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
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!