matplotlib-practice-examples

A collection of simple and intermediate Matplotlib examples taken from the Matplotlib.ipynb notebook. The notebook demonstrates line plots, subplots, custom axes, figure sizing, saving figures, and basic legends — useful for learning plotting idioms in Python.

Quick start

• Requirements: python (3.8+ recommended), matplotlib, numpy, and Jupyter or VS Code.
• Install the required packages with pip:

python -m pip install --user matplotlib numpy jupyterlab

Run the notebook

• Open the notebook and run cells interactively:

jupyter notebook Matplotlib.ipynb
# or open the file in VS Code
code Matplotlib.ipynb

Examples (extracted from Matplotlib.ipynb)

Below are concise, runnable snippets that mirror the notebook examples.

1. Basic plot

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 10, 100)
y = x ** 2

plt.plot(x, y)
plt.title('Plot of y = x^2')
plt.xlabel('x')
plt.ylabel('y')
plt.show()

2. Two subplots (side-by-side) with different styles

plt.subplot(1, 2, 1)
plt.plot(x, y, 'r-')
plt.title('Red Line')

plt.subplot(1, 2, 2)
plt.plot(x, y, 'b--')
plt.title('Blue Dashed Line')
plt.show()

3. Creating a figure and axes with add_axes

fig = plt.figure()
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])  # left, bottom, width, height (0-1)
ax.plot(x, y)
ax.set_title('Title')
ax.set_xlabel('X-axis')
ax.set_ylabel('Y-axis')
plt.show()

4. Figure with an inset (larger and smaller axes)

fig = plt.figure()
ax1 = fig.add_axes([0.1, 0.1, 0.8, 0.8])
ax2 = fig.add_axes([0.2, 0.5, 0.4, 0.3])
ax1.plot(x, y)
ax1.set_title('Larger Plot')
ax2.plot(y, x)
ax2.set_title('Smaller Plot')
plt.show()

5. Using subplots to create an axes array

fig, axs = plt.subplots(nrows=1, ncols=2)
axs[0].plot(x, y)
axs[1].plot(x, y, '--')
plt.tight_layout()
plt.show()

6. Figure size, DPI, and saving

fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(10, 7), dpi=100)
plt.tight_layout()
# Save figure to file at higher DPI
fig.savefig('my_figure.png', dpi=200)

7. Plotting multiple lines and showing a legend

fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1])
ax.plot(x, x**2, label='x squared')
ax.plot(x, x**3, label='x cubed')
ax.set_xlabel('X-axis')
ax.set_ylabel('Y-axis')
ax.set_title('Title')
ax.legend()
plt.show()

Notes and next steps

• The notebook contains runnable cells with small explanatory comments and printed outputs — open Matplotlib.ipynb to run everything interactively.
• Running the save example will create my_figure.png in the repository root; include or commit that image if you want a visual reference in this README.
• If you want, I can:
  • add inline images (rendered PNGs) to this README,
  • extract each example into small examples/ scripts, or
  • create a requirements.txt for this repo.