This project demonstrates how to load, analyze, and visualize the famous Iris dataset using Python, Pandas, and Matplotlib.
The Iris dataset is one of the most popular datasets in machine learning, containing measurements of iris flowers across three species: Setosa, Versicolor, and Virginica.
- Load the Iris dataset directly from scikit-learn.
- Perform quick data exploration with:
- Dataset head preview
- Info (column types, non-null counts)
- Statistical summary
- Class distribution
- Visualize the dataset with:
- 📊 Histogram → Distribution of petal lengths
- 🔵 Scatter Plot → Sepal length vs. sepal width (colored by species)
- 🟧 Bar Chart → Average petal length per species
- 🟢 Line Chart → Petal length trend for the first 50 samples
Make sure you have the following installed:
- Python 3.8+
- Pandas
- Matplotlib
- scikit-learn
You can install dependencies with:
pip install pandas matplotlib scikit-learn
python iris_analysis.py