Employee Network Analysis

This project was created for DataCamp competition on network analysis. The aim of this study is to create an employee network using message data and use this network to gain insight on relationships among employess and departments.

It is built using Python and several libraries for data analysis and visualization, including NetworkX, Pandas, and Matplotlib.

Data

Data is provided in 2 separate files: "employees.csv" and "messages.csv"

• Messages has information on the sender, receiver, time and message length
• Employees has information on each employee including id, department, location and age.

Analysis

The project includes several features to analyze the employee network:

• Network visualization: A non directional weighted graph is produced using the NetworkX library. The graph nodes contain information on different aspects of the network, such as the departments or ages of the employees.

• Data Analysis: Relationships between messages and age, department and date are explored using graph data.

• Centrality metrics: Several centrality metrics are calculated including degree centrality, betweenness centrality. These metrics are to identify the most important employees in the network.

Installation

To install the required libraries, you can use pip:

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pip install networkx pandas matplotlib

You will also need to download the data files from the data folder in this repository.

Usage

The main entry point for the project is the employee_network_analysis.py script. You can run it from the command line:

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python employee_network_analysis.py

This will load the data, analyze the network, and produce several graphs and metrics.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contributing

Contributions are welcome! If you want to contribute to this project, please fork the repository and submit a pull request with your changes.