pynhts

Typed, survey-weight-aware Python access to US National Household Travel Survey (NHTS) microdata.

Scope and status (0.1.0, alpha). Only the 2017 wave is supported; other waves come after this one is solid. The API may still change. Results are validated against FHWA's published tables: 20 of 24 figures reproduce completely and 4 gaps are reported openly in docs/validation.md.

Install

pip install pynhts
pynhts fetch --replicates        # download, verify (SHA-256) and convert; about 0.4 GB of Parquet, plus 1.8 GB of raw CSV that you may delete afterwards

Already have the NHTS 2017 CSV files? pynhts register <folder> adopts them after checking their hashes.

What it does

import pynhts
data = pynhts.load(2017)

# lazy, validated tables: columns are joined from the table that owns them
trips = data.trips(["TRPMILES", "TRPTRANS", "HHFAMINC", "R_AGE"])

# weighted statistics with jackknife (JKn) standard errors and 95 % margins of error
s = data.survey("person", ["R_AGE_IMP", "DRIVER"])
s.total(domain=s.rows["DRIVER"] == "01")        # 223,277 thousand drivers, MOE 827 thousand
data.survey("trip", ["TRPMILES"]).mean("TRPMILES")   # 10.70 miles, MOE 0.40

# replicate a published table and see every gap
from pynhts import recipes
print(recipes.to_markdown(recipes.run("stt2017", data)))

# machine-learning bridge
from pynhts import ml
arr = ml.to_arrays(trips, ["TRPMILES", "R_AGE"], target="TRPTRANS", weight="WTTRDFIN")

Why a library

Correct NHTS analysis has many silent traps (a data server that returns HTTP 200 for missing files, string codes with leading zeros, -1 skips that are not missing data, 107 copied parent columns in the child tables, a vehicle PERSONID that is not the person key, ...). They are documented in docs/data_notes.md and each is covered by a test.

Validation

• All 3,807 coded values of the official codebook (counts and weighted totals) reproduce.
• 24 figures from Tables 1 and 3 of FHWA's Summary of Travel Trends: 2017 NHTS, with margins of error: 20 reproduce completely, 2 reproduce the estimate but not the margin of error, 2 do not reproduce. See docs/validation.md.

Documentation

Methods · Data notes · Validation · Roadmap · Contributing · Changelog

Data

The NHTS microdata are public data of the US Federal Highway Administration (https://nhts.ornl.gov). They are never bundled with or committed to this repository.

Development

uv venv && uv pip install -e ".[dev]"
pytest                             # unit tests, no data needed
pytest -m data                     # real-data tests (files registered in the pynhts cache)
pytest -m network -o addopts=-ra   # live ORNL download, manual only

Citation

See CITATION.cff. License: BSD-3-Clause.