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The project includes various stages of data processing, from raw data preparation to final cleaned datasets, and employs Python and popular data analysis libraries to uncover insights and trends.\n\n## Features\n\n- **Data Cleaning**: Prepares the dataset by removing inconsistencies and filling missing values.\n- **Exploratory Analysis**: Analyzes customer profiles and contact preferences to identify patterns.\n- **Data Visualization**: Utilizes graphs and charts to illustrate findings and trends.\n- **Customer Profiling**: Provides insights into customer behavior and geographical distribution.\n\n## Technologies Used\n\n- **Python**\n- **Jupyter**\n- **Pandas**\n- **Plotly**\n\n## Contributing\n\nFeel free to contribute to the project by submitting issues, suggesting improvements, or making pull requests.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nFor questions or feedback, please reach out to [mdaffailhami@gmail.com](mailto:mdaffailhami@gmail.com).\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmdaffailhami%2Fcustomer-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmdaffailhami%2Fcustomer-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmdaffailhami%2Fcustomer-data-analysis/lists"}