NCES K-12 public schools
National Center for Education Statistics (via Urban Institute Education Data API)
In a RepVector build, this dataset profiles the schools, training pipelines and workforce supply of a territory.
| School | District | City | Enrollment | Teachers (FTE) | Free/reduced lunch students |
|---|---|---|---|---|---|
| Chatham High School | School District of the Chathams | CHATHAM | 1,315 | 102 | 21 |
| Chatham Middle School | School District of the Chathams | CHATHAM | 984 | 91 | 13 |
| Lafayette Avenue School | School District of the Chathams | CHATHAM | 592 | 58 | 11 |
| Milton Avenue School | School District of the Chathams | CHATHAM | 284 | 22 | 3 |
| Washington Avenue School | School District of the Chathams | CHATHAM | 314 | 28 | 6 |
| Southern Boulevard School | School District of the Chathams | CHATHAM | 414 | 39 | 3 |
| Developmental Learning Center Warren | Morris-Union Jointure Commisson School District | WARREN | 150 | 31 | 12 |
| Developmental Learning Center New Providence | Morris-Union Jointure Commisson School District | NEW PROVIDENCE | 68 | 15 | 15 |
What this dataset is
Every public K-12 school, with district, grade span, enrollment, teacher counts and free/reduced-lunch share, addressed to city and county. Maps the full public school system in an area — not just district headquarters but every individual school building. It is published by National Center for Education Statistics (via Urban Institute Education Data API) and can be queried at county and state level, refreshed annually. Each row is an individual entity — an organisation, site or practitioner — so results can be filtered, routed and turned directly into a call list.
Why it is useful
- Indicates where trained workforce is produced, which predicts staffing capacity.
- Identifies institutional buyers that sit outside commercial registries.
- Adds a demographic dimension that population counts alone miss.
Questions it helps answer
- Where does this territory's workforce pipeline come from?
- Which institutions in this market are buyers in their own right?
How different verticals use it
RepVector is vertical-agnostic: this dataset is selected by what your question asks for, not by industry. These are common ways teams put it to work.
Sizes enrolment, outcomes and institution mix inside a territory.
Targets districts and campuses by enrolment and programme type.
Locates training pipelines that feed local clinical staffing.
Maps student and graduate populations behind lending demand.
How RepVector uses it
- You describe a market in plain language. The geography resolver turns the place you named into the exact identifiers this dataset needs — city to county to state, plus DMA where relevant — so a query at county runs without you knowing any codes.
- The planner selects NCES K-12 public schools only when your question matches what it actually reports. It is never included to pad a result.
- Returned rows are normalised into the shared metric layer, so figures from National Center for Education Statistics (via Urban Institute Education Data API) line up with every other source in the same dashboard instead of sitting in an isolated table.
- Quality checks score coverage and recency. If National Center for Education Statistics (via Urban Institute Education Data API) suppresses or omits a value for your geography, the gap is reported as a gap — nothing is estimated or filled in.
- The result renders as charts, KPIs and, where the rows are entities, prioritised targets you can export to PDF, Excel, CSV or JSON.
What it does not tell you
- Reported on an academic cycle, so it lags in-year staffing changes.
| Field | Key | Type |
|---|---|---|
| School | name | string |
| District | district | string |
| City | city | string |
| Enrollment | enrollment | number |
| Teachers (FTE) | teachersFte | number |
| Free/reduced lunch students | freeOrReducedLunch | number |
| Lowest grade | lowestGrade | number |
| Highest grade | highestGrade | number |
| ZIP | zip | geo |
How it fits with the rest of the catalog
Workforce supply reads best against the population it serves and the sites that employ it. RepVector queries every selected dataset against the same resolved geography and time window, then normalises the results into one metric layer so they can be charted side by side. These datasets are the most common companions to NCES K-12 public schools:
Other education datasets
Common questions
What does NCES K-12 public schools contain?
Every public K-12 school, with district, grade span, enrollment, teacher counts and free/reduced-lunch share, addressed to city and county. Maps the full public school system in an area — not just district headquarters but every individual school building. It is published by National Center for Education Statistics (via Urban Institute Education Data API) at county and state grain.
How often is it refreshed?
National Center for Education Statistics (via Urban Institute Education Data API) publishes on a annually cycle. RepVector re-reads the source on that cadence and keeps every prior capture, so you can see what changed.
Do I need an account to use it?
No. Browsing the catalog and the free lookup tools needs no account. Running a full market build across every county in a territory is the paid product.
Build the list for one county and see whether the names are right.
Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.
3 free runs — no card required.