What is in the Crawlora US Housing Markets dataset?

Redfin market statistics for 52,051 US regions — every metro, county, city and ZIP code — monthly back to 2012, for 17,927,456 region-month records. Each row carries median sale and list price, price per square foot, homes sold, new listings, inventory, months of supply, days on market and competitiveness measures, plus a Census-income join that adds price-to-income, salary-needed-to-buy and the affordability gap. It is aggregate market data only — no listings, addresses or personal data.

Where does the housing data come from?

Market statistics come from Redfin's public Data Center (please credit Redfin as the source), and median household income comes from the US Census Bureau's ACS 2024 5-year estimates (public domain). Crawlora's contribution is the join and the derived affordability metrics, refreshed monthly. This is a bulk-file dataset, not live scraping.

What salary do I need to buy a home, and how is it computed?

salary_to_buy is the gross annual income at which the monthly cost of the median home reaches 28% of pay, assuming 20% down, a 30-year fixed mortgage at 6.49% (Freddie Mac, week of 2026-07-09), plus property tax and insurance. Nationally that is about $121,483 for the $449,846 median home — well above the $80,734 the median household earns.

How accurate is the affordability ratio?

Cities, counties and ZIP codes join to their own Census geography, so their price-to-income is accurate. Metro rows join to state income (Redfin metros don't map to a single Census geography), which inflates ratios for high-cost metros in populous states — a documented approximation. Ratios are sale-based; thin markets with only a handful of monthly sales have noisy medians, so rank with a min_homes_sold filter.

How do I query the housing dataset?

Call GET /datasets/housing-markets/search with filters like region_type, state_code, property_type, latest=true and numeric ranges (min/max on price, price_to_income, salary_to_buy, days on market); /facets for aggregate counts; and /items/{region_type}/{table_id}?history=true for one region's full monthly series. It reads a stored index, so there is no live scraping or proxy routing, and the same endpoints are available as hosted MCP tools.

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Real-estate intelligence

Every US housing market, monthly, as one queryable API

Name: Crawlora US Housing Markets Dataset
Creator: Crawlora
License: https://creativecommons.org/licenses/by/4.0/

Redfin market statistics for 52,051 US regions — metro, county, city and ZIP — with 173 months of history, joined to Census income so every row answers “how many years of income does this home cost, and what salary do you need to buy?” Aggregate market data only. Snapshot September 6, 2026.

Query the API Read the affordability study

52K regions

of US housing-market data — every metro, county, city and ZIP Redfin publishes — each with 173 months of history back to 2012, for 17,927,456 region-month records in one queryable index.

5.57×

the median US home ($449,846) costs relative to the median household income ($80,734) — against the classic 3× affordable line. Buying it needs a $121,483 salary.

34.1%

of the 952 US counties with real transaction volume price the typical home above 5× income; only 3.7% still sit under the 3× line. Affordability is now the exception.

95.4%

of region-months carry a Census income join, so price-to-income, salary_to_buy and the affordability gap are computed and filterable — not just raw prices.

Coverage

Five geographic grains, 173 months deep

One record per region × month × property type. Filter latest=true for the current snapshot, or pull a region's full history.

24,619

ZIP codes

23,412

Cities

3,087

Counties

932

Metros

National

What the data says

The least and most affordable big cities

Sale price ÷ median household income for cities with real transaction volume (100+ recent sales). Sale-based; the study headlines a list-based cut. Detroit is the only major city a sub-$30K income can buy the median home in.

Least affordable

City	Price ÷ income	Salary to buy
Los Angeles, CA	12.87×	$284,773
San Francisco, CA	12.56×	$477,997
Newark, NJ	12.10×	$170,135
Huntington Beach, CA	11.37×	$371,326
Irvine, CA	11.26×	$415,885
New York, NY	11.17×	$242,779

Most affordable

City	Price ÷ income	Salary to buy
Detroit, MI	2.38×	$25,655
Davenport, IA	2.70×	$48,205
Lansing, MI	2.71×	$39,833

Want the full curated picture — state map, 100-metro ranking and the salary-vs-income gap? Read “Unaffordable America”, the data study built on this dataset.

Metro league tables

Where a paycheck goes furthest, metro by metro

The same price-to-income lens applied to metropolitan areas with 100+ sales in the latest month, plus the raw price table: the priciest and cheapest metros by median sale price, with year-over-year change, days on market and sales volume. Every row is one `region_type=metro` record from the search endpoint, so the tables below are exactly what the API returns.

