Numpy arrays:python arrays

NumPy is a Python library for scientific computing, which provides support for working with arrays. NumPy arrays are homogeneous collections of elements, with a fixed size and shape. They can contain numeric data (integers, floating point numbers, etc.) as well as boolean and string data. NumPy arrays are faster and more efficient than Python's built-in lists, especially for larger datasets.

import numpy as np

You can access elements of a NumPy array using indexing, just like with Python lists:

a[0] # returns the first element of a
b[1, 2] # returns the element in the second row and third column of b
NumPy provides a wide range of functions for performing mathematical operations on arrays, including element-wise operations, linear algebra, and statistical functions. For example, to add two arrays element-wise:

e = c + d # returns array([5, 7, 9])
Overall, NumPy arrays are a powerful and essential tool for scientific computing in Python.#numpy arrays#python arrays#how to create empty numpy array#how to learn numpy#why use numpy#numpy in python#data science#numpy functions#list vs numpy arrays#numpy histogram#numpy zeros#numpy array vs python list##aiwithsaeed#numpy arange