This repository contains Jupyter notebooks that demonstrate data visualization techniques using the Seaborn library in Python. The project is centered around analyzing and visualizing the diamonds.csv dataset, providing insights into various features of the dataset through visual representation.
To run the notebooks in this project, you'll need to have Python installed, along with the following libraries:
seabornpandasmatplotlibjupyter
You can install the required libraries by running:
pip install seaborn pandas matplotlib jupyter
## Usage
### Clone the repository:
```bash
git clone https://github.com/sujal-GITHUB/Seaborn.gitcd Seabornjupyter notebookOpen and run the notebooks (1.ipynb and 2.ipynb) to view the visualizations and analysis.
The diamonds.csv dataset contains the following attributes related to diamonds:
- Carat: Weight of the diamond
- Cut: Quality of the cut (Fair, Good, Very Good, Premium, Ideal)
- Color: Diamond color, with D being the best
- Clarity: Diamond clarity (I1, SI1, SI2, VS1, VS2, VVS1, VVS2, IF)
- Price: Price in USD
- X, Y, Z: Length, width, and depth of the diamond
This dataset is used to explore relationships between various features and to create meaningful visualizations.
Contributions are welcome! If you'd like to contribute to this project, please follow these steps:
- Fork the repository.
- Create a new branch (
git checkout -b feature-branch). - Commit your changes (
git commit -m 'Add new feature'). - Push to the branch (
git push origin feature-branch). - Create a new Pull Request.
This project is licensed under the MIT License. See the LICENSE file for more details.