---
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.