series_id large_stringclasses 182
values | date date32 | value float64 -14,508 119M |
|---|---|---|
ALLACBW027SBOG | 2025-11-05 | 202.6188 |
ALLACBW027SBOG | 2025-11-12 | 202.7449 |
ALLACBW027SBOG | 2025-11-19 | 202.6666 |
ALLACBW027SBOG | 2025-11-26 | 203.044 |
ALLACBW027SBOG | 2025-12-03 | 202.905 |
ALLACBW027SBOG | 2025-12-10 | 202.4437 |
ALLACBW027SBOG | 2025-12-17 | 202.5592 |
ALLACBW027SBOG | 2025-12-24 | 202.4888 |
ALLACBW027SBOG | 2025-12-31 | 199.9801 |
ALLACBW027SBOG | 2026-01-07 | 200.8348 |
ALLACBW027SBOG | 2026-01-14 | 200.8003 |
ALLACBW027SBOG | 2026-01-21 | 200.7346 |
ALLACBW027SBOG | 2026-01-28 | 200.9347 |
ALLACBW027SBOG | 2026-02-04 | 200.4174 |
ALLACBW027SBOG | 2026-02-11 | 200.0495 |
ALLACBW027SBOG | 2026-02-18 | 199.5948 |
ALLACBW027SBOG | 2026-02-25 | 200.4561 |
ALLACBW027SBOG | 2026-03-04 | 200.6296 |
ALLACBW027SBOG | 2026-03-11 | 200.399 |
ALLACBW027SBOG | 2026-03-18 | 200.6549 |
ALLACBW027SBOG | 2026-03-25 | 200.5163 |
ALLACBW027SBOG | 2026-04-01 | 201.0584 |
ALLACBW027SBOG | 2026-04-08 | 202.0502 |
ALLACBW027SBOG | 2026-04-15 | 202.2543 |
ALLACBW027SBOG | 2026-04-22 | 202.0751 |
ALLACBW027SBOG | 2026-04-29 | 202.3751 |
ALLACBW027SBOG | 2026-05-06 | 202.2884 |
ALLACBW027SBOG | 2026-05-13 | 202.4844 |
ALLACBW027SBOG | 2026-05-20 | 202.1087 |
ALLACBW027SBOG | 2026-05-27 | 202.5491 |
ALLACBW027SBOG | 2026-06-03 | 202.5364 |
ALLACBW027SBOG | 2026-06-10 | 202.4927 |
ALLACBW027SBOG | 2026-06-17 | 202.5678 |
ALLACBW027SBOG | 2026-06-24 | 203.3153 |
ALLACBW027SBOG | 2026-07-01 | 201.7663 |
ALLACBW027SBOG | 2026-07-08 | 201.0552 |
ALLACBW027SBOG | 2026-07-15 | 201.9469 |
ALLACBW027SBOG | 2026-07-22 | 201.7772 |
ALLACBW027SBOG | 2026-07-29 | 202.1114 |
ALLACBW027SBOG | 2026-08-05 | 202.2371 |
ALLACBW027SBOG | 2026-08-12 | 202.1301 |
ALLACBW027SBOG | 2026-08-19 | 201.8783 |
ALLACBW027SBOG | 2026-08-26 | 202.3713 |
ALLACBW027SBOG | 2026-09-02 | 202.476 |
ALLACBW027SBOG | 2026-09-09 | 202.37 |
ALLACBW027SBOG | 2026-09-16 | 202.4924 |
ALLACBW027SBOG | 2026-09-23 | 203.1424 |
ALLACBW027SBOG | 2026-09-30 | 201.3953 |
ALLACBW027SBOG | 2026-10-07 | 202.1391 |
ALLACBW027SBOG | 2026-10-14 | 202.2297 |
ALLACBW027SBOG | 2026-10-21 | 202.144 |
AOLACBW027SBOG | 2025-11-05 | 2,954.7238 |
AOLACBW027SBOG | 2025-11-12 | 2,969.8175 |
AOLACBW027SBOG | 2025-11-19 | 2,975.384 |
AOLACBW027SBOG | 2025-11-26 | 2,989.4457 |
AOLACBW027SBOG | 2025-12-03 | 2,984.2234 |
AOLACBW027SBOG | 2025-12-10 | 3,004.9718 |
AOLACBW027SBOG | 2025-12-17 | 3,007.4124 |
AOLACBW027SBOG | 2025-12-24 | 3,019.1467 |
AOLACBW027SBOG | 2025-12-31 | 3,034.5307 |
