FRED Economic Data Analysis Tool

A comprehensive Python tool for collecting, analyzing, and visualizing Federal Reserve Economic Data (FRED) using the FRED API.

Features

Data Collection: Fetch economic indicators from FRED API
Data Analysis: Generate summary statistics and insights
Visualization: Create time series plots and charts
Data Export: Save data to CSV format
Flexible Configuration: Easy customization of indicators and date ranges

Setup

1. Install Dependencies

pip install -r requirements.txt

2. API Key Configuration

Get your FRED API key from FRED API
Copy .env.example to .env:
```
cp .env.example .env
```
Edit .env and add your API key:
```
FRED_API_KEY=your_actual_api_key_here
```

3. Project Structure

FRED_ML/
├── config/               # Configuration settings
│   ├── settings.py       # Environment variables and settings
│   └── pipeline.yaml     # Pipeline configuration
├── src/                  # Source code
│   ├── core/            # Core functionality
│   ├── analysis/        # Analysis modules
│   ├── utils/           # Utility functions
│   └── visualization/   # Visualization modules
├── scripts/             # Executable scripts
├── tests/               # Test files
├── data/                # Data directories
│   ├── raw/            # Raw data
│   ├── processed/      # Processed data
│   └── exports/        # Exported files
├── requirements.txt     # Python dependencies
├── .env.example        # Environment variables template
└── README.md           # This file

Usage

Basic Usage

Run the EDA script to perform exploratory data analysis:

python scripts/run_eda.py

Or run the advanced analytics:

python scripts/run_advanced_analytics.py

This will:

Fetch data for key economic indicators (GDP, Unemployment Rate, CPI, Federal Funds Rate, 10-Year Treasury Rate)
Generate summary statistics
Create visualizations
Save data to CSV files

Custom Analysis

You can customize the analysis by importing the modules:

from src.core.fred_client import FREDDataCollectorV2
from src.analysis.advanced_analytics import AdvancedAnalytics

# Initialize collector
collector = FREDDataCollectorV2()

# Custom series and date range
custom_series = ['GDP', 'UNRATE', 'CPIAUCSL']
start_date = '2020-01-01'
end_date = '2024-01-01'

# Run analysis
df, summary = collector.run_analysis(
    series_ids=custom_series,
    start_date=start_date,
    end_date=end_date
)

Available Economic Indicators

The tool includes these common economic indicators:

Series ID	Description
GDP	Gross Domestic Product
UNRATE	Unemployment Rate
CPIAUCSL	Consumer Price Index
FEDFUNDS	Federal Funds Rate
DGS10	10-Year Treasury Rate
DEXUSEU	US/Euro Exchange Rate
PAYEMS	Total Nonfarm Payrolls
INDPRO	Industrial Production
M2SL	M2 Money Stock
PCE	Personal Consumption Expenditures

Output Files

Data Files

CSV files saved in the data/ directory
Timestamped filenames (e.g., fred_economic_data_20241201_143022.csv)

Visualization Files

PNG plots saved in the plots/ directory
High-resolution charts with economic indicator time series

API Rate Limits

The FRED API has rate limits:

120 requests per minute
1000 requests per day

The tool includes error handling for rate limit issues.

Configuration

Edit config/settings.py to customize:

Default date ranges
Output directories
Default indicators

The API key is now managed through environment variables (see Setup section above).

Dependencies

fredapi: FRED API client
pandas: Data manipulation
numpy: Numerical computing
matplotlib: Plotting
seaborn: Statistical visualization
jupyter: Interactive notebooks (optional)

Error Handling

The tool includes comprehensive error handling for:

API connection issues
Invalid series IDs
Rate limit exceeded
Data format errors

Contributing

To add new features:

Extend the FREDDataCollector class
Add new methods for specific analysis
Update the configuration as needed

License

This project is for educational and research purposes. Please respect FRED API terms of service.

Support

For issues with the FRED API, visit: https://fred.stlouisfed.org/docs/api/