Business counts by trade, five vintages
The number of businesses of each kind in this market, five vintages deep. This is the one layer that describes the visitor rather than their city: an owner finds their own trade here and learns whether there are more or fewer of them than five years ago.
A row here is a trade, not a place. The Census Bureau publishes these counts for the whole metro and suppresses anything finer, so cutting them to a radius would mean inventing the split.
The file
business counts 2017 · 2019 · 2021 · 2022 · 2023 · employment and pay 2025 Q4
318 rowsCounties in this file: Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, Washington · 13 columns available · free, no account, no rate limit.
What the rows look like
10 real rows from this file, spread evenly across it rather than taken off the top — every file here is written in some order, so its first rows are never a fair sample of it. These are the default columns, which is what the download button hands over.
| trade | naics | 2017 | 2019 | 2021 | 2022 | 2023 | net % | employees now | avg weekly wage |
|---|---|---|---|---|---|---|---|---|---|
| Limited-service restaurants | 722513 | 2,339 | 2,337 | 2,298 | 2,406 | 2,358 | 0.9 | 39,861 | 503 |
| Electronic shopping and mail-order houses | 454110 | 500 | 494 | 586 | 581 | 586 | 18.6 | — | — |
| Tax preparation services | 541213 | 310 | 336 | 343 | 304 | 306 | -8.9 | — | — |
| Interior design services | 541410 | 189 | 195 | 190 | 195 | 199 | 2.1 | 538 | 1,773 |
| Offices of real estate appraisers | 531320 | 180 | 170 | 173 | 160 | 141 | -17.1 | — | — |
| Electronics stores | 443142 | 197 | 153 | 132 | 121 | 108 | -29.4 | — | — |
| All other miscellaneous manufacturing | 339999 | 116 | 88 | 80 | 86 | 78 | -11.4 | — | — |
| All other legal services | 541199 | 56 | 51 | 54 | 59 | 61 | 19.6 | 442 | 2,088 |
| Book publishers | 511130 | 57 | 56 | 53 | 48 | 47 | -16.1 | — | — |
| Children's and infants' clothing stores | 448130 | 65 | 46 | 24 | 21 | 21 | -54.3 | — | — |
An em dash means the record is blank, and that is the source's gap rather than ours. Across the whole file: employees now is blank on 63.8% of rows, avg weekly wage is blank on 63.8% of rows.
The cuts of this file
Every cut is the same columns, filtered. Pick one and the row count changes; the file does not.
Every column in this file
Columns marked default come down unless you pick your own with
&columns=.
| Column | What it is | In the default file |
|---|---|---|
trade |
trade | default |
naics |
naics | default |
y2017 |
2017 | default |
y2019 |
2019 | default |
y2021 |
2021 | default |
y2022 |
2022 | default |
y2023 |
2023 | default |
change_pct |
net % | default |
workers_per_business |
workers per business | optional |
avg_pay_per_worker_usd |
avg pay per worker | optional |
employees_now |
employees now | default |
avg_weekly_wage_usd |
avg weekly wage | default |
wage_basis_pct |
wage measured over % of the trade | optional |
Where it comes from
U.S. Census Bureau, County Business Patterns; U.S. Bureau of Labor Statistics, Quarterly Census of Employment and Wages
This source does not stamp the day it was published, so we cannot honestly date our copy of it and will not guess. The period the records themselves cover is on the system card.
What this layer cannot answer is stated in full on the system card — read it before quoting a figure.
What you may do with it
Creative Commons Attribution 4.0 International (CC BY 4.0). Share it, change it, build a product on it, sell that product — all fine. The one condition is credit: say it came from Brick & Mortar and link back.
Records published by U.S. Census Bureau, U.S. Bureau of Labor Statistics. A work of the United States government, which is not subject to copyright protection in the U.S. (17 U.S.C. § 105).
Read the full licence · how we license every dataset, and the two we do not
Without the page
/api/export?dataset=trades&format=csv returns the
same file. Call /api/export
with no arguments for the whole catalogue.
Point an AI at it
Every file carries its own source, its capture date and the layer's own warnings in the header, so a model reading one gets the caveats with the numbers rather than the numbers alone. Paste this at an assistant that can fetch a URL:
Read https://brickandmortar.dev/api/export?dataset=trades&format=csv
Everything above the header row is provenance and limits. Read it first,
then answer using only what the rows support.llms.txt describes the whole warehouse the same way — what each dataset holds, which counties it really covers, and what it cannot answer.