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This project provides a comprehensive framework for performing exploratory data analysis (EDA) on datasets. It generates summary statistics, visualizations, and correlation heatmaps to help users uncover insights from their data. Ideal for data scientists looking to enhance their EDA skills, this project emphasizes data-driven decision-making.

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Exploratory Data Analysis (EDA) Project

Overview

This project performs exploratory data analysis (EDA) on a given dataset. It includes generating summary statistics, visualizations, and correlation heatmaps.

Project Structure

        eda-project /
                    │ 
                    ├── data/ # Data files 
                            │ 
                            └── dataset.csv # Example dataset 
                    ├── src/ 
                           │ 
                           ├── eda.py # EDA script 
                           │ 
                           └── utils.py # Utility functions
                    ├── tests/ # Test scripts 
                             │ 
                             └── test_utils.py # Unit tests for utilities 
                    ├── requirements.txt # Dependencies 
                    └── README.md # Project documentation 

Installation

  1. Clone the repository:

    git clone https://github.com/karimosman89/eda-project.git
    cd eda-project
    
  2. Install the required packages:

       pip install -r requirements.txt
    

Usage

  1. Prepare your dataset in the /data directory and name it dataset.csv.

  2. Run the EDA script:

       python src/eda.py
    

Testing

 python -m unittest discover -s tests

License

This project is licensed under the MIT License.

About

This project provides a comprehensive framework for performing exploratory data analysis (EDA) on datasets. It generates summary statistics, visualizations, and correlation heatmaps to help users uncover insights from their data. Ideal for data scientists looking to enhance their EDA skills, this project emphasizes data-driven decision-making.

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