Datasets:

FinzData
/

macro-other-indicators

---
license: other
license_name: public-domain-source-us-government
pretty_name: "US Macro Data: Other Indicators"
language:
- en
tags:
- finance
- economics
- macroeconomics
- time-series
- fred
- other-indicators
- quant
- backtesting
size_categories:
- 10K<n<100K
configs:
- config_name: long
  data_files: data/long.parquet
  default: true
- config_name: wide_daily
  data_files: data/wide_daily.parquet
- config_name: wide_weekly
  data_files: data/wide_weekly.parquet
- config_name: wide_monthly
  data_files: data/wide_monthly.parquet
- config_name: wide_quarterly
  data_files: data/wide_quarterly.parquet
- config_name: wide_annual
  data_files: data/wide_annual.parquet
- config_name: wide_other
  data_files: data/wide_other.parquet
---
# US macro data: Other Indicators (363 series)

363 other indicators series from US government sources, cleaned into one consistent format and ready for pandas.
This free package holds the **last 12 months** (2025-11-02 on) of each series' latest values. It is refreshed weekly.

```python
import pandas as pd
df = pd.read_parquet("hf://datasets/FinzData/macro-other-indicators/data/long.parquet")      # series_id, date, value
wide = pd.read_parquet("hf://datasets/FinzData/macro-other-indicators/data/wide_daily.parquet")  # one column per series
```

or `datasets.load_dataset("FinzData/macro-other-indicators")`. Wide tables by frequency: `wide_daily` (36 series), `wide_weekly` (31 series), `wide_monthly` (151 series), `wide_quarterly` (132 series), `wide_annual` (11 series), `wide_other` (2 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:

```python
import finzdata as fz                     # pip install finzdata
c = fz.Client()                           # free API key: https://api.finzdata.com/
c.macro("APU0000703112")                        # full history, latest values
c.macro("APU0000703112", vintage="first")       # as first released
c.macro("APU0000703112", as_of="2020-03-01")    # exactly what was known on that date
c.macro_series(category="other_indicators")          # the catalogue for this category
```

## Most-watched series in this package

| ID | Title | Units | Frequency | Full history from |
|---|---|---|---|---|
| `APU0000703112` | Average Price: Ground Beef, 100% Beef (Cost per Pound/453.6 Grams) in U.S. City Average | U.S. Dollars | Monthly | 1984 |
| `APU0000708111` | Average Price: Eggs, Grade A, Large (Cost per Dozen) in U.S. City Average | U.S. Dollars | Monthly | 1980 |
| `GASREGW` | US Regular All Formulations Gas Price | Dollars per Gallon | Weekly, Ending Monday | 1990 |
| `CP` | Corporate Profits After Tax (without IVA and CCAdj) | Billions of Dollars | Quarterly | 1946 |
| `DPRIME` | Bank Prime Loan Rate | Percent | Daily | 1955 |
| `FYFSD` | Federal Surplus or Deficit [-] | Millions of Dollars | Annual, Fiscal Year | 1901 |
| `MMMFFAQ027S` | Money Market Funds; Total Financial Assets, Level | Millions of U.S. Dollars | Quarterly, End of Period | 1945 |
| `APU000072610` | Average Price: Electricity per Kilowatt-Hour in U.S. City Average | U.S. Dollars | Monthly | 1978 |
| `APU0000709112` | Average Price: Milk, Fresh, Whole, Fortified (Cost per Gallon/3.8 Liters) in U.S. City Average | U.S. Dollars | Monthly | 1995 |
| `FEDTARMD` | FOMC Summary of Economic Projections for the Fed Funds Rate, Median | Percent | Annual | 2015 |
| `GDPNOW` | GDPNow | Percent Change at Annual Rate | Quarterly | 2011 |
| `PRIME` | Bank Prime Loan Rate Changes: Historical Dates of Changes and Rates | Percent | Not Applicable | 1955 |
| `WFRBST01134` | Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) | Percent of Aggregate | Quarterly | 1989 |
| `MTSDS133FMS` | Federal Surplus or Deficit [-] | Millions of Dollars | Monthly | 1980 |
| `IUDSOIA` | Daily Sterling Overnight Index Average (SONIA) Rate | Percent | Daily | 1997 |
| `APU0000FF1101` | Average Price: Chicken Breast, Boneless (Cost per Pound/453.6 Grams) in U.S. City Average | U.S. Dollars | Monthly | 2006 |
| `BOGZ1FL192090005Q` | Households; Net Worth, Level | Millions of U.S. Dollars | Quarterly, End of Period | 1987 |
| `OBFR` | Overnight Bank Funding Rate | Percent | Daily | 2016 |
| `RPONTTLD` | Overnight Repurchase Agreements: Total Securities Purchased by the Federal Reserve in the Temporary Open Market Operations | Billions of US Dollars | Daily | 2000 |
| `WJFUELUSGULF` | Kerosene-Type Jet Fuel Prices: U.S. Gulf Coast | Dollars per Gallon | Weekly, Ending Friday | 1990 |
| `WFRBLTP1246` | Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) | Millions of Dollars | Quarterly | 1989 |
| `APU0000702111` | Average Price: Bread, White, Pan (Cost per Pound/453.6 Grams) in U.S. City Average | U.S. Dollars | Monthly | 1980 |
| `GPDIC1` | Real Gross Private Domestic Investment | Billions of Chained 2017 Dollars | Quarterly | 1947 |
| `SWPT` | Assets: Central Bank Liquidity Swaps: Central Bank Liquidity Swaps: Wednesday Level | Millions of U.S. Dollars | Weekly, As of Wednesday | 2002 |
| `BOGZ1FL153064486Q` | Households and Nonprofit Organizations; Directly and Indirectly Held Corporate Equities as a Percentage of Financial Assets; Assets, Level | Percent | Quarterly, End of Period | 1945 |