AOLACBW027SBOG | 2026-01-07 | 3,048.5862 |
AOLACBW027SBOG | 2026-01-14 | 3,060.4984 |
AOLACBW027SBOG | 2026-01-21 | 3,077.8128 |
AOLACBW027SBOG | 2026-01-28 | 3,081.844 |
AOLACBW027SBOG | 2026-02-04 | 3,096.893 |
AOLACBW027SBOG | 2026-02-11 | 3,114.4124 |
AOLACBW027SBOG | 2026-02-18 | 3,121.1831 |
AOLACBW027SBOG | 2026-02-25 | 3,131.1321 |
AOLACBW027SBOG | 2026-03-04 | 3,131.7599 |
AOLACBW027SBOG | 2026-03-11 | 3,146.2958 |
AOLACBW027SBOG | 2026-03-18 | 3,142.1663 |
AOLACBW027SBOG | 2026-03-25 | 3,158.8388 |
AOLACBW027SBOG | 2026-04-01 | 3,198.6988 |
AOLACBW027SBOG | 2026-04-08 | 3,203.1729 |
AOLACBW027SBOG | 2026-04-15 | 3,208.1481 |
AOLACBW027SBOG | 2026-04-22 | 3,211.5316 |
AOLACBW027SBOG | 2026-04-29 | 3,207.002 |
AOLACBW027SBOG | 2026-05-06 | 3,218.462 |
AOLACBW027SBOG | 2026-05-13 | 3,232.0365 |
AOLACBW027SBOG | 2026-05-20 | 3,241.7205 |
AOLACBW027SBOG | 2026-05-27 | 3,244.8296 |
AOLACBW027SBOG | 2026-06-03 | 3,234.8608 |
AOLACBW027SBOG | 2026-06-10 | 3,262.2493 |
AOLACBW027SBOG | 2026-06-17 | 3,266.5765 |
AOLACBW027SBOG | 2026-06-24 | 3,268.1551 |
AOLACBW027SBOG | 2026-07-01 | 3,287.1938 |
AOLACBW027SBOG | 2026-07-08 | 3,289.8533 |
AOLACBW027SBOG | 2026-07-15 | 3,311.3233 |
AOLACBW027SBOG | 2026-07-22 | 3,302.159 |
AOLACBW027SBOG | 2026-07-29 | 3,299.2506 |
AOLACBW027SBOG | 2026-08-05 | 3,319.7709 |
AOLACBW027SBOG | 2026-08-12 | 3,327.4909 |
AOLACBW027SBOG | 2026-08-19 | 3,338.2967 |
AOLACBW027SBOG | 2026-08-26 | 3,345.8855 |
AOLACBW027SBOG | 2026-09-02 | 3,338.5541 |
AOLACBW027SBOG | 2026-09-09 | 3,357.2973 |
AOLACBW027SBOG | 2026-09-16 | 3,370.2775 |
AOLACBW027SBOG | 2026-09-23 | 3,376.7574 |
AOLACBW027SBOG | 2026-09-30 | 3,392.273 |
AOLACBW027SBOG | 2026-10-07 | 3,407.4652 |
US macro data: Money and Credit (182 series)
182 money and credit series from US government sources, cleaned into one consistent format and ready for pandas. This free package holds the last 12 months (2025-11-01 on) of each series' latest values. It is refreshed weekly.
import pandas as pd
df = pd.read_parquet("hf://datasets/FinzData/macro-money-credit/data/long.parquet") # series_id, date, value
wide = pd.read_parquet("hf://datasets/FinzData/macro-money-credit/data/wide_daily.parquet") # one column per series
or datasets.load_dataset("FinzData/macro-money-credit"). Wide tables by frequency: wide_daily (1 series), wide_weekly (38 series), wide_biweekly (1 series), wide_monthly (57 series), wide_quarterly (84 series), wide_other (1 series). series.csv lists every series
with its title, units, frequency and how far back the full history goes.
