"The Iris Unfolded" is a data visualization project that delves into the classic Iris dataset. This project employs a range of visualization techniques to explore the relationships, patterns, and distributions within the dataset, which includes 150 samples across three species of Iris flowers.
- Visualizations of sepal length, sepal width, petal length, and petal width.
- Analysis of relationships between various features of the Iris species.
- Utilization of Python libraries such as Matplotlib and Seaborn for creating plots.
- Scatter Plot
- Pair Plot
- Box Plot
- Violin Plot
- Histogram
- Heatmap of Correlation Matrix
- Swarm Plot
- Python 3.x
- Pandas
- Matplotlib
- Seaborn
To set up the project environment:
- Clone the repository: git clone https://github.com/miliansolberg/Iris-Dataset-Visualization
- Install the required Python packages: pip install pandas matplotlib seaborn
Run the Jupyter notebooks or Python scripts included in the project. Each script corresponds to a different type of visualization.
The Iris dataset used in this project is a popular dataset in data science and machine learning, often used for classification and visualization tasks. It can be found here: https://archive.ics.uci.edu/dataset/53/iris
This project is available under the MIT License.
Special thanks to the creators of the Iris dataset and the Python community for the excellent visualization libraries.