Matplotlib Visualization Practice

This repository contains a collection of Python scripts and Jupyter Notebooks created as part of my journey to master data visualization with Matplotlib. As an AIML student, I'm using this space to practice, experiment, and document my learning process.

📈 Notebooks in this Repository

1. 3D Scatter Plot (Phase1 MatPlotLib.ipynb)

• Description: This notebook demonstrates how to create a 3D scatter plot using Matplotlib's mplot3d toolkit. It visualizes randomly generated sinusoidal data points in three dimensions, showcasing the use of color maps (cmap) to represent data depth.
• Key Concepts: plt.figure(), fig.add_subplot(projection='3d'), ax.scatter().

(More visualizations will be added as I continue to explore the library...)

🛠️ Technologies Used

• Python
• Matplotlib
• NumPy
• Jupyter Notebook

🚀 Getting Started

To run these notebooks on your local machine, follow these steps:

1. Clone the repository:

   git clone [https://github.com/parikhdev/MatPlotLib-.git](https://github.com/parikhdev/MatPlotLib-.git)

2. Navigate to the project directory:

   cd MatPlotLib-

3. Install the required libraries:

   pip install matplotlib numpy jupyterlab

4. Launch Jupyter Lab and open a notebook:

   jupyter lab

👤 Author

• Yash Parikh - parikhdev