Finance QC clean AI-training-safe

US Treasury Cash Balance & Reverse Repo

The daily Treasury General Account (TGA) closing balance and the Fed's overnight Reverse Repo (RRP) accepted volume, in $ billions, 2018-present - the two biggest swings in US dollar liquidity, served as one clean aligned daily Parquet.

3K
rows
1
zones
2018-2026
coverage
0.1 MB
download
Source
U.S. Treasury
Licence
Redistributable open data
Updates
Daily
Data through
2026-07-31
Quality
QC clean · 0 failures
Format
Apache Parquet + dictionary

Safe to train on

Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.

What's included

  • Daily TGA closing balance + Reverse Repo accepted volume, $ bn, 2018-present
  • series = Treasury General Account / Reverse Repo; one row per series × day
  • TGA from the Daily Treasury Statement; RRP from the NY Fed Markets API
  • Source: U.S. Treasury & Federal Reserve Bank of New York (public domain)

Schema

ColumnTypeDescriptionFilledDistinct
zone str Always US 100.0% 1
ts timestamp (UTC) Trading day 100.0% 2,147
series str Treasury General Account / Reverse Repo 100.0% 2
usd_bn float Balance / accepted volume, $ billions 100.0% 2,995
unit str Unit 100.0% 1
res_min int Native resolution (daily = 1440) 100.0% 1

Sample & preview

Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: U.S. Treasury (redistributable open data; attribution passes through - see our Licence).

Don't trust screenshots - drop the sample into your notebook right now.

import pandas as pd
df = pd.read_parquet("us-treasury-cash-and-repo_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join
⬇ Download free Parquet sample or CSV for Excel
Coverage: 1 zones

US