| --- |
| license: other |
| license_name: public-domain-source-us-government |
| pretty_name: "US Macro Data: Population" |
| language: |
| - en |
| tags: |
| - finance |
| - economics |
| - macroeconomics |
| - time-series |
| - fred |
| - population |
| - quant |
| - backtesting |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: long |
| data_files: data/long.parquet |
| default: true |
| - config_name: wide_monthly |
| data_files: data/wide_monthly.parquet |
| - config_name: wide_quarterly |
| data_files: data/wide_quarterly.parquet |
| --- |
| |
| # US macro data: Population (13 series) |
|
|
| 13 population 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-population/data/long.parquet") # series_id, date, value |
| wide = pd.read_parquet("hf://datasets/FinzData/macro-population/data/wide_monthly.parquet") # one column per series |
| ``` |
|
|
| or `datasets.load_dataset("FinzData/macro-population")`. Wide tables by frequency: `wide_monthly` (12 series), `wide_quarterly` (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: |
|
|
| ```python |
| import finzdata as fz # pip install finzdata |
| c = fz.Client() # free API key: https://api.finzdata.com/ |
| c.macro("POPTHM") # full history, latest values |
| c.macro("POPTHM", vintage="first") # as first released |
| c.macro("POPTHM", as_of="2020-03-01") # exactly what was known on that date |
| c.macro_series(category="population") # the catalogue for this category |
| ``` |
|
|
| ## Most-watched series in this package |
|
|
| | ID | Title | Units | Frequency | Full history from | |
| |---|---|---|---|---| |
| | `POPTHM` | Population | Thousands | Monthly | 1959 | |
| | `CNP16OV` | Population Level | Thousands of Persons | Monthly | 1948 | |
| | `LNU00074597` | Population - With a Disability, 16 Years and over | Thousands of Persons | Monthly | 2008 | |
| | `POP` | Total Population: All Ages including Armed Forces Overseas | Thousands | Monthly | 1952 | |
| | `LNU00073395` | Population Level - Foreign Born | Thousands of Persons | Monthly | 2007 | |
| | `LNU00024230` | Population Level - 55 Yrs. & over | Thousands of Persons | Monthly | 1948 | |
| | `LNU00000060` | Population Level - 25-54 Yrs. | Thousands of Persons | Monthly | 1948 | |
| | `B230RC0Q173SBEA` | Population | Thousands | Quarterly | 1947 | |
| | `LNU00000012` | Population Level - 16-19 Yrs. | Thousands of Persons | Monthly | 1948 | |
| | `LNU00073413` | Population Level - Native Born | Thousands of Persons | Monthly | 2007 | |
| | `LNU00000036` | Population Level - 20-24 Yrs. | Thousands of Persons | Monthly | 1948 | |
| | `LNU00000006` | Population Level - Black or African American | Thousands of Persons | Monthly | 1972 | |
| | `LNU00049526` | Population Level - Total Veterans, 18 Years and over | Thousands of Persons | Monthly | 2000 | |
|
|
| All 13 series: `series.csv`. Browse them at https://finzdata.com/macro/category/population. |
|
|
| ## 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. |
|
|