All 363 series: `series.csv`. Browse them at https://finzdata.com/macro/category/other-indicators.

## 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.

	---
	license: other
	license_name: public-domain-source-us-government
	pretty_name: "US Macro Data: Other Indicators"
	language:
	- en
	tags:
	- finance
	- economics
	- macroeconomics
	- time-series
	- fred
	- other-indicators
	- quant
	- backtesting
	size_categories:
	- 10K<n<100K
	configs:
	- config_name: long
	data_files: data/long.parquet
	default: true
	- config_name: wide_daily
	data_files: data/wide_daily.parquet
	- config_name: wide_weekly
	data_files: data/wide_weekly.parquet
	- config_name: wide_monthly
	data_files: data/wide_monthly.parquet
	- config_name: wide_quarterly
	data_files: data/wide_quarterly.parquet
	- config_name: wide_annual
	data_files: data/wide_annual.parquet
	- config_name: wide_other
	data_files: data/wide_other.parquet
	---

	# US macro data: Other Indicators (363 series)

	363 other indicators series from US government sources, cleaned into one consistent format and ready for pandas.
	This free package holds the last 12 months (2025-11-02 on) of each series' latest values. It is refreshed weekly.

	```python
	import pandas as pd
	df = pd.read_parquet("hf://datasets/FinzData/macro-other-indicators/data/long.parquet") # series_id, date, value
	wide = pd.read_parquet("hf://datasets/FinzData/macro-other-indicators/data/wide_daily.parquet") # one column per series
	```

	or `datasets.load_dataset("FinzData/macro-other-indicators")`. Wide tables by frequency: `wide_daily` (36 series), `wide_weekly` (31 series), `wide_monthly` (151 series), `wide_quarterly` (132 series), `wide_annual` (11 series), `wide_other` (2 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:

	```python
	import finzdata as fz # pip install finzdata
	c = fz.Client() # free API key: https://api.finzdata.com/
	c.macro("APU0000703112") # full history, latest values
	c.macro("APU0000703112", vintage="first") # as first released
	c.macro("APU0000703112", as_of="2020-03-01") # exactly what was known on that date
	c.macro_series(category="other_indicators") # the catalogue for this category
	```

