Twin Cities Recorded Commercial Sales (7 metro counties)
Updated Oct 20, 2026
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, no redistribution
- Source / creator
- Brick & Mortar, compiled from Minnesota county, city and federal public records
- Collection method
- Public APIs and bulk files of each office of record, joined on the county parcel id
- Coverage start
- Not applicable
- Coverage end
- Not applicable
- Data last updated
- 2026-10-20
- Update schedule
- snapshot
Sample structure score: 82.3 / 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 | 33.5 / 50 | 154 of 230 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 28.8 / 30 | 148 of 154 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 |
|---|---|---|---|
| address | 1 / 10 | string | 0 / 9 |
| arms_length | 1 / 10 | boolean | 0 / 9 |
| assessed | 0 / 10 | number | 0 / 10 |
| building_sqft | 9 / 10 | number | 0 / 1 |
| building_sqft_method | 9 / 10 | string | 0 / 1 |
| county | 0 / 10 | string | 0 / 10 |
| footprint_sqft | 6 / 10 | number | 0 / 4 |
| lot_sqft | 0 / 10 | number | 0 / 10 |
| owner_type | 0 / 10 | string | 0 / 10 |
| parcel_id | 0 / 10 | number | 4 / 10 |
| price | 0 / 10 | number | 0 / 10 |
| price_per_building_sqft | 9 / 10 | number | 0 / 1 |
| price_per_lot_sqft | 0 / 10 | number | 0 / 10 |
| sale_month | 0 / 10 | string | 0 / 10 |
| sale_year | 0 / 10 | number | 0 / 10 |
| shares_price_and_month | 4 / 10 | boolean | 0 / 6 |
| stories | 7 / 10 | number | 0 / 3 |
| structures | 6 / 10 | number | 0 / 4 |
| usable_comp | 5 / 10 | boolean | 0 / 5 |
| use | 0 / 10 | string | 2 / 10 |
| year_built | 5 / 10 | number | 0 / 5 |
| all_footprint_sqft | 9 / 10 | number | 0 / 1 |
| multi_parcel_deed | 5 / 10 | boolean | 0 / 5 |
About this data
34,302 recorded sales of record on commercial, industrial and apartment parcels across the seven Twin Cities metro counties: price, sale month, lot and building square feet, price per foot, arms-length flag and owner type (entity or individual). Minnesota is a disclosure state, so these are actual recorded prices. From the county assessors. Joins to any parcel file on county + parcel_id. Owner and taxpayer names removed for this marketplace. One CSV file; Parquet and full schema on request.
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 16dd7e23-1660-482d-b3fa-33f39b94697b --output dataset.bin
Schema
| Name | Type | Description |
|---|---|---|
| address | string | |
| arms_length | boolean | |
| assessed | number | |
| building_sqft | number | |
| building_sqft_method | string | |
| county | string | |
| footprint_sqft | number | |
| lot_sqft | number | |
| owner_type | string | |
| parcel_id | number | |
| price | number | |
| price_per_building_sqft | number | |
| price_per_lot_sqft | number | |
| sale_month | string | |
| sale_year | number | |
| shares_price_and_month | boolean | |
| stories | number | |
| structures | number | |
| usable_comp | boolean | |
| use | string | |
| year_built | number | |
| all_footprint_sqft | number | |
| multi_parcel_deed | boolean |
Sample Data
Download a free sample to inspect the data before purchasing.
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
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# 2. Your agent can then call:
search_datasets({ query: "Twin Cities Recorded Commercia" })
// Found: 16dd7e23-1660-482d-b3fa-33f39b94697b
buy_now({ dataset_id: "16dd7e23-1660-482d-b3fa-33f39b94697b" }) // uses your saved card# Authenticate with your API key:
curl https://api.databazaar.io/datasets/16dd7e23-1660-482d-b3fa-33f39b94697b \
-H "Authorization: Bearer YOUR_API_KEY"
# Purchase:
curl -X POST https://api.databazaar.io/datasets/16dd7e23-1660-482d-b3fa-33f39b94697b/buy \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"dataset_id": "16dd7e23-1660-482d-b3fa-33f39b94697b"}'