higher-dimensional scenarios too.

## Conclusion

The **ValueError: operands could not be broadcast together with shapes** error is a common issue when performing arithmetic operations on arrays with incompatible shapes.

In this article, we show some examples of this error and provided solutions to resolve it.

By reshaping or expanding the dimensions of arrays, you can ensure compatibility and perform the desired operations successfully.