https://github.com/mdaffailhami/customer-data-analysis

This repository contains code and analysis for exploring customer data, focusing on profiling and contact preferences. 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.
https://github.com/mdaffailhami/customer-data-analysis

data-analysis data-cleaning data-science data-visualization jupyter jupyter-notebook pandas plotly python

Last synced: 26 days ago
JSON representation

This repository contains code and analysis for exploring customer data, focusing on profiling and contact preferences. 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.

• Host: GitHub
• URL: https://github.com/mdaffailhami/customer-data-analysis
• Owner: mdaffailhami
• License: mit
• Created: 2024-08-07T13:22:00.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-08-13T08:55:59.000Z (3 months ago)
• Last Synced: 2024-09-28T23:21:21.373Z (about 1 month ago)
• Topics: data-analysis, data-cleaning, data-science, data-visualization, jupyter, jupyter-notebook, pandas, plotly, python
• Language: Jupyter Notebook
• Homepage:
• Size: 54.7 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Customer Data Analysis

This repository contains code and analysis for exploring customer data, focusing on profiling and contact preferences. 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.

## Features

- **Data Cleaning**: Prepares the dataset by removing inconsistencies and filling missing values.

- **Exploratory Analysis**: Analyzes customer profiles and contact preferences to identify patterns.

- **Data Visualization**: Utilizes graphs and charts to illustrate findings and trends.

- **Customer Profiling**: Provides insights into customer behavior and geographical distribution.

## Technologies Used

- **Python**

- **Jupyter**

- **Pandas**

- **Plotly**

## Contributing

Feel free to contribute to the project by submitting issues, suggesting improvements, or making pull requests.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contact

For questions or feedback, please reach out to [[email protected]](mailto:[email protected]).