To compute the average of a 2D array in Python, you can use the NumPy library. Here’s an example:

```
import numpy as np
# Define a 2D array
array_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
# Compute the average
average = np.mean(array_2d)
print("Average:", average)
```

In this example, the NumPy library is imported to work with arrays and numerical operations. The `array_2d`

variable is defined as a NumPy array representing the 2D array. The `np.mean()`

function is then used to compute the average of all the elements in the 2D array. The resulting average is stored in the `average`

variable and printed.

Make sure to have NumPy installed (`pip install numpy`

) before running this code. The `np.mean()`

function computes the average of all the elements in the array, treating the 2D array as a flattened 1D array. If you want to compute the average along a specific axis (e.g., row-wise or column-wise), you can specify the `axis`

parameter of the `np.mean()`

function accordingly.

Feel free to adapt the code based on your specific 2D array and requirements.

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