To determine the shape of a NumPy array, you can utilize the `shape`

attribute, which provides a tuple representing the number of rows and columns. For instance, a 3x4 array will yield a shape of `(3, 4)`

. The `shape`

attribute is essential for understanding array dimensions and enabling diverse operations.

Here is an example code of how you can use the `shape`

attribute:

This is just one method of finding the shape of an array, if you have other alternate methods and techniques, feel free to share them below!

Hi @Hyder_Zaidi, another method of finding the shape is by utilizing the `np.size()`

function. This function can be used to count the number of elements along each axis, providing a tuple of dimensions for the 2D array and a single-element tuple for the 1D array.

Note: You have to specify each axis separately. For example, if you have three axes, you would also specify `np.size(array, 2)`

to find the dimensions along the third axis.

Hello @Hyder_Zaidi, the approach I use often involves using the `np.shape()`

function to determine the shape of my NumPy arrays. This method returns a tuple with the number of rows and columns.

Hope this helps you!