This project utilizes the Federal Reserve Economic Data (FRED) API and Python's Pandas library to gather, clean, and analyze economic data. The project walks through the process of pulling down data for various economic indicators, cleaning and joining the data, and using the FRED API to obtain up-to-date data.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
![Demo Screenshot]
- A FRED API key, which can be obtained here
- Python 3
- Required libraries:
- pandas
- requests
- Fred
1. Clone the repository to your local machine using `git clone https://github.com/TABREZ-96/Economic-Intelligence.git`
2. Navigate to the project directory using `cd EconomicDataAnalysis`
3. Install the required libraries by running `pip install -r requirements.txt`
4. Add your FRED API key to the `main.py` file.
1. Run the script using `python main.py`. The script will automatically retrieve the data from the FRED API and perform data cleaning and joining.
2. The script will then perform analysis on the unemployment rate as an example.
3. You can also explore the data by running different query and comparison on the data.
- The script can be modified to retrieve data on other metrics and perform analysis on them by replacing the series id and variable name in the `main.py` file.
- The script can also be modified to include additional data cleaning, joining, analysis, or visualization.
-Fork the repo
If you found this project helpful or you learned something from it and want to show your appreciation, you can buy me a coffee. Your support will help me to continue maintaining and updating this project.
- TABREZ SAYED - ECONOMIC INTELLGENCE
This project is licensed under the MIT License - see the LICENSE.md file for details
- FRED API for providing the economic data
- Python's Pandas library for data manipulation
- Inspiration from other data analysis projects
If you have any question or feedback, feel free to reach out to me via github or email.