The full history, point in time, through one API
The FinzData API serves every series back to its first observation, every revision (what was known on any past date, so backtests do not peek at later revisions), and daily updates, in the same format:
import finzdata as fz # pip install finzdata
c = fz.Client() # free API key: https://api.finzdata.com/
c.macro("M2SL") # full history, latest values
c.macro("M2SL", vintage="first") # as first released
c.macro("M2SL", as_of="2020-03-01") # exactly what was known on that date
c.macro_series(category="money_credit") # the catalogue for this category
Most-watched series in this package
| ID | Title | Units | Frequency | Full history from |
|---|---|---|---|---|
M2SL |
M2 | Billions of Dollars | Monthly | 1959 |
GFDEBTN |
Federal Debt: Total Public Debt | Millions of Dollars | Quarterly, End of Period | 1966 |
GFDEGDQ188S |
Federal Debt: Total Public Debt as Percent of Gross Domestic Product | Percent of GDP | Quarterly | 1966 |
WM2NS |
M2 | Billions of Dollars | Weekly, Ending Monday | 1980 |
M2V |
Velocity of M2 Money Stock | Ratio | Quarterly | 1959 |
M1SL |
M1 | Billions of Dollars | Monthly | 1959 |
BOGMBASE |
Monetary Base: Total | Billions of Dollars | Monthly | 1959 |
M2REAL |
Real M2 Money Stock | Billions of 1982-84 Dollars | Monthly | 1959 |
TOTRESNS |
Reserves of Depository Institutions: Total | Billions of Dollars | Monthly | 1959 |
DRTSCILM |
Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms | Percent | Quarterly | 1990 |
DRCLACBS |
Delinquency Rate on Consumer Loans, All Commercial Banks | Percent | Quarterly, End of Period | 1987 |
DPSACBW027SBOG |
Deposits, All Commercial Banks | Billions of U.S. Dollars | Weekly, Ending Wednesday | 1973 |
BUSLOANS |
Commercial and Industrial Loans, All Commercial Banks | Billions of U.S. Dollars | Monthly | 1947 |
TOTBKCR |
Bank Credit, All Commercial Banks | Billions of U.S. Dollars | Weekly, Ending Wednesday | 1973 |
TOTLL |
Loans and Leases in Bank Credit, All Commercial Banks | Billions of U.S. Dollars | Weekly, Ending Wednesday | 1973 |
DRCRELEXFACBS |
Delinquency Rate on Commercial Real Estate Loans (Excluding Farmland), Booked in Domestic Offices, All Commercial Banks | Percent | Quarterly, End of Period | 1991 |
FDHBFIN |
Federal Debt Held by Foreign and International Investors | Billions of Dollars | Quarterly, End of Period | 1970 |
WM1NS |
M1 | Billions of Dollars | Weekly, Ending Monday | 1975 |
DRALACBN |
Delinquency Rate on All Loans, All Commercial Banks | Percent | Quarterly, End of Period | 1985 |
FYGFGDQ188S |
Federal Debt Held by the Public as Percent of Gross Domestic Product | Percent of GDP | Quarterly | 1970 |
M1V |
Velocity of M1 Money Stock | Ratio | Quarterly | 1959 |
DRBLACBS |
Delinquency Rate on Business Loans, All Commercial Banks | Percent | Quarterly, End of Period | 1987 |
M2NS |
M2 | Billions of Dollars | Monthly | 1959 |
TOTALSL |
Total Consumer Credit Owned and Securitized | Millions of U.S. Dollars | Monthly | 1943 |
BCNSDODNS |
Nonfinancial Corporate Business; Debt Securities and Loans; Liability, Level | Millions of U.S. Dollars | Quarterly, End of Period | 1945 |
All 182 series: series.csv. Browse them at https://finzdata.com/macro/category/money-credit.
More from FinzData
- Every macro category: https://huggingface.co/FinzData · index on GitHub: https://github.com/FinzData/macro-data
- Survivorship-free US stock prices since 2000, COT positioning, 13F holdings, insider trades, short interest
- Pricing (history bundles from $195 once): https://finzdata.com/pricing
- Python client (open source): https://github.com/FinzData/finzdata-python
Source: U.S. government agencies via FRED/ALFRED (Federal Reserve Bank of St. Louis). Compiled by FinzData. Data for research, not investment advice.
- Downloads last month
- 358