Python NumPy Tutorial for Beginners

NumPy is a fundamental package for scientific computing in Python. It provides support for arrays, matrices, and mathematical functions to operate on these arrays efficiently.

Here’s an overview to get you started:

1. Installation

If you haven’t installed NumPy yet, you can do so via pip:

pip install numpy

2. Importing

After installation, you can import NumPy in your Python script or interpreter:

import numpy as np

3. NumPy Arrays

NumPy’s primary object is the homogeneous multidimensional array, numpy.ndarray. You can create NumPy arrays using lists or other array-like objects.

Creating Arrays:

# From a list
arr1 = np.array([1, 2, 3, 4, 5])

# Multidimensional array
arr2 = np.array([[1, 2, 3], [4, 5, 6]])

# Zeros array
zeros_array = np.zeros((3, 4))  # Creates a 3x4 array of zeros

# Ones array
ones_array = np.ones((2, 3))    # Creates a 2x3 array of ones

# Array with a range of values
range_array = np.arange(0, 10, 2)  # Creates an array from 0 to 10 (exclusive) with a step of 2

# Random array
random_array = np.random.rand(3, 3)  # Creates a 3x3 array of random values between 0 and 1