Python Data Analysis

One-dimensional slicing and indexing

Slicing of one-dimensional NumPy arrays works just like the slicing of standard Python lists. Let's define an array containing the numbers 0, 1, 2, and so on up to and including 8. We can select a part of the array from indexes 3 to 7, which extracts the elements of the arrays 3 through 6 (have a look at slicing1d.py in this book's code bundle):

In: a = arange(9)
In: a[3:7]
Out: array([3, 4, 5, 6])

We can choose elements from indexes the 0 to 7 with an increment of 2:

In: a[:7:2]
Out: array([0, 2, 4, 6])

Just as in Python, we can use negative indices and reverse the array:

In: a[::-1]
Out: array([8, 7, 6, 5, 4, 3, 2, 1, 0])