Least affordable metros

Metro	Price ÷ income	Salary to buy
San Francisco, CA metro area	18.07×	$483,669
San Rafael, CA metro area	16.29×	$436,139
San Jose, CA metro area	16.24×	$434,789
Key West, FL metro area	14.15×	$284,908
Breckenridge, CO metro area	12.96×	$334,193
Anaheim, CA metro area	12.71×	$340,269
Heber, UT metro area	12.08×	$310,563
Santa Cruz, CA metro area	11.60×	$310,563

Most affordable metros

Metro	Price ÷ income	Salary to buy
Decatur, IL metro area	1.80×	$40,508
Ottawa, IL metro area	2.13×	$47,867
Carbondale, IL metro area	2.13×	$48,002
Peoria, IL metro area	2.19×	$49,285
Binghamton, NY metro area	2.34×	$54,281
Muncie, IN metro area	2.50×	$48,583
Pottsville, PA metro area	2.51×	$52,931
Springfield, IL metro area	2.52×	$56,712

Priciest metros by median sale price

Metro	Median sale price	YoY	Days on market	Homes sold
San Francisco, CA metro area	$1,791,000	+11.9%	15	1,044
San Rafael, CA metro area	$1,615,000	-5.0%	21	289
San Jose, CA metro area	$1,610,000	-5.3%	16	1,194
Anaheim, CA metro area	$1,260,000	+5.0%	38	1,829
Breckenridge, CO metro area	$1,237,500	+23.8%	48	111
Santa Cruz, CA metro area	$1,150,000	-4.2%	18	162
Heber, UT metro area	$1,150,000	-23.3%	52	166
Santa Maria, CA metro area	$1,069,500	-7.1%	38	282

Cheapest metros by median sale price

Metro	Median sale price	YoY	Days on market	Homes sold
Decatur, IL metro area	$150,000	+6.2%	29	121
Ottawa, IL metro area	$177,250	+7.4%	57	118
Carbondale, IL metro area	$177,750	-1.2%	64	125
Muncie, IN metro area	$179,900	+12.4%	13	121
Youngstown, OH metro area	$180,000	-2.7%	42	468
Peoria, IL metro area	$182,500	+4.3%	18	481
Battle Creek, MI metro area	$185,000	-5.1%	25	117
Charleston, WV metro area	$185,236.5	+6.8%	20	150

Metro rows aggregate every county Redfin assigns to the metropolitan area; the income join uses the metro's ACS median household income. Coastal California and Hawaii fill the least-affordable table because incomes there are high but prices are higher still — the ratio, not the price, is what the table ranks.

Schema

What each record carries

Every field is filterable, facetable or sortable over the API.

Identity

region_typeregionstate_codeparent_metroproperty_typeperiod_begin

Prices

median_sale_pricemedian_list_pricemedian_ppsf*_mom*_yoy

Market

homes_soldnew_listingsinventorymonths_of_supplymedian_domsold_above_list

Affordability

median_household_incomeprice_to_incomesalary_to_buyaffordability_gap

Query it

Example requests

Reads a stored index — no live scraping. Also available as hosted MCP tools.

Least affordable cities right now

region_type=city&latest=true&min_homes_sold=100&sort=price_to_income_desc

Cheapest counties to buy in Texas

region_type=county&state_code=TX&latest=true&sort=salary_to_buy_asc

One ZIP's full monthly price history

items/zip/{table_id}?history=true

Facet region counts by state

facets?facet=state_code&region_type=county&latest=true

Sources & method

How it's built, and the honest caveats

Market data is Redfin’s public Data Center (please credit Redfin); income is US Census ACS 2024 5-year (public domain). Aggregate market statistics only — no listings, addresses or PII.
salary_to_buy assumes 20% down, a 30-year fixed at 6.49% (Freddie Mac, week of 2026-07-09), plus taxes and insurance, at 28% of gross income.
City / county / ZIP join to their own Census geography (accurate); metro rows use state income as an approximation, which inflates high-cost metros.
Ratios are sale-based; a place with only a few monthly sales has a noisy median — rank with min_homes_sold. ACS income lags home prices by ~1–2 years.

Built with the same structured web-data API that powers our GitHub Users and Airbnb markets datasets. See the full data catalog.