Foreign Direct Investment (FDI) Data Analysis and Dashboard

This repository contains an exploratory data analysis (EDA) and visualization project on a dataset of Foreign Direct Investment (FDI) by companies. The objective is to analyze FDI trends and present key insights through an interactive Tableau dashboard.

Project Overview

The project involves the following steps:

1. Data Cleaning and Preprocessing: Handling missing values, correcting data types, and performing feature engineering.
2. Exploratory Data Analysis (EDA): Using Python to analyze data distributions, identify patterns, and detect anomalies.
3. Visualization: Creating a Tableau dashboard to present key findings and metrics.

Repository Structure

Foreign-Direct-Investment-Analytics/
│
├── data/
│   ├── processed/
│
├── notebooks/
│   └── EDA.ipynb
│
├── tableau/
│   └── FDI_Dashboard.twbx
│
├── images/
│   └── dashboard_screenshot.png
│
└── README.md

• data/: Contains processed datasets.
• notebooks/: Jupyter notebooks used for data cleaning and exploratory data analysis.
• tableau/: Tableau workbook file containing the dashboard.
• images/: Screenshot of the Tableau dashboard.

Tableau Dashboard

The Tableau dashboard provides insights into:

• Yearly trends and patterns in FDI
• Top sectors attracting FDI.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

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