CyberMax-tools/curvewire-us-macro-panel

Curvewire: US Treasury yield curve + BLS macro panel

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Need it fresh, filtered or via API? This free file is a snapshot (US macro series up to the last refresh), last updated 2026-09-24.

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Information only, not investment advice.

The US numbers macro models, trading bots and LLM agents ask for most, taken straight from the agencies that publish them (US Treasury and the Bureau of Labor Statistics), not scraped from redistributors, and cleaned into three tidy tables:

config	rows	what
treasury_yields (default)	9,189	Daily par yield curve, 1 month to 30 years, 1990-01-02 → 2026-09-23, with 10y–2y and 10y–3m spreads
treasury_real_yields	5,936	Daily real (TIPS) par yield curve, 5 to 30 years, 2003-01-02 → 2026-09-23
bls_monthly	7,514	15 headline monthly series in long format, with 1-month and 12-month changes

Latest readings in this build (see meta.json): 10-year yield 5.11%, 2-year 4.85% (10y–2y spread +0.26 pt), 3-month 4.19%; August 2026 CPI +3.35% year on year (core +2.45%), unemployment rate 4.1%, payrolls +162k on the month; JOLTS job openings 7.27 million (July).

BLS series included

series_id	series	units
CUSR0000SA0 / CUUR0000SA0	CPI-U, all items (seasonally adjusted / not)	index 1982-84=100
CUSR0000SA0L1E	Core CPI (less food and energy)	index
CUSR0000SAF1, CUSR0000SA0E, CUSR0000SAH1	CPI food, energy, shelter	index
CES0000000001	Total nonfarm payrolls	thousands
CES0500000003, CES0500000002	Average hourly earnings, average weekly hours (private)	USD, hours
LNS14000000, LNS11300000, LNS12300000	Unemployment rate, participation rate, employment-population ratio	percent
JTS000000000000000JOL, JTS000000000000000QUR	JOLTS job openings, quits rate	thousands, percent
WPSFD4	PPI final demand	index

bls_monthly columns: series_id, series_name, units, seasonally_adjusted, date (first day of the month), value, footnote_codes (BLS codes, e.g. P = preliminary), change_1m, pct_change_1m, pct_change_12m (null for series already in percent), change_12m.

treasury_yields columns: date, y_1m, y_6w (1.5-month bill, from 2025), y_2m, y_3m, y_4m, y_6m, y_1y, y_2y, y_3y, y_5y, y_7y, y_10y, y_20y, y_30y (percent), spread_10y_2y, spread_10y_3m (percentage points). Maturities Treasury didn't publish on a date (e.g. 20-year before 1993, 30-year in 2002–2006) are null.

Use it

from datasets import load_dataset
curve = load_dataset("CyberMax-tools/curvewire-us-macro-panel", "treasury_yields", split="train").to_pandas()
print(curve[curve.spread_10y_2y < 0].date.agg(["min", "max", "count"]))   # inversion days

bls = load_dataset("CyberMax-tools/curvewire-us-macro-panel", "bls_monthly", split="train").to_pandas()
cpi = bls[bls.series_id == "CUSR0000SA0L1E"].set_index("date")["pct_change_12m"]
print(cpi.tail(12))   # core CPI inflation, last 12 months

Refresh and revisions

Rebuilt from the agencies' own files (Treasury's daily CSVs, BLS bulk time-series files); meta.json has the build time and each series' latest month. BLS revises recent months (payrolls for two months, CPI seasonal factors each February), and every refresh picks the revisions up, so always use the latest build rather than stitching old ones together.

Licence

US Treasury and BLS data are works of the US federal government, in the public domain; this compilation is released under CC0 1.0. Please cite the agencies as the source. Compiled by CyberMax. Not affiliated with or endorsed by the US Treasury or BLS. Not investment advice. Series from redistributors with third-party copyright (e.g. some FRED series) are deliberately not included.

Also from CyberMax

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Quickstart notebook

Load this dataset with pandas and see real outputs in the quickstart notebook.