Python NumPy Tutorial | Learn With Examples
In this Python NumPy Tutorial with examples, you will learn what is NumPy? its features, advantages, modules, packages, and how to use NumPy Arrays with sample examples in Python code.
Every sample example explained here is tested in our development environment and is available at PySpark Examples Github project for reference.
All examples provided in this Python NumPy tutorial are basic, simple, and easy to practice for beginners who are enthusiastic to learn NumPy and advance their careers.
Note: In case you can’t find the NumPy examples you are looking for on this tutorial page, I would recommend using the Search option from the menu bar to find your tutorial and sample example code.
What is Numpy Array?
In order to use Numpy, you need to install it first and use the following import.
# Import NumPy package import numpy as np
What is ndarray (N-dimensional array)?
numpy.ndarray is an array object in Python that is used to represent a fixed size multidimensional array of the same types.
This constructor of the ndarray is low-level and the users should not use it to create NumPy array.
The type of items in the array is specified by a separate data-type object (dtype), one of which is associated with each ndarray.
Install Python Numpy Library
Create Numpy Array
numpy.ndarray provides a constructor to create an array, it is not recommended to use as it is a low-level constructor and recommends to use
numpy.array() function to create NumPy array.
numpy.array() returns the ndarray object of type
# Create Numpy array nparray = np.array([[10, 20, 30], [40, 50, 60]]
This creates a NumPy array
nparray object. Let’s check the
dtype of elements of this array.
# Type of array type(nparray) #<class 'numpy.ndarray'> # Share of array nparray.shape #(2, 3) # Type of elements nparray.dtype #dtype('int32')
Access the Array Elements using the Index
Update Array Elements
Convert NumPy Array to Python List
Convert Python List to AnumPy Array
Numpy Array Properties
NumPy Array Functions