NumPy Array Indexing and Slicing

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Learn how to perform NumPy array indexing and slicing in Python.


NumPy Array Indexing

Indexing refers to the way elements are accessed in a NumPy array.

The indexing of elements in a NumPy Array starts at 0 and you can access any element of an n-dimensional array by using the index number of the elements.

You’ll understand this better with the help of the following examples of 1D and 2D NumPy arrays.

Accessing elements of a 1D NumPy Array

The syntax for accessing the elements of a 1D NumPy array is as follows:

numpy.array([elements])[i]

Here, numpy.array([elements]) is a 1D NumPy array and [i] refers to the index position of the ith element.

The following example showcases how to access elements of a 1D NumPy array:

1D NumPy Array Indexing
# Importing the NumPy library as np
import numpy as np

# Creating a NumPy array from a Python List
num_array = np.array([1, 2, 3])

# Printing the content
print("The content of the NumPy array: ", num_array)

# Printing the first element by accessing index 0
print("The first element of the NumPy array: ", num_array[0])

# Printing the second element by accessing index 1
print("The second element of the NumPy array: ", num_array[1])

# Printing the third element by accessing index 2
print("The third element of the NumPy array: ", num_array[2])
The content of the NumPy array: [1 2 3]
The first element of the NumPy array: 1
The second element of the NumPy array: 2
The third element of the NumPy array: 3

You can also use negative indexing to access elements of a NumPy array. This means that the last element of a NumPy array is indexed as -1, the second last element of a NumPy array is indexed as -2, and so on.

So, the same 1D NumPy array with negative indexing can be understood as the following.

1D NumPy Array Negative Indexing
# Importing the NumPy library as np
import numpy as np

# Creating a NumPy array from a Python List
num_array = np.array([1, 2, 3])

# Printing the content
print("The content of the NumPy array: ", num_array)

# Printing the first element by accessing index -3
print("The first element of the NumPy array: ", num_array[-3])

# Printing the second element by accessing index -2
print("The second element of the NumPy array: ", num_array[-2])

# Printing the third element by accessing index -1
print("The thrird element of the NumPy array: ", num_array[-1])
The content of the NumPy array: [1 2 3]
The first element of the NumPy array: 1
The second element of the NumPy array: 2
The third element of the NumPy array: 3

Accessing elements of a 2D NumPy Array

The syntax for accessing the elements of a 2D NumPy array is as follows:

numpy.array([[elements]])[i][j]

Here, numpy.array([[elements]]) is a 2D NumPy array and [i] refers to the index position of the ith element in the first axis and [j] refers to the index position of the jth element in the second axis.

The following example showcases how to access elements of a 2D NumPy array:

2D NumPy Array Indexing
# Importing the NumPy library as np
import numpy as np

# Creating a NumPy array from a Python List
num_array = np.array([[1, 2, 3], [4, 5, 6]])

# Printing the content
print("The content of the NumPy array: ", num_array)

# Printing the element at position 0
print("The element at position 0 of the NumPy array: ", num_array[0])

# Printing the element at position (0, 0)
print("The element at position (0,0) of the NumPy array: ", num_array[0][0])

# Printing the element at position (0, 1)
print("The element at position (0,1) of the NumPy array: ", num_array[0][1])

# Printing the element at position (1)
print("The element at position (1) of the NumPy array: ", num_array[1])

# Printing the element at position (1, 0)
print("The element at position (1, 0) of the NumPy array: ", num_array[1][0])

# Printing the element at position (1, 1)
print("The element at position (1, 1) of the NumPy array: ", num_array[1][1])
The content of the NumPy array:  [[1 2 3]
                                  [4 5 6]]
The element at position 0 of the NumPy array:  [1 2 3]
The element at position (0,0) of the NumPy array:  1
The element at position (0,1) of the NumPy array:  2
The element at position (1) of the NumPy array:  [4 5 6]
The element at position (1, 0) of the NumPy array:  4
The element at position (1, 1) of the NumPy array:  5

You can take this concept of indexing even further and generalize it for n-dimensional arrays.


NumPy Array Slicing

Slicing a NumPy array refers to accessing/retrieving elements in between a starting and ending index position of an array. The general syntax for NumPy array slicing is as follows:

numpy.array()[start:end:step]

Here, numpy.array() is a NumPy array and,

  • start refers to the starting index position from where the slice should happen. If start is not specified, it is set as 0 by default.
  • end refers to the ending index position till where the slice should happen. If end is not specified, it is set as the length of the array by default.
  • step refers to the distance between two adjacent values in the array to be sliced. The default step size is 1.

The following example showcases how to slice a 1D NumPy array in different ways:

# Importing the NumPy library as np
import numpy as np

# Creating a 1D NumPy array
num_array = np.array([1, 2, 3, 4, 5])

print("The content of the NumPy array: ", num_array)

print("Elements starting from index 1:", num_array[1:])

print("Elements from index 1 to index 5: ", num_array[1:5])

print("Elements starting from index 1 to index 5 with a step of 2: ", num_array[1:5:2])

print("Elements starting from index 1 with a step of 2: ", num_array[1::2])

print("Elements starting with a step of 2: ", num_array[::2])

print("Elements till and not including index 1: ", num_array[:1])

print("Elements till and not including index 4: ", num_array[:4])

print("Elements till and not including index 4 with a step of 2: ", num_array[:4:2])

print("Elements except the last two indexes: ", num_array[:-2])

print("Elements starting from the second last index: ", num_array[-2:])

print("All elements of the array: ", num_array[:])
The content of the NumPy array: [1 2 3 4 5]
Elements starting from index 1: [2 3 4 5] 
Elements from index 1 to index 5: [2 3 4 5] 
Elements starting from index 1 to index 5 with a step of 2: [2 4] 
Elements starting from index 1 with a step of 2: [2 4] 
Elements starting with a step of 2: [1 3 5] 
Elements till and not including index 1: [1] 
Elements till and not including index 4: [1 2 3 4] 
Elements till and not including index 4 with a step of 2: [1 3] 
Elements except the last two indexes: [1 2 3] 
Elements starting from the second last index: [4 5] 
All elements of the array: [1 2 3 4 5]

That is it for this lesson on indexing and slicing NumPy array.

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