Housing Market Data Download: HUD Rent Benchmarks + Airbnb Listings

Two datasets that answer each other's questions: HUD's FY2026 Fair Market Rent benchmarks for 51,895 ZIP codes, and 90,169 real Airbnb listings across six US cities. The rent side gives you a federal benchmark per ZIP; the listings side gives you actual asking rents and supply in six markets. Both ship as clean CSV in one bundle. If you want to test the columns first, there's a free rent data sample and a separate page on the Airbnb data by city.

Two Housing Datasets, One Download

These two packs are part of the Studio & Data Vault Bundle (four packs: NFL games, HUD rent, Airbnb listings, wallpapers). Each component zip is byte-identical to the standalone product.

Side A: HUD Fair Market Rent, 51,895 ZIP Rows

51,895 ZIP-level rows from HUD's official FY2026 Fair Market Rent files, plus 3,229 county rows and 52 state summaries for higher-level views. Five bedroom sizes (0BR through 4BR) in every file, monthly USD. What makes the ZIP level useful: for FY2026, many metro areas use Small Area FMRs (SAFMRs), which HUD sets per ZIP instead of one number for the whole metro. ZIPs without a SAFMR carry their metro's FMR. That gives you a rent benchmark at two granularities in one table, and the data dictionary documents HUD's FMR definition and methodology so the numbers survive a skeptical reviewer.

Side B: Airbnb Listings, 90,169 Rows in 6 Cities

90,169 listing rows with a single 12-column schema across all six files, so joins and group-bys work without schema surgery:

Host personal data is excluded by design and coordinates are rounded to 4 decimals. One row per listing: price, room type, minimum nights, availability, reviews, neighborhood, coordinates.

Questions You Can Answer With the Pair

Each dataset is useful alone. Put the two in the same notebook and the ZIP code becomes the join key:

• Affordability gap by ZIP. Join Airbnb's median asking price per neighborhood or ZIP against the HUD benchmark for that ZIP. Where asking rents sit far above the FMR, you're looking at the premium the market charges over the federal benchmark; where they sit close, the two sources agree. That's a descriptive comparison you compute per ZIP.
• Supply per city. The per-city row counts above are the headline, but the files support the deeper version: listings per neighborhood, by room type, by minimum-nights band, per availability tier. Six markets side by side in one group-by.
• Rent vs FMR delta. For each of the six cities, take the median listing price and subtract the ZIP's FMR for a given bedroom size. Sort by the gap. The output is a table of where asking prices and the federal benchmark diverge, computed from the two CSVs with a group-by and a merge.
• SAFMR vs standard metro FMR. The HUD file lets you split ZIPs into SAFMR-assigned and metro-level rows. Compare the spread within each metro to see how much ZIP-level variation the metro average hides.

All four are descriptive computations on clean, dated inputs. The pack ships data and documentation only: positioning stays that way on purpose. Clean data for your own analysis, not a model or a recommendation.

Snapshots, Not Live Feeds

Licensing, in Plain Terms

The rent data is a US federal government work (HUD FY2026 Fair Market Rent), public domain under 17 USC §105, no attribution required. The Airbnb data is Inside Airbnb's, CC BY 4.0: copy, remix, republish and build commercial work on it, with one condition. If you republish, include "Data by Inside Airbnb, InsideAirbnb.com, CC BY 4.0". The credit line ships inside the zip in ATTRIBUTION.txt. Both datasets load straight into pandas, Excel or R, with a data dictionary for every column.

one-time · 4 packs incl. both housing datasets · SHA256SUMS verified · HUD public domain / Inside Airbnb CC BY 4.0 · instant download