fred-economic-data

Files (12)

• SKILL.md
• api_basics.md · references/
• categories.md · references/
• geofred.md · references/
• releases.md · references/
• series.md · references/
• sources.md · references/
• tags.md · references/
• fred_examples.cpython-313.pyc · scripts/__pycache__/
• fred_query.cpython-313.pyc · scripts/__pycache__/
• fred_examples.py · scripts/
• fred_query.py · scripts/

SKILL.md (first lines)

# FRED Economic Data Access

## Overview

Access comprehensive economic data through FRED (Federal Reserve Economic Data), a database maintained by the Federal Reserve Bank of St. Louis containing over 800,000 economic time series from over 100 sources.

**Key capabilities:**
- Query economic time series data (GDP, unemployment, inflation, interest rates)
- Search and discover series by keywords, tags, and categories
- Access historical data and vintage (revision) data via ALFRED
- Retrieve release schedules and data publication dates
- Map regional economic data with GeoFRED
- Apply data transformations (percent change, log, etc.)

## API Key Setup

**Required:** All FRED API requests require an API key.

1. Create an account at https://fredaccount.stlouisfed.org
2. Log in and request an API key through the account portal
3. Set as environment variable:

```bash
export FRED_API_KEY="your_32_character_key_here"
```

Or in Python:
```python
import os
os.environ["FRED_API_KEY"] = "your_key_here"
```

## Quick Start

### Using the FREDQuery Class

```python
from scripts.fred_query import FREDQuery

# Initialize with API key
fred = FREDQuery(api_key="YOUR_KEY")  # or uses FRED_API_KEY env var

# Get GDP data
gdp = fred.get_series("GDP")
print(f"Latest GDP: {gdp['observations'][-1]}")

# Get unemployment rate observations
unemployment = fred.get_observations("UNRATE", limit=12)
for obs in unemployment["observations"]:
    print(f"{obs['date']}: {obs['value']}%")

# Search for inflation series
inflation_series = fred.search_series("consumer price index")
for s in inflation_series["seriess"][:5]:
    print(f"{s['id']}: {s['title']}")
```

### Direct API Calls

```python
import requests
import os

API_KEY = os.environ.get("FRED_API_KEY")
BASE_URL = "https://api.stlouisfed.org/fred"

# Get series observations
response = requests.get(
    f"{BASE_URL}/series/observations",
    params={
        "api_key": API_KEY,
        "series_id": "GDP",
        "file_type": "json"
    }
)
data = response.json()
```

## Popular Economic Series

| Series ID | Description | Frequency |
|-----------|-------------|-----------|
| GDP | Gross Domestic Product | Quarterly |
| GDPC1 | Real Gross Domestic Product | Quarterly |
| UNRATE | Unemployment Rate | Monthly |
| CPIAUCSL | Consumer Price Index (All Urban) | Monthly |
| FEDFUNDS | Federal Funds Effective Rate | Monthly |
| DGS10 | 10-Year Treasury Constant Maturity | Daily |
| HOUST | Housing Starts | Monthly |
| PAYEMS | Total Nonfarm Payrolls | Monthly |
| INDPRO | Industrial Production Index | Monthly |
| M2SL | M2 Money Stock | Monthly |
| UMCSENT | Consumer Sentiment | Monthly |
| SP500 | S&P 500 | Daily |

## API Endpoint Categories

### Series Endpoints

Get economic data series metadata and observations.

**Key endpoints:**
- `fred/series` - Get series metadata
- `fred/series/observations` - Get data values (most commonly used)
- `fred/series/search` - Search for series by keywords
- `fred/series/updates` - Get recently updated series

```python
# Get observations with transformations
obs = fred.get_observations(
    series_id="GDP",
    units="pch",  # percent change
    frequency="q",  # quarterly
    observation_start="2020-01-01"
)

# Search with filters
results = fred.search_series(
    "unemployment",

From lamm-mit/scienceclaw, Apache-2.0.

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