Iris Dataset Analysis This project performs data loading, cleaning, basic analysis, and visualization using the popular Iris dataset. It is designed for beginners who want to learn pandas, matplotlib, and seaborn for data analysis. 📂 Project Structure

• iris_analysis.py – Main Python script containing:
  • Data loading (using seaborn's built-in Iris dataset)
  • Data cleaning (handling missing values)
  • Basic statistics and grouping
  • Data visualization (line chart, bar chart, histogram, scatter plot) 🛠️ Requirements Make sure you have Python 3 installed. Then install dependencies using:

pip install pandas matplotlib seaborn ▶️ How to Run

1. Clone this repository: git clone https://github.com/yourusername/iris-analysis.git cd iris-analysis

2. Run the script: python iris_analysis.py

3. View the output directly in your terminal (and see charts pop up in separate windows). 📊 Features

• Exploratory Data Analysis: Summarizes dataset statistics, groups by species, and identifies patterns.
• Visualizations: Line chart, bar chart, histogram, and scatter plot to explore data relationships.
• Beginner-Friendly Code: Fully commented for easy understanding. 📷 Example Output Species Avg Petal Length Avg Sepal Length setosa 1.464 5.006 versicolor 4.260 5.936 virginica 5.552 6.588 🤝 Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. 📜 License This project is licensed under the MIT License - feel free to use and modify.