FRED Data Viz
/install fred-data-viz
FRED Data Visualization
Create indexed comparison charts from Federal Reserve Economic Data (FRED) series.
Quick Start
For a simple two-series comparison:
python3 scripts/fred_chart.py --config chart_config.json --output chart.png
Workflow
1. Identify the FRED series
Find series IDs at fred.stlouisfed.org:
| Indicator | Common Series |
|---|---|
| Real GDP | GDPC1 |
| GDP Per Capita | A939RX0Q048SBEA (or compute from GDPC1 + POPTHM) |
| Compensation Per Hour | COMPRNFB |
| Median Weekly Earnings | LES1252881600Q |
| Corporate Profits | CP |
| CPI | CPIAUCSL |
| Unemployment | UNRATE |
2. Create config JSON
{
"title": "USA: GDP vs Wages (1959 = 100)",
"series": [
{
"id": "A939RX0Q048SBEA",
"label": "Real GDP Per Capita",
"color": "#2E86AB"
},
{
"id": "COMPRNFB",
"label": "Real Compensation Per Hour",
"color": "#F18F01"
}
],
"start_date": "1959-01-01",
"end_date": "2026-12-31",
"fill_gap": true,
"annotations": [
{
"date": "1971-08-15",
"label": "Nixon Shock",
"position": "top",
"y": 140
}
]
}
Config fields:
title: Chart titleseries[].id: FRED series IDseries[].label: Legend labelseries[].color: Optional hex colorstart_date/end_date: Date range filterfill_gap: Shade area between first two series (default: true)annotations[].date: Event date (YYYY-MM-DD)annotations[].label: Event text (supports newlines with\)annotations[].position:"top"or"bottom"annotations[].y: Vertical position for label placement
3. Generate chart
python3 scripts/fred_chart.py --config my_chart.json --output my_chart.png
Advanced: GDP Per Capita Calculation
When FRED lacks a direct GDP per capita series, compute it from GDP (GDPC1) and population (POPTHM):
# gdp_pc = (GDP in billions * 1e9) / (Population in thousands * 1e3)
# Or use the pre-computed series: A939RX0Q048SBEA (available from 1979)
# For earlier dates, manual calculation required
Tips
- Indexing: All series are automatically indexed to their first observation (set to 100) for fair comparison
- Annotations: Use
\for multi-line labels. Position alternates top/bottom to avoid overlap - Zooming: Use
start_date/end_dateto focus on specific eras (e.g., 1959-1985) - Colors: Choose contrasting colors. Blue (#2E86AB) and orange (#F18F01) work well
- Multiple series: Up to 5 series supported. Gap fill only applies to first two
Common Chart Patterns
| Pattern | Series | Use Case |
|---|---|---|
| Productivity-Pay Gap | A939RX0Q048SBEA, COMPRNFB |
Show worker compensation vs economic output |
| Wage-Inflation Comparison | CES0500000003, CPIAUCSL |
Real vs nominal wage growth |
| Profit-Wage Divergence | CP, COMPRNFB |
Where surplus goes |
| Historical Events | Any + annotations | Annotated economic timeline |
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install fred-data-viz - After installation, invoke the skill by name or use
/fred-data-viz - Provide required inputs per the skill's parameter spec and get structured output
What is FRED Data Viz?
Create publication-ready economic comparison charts from Federal Reserve Economic Data (FRED). Use when the user needs to visualize, compare, or analyze econ... It is an AI Agent Skill for Claude Code / OpenClaw, with 47 downloads so far.
How do I install FRED Data Viz?
Run "/install fred-data-viz" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is FRED Data Viz free?
Yes, FRED Data Viz is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does FRED Data Viz support?
FRED Data Viz is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created FRED Data Viz?
It is built and maintained by Pratyush Chauhan (@pratyushchauhan); the current version is v1.0.0.