A comprehensive guide to visualizing data with Matplotlib, from basic plotting techniques to advanced customization, for effective data storytelling in data science and analysis.
- Introduction
Get started with the basics of Matplotlib and its capabilities. - Basic Plotting
Learn how to create simple plots and visualize data. - Styling Plots
Discover how to customize and style your plots for better presentation. - Sub Plots
Understand how to create and manage multiple plots in a single figure. - Work with Images
Explore techniques for displaying and processing images using Matplotlib - 3D Plotting
Dive into creating and visualizing three-dimensional plots.
- Programming Fundamentals
- Proficiency in Python (data types, control structures, functions, etc.).
- My Python Workshop: github.com/mr-pylin/python-workshop
- Proficiency in Python (data types, control structures, functions, etc.).
- Basic Knowledge of NumPy
- Understanding of NumPy arrays and basic operations.
- My NumPy Workshop: github.com/mr-pylin/numpy-workshop
- Understanding of NumPy arrays and basic operations.
This project was developed using Python v3.12.3. If you encounter issues running the specified version of dependencies, consider using this specific Python version.
You can install all dependencies listed in requirements.txt using pip.
pip install -r requirements.txt- Open the root folder with VS Code
- Windows/Linux:
Ctrl + Kfollowed byCtrl + O - macOS:
Cmd + Kfollowed byCmd + O
- Windows/Linux:
- Open
.ipynbfiles using Jupyter extension integrated with VS Code - Allow VS Code to install any recommended dependencies for working with Jupyter Notebooks.
- Note: Jupyter is integrated with both VS Code & Google Colab
- Matplotlib Website:
- The official website for Matplotlib, providing information, tutorials, and resources for the Matplotlib library
- Official site: matplotlib.org
- Matplotlib Documentation:
- Comprehensive guide and reference for all functionalities and features of the Matplotlib library
- Doc: matplotlib.org/stable/index.html
- Matplotlib Source Code:
- Over 1000 contributors are currently working on Matplotlib!
- Link: github.com/matplotlib/matplotlib
- Matplotlib Cheatsheets & Handouts
- Cheatsheets [pdf]:
- Handouts [pdf]:
- Looking Ahead:
- Seaborn
- A statistical data visualization library based on Matplotlib
- Official site: seaborn.pydata.org
- My Seaborn Workshop: Coming Soon
- Plotly
- An interactive graphing library for Python
- Official site: plotly.com
- My Plotly Workshop: Coming Soon
- Seaborn
Any mistakes, suggestions, or contributions? Feel free to reach out to me at:
I look forward to connecting with you! 🏃♂️
- Digital Image Processing by Gonzalez & Woods:
- The images located in the ./assets/images/third_party/dip_3rd/ folder are licensed under the table below.
- Resources are available for
personal educational or research purposesat imageprocessingplace.com.
| Image | Copyright Owner | Address |
|---|---|---|
| CH02_Fig0222(b)(cameraman).tif | Massachusetts Institute of Technology | MIT.edu |
| CH06_Fig0638(a)(lenna_RGB).tif | Public domain | - |
This project is licensed under the Apache License 2.0.
You are free to use, modify, and distribute this code, but you must include copies of both the LICENSE and NOTICE files in any distribution of your work.
-
Original Images:
- The images located in the ./assets/images/original/ folder are licensed under the CC BY-ND 4.0.
- Note: This license restricts derivative works, meaning you may share these images but cannot modify them.
-
Third-Party Assets:
- Additional images located in ./assets/images/third_party/ are used with permission or according to their original licenses.
- Attributions and references to original sources are included in the code where these images are used.