---
license: cc0-1.0
task_categories:
- tabular-classification
- tabular-regression
- question-answering
language:
- en
tags:
- education
- k12
- schools
- us-schools
- nces
- school-directory
- demographics
- public-schools
- private-schools
- principal-directory
- crdc
pretty_name: US K-12 Schools Directory
size_categories:
- 100K<n<1M
dataset_info:
  features:
  - name: nces_school_id
    dtype: string
  - name: school_name
    dtype: string
  - name: state_school_id
    dtype: string
  - name: address
    dtype: string
  - name: city
    dtype: string
  - name: state
    dtype: string
  - name: zip_code
    dtype: string
  - name: county
    dtype: string
  - name: latitude
    dtype: float64
  - name: longitude
    dtype: float64
  - name: locale_description
    dtype: string
  - name: school_type
    dtype: string
  - name: school_level
    dtype: string
  - name: grade_span
    dtype: string
  - name: charter_school
    dtype: bool
  - name: magnet_school
    dtype: bool
  - name: virtual_school
    dtype: bool
  - name: title_i_status
    dtype: string
  - name: phone
    dtype: string
  - name: website
    dtype: string
  - name: district_nces_id
    dtype: string
  - name: district_name
    dtype: string
  - name: total_students
    dtype: int64
  - name: total_teachers
    dtype: float64
  - name: student_teacher_ratio
    dtype: float64
  - name: demographics_json
    dtype: string
  - name: pct_free_reduced_lunch
    dtype: float64
  - name: pct_english_learners
    dtype: float64
  - name: pct_special_education
    dtype: float64
  - name: pct_white
    dtype: float64
  - name: pct_black
    dtype: float64
  - name: pct_hispanic
    dtype: float64
  - name: pct_asian
    dtype: float64
  - name: performance_json
    dtype: string
  - name: accountability_rating
    dtype: string
  - name: graduation_rate
    dtype: float64
  - name: greatschools_rating
    dtype: float64
  - name: niche_rating
    dtype: string
  - name: staff_json
    dtype: string
  - name: principal_name
    dtype: string
  - name: principal_email
    dtype: string
  - name: school_year
    dtype: string
  - name: status
    dtype: string
  - name: data_sources_json
    dtype: string
  - name: last_updated
    dtype: string
  splits:
  - name: train
    num_examples: 87229
  - name: validation
    num_examples: 18692
  - name: test
    num_examples: 18692
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-00000-of-00001.parquet
  - split: validation
    path: data/validation-00000-of-00001.parquet
  - split: test
    path: data/test-00000-of-00001.parquet
---

# US K-12 Schools Directory

A directory of 124,613 US K-12 schools covering all 50 states, DC, and US territories,
compiled from federal and state government sources. Each record carries directory
information (address, phone, website), enrollment and demographics, and, where a source
supplied it, a principal name and email.

This is a compilation of public government data. It is not a survey, and no field was
independently verified against the school itself.

## Loading

```python
from datasets import load_dataset

ds = load_dataset("robworks-software/us-k12-schools-directory")

texas = ds["train"].filter(lambda x: x["state"] == "TX")
with_principal = ds["train"].filter(lambda x: x["principal_name"] is not None)
```

The pre-split `train`/`validation`/`test` configuration is a random 70/15/15 partition of
the same rows; `full.parquet` in the repo holds all 124,613 records unsplit. The splits
carry no semantic meaning - use `full.parquet` for directory lookups.

## Splits

| Split | Rows |
|-------|------|
| train | 87,229 |
| validation | 18,692 |
| test | 18,692 |
| **total** | **124,613** |

## Field coverage

Coverage is uneven, and the gaps are large enough to matter for most analyses:

| Field | Populated | Coverage |
|-------|-----------|----------|
| Phone | 124,190 | 99.7% |
| Performance data | 123,624 | 99.2% |
| Demographics | 119,209 | 95.7% |
| Website | 71,117 | 57.1% |
| Principal name | 63,161 | 50.7% |
| Principal email | 36,650 | 29.4% |

## Sources

- **NCES Common Core of Data (CCD)** - public school directory, enrollment, demographics
- **NCES Private School Universe Survey (PSS)** - private school directory
- **Civil Rights Data Collection (CRDC)** - enrollment demographics
- **State education agency directories** (22 states) - principal names, emails, websites
- **State report cards** - graduation rates, accountability ratings
- **Urban Institute Education Data API** - demographics enrichment
- **School website scraping** (~28,000 sites) - principal names and emails extracted
  automatically from school web pages

## Limitations

- **Principal contacts are half-covered and unevenly distributed.** The 50.7% name /
  29.4% email coverage is concentrated in the 22 states with a usable state directory.
  Schools in the other 28 states are much more likely to have no principal at all.
- **Scraped contacts are unverified.** Roughly 5,700 principal names and 1,300 emails came
  from automated extraction of school websites, at about a 20% hit rate. These were not
  checked by hand and some will be wrong, stale, or attached to the wrong person.
- **Staff turnover makes contacts decay quickly.** Principal assignments change every
  year; treat any name or email here as a lead, not a fact.
- **Mixed vintages.** Public school data is 2022-2023; private school data is 2021-2022
  (PSS is biennial); CRDC lags 1-2 years; state report cards vary by state.
- **State-constructed IDs required remapping.** Several state directories build NCES IDs
  that do not match federal CCD IDs. Those records were matched back by school name and
  city, which is imperfect - match rates ranged from about 69% to 95% by state.
- **Ratings are sparse and third-party.** `greatschools_rating` and `niche_rating` come
  from commercial sources with limited coverage and their own methodologies.
- **No maintenance schedule.** This is a snapshot. It is not updated on a fixed cadence.

## License

**CC0-1.0 (Public Domain Dedication).** The underlying data comes from US federal and
state government sources and is public domain under 17 U.S.C. Sec. 105 and state public
records laws.

Attribution is appreciated but not required: NCES, US Department of Education Office for
Civil Rights, the state education agencies listed above, and the Urban Institute
Education Data Portal.

## Citation

```bibtex
@dataset{us_k12_schools,
  title  = {US K-12 Schools Directory},
  author = {Robworks Software},
  year   = {2026},
  publisher = {Hugging Face},
  url    = {https://huggingface.co/datasets/robworks-software/us-k12-schools-directory}
}
```