There are primarily two ways of accessing data by slicing and indexing. They are called copies and views: you can either access elements directly from an array, or create a copy of the array that contains only the accessed elements. Since a view is a reference of the original array (in Python, all variables are references), modifying a view modifies the original array too. This is not true for copies.
The may_share_memory function in NumPy miscellaneous routines can be used to determine whether two arrays are copies or views of each other. While this method does the job in most cases, it is not always reliable, since it uses heuristics. It may return incorrect results too. For introductory purposes, however, we shall take it for granted.
Generally, slicing an array creates a view and indexing it creates a copy. Let us study these differences through a few code snippets. First, let's create a random 100x10 array.
In [21]: x = np.random.rand(100,10)
Now, let us extract...
