Software Automation
Matplotlib

Part 1: What is Matplotlib?

Matplotlib is a Python library used for creating graphs and charts. It is especially powerful when used with NumPy arrays.

Why use Matplotlib with NumPy?

• NumPy allows you to generate and manipulate numerical data efficiently.

• Matplotlib takes that data and turns it into clear, informative visuals.

• They work hand-in-hand in data science and machine learning workflows.

Part 2: Setup and Imports

Before we can begin, we need to install and import the right tools.

Step 1: Install Required Libraries (only once)

pip install numpy matplotlib

Step 2: Import NumPy and Matplotlib

import numpy as np

import matplotlib.pyplot as plt

We use np for NumPy and plt for Matplotlib—these are standard abbreviations used in the industry.

Part 6: Exercises

Use NumPy arrays to complete the tasks below. Try to modify and experiment with the values.

🔹 Exercise 1: Line Plot

• Use np.arange() to create x = [0, 1, 2, ..., 10]

• Let y = x ** 2

• Plot x and y with a title, labels, and grid.
  
  

🔹 Exercise 2: Scatter Plot

• Generate two arrays of 100 random values each using np.random.rand(100).

• Create a scatter plot of x vs y.
  
  

🔹 Exercise 3: Bar Chart

• Create arrays for 5 categories and their values.

• Plot them as a bar chart.
  
  

🔹 Exercise 4: Histogram

• Generate 1000 random numbers from a normal distribution using np.random.randn(1000).

• Plot a histogram with 25 bins.
  
  

🔹 Final Challenge

• Create two sets of y-values: y1 = np.sin(x) and y2 = np.cos(x).

• Plot them on the same graph using plt.plot() twice.

• Add a legend using plt.legend() to label each line.