	## Most-watched series in this package

	\| ID \| Title \| Units \| Frequency \| Full history from \|
	\|---\|---\|---\|---\|---\|
	\| `APU0000703112` \| Average Price: Ground Beef, 100% Beef (Cost per Pound/453.6 Grams) in U.S. City Average \| U.S. Dollars \| Monthly \| 1984 \|
	\| `APU0000708111` \| Average Price: Eggs, Grade A, Large (Cost per Dozen) in U.S. City Average \| U.S. Dollars \| Monthly \| 1980 \|
	\| `GASREGW` \| US Regular All Formulations Gas Price \| Dollars per Gallon \| Weekly, Ending Monday \| 1990 \|
	\| `CP` \| Corporate Profits After Tax (without IVA and CCAdj) \| Billions of Dollars \| Quarterly \| 1946 \|
	\| `DPRIME` \| Bank Prime Loan Rate \| Percent \| Daily \| 1955 \|
	\| `FYFSD` \| Federal Surplus or Deficit [-] \| Millions of Dollars \| Annual, Fiscal Year \| 1901 \|
	\| `MMMFFAQ027S` \| Money Market Funds; Total Financial Assets, Level \| Millions of U.S. Dollars \| Quarterly, End of Period \| 1945 \|
	\| `APU000072610` \| Average Price: Electricity per Kilowatt-Hour in U.S. City Average \| U.S. Dollars \| Monthly \| 1978 \|
	\| `APU0000709112` \| Average Price: Milk, Fresh, Whole, Fortified (Cost per Gallon/3.8 Liters) in U.S. City Average \| U.S. Dollars \| Monthly \| 1995 \|
	\| `FEDTARMD` \| FOMC Summary of Economic Projections for the Fed Funds Rate, Median \| Percent \| Annual \| 2015 \|
	\| `GDPNOW` \| GDPNow \| Percent Change at Annual Rate \| Quarterly \| 2011 \|
	\| `PRIME` \| Bank Prime Loan Rate Changes: Historical Dates of Changes and Rates \| Percent \| Not Applicable \| 1955 \|
	\| `WFRBST01134` \| Share of Net Worth Held by the Top 1% (99th to 100th Wealth Percentiles) \| Percent of Aggregate \| Quarterly \| 1989 \|
	\| `MTSDS133FMS` \| Federal Surplus or Deficit [-] \| Millions of Dollars \| Monthly \| 1980 \|
	\| `IUDSOIA` \| Daily Sterling Overnight Index Average (SONIA) Rate \| Percent \| Daily \| 1997 \|
	\| `APU0000FF1101` \| Average Price: Chicken Breast, Boneless (Cost per Pound/453.6 Grams) in U.S. City Average \| U.S. Dollars \| Monthly \| 2006 \|
	\| `BOGZ1FL192090005Q` \| Households; Net Worth, Level \| Millions of U.S. Dollars \| Quarterly, End of Period \| 1987 \|
	\| `OBFR` \| Overnight Bank Funding Rate \| Percent \| Daily \| 2016 \|
	\| `RPONTTLD` \| Overnight Repurchase Agreements: Total Securities Purchased by the Federal Reserve in the Temporary Open Market Operations \| Billions of US Dollars \| Daily \| 2000 \|
	\| `WJFUELUSGULF` \| Kerosene-Type Jet Fuel Prices: U.S. Gulf Coast \| Dollars per Gallon \| Weekly, Ending Friday \| 1990 \|
	\| `WFRBLTP1246` \| Net Worth Held by the Top 0.1% (99.9th to 100th Wealth Percentiles) \| Millions of Dollars \| Quarterly \| 1989 \|
	\| `APU0000702111` \| Average Price: Bread, White, Pan (Cost per Pound/453.6 Grams) in U.S. City Average \| U.S. Dollars \| Monthly \| 1980 \|
	\| `GPDIC1` \| Real Gross Private Domestic Investment \| Billions of Chained 2017 Dollars \| Quarterly \| 1947 \|
	\| `SWPT` \| Assets: Central Bank Liquidity Swaps: Central Bank Liquidity Swaps: Wednesday Level \| Millions of U.S. Dollars \| Weekly, As of Wednesday \| 2002 \|
	\| `BOGZ1FL153064486Q` \| Households and Nonprofit Organizations; Directly and Indirectly Held Corporate Equities as a Percentage of Financial Assets; Assets, Level \| Percent \| Quarterly, End of Period \| 1945 \|

	All 363 series: `series.csv`. Browse them at https://finzdata.com/macro/category/other-indicators.

	## 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.