NumPy: A Comprehensive Guide with Examples | Lecture 1
NumPy: A Comprehensive Guide with Examples NumPy (Numerical Python) is a powerful library in Python for numerical computing. It provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays. Key Features of NumPy Efficient multi-dimensional array support : ndarray is the core object. Broadcasting : Operate on arrays of different shapes. Vectorized operations : Faster computation compared to loops. Integration with other libraries : Pandas, SciPy, etc. Extensive math functions : Trigonometric, statistical, and linear algebra. Getting Started with NumPy Installation pip install numpy Importing NumPy import numpy as np Core Concepts 1. Creating Arrays # 1D array arr1 = np.array([1, 2, 3, 4]) print(arr1) # 2D array arr2 = np.array([[1, 2], [3, 4]]) print(arr2) # Array with zeros zeros = np.zeros((3, 3...
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