Twin Cities Homes for Sale: 14.5k Active Listings with Address, Parcel ID, Ask and County Value
Updated Oct 20, 2026
$149
Fixed price
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Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Brick & Mortar data licence: internal commercial use incl. model training, no redistribution
- Source / creator
- Public Realtor.com listing pages (seven Twin Cities metro counties), 2026-10-12; county assessor estimated market values.
- Collection method
- Every for-sale listing we could read in the seven metro counties on 2026-10-12, matched to its county parcel (PIN) on 99% of rows, with the assessor's estimated market value beside the ask. Ask against county value is a first screen for how a home is priced; our closed-sales file shows homes close at 0.994 of the last ask, so a gap here is usually condition the records cannot see.
- Coverage start
- Not applicable
- Coverage end
- Not applicable
- Data last updated
- 2026-10-20
- Update schedule
- snapshot
Sample structure score: 98.7 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (CSV) on 2026-10-20. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 48.7 / 50 | 185 of 190 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 185 of 185 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| listing_id | 0 / 10 | string | 0 / 10 |
| address | 0 / 10 | string | 0 / 10 |
| city | 0 / 10 | string | 0 / 10 |
| zip | 0 / 10 | number | 0 / 10 |
| county | 0 / 10 | string | 0 / 10 |
| parcel_id | 0 / 10 | number | 0 / 10 |
| list_price | 0 / 10 | number | 0 / 10 |
| county_value | 0 / 10 | number | 0 / 10 |
| property_type | 0 / 10 | string | 0 / 10 |
| beds | 1 / 10 | number | 0 / 9 |
| baths | 1 / 10 | number | 0 / 9 |
| sqft | 1 / 10 | number | 0 / 9 |
| lot_sqft | 1 / 10 | number | 0 / 9 |
| year_built | 1 / 10 | number | 0 / 9 |
| days_on_market | 0 / 10 | number | 0 / 10 |
| observed_on | 0 / 10 | string | 0 / 10 |
| lat | 0 / 10 | number | 0 / 10 |
| lon | 0 / 10 | number | 0 / 10 |
| url | 0 / 10 | string | 0 / 10 |
About this data
14,556 homes for sale across the seven-county Minneapolis-Saint Paul metro (October 2026): address, county parcel id, asking price, the county's estimated market value, beds, baths, square feet, lot, year built, days on market and a link to the listing. The county parcel id joins every row to the public record. One CSV, 14,556 rows; column meanings in the schema. No listing agents, brokerages, agent phones or emails.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py f7bc5b65-571d-46a8-b55f-5878034b326d --output dataset.bin
Schema
| Name | Type | Description |
|---|---|---|
| listing_id | string | |
| address | string | |
| city | string | |
| zip | number | |
| county | string | |
| parcel_id | number | |
| list_price | number | |
| county_value | number | |
| property_type | string | |
| beds | number | |
| baths | number | |
| sqft | number | |
| lot_sqft | number | |
| year_built | number | |
| days_on_market | number | |
| observed_on | string | |
| lat | number | |
| lon | number | |
| url | string |
Sample Data
Download a free sample to inspect the data before purchasing.
Public sample only. Sign in to retrieve the full dataset, including free datasets.
For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Twin Cities Homes for Sale: 14" })
// Found: f7bc5b65-571d-46a8-b55f-5878034b326d
buy_now({ dataset_id: "f7bc5b65-571d-46a8-b55f-5878034b326d" }) // uses your saved card# Authenticate with your API key:
curl https://api.databazaar.io/datasets/f7bc5b65-571d-46a8-b55f-5878034b326d \
-H "Authorization: Bearer YOUR_API_KEY"
# Purchase:
curl -X POST https://api.databazaar.io/datasets/f7bc5b65-571d-46a8-b55f-5878034b326d/buy \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"dataset_id": "f7bc5b65-571d-46a8-b55f-5878034b326d"}'