Iris-DataSet-Analysis

This project explores the classic Iris dataset using Python libraries such as pandas, matplotlib, seaborn, and scikit-learn. It performs data inspection, computes summary statistics, and visualizes key relationships between iris flower features.

Features

• Load the Iris dataset with scikit-learn.

• Inspect dataset preview, info, and missing values.

• Compute basic statistics for numerical columns.

• Calculate mean values grouped by species.

• Generate visualizations:

  • Line plot of petal length over samples.
  • Bar chart of average petal length per species.
  • Histogram of sepal length distribution.
  • Scatter plot of sepal vs petal length by species.

Requirements

• Python 3.7+
• pandas
• matplotlib
• seaborn
• scikit-learn

Install dependencies with:

pip install pandas matplotlib seaborn scikit-learn

Usage

Run the script:

python iris_analysis.py

The script will display dataset insights in the console and show the plots sequentially.

See Full Docs

https://hackmd.io/@I5OyzHQDSGWGWqeLjg1tSg/rkE0cA43xx