The useful thing about numpy is it can create a multi-dimensional array.
<pre><code class="lang-python">a_mul = np.array([[1,2,3], [4,5,6], [7, 8, 9]])
print(a_mul)

[[1 2 3]
 [4 5 6]
 [7 8 9]]
</code></pre>
If I print(a_mul[0, 1]), what would I get? This means the first row, second column. So, it should be 2.
Likewise, you can print a_mul.shape.
This should return (3, 3) because it is the matrix has three rows and three columns.

The useful thing about numpy is it can create a multi-dimensional array.

```python
a_mul = np.array([[1,2,3], [4,5,6], [7, 8, 9]])
print(a_mul)

[[1 2 3]
 [4 5 6]
 [7 8 9]]
```

If I print(a\_mul\[0, 1\]), what would I get? This means the first row, second column. So, it should be 2.

Likewise, you can print a\_mul.shape.

This should return (3, 3) because it is the matrix has three rows and three columns.

numpy multi-dimensional array