Data Visualization in Matplotlib

This repo contains different data visualization techniques in Python.

Table of Contents

• Introduction
• Installation
• Usage
• Features
• Contributing
• License
• Contact

Introduction

This repository showcases various data visualization techniques using Matplotlib in Python. It is intended to help users understand and implement different types of visualizations for their data analysis projects.

Installation

To get started with this project, clone the repository to your local machine:

git clone https://github.com/Arison99/Data-Visualization-in-Matplotlib.git

Then, navigate to the project directory:

cd Data-Visualization-in-Matplotlib

It's recommended to use a virtual environment for managing dependencies. You can create one using:

python -m venv env

Activate the virtual environment:

• On Windows: env\Scripts\activate
• On macOS/Linux: source env/bin/activate

Install the required packages:

pip install -r requirements.txt

Usage

To use the data visualization scripts, simply run them with Python:

python script_name.py

Replace script_name.py with the name of the script you wish to run.

Features

• Bar Charts: Demonstrates how to create bar charts to compare categorical data.
• Line Graphs: Shows how to plot line graphs to visualize trends over time.
• Scatter Plots: Illustrates how to use scatter plots to identify relationships between variables.
• Histograms: Provides examples of creating histograms for data distribution analysis.

Contributing

Contributions are welcome! If you have any suggestions or improvements, please open an issue or submit a pull request.

1. Fork the repository
2. Create a new branch (git checkout -b feature-branch)
3. Make your changes
4. Commit your changes (git commit -am 'Add new feature')
5. Push to the branch (git push origin feature-branch)
6. Open a pull request

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or inquiries, please reach out to Arison99.

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