How to select elements from Numpy array in Python?

In this article, we will show you how to select elements from a NumPy array in Python using indexing and slicing techniques.

What is a NumPy Array?

A NumPy array is a central data structure of the NumPy library. NumPy (Numerical Python) is a powerful library that provides high-performance multidimensional array objects for efficient scientific computing in Python.

We can select elements from a NumPy array in several ways ?

• Selecting a single element using indexing
• Selecting a sub-array using slicing with start and stop values
• Selecting a sub-array with only stop value
• Selecting a sub-array with only start value

Selecting a Single Element

Each element in a NumPy array can be accessed using its index number. Python supports both positive and negative indexing ?

import numpy as np

# Creating a 1-Dimensional NumPy array
input_array = np.array([4, 5, 1, 2, 8])
print("Input array:", input_array)

# Positive indexing - accessing element at index 1
print("Element at index 1:", input_array[1])

# Negative indexing - accessing last element
print("Element at index -1 (last element):", input_array[-1])

Input array: [4 5 1 2 8]
Element at index 1: 5
Element at index -1 (last element): 8

Note: Negative indexing allows accessing elements from the end. The last element has index -1, second last has -2, and so on.

Selecting Sub-arrays Using Slicing

To obtain a sub-array, we use slicing with the syntax array[start:stop] where start is included and stop is excluded ?

import numpy as np

# Creating a 1-Dimensional NumPy array
input_array = np.array([4, 5, 1, 2, 8, 9, 7])
print("Input Array:", input_array)

# Getting sub-array from index 2 to 5 (excluded)
sub_array = input_array[2:5]
print("Sub-array from index 2 to 5:", sub_array)

Input Array: [4 5 1 2 8 9 7]
Sub-array from index 2 to 5: [1 2 8]

Slicing with Only Stop Value

When you omit the start index, slicing begins from index 0 by default ?

import numpy as np

# Creating a 1-Dimensional NumPy array
input_array = np.array([4, 5, 1, 2, 8, 9, 7])
print("Input Array:", input_array)

# Getting sub-array from start to index 5 (excluded)
sub_array = input_array[:5]
print("Sub-array till index 5:", sub_array)

Input Array: [4 5 1 2 8 9 7]
Sub-array till index 5: [4 5 1 2 8]

Slicing with Only Start Value

When you omit the stop index, slicing extends to the last element by default ?

import numpy as np

# Creating a 1-Dimensional NumPy array
input_array = np.array([4, 5, 1, 2, 8, 9, 7])
print("Input Array:", input_array)

# Getting sub-array from index 2 to end
sub_array = input_array[2:]
print("Sub-array from index 2 to end:", sub_array)

Input Array: [4 5 1 2 8 9 7]
Sub-array from index 2 to end: [1 2 8 9 7]

Summary

Conclusion

NumPy arrays support flexible element selection through indexing and slicing. Use single indexing for individual elements and slicing for sub-arrays. Remember that slicing creates views of the original data, making it memory-efficient.