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Pandas & NumPy Academy · Lesson

Array Slicing and Indexing

Select individual elements, rows, columns, and sub-arrays using integer and slice notation on multi-dimensional arrays.

Integer Indexing in 1-D Arrays

A 1-D array is indexed just like a list: a[0] is first, a[-1] is last. Indexing returns a single scalar, and negative numbers count from the end.

import numpy as np

a = np.array([10, 20, 30, 40, 50])
print(a[0])    # 10
print(a[-1])   # 50
print(a[2])    # 30

Slicing 1-D Arrays

Slices use start:stop:step like lists, but a NumPy slice returns a view — no copy. Change the slice and you change the original, so use .copy() when needed.

import numpy as np

a = np.arange(10)  # [0 1 2 3 4 5 6 7 8 9]
print(a[2:7])      # [2 3 4 5 6]
print(a[::2])      # [0 2 4 6 8]
print(a[::-1])     # [9 8 7 6 5 4 3 2 1 0]

All lessons in this course

  1. Creating NumPy Arrays
  2. Array Attributes and Inspection
  3. Element-Wise Arithmetic
  4. Array Slicing and Indexing
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