I have an array `A1`

. I am deleting the zero rows and columns but I also want to identify which row and column was deleted. I present the current and expected output.

```
import numpy as np
A1=np.array([[0, 1, 2],
[0, 0, 0],
[0, 3, 4]])
mask = A1!= 0
A2 = A1[np.ix_(mask.any(1), mask.any(0))]
print([A2])
```

The current output is

```
[array([[1, 2],
[3, 4]])]
```

The expected output is

```
[array([[1, 2],
[3, 4]])]
[1] where 1 is the deleted row,
[0] where 0 is the deleted column
```

### >Solution :

This is the code for get your desired output:

```
import numpy as np
A1=np.array([[0, 1, 2],
[0, 0, 0],
[0, 3, 4]])
mask = A1 != 0
deleted_rows = np.where(~mask.any(axis=1))[0]
deleted_columns = np.where(~mask.any(axis=0))[0]
A2 = A1[np.ix_(mask.any(1), mask.any(0))]
print([A2])
print("Deleted rows:", deleted_rows)
print("Deleted columns:", deleted_columns)
```

**Result:**

```
array([[1, 2],
[3, 4]])]
Deleted rows: [1]
Deleted columns: [0]
```