Getting Started with NumPy: A Friendly Guide for School Students

As you are learning Python and wanted to do cool things with numbers, arrays, and data, then NumPy is your new best friend! Let's explore what NumPy is, why it's useful, and look at some fun examples.

What is NumPy?

NumPy (Numerical Python) is a Python library that makes it super easy to work with numbers, especially lists of numbers (which we call arrays). It is faster and more powerful than using regular Python lists when it comes to math and data analysis.

Why Use NumPy?

• Speed: NumPy can handle large amounts of data much faster than normal Python lists.

• Functions: It comes with many built-in functions for math, statistics, and more.

• Easy math on arrays: You can add, subtract, multiply, or divide entire arrays at once.

Installing NumPy

Before you use NumPy, you need to install it. You can do this by running:

pip install numpy

Let's See NumPy in Action!

First, we import NumPy. Usually, we give it a nickname np:

import numpy as np

1. Creating Arrays

# A simple array of numbers
arr = np.array([1, 2, 3, 4, 5])
print(arr)

Output:

[1 2 3 4 5]

2. Doing Math with Arrays

arr2 = arr * 2
print(arr2)

Output:

[ 2  4  6  8 10]

See how easy it is to multiply every number by 2?

3. Creating Arrays with Zeros and Ones

zeros = np.zeros(5)
print(zeros)  # [0. 0. 0. 0. 0.]

ones = np.ones(5)
print(ones)   # [1. 1. 1. 1. 1.]

4. Making a Range of Numbers

range_arr = np.arange(0, 10, 2)
print(range_arr)

Output:

[0 2 4 6 8]

5. Finding the Mean and Sum

numbers = np.array([10, 20, 30, 40, 50])
print("Sum:", np.sum(numbers))     # 150
print("Mean:", np.mean(numbers))   # 30.0

Conclusion

NumPy is a powerful tool that can make working with numbers much easier and faster. If you want to do more with data, graphs, or scientific computing in the future, learning NumPy is a great first step.

Happy coding!