NumPy Joining Array

In NumPy, joining arrays refers to combining the elements of multiple arrays into a single new array. There are two main ways to achieve this:

1. Concatenation: This involves joining arrays along a specified axis. The most common function for concatenation is np.concatenate. It takes a sequence of arrays as its first argument and optionally the axis along which to join them. By default, concatenation happens along axis 0 (rows for 2D arrays).

Here's an example of concatenating two arrays:

 

2. Stacking: This is similar to concatenation but with a key difference. Stacking creates a new axis along which the arrays are joined. NumPy provides convenience functions for stacking along specific axes:

• np.hstack: Stacks arrays horizontally (column-wise) by creating a new axis 1.
• np.vstack: Stacks arrays vertically (row-wise) by creating a new axis 0.
• np.dstack: Stacks arrays along depth (useful for 3D arrays) by creating a new axis 2.

Here are examples