Indexing and Slicing

To illustrate indexing, let's first create an array with random data using the following command:

import numpy.random
a = np.random.rand(6,5)
print a

This creates an array of dimension (6,5) that contains random data. Individual elements of the array are accessed with the usual index notation, for example, a[2,4].

An important technique to manipulate data in NumPy is the use of slices. A slice can be thought of as a subarray of an array. For example, let's say we want to extract a subarray with the middle two rows and first two columns of the array a. Consider the following command lines:

b = a[2:4,0:2]
print b

Now, let's make a very important observation. A slice is simply a view of an array, and no data is actually copied. This can be seen by running the following commands:

b[0,0]=0
print a

So, changes in b affect the array a! If we really need a copy, we need to explicitly say we want one. This can be done using the following command line:

c = np.copy